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UNIVERS IDADE FEDERAL DO RIO GRANDE DO NORTE
PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS
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DO FAST RET INAL OSC ILLAT IONS PLAY A ROLE IN V I S ION? A STUDY IN THE ANESTHET IZED AND AWAKE C AT
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G I O V A N N E R O S S O
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N a t a l , 2 0 1 5
I N S T I T U TO D O !C É R E B RO
!UNIVERS IDADE FEDERAL DO RIO GRANDE DO NORTE
PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS
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DO FAST RET INAL OSC ILLAT IONS PLAY A ROLE IN V I S ION? A STUDY IN THE ANESTHET IZED AND AWAKE C AT
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G I O V A N N E R O S S O
!TRABALHO APRESENTADO AO PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS DA UNIVERSIDADE
FEDERAL DO RIO GRANDE DO NORTE COMO REQUISITO PARCIAL PARA A OBTENÇÃO DO
G R A U D E M E S T R E !OR I E N TA D O R : Pro f . Dr. SERGIO NEUENSCHWANDER
NEUROBIOLOGIA DE SISTEMAS E COGNIÇÃO
!!!!
N a t a l , 2 0 1 5
I N S T I T U TO D O !C É R E B RO
UNIVERS IDADE FEDERAL DO RIO GRANDE DO NORTE
PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS
��� !!!
DO FAST RET INAL OSC ILLAT IONS PLAY A ROLE IN V I S ION? A STUDY IN THE ANESTHET IZED AND AWAKE C AT
!!!
G I O V A N N E R O S S O
!DISSERTAÇÃO APRESENTADA AO PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS
DA UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE
COMO REQUISITO PARCIAL PARA A OBTENÇÃO DO GRAU DE MESTRE.
ÁREA DE CONCENTRAÇÃO: NEUROBIOLOGIA DE SISTEMAS E COGNIÇÃO. !!APROVADA EM: 16.11.2015
B A N C A E X A M I N A D O R A : PROF. DR. SERGIO NEUENSCHWANDER
PROF. DR. CLAUDIO QUEIROZ
PROF. DR. JEROME BARON
I N S T I T U TO D O !C É R E B RO
!!!!!!!!!!!!!!
!EXPERIMENTS ARE THE ONLY MEANS OF KNOWLEDGE AT OUR DISPOSAL.
THE REST IS POETRY, IMAGINATION.
MAX PLANCK !
AB S T R A C T
Early physiologists were dazzled by the occurrence of high-amplitude, periodic oscillations, easily discernible in recording traces from the eye, optic tract and optic ganglia. Numerous studies thereafter pointed to retinal ganglion cell as the elements responsible for the generation of these fast rhythms, which were known to propagate to the lateral geniculate and to the cortex. Only recently, however, these early observations gained renewed interest, mainly in the light of recent theories linking neuronal oscillations to various cognitive processes, such as perceptual binding, attention and memory. In this context, fast retinal oscillations have been associated to the binding of contiguous contours or surfaces, which in principle could support a fast feedforward segmentation process. In addition, a series of experiments in the cat have shown that fast oscillations in the retina may convey global stimulus properties, such as size.
A limitation in these previous studies, however, was that most of them where were made in the anesthetized and paralyzed cat. Only a few early studies have been performed in the non-anesthetized but still paralyzed cat. Another concern was that, in these latter experiments, visual stimuli were often limited to ganzfeld flashes, far from natural vision conditions. Moreover, very recently we made the surprising observation that fast retinal oscillations depend strongly on halothane (and isoflurane) anesthesia. It was therefore imperative to verify whether oscillatory activity is also present in the awake cat, under naturalistic conditions, such as during free-viewing of a visual scene. This is the main goal of the present study.
Simultaneous multiple-electrode recordings were made from the lateral geniculate nucleus (LGN) and the retina of anesthetized cats (N= 3) and from the LGN of an awake cat (N= 1). Comparisons were made for responses to natural movies and flashed stationary light stimuli. To test specifically the role of retinal oscillations in encoding stimulus size we designed a protocol made of a light circle of varying size along the trial. Spike sorting techniques allowed us to study separately the ON- and OFF-components of the responses. Analysis consisted in measuring synchronous oscillations for single cell spiking activity in the time (sliding correlation analysis) and spectral domains (multitaper spectral analysis, multitaper coherence). Our present results based on single-cells extend our previous findings in the anesthetized cat, which were restricted to an autocorrelation analysis of LGN mutiunitary responses. Both ON- and OFF-responses to varying size stimuli show that coherent oscillations appear only after the stimulus attained a minimum size of about 5° (depending on the contrast level), suggesting that oscillations in the retina are rather limited in encoding subtle changes in stimulus size. Recordings obtained directly from eye showed that oscillations in the retina, as in the LGN, are highly correlated with the concentrations level of halothane. Notably, in a series of sessions we were able to record LGN responses in an awake cat, which was subsequently anesthetized with halothane, keeping the same recording site. Oscillations were completely absent in the awake condition and appeared strong as usual during the halothane anesthesia.
Overall these results weaken substantially the notion that fast retinal oscillations are meaningful for vision. Nevertheless, as shown from our single cell analysis, retinal oscillations share many of the properties of cortical gamma oscillations. In this respect, oscillations in the retina induced by halothane serve as a valuable preparation, even though artificial, for studying oscillatory neuronal dynamics. !!
Key words: retina, geniculate, oscillation, coherence, halothane, awake.
RE S U M O
Os primeiros fisiologistas ficaram certamente impressionados com a existência de oscilações periódicas de alta amplitude, claramente visíveis nos traçados obtidos da retina, trato óptico e gânglios ópticos. Posteriormente vários estudos mostraram ser a células ganglionares os elementos responsáveis pela geração destes ritmos rápidos, que sabia-se podem propagar da retina ao geniculado lateral e ao córtex. Apenas recentemente, no entanto, estas observações ganharam novo interesse, principalmente a luz de teorias e conjecturas que atribuem às oscilações neuronais vários processos cognitivos, como a ligação perceptual, a atenção e a memória. Segundo esta hipótese, oscilações rápidas da retina seriam importantes para a ligação de contornos contíguos ou superfícies, podendo assim constituir um mecanismo feedforward importante na segmentação visual. Em acordo com estas noções, uma série de experimentos no gato mostraram que oscilações rápidas da retina podem ser informativas sobre propriedades globais do estímulo como o seu tamanho.
Uma grande limitação nestes estudos, no entanto, foi o fato de terem sido feitos sob anestesia e paralisia. Apenas alguns experimentos foram realizados em gatos não-anestesiados, mesmo assim, paralisados. Uma outra limitação foi o uso de estímulos visuais limitados a breves exposições, que ocupavam todo o campo visual, muito longe de condições naturais da visão. Por outro lado, muito recentemente, fizemos uma observação inesperada no nosso laboratório: oscilações rápidas da retina dependem fortemente da anestesia por halotano (e isoflurano). Tornou-se assim imperativo investigar se as oscilações rápidas da retina estão presentes ou não no gato não anestesiado, em condições naturais, como por exemplo durante a observação-livre de uma cena visual. Este é o principal objetivo deste estudo.
Para isto, registros simultâneos através de eletródios-múltiplos foram feitos no geniculado lateral e na retina de gatos anestesiados (N= 3) e acordado (N= 1). Comparações foram feitas para respostas a filmes de cenas naturais e estímulos estacionários, como círculos luminosos. Para testar especificamente o papel das oscilações rápidas da retina na codificação do tamanho do estímulo visual aplicamos um protocolo que consiste em apresentar sobre os campos receptores um círculo luminoso de tamanho variável ao longo do tempo. Técnicas de separação de potenciais-de-ação nos permitiu estudar individualmente os componentes ON e OFF das respostas multi-unitárias. Nossa análise consistiu em obter medidas das oscilações sincrônicas para células isoladas ao longo do tempo no domínio temporal (análise de correlação por janela deslizante) e no domínio espectral (análise espectral por afunilamento múltiplo, coerência por afunilamento múltiplo). Estes resultados estendem os nossos achados prévios no gato anestesiado, que foram restritos à análise de auto-correlação de repostas multi-unitárias do geniculado lateral. Tanto as repostas ON como as respostas OFF a estímulos visuais de tamanho variável mostram que oscilações coerentes, que aparecem apenas para estímulos que atingem um tamanho mínimo de cerca de 5° (dependendo do nível de contraste do estímulo). Estes resultados sugerem que oscilações rápidas da retina codificam mal mudanças sutis no tamanho do estímulo visual. Como nos estudos anteriores no geniculado lateral, registros obtidos diretamente da retina mostraram que oscilações rápidas da retina são altamente dependentes dos níveis de anestesia por halotano. E mais importante, em uma série de experimentos pode-se registrar respostas do geniculado lateral em um gato acordado, que foi subsequentemente anestesiado por halotano, mantendo-se o mesmo sítio de registro.
Oscilações rápidas da retina, ausentes durante a condição acordado, apareceram fortes como usualmente na condição de anestesia por halotano.
Estes resultados como um todo enfraquecem substancialmente a noção de serem as oscilações rápidas da retina importantes para o processamento visual. Por outro lado, demonstram que oscilações rápidas da retina podem apresentar propriedades semelhantes a oscilações gama no cortex. Desta forma, oscilações da retina induzidas por halotano podem servir como uma preparação interessante, mesmo se artificial, para o estudo da dinâmica de oscilações neuronais. !!
Palavras-chave: retina, geniculado, oscilação, coerência, halotano, acordado.
LI S T O F F I G U R E S A N D TA B L E S
Figure 1│ Seeing Matisse.
Figure 2│ Why Matisse would never build the collage to the right?
Figure 3│ Fast retinal oscillations.
Figure 4│ Maintained oscillatory responses in the retina and the LGN.
Figure 5│ Synchronization of oscillatory responses in the retina depend on size and continuity of
the stimulus.
Figure 6│ Oscillatory responses vanish in absence of halothane.
Figure 7│ An alert cat during a recording session.
Figure 8│ Head fixation apparatus and recording device X-Y table.
Figure 9│ Schematic representation of the electrodes and guide tubes.
Figure 10│ Recording device
Figure 11│ Visual stimuli used in the experiments in awake cats.
Figure 12│ Single-cell responses in the LGN are often oscillatory.
Figure 13│ Synchronization of ON and OFF-cell responses.
Figure 14│ Fast retinal oscillations arise from population interactions.
Figure 15│ Stimulus size and luminance modulate synchronous oscillations in single-cell responses
of the retina
Figure 16│ Single-cell contribution to a population rhythm.
Figure 17│ ON- and the OFF-oscillations are independent.
Figure 18│ Retinal oscillations in LGN vanish in absence of halothane.
Figure 19│ Oscillations are absent during ketamine anesthesia.
Figure 20│ In the awake cat, fast retinal oscillations are absent.
Figure 21│ Recordings in the LGN of an alert cat and during halothane anesthesia.
Figure 22│ Entrainment of responses to the refresh of a CRT monitor display.
Table 1│ Table 1.
SUMMARY
!AB S T R A C T A N D K E Y W O R D S …………..…….…….………………… 05
RE S U M O E PA L AV R A S-C H AV E …………..…….…….……………… 06
LI S T O F F I G U R E S A N D TA B L E S ………….….….….………………… 08
SU M M A RY ……………………..…….….….….…………………… 10
IN T R O D U C T I O N ……………………..…….….….….……………… 11
1.1 MAT I S S E S C I S S O R S ……………………………………..……… 11
1.3 OS C I L L AT I O N S I N T H E V I S U A L S Y S T E M……..…….……………….. 16
1.4 GR O U N D Z E R O …………………………………………………. 19
2. OB J E C T I V E S ……………………..……..….….……………… 21
Speci f ic goals ……….……….……………….……….…………… 21
3. ME T H O D S ………………………………………………………… 23
3.1 EX P E R I M E N TA L S E S S I O N S…………..…..…..…..…..…..…..…..…. 23
3.1 .1 SU R G I C A L P R O C E D U R E S……………………………….. 24
3.1 .2 RE C O R D I N G S……………………………………….…. 26
3.1 .3 DATA A C Q U I S I T I O N…………………………………..… 29
3.2 . V I S U A L S T I M U L I ………………………………………………… 30
3.4 . DATA A N A LY S I S …………………………………………………… 31
4. RE S U LT S ………………………………………………………… 34
4.1 . S I N G L E-C E L L A N A LY S I S ………………………………………… 34
4.2 . OS C I L L AT I O N DY N A M I C S ……………….………………………. 39
4.3 . DE P E N D E N C I E S O N H A L O T H A N E ……….………………………. 41
4.4 . NO-H A L O T H A N E C O N D I T I O N …………………………………… 41
4.5 . RE C O R D I N G S I N T H E AWA K E C AT………….…… ………………… 42
4.5 . ST I M U L U S E N T R A I N M E N T………….…… …………..…………… 44
5. D I S C U S S I O N ………… …………………………………………… 45
6. CO N C L U S I O N ………………………………………………………… 48
7. RE F E R E N C E S ………………...……………………………………… 49
8. TA B L E S……………………...……………………………………… 56
9. F I N A N C I A L S U P P O RT……….………………………………………… 57
10. AC K N O W L E D G M E N T S……….……………………………………… 58
!!
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Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "11
!!1. IN T R O D U C T I O N
1 .1 MAT I S S E S C I S S O R S
The Matisse: The Cut-Outs exhibition at Tate in 2014, London, was a big
success. Half a million visitors came to see the bold colorful shapes, deceptively
simple, but majestic in their composition and force. Matisse has been always
loved for the warm, intense colors of his paintings. It is his cut-outs, however,
that vibrantly show a dialogue between texture, colors and forms. By cutting
shapes from colored papers, Matisse forges new dimensions of visual expression.
At the same time he exposes the very process of seeing:
It is no longer the brush that slips and slides over the canvas, it is the scissors
that cut into the paper and into the color. […] The contour of the figure springs from
the discovery of the scissors that give it the movement of circulating life. This tool
doesn’t modulate, it doesn’t brush on, but it incises in, […] because the criteria of
observation will be different. Henri Matisse1
In his collages, simple pieces of paper unfold their colors and shapes into
new fresh contexts. Matisse viewed them as virtual worlds, inhabited by flowers,
leaves and birds. So, it is not surprising to find mural-sized compositions in his
late work (Figure 1). He defined cut-out as „painting with scissors“, and saw in it
a source of liberating creativity and joy.
If for Matisse, seeing was a feast for the eyes, for the physiologist it may
represent life enduring questions. How shapes are cut from scenes, colors bound
to surfaces and pieces bound into wholes?
Admittedly, these are hard and largely unresolved problems. Yet, the last
decades have seen important conceptual and experimental advancements.
Basically we are confronted with two sets of questions. The first one refers to
the encoding of features, such as texture, color and shapes. When seeing the
mural in Figure 1, are colors and shapes processed together? Are curves and
1 quoted by Jodi Hauptman, in Henri Matisse The Cut-Outs Art-book, Museum of Modern Art, New York, 2014.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "12
lines represented in the same way? Do we have dedicated circuits for seeing
faces? In the past years, some of these questions could be addressed rather
directly. An invaluable approach has been the characterization of response
properties of single cells, for which the work of Hubel and Wiesel (1961) is a
paradigmatic example. By recording neuronal responses in the visual cortex of
the cat, they discovered that responses can be very selective to specific stimulus
features, such as the orientation and the direction of movement. These seminal
findings triggered a full-blown research program, leading to a detailed account of
how the visual system breaks and encodes bits of visual information (Barlow,
1972). There is today a broad consensus on the parallel and hierarchical
organization of the visual system (Felleman and Van Essen, 1991; Gattass et al.,
2005). This body of knowledge ultimately explains how selective responses to
basic features (such as orientation, color, texture) are combined into higher-
order representations, such as for example during the recognition of complex
shapes or faces (Mazer and Gallant, 2000; Orban et al., 2004; Yovel and Freiwald,
2013).
Figure 1. Seeing Matisse. The Cut-Outs exhibition, Tate Modern, London, April 2014. Photograph by Guy Bell. © REX.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "13
Still, a closer examination of Matisse’s panel reveals a radically different set
of questions. Why do all elements in a flower have the same color? Why colors
do not spill over into neighboring regions? Why we see some shapes as figures,
and some others as ground? Why do we see flowers or faces, and not something
else? Why are shapes sometimes pleasing and intense? These questions are more
difficult, and until recently eluded our best efforts. Essentially they broach
fundamental problems about large-scale integration in the brain. For a long time
we missed a clear understanding of how perceptions, thoughts and emotions are
put together from highly distributed networks. One obstacle comes from the
very dynamical nature of the cognitive processes. Perceptual or emotional
conjunctions are not fixed. On the contrary, they are distinctly contextual and
dynamical. When Matisse says that „the criteria of observation will be different“
he points out to the contextual nature of seeing (Figure 2).
Figure 2. Why Matisse would never build the collage to the right? Although the two pictures share the same local elements, globally they appear radically different. Perception is highly sensitive to context. Blue Nude IV, Henri Matisse, Spring 1952. Gouache on paper, cut and pasted, and charcoal on white paper 102.9 x 76.8 cm © Estate of H. Matisse 2014 (Tate Shop reproduction, London).
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Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "14
From perceptual grouping to contextual inference, shape recognition and
learning — soon it became clear that many aspects of cognition go beyond the
single-cell level. Put simply, one single electrode in the brain would not be enough
for understanding large-scale integration. Meanwhile, multi-electrode recording
techniques, championed by a handful of groups in the 60’s (Gerstein and Clark,
1964; Gerstein and Perkel, 1969, Freeman, 1975), became progressively a routine
in many laboratories worldwide. Today, even a modest laboratory has a high-
density, 128-channel neural signal acquisition system. Surely, this revolution was
only possible because of the accessibility of computers, everyday cheeper and
faster. Considerable efforts have also been made in the design of increasingly
large arrays of electrodes and the development of new bio-compatible implant
technologies.
The problem, however, was not only technological. Key concepts were
missing. What is the nature of the interactions in the brain? What are the
mechanisms that coordinate multi-scale activity bridging different levels in the
neural systems?
An attractive idea was put forward by Christoph von der Malsburg in the
early 80's (Malsburg, 1981; von der Malsburg, 1994; Singer and Gray, 1995). Briefly,
his proposal was that neuronal interactions come about in the time domain, at a
very fine scale (milliseconds). This conjecture was supported by abundant
experimental evidence (Singer, 1999; Buzsáki, 2006). Neuronal responses often
exhibit a fine temporal structure, characterized by periodic fluctuations or
oscillations (Gray and Singer, 1989; Singer, 1993). These observations paved the
now common notion that not only the rate, but also the timing of the action
potentials matters for cognitive processing.
In the visual system, oscillations were known to be an integral component
of the responses in various structures, and at different hierarchical levels. It was
in the cortex, however, that the observation of rhythms turned to be central for
our understanding of mechanisms (Eckhorn et al., 1988; Gray et al., 1989). The
core hypothesis was that the brain provides precise time relationships to build
active conjunctions at the perceptual level. In Figure 2, for example, the same set
of elements are bound into different percepts. In accord to the synchronization
hypothesis, the two figures results from different conjunctions defined by the
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "15
rhythmic firing of the neuronal ensembles. Seeing different compositions implies
in different synchronization patterns, even when the activation levels (rates) are
the same (locally the figures are the same).
The binding by synchronization hypothesis received copious experimental
and theoretical support (Singer, 1993). A first important finding was that
synchronization appeared to be restricted to fast frequencies, from 35 to 85 Hz
— the gamma band (Eckhorn et al., 1988; Gray et al., 1989). Another critical
result in these early studies was contextual sensitivity. Synchronization appeared
only for single-contour objects (such as a single coherent bar, Gray et al., 1989)
and not for contours moving in conflicting directions (Engel et al., 1991), even if
locally the stimuli were nearly the same. These experimental findings were in
agreement with the idea that synchronous oscillations provide a flexible
mechanism for perceptual segmentation and binding. Other studies in cats and
monkeys extended these conclusions, mainly by testing how global properties of
the stimulus modulates synchronization (Engel et al., 1991; Kreiter and Singer,
1996). Castelo-Branco et al. (2000) used bi-stable stimuli (moving plaids) to
demonstrate that response synchronization depends on the transparency of
superimposed surfaces. These results were relevant in showing that
synchronization can flexibly control the segregation of surfaces or objects.
A number of other studies, however, raised serious concern on the
significance of gamma oscillations for feature binding (Merker, 2013). Many
studies, mostly in behaving monkeys, failed to demonstrate a clear correlation
between gamma responses and perception (Thiele and Stoner, 2003; Roelfsema et
al., 2004; Palanca and DeAngelis, 2005; Lima et al., 2009; Ray and Maunsell, 2010;
Burns et al., 2011; Xing et al., 2102). Moreover, based on an information theory
analysis, it has been argued that that gamma oscillations arise because of
unspecific excitation–inhibition interactions in the networks, mechanistically
irrelevant for computations in the brain (Ray and Maunsell, 2015).
Notwithstanding these objections, beyond feature binding, gamma
oscillations have been associated with a number of other cognitive operations,
such as sensorimotor integration, attention, temporal expectancy and memory
(Fries et al. 2001; Womelsdorf et al., 2007; Lima et al., 2000; Engel and Fries,
2016). Gamma synchronization has been related to feature encoding (Vinck et al.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "16
2010; Womelsdorf et al., 2012), a mechanism that could be complementary to
rate (Biederlack et al., 2006). Gamma responses have also been linked to
attention (Engel et al., 2001; Fries et al., 2001, see review in Fries, 2009) and
control of information flow in the brain (Akam and Kullmann, 2012). From an
engineering point of view, phase-locking of periodic signals are ideal for building
flexible relationships in highly distributed parallel networks, and may work as a
very basic mechanism controlling the flow of information in the brain (Akam and
Kullmann, 2014). This may explain why neuronal oscillations are ubiquitous across
diverse neural systems and well conserved during the evolution (Buzsáki et al.,
2013).
1.2 OS C I L L AT I O N S I N T H E V I S U A L S Y S T E M
High-amplitude rhythmic responses have been observed in the visual
system of different species as early as the beginning of the century (Gotch, 1903;
Einthoven and Jolly, 1908; Frohlich, 1914; Granit and Therman, 1935). Oscillations
have been found in retinal activity of various species of different vertebrates
groups, such as the frog (Ishikane et al., 1999), salamander (Wachtmeister &
Dowling, 1978), rabbit (Ariel et al., 1983), cat (Doty and Kimura, 1963; Laufer and
Verzeano, 1967 ; Arnet t , 1975 ; Neuenschwander and S inger, 1996 ;
Neuenschwander et al., 1999) and monkey (Doty and Kimura, 1963). Oscillatory
responses was found at different stages of the visual processing, from the retina
to the cortex. In the retina and the LGN, oscillations were observed in response
to large light stimuli (Neuenschwander et al., 1996), to an homogeneous
illumination of the whole visual field (Laufer and Verzeano, 1967) and
spontaneously, in maintained responses to light and in the dark (Bishop et al.,
1964; Laufer and Verzeano, 1967; Arnett, 1975; Neuenschwander et al., 1999).
Figures 3 and 4 shows examples of these early observations in the cat.
These early studies studies showed that oscillatory responses in the retina
are highly dependent on the size and the contrast of the stimulus. In the cat,
synchronization of oscillatory responses has been observed for distances large as
20 degrees of visual angle across the retina (Neuenschwander and Singer, 1996)
and were found in responses to all functional types (ON and OFF-cells, X- and Y-
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "17
cells) both in the retina and in the LGN (Ariel et al., 1983; Neuenschwander et
al., 1999; Ito et al., 2010).
In the cortex, gamma oscillatory responses (frequencies higher than
30Hz), were first reported in the 30s (Jasper and Andrews, 1938) as early as the
EEG recordings became available and by Adrian, in a study of the olfactory bulb
of hedgehogs (Adrian, 1942). These small variations in the EEG were originally
considered noise, especially when compared with the larger, slower rhythms and
evoked responses. More recently, however, there was a growing interest in fast
rhythms, which may play an important mechanistically role in perception and
cognition (Singer 2001; Singer, 1995; von der Malsburg, 1981).
It is important, however, not to mistake gamma oscillations with the retinal
oscillations. The term fast retinal oscillations are well used for those oscillations
in the 30-120 band generated in the retina but observed both in the retina and
the LGN recordings, since the LGN spiking patterns are inherited from retinal
ganglion cells activity (Sincich et al., 2007). Although fast retinal oscillations are
transmitted to the cortex, they do not necessarily contribute to generate
cortical gamma. In the study of Castelo-Branco et al. (1998) in the cat, data
obtained in simultaneous recordings from the retina, LGN and the cortex (areas
A17 and A18) show that gamma oscillations in the cortex follow a different
dynamics over time. Another important difference is that, in the cortex, gamma
responses are very sensitive to the orientation selectivity of the cells (Gray and
Singer, 1989), a feature that is not encoded in the retina.
Despite numerous studies it is still unknown, how the different features of
a visual scene (as in the Matisse’s cut-outs) are linked or segregated. Several
groups proposes that a possible and efficient mechanism for the linking of regions
and attributes that define the pattern could be based on temporal correlations,
and that the partial coherence of action potentials within a neural population
could be an operating principle for visual binding. Meanwhile, most of the studies
of fast retinal oscillations were made in the anesthetized and paralyzed cat. These
limitations raise questions about the role of oscillations in the retina. Do they
work as a binding mechanism or they are just epiphenomena? Are they an artifact
from the anesthesia?
!
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "18
200 ms
RETINA
RETINA
LGN
Figure 4. Maintained oscillatory responses in the retina and the LGN. Recordings made by Laufer and Verzeano in the 60’s (Laufer and Verzeano, 1967). Upper trace, mass activity recordings from the optic tract. Lower traces, simultaneous micro-electrode recordings from the retina (channels 1, 2 and 3) and the LGN (channel 4). Distances from the electrodes in the retina were about 200 µm. Ganzfeld illumination at 75 lux. Recordings were made in a non-anesthetized, paralyzed cat.
Figure 3. Fast retinal oscillations. Upper left, schematic representation of the experimental setup, recording system and correlation analysis implemented by D. Arnett in 1975. Synchronization was evaluated in realtime with a crosscorrelator device, which computed and displayed a crosscorrelogram between spike trains of two simultaneously recorded cells. Spikes were sorted from MUA signals by a logic circuit (spike classifier) based on time-amplitude window discrimination. Right, cross-correlograms computed for responses of a pair of ON-cells recorded in the LGN of a cat under halothane anesthesia (modified from Arnett, 1975; Figure 9; the bottom correlogram has a higher resolution). Lower left, mass activity traces from the optic tract in a non-anesthetized cat in response to steady illumination (Laufer and Verzeano, 1967; Figure 1).
SCOPE
TAPEREC
AUDIO PRE-AMP
SPIKECLASS
BOARD
MIRROR
CRT
PLOT
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Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "19
1.3 GR O U N D Z E R O
In this study we focus on the role of fast retinal oscillations in visual
processing, without the constrains of anesthesia and paralysis. In the past years,
only a few experiments were made in the LGN to study oscillatory activity (Ito
et al., 2010), and we hoped to offer a fresh view on the results obtained in the
60’s in the non-anesthetized, yet paralyzed cat (Laufer and Verzeano, 1967).
Another motivation for studying the awake cat, however, came from an
observation we made recently in our laboratory, which was quite unexpected.
During an experiment in the anesthetized cat, we were forced to acutely
discontinue the halothane and replace it by ketamine (given i.m.). This happened
unwillingly, because of a failure in exchanging a gas bottle. The experiment was
running well, and as in many other occasions we were able to observe stunning
fast oscillations in the LGN.
A few minutes after withdrawing the halothane, however, for our surprise
and bewilderment, the oscillations vanished almost completely from the
responses (Figure 6). These unexpected findings prompt us to carry out a series
of new experiments to verify whether oscillation strength correlates with
Time (ms)
3° 3°
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2
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109 Hz 104 Hz
111 Hz
104 Hz
106 Hz
Figure 5. Synchronization of oscillatory responses in the retina depend on size and continuity of the stimulus. Notice that synchronization appears only the stimulus was continuous bridging the two receptive fields. RF distance, 6°. Responses from a pair of two ON-cells. Recordings were made directly from the retina, during halothane anesthesia (modified from Neuenschwander and Singer, 1996).
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "20
halothane concentration levels. We made also tests for isoflurane, which has
similar pharmacological properties. Our preliminary results in the LGN were
very conclusive. Retinal oscillations appears to be highly dependent on halothane
anesthesia.
Are fast retinal oscillations (at least in the cat) an artifact from the
halothane anesthesia? Do they play a role on vision as we initially thought
(Neuenschwander and Singer, 1996)? With the present study we want to provide
a definitive answer to these questions. Our main approach will be to characterize
the oscillatory behavior of the responses in the awake cat, under naturalistic
conditions, such as during free-viewing of a visual scene, and compare to data
obtained during anesthesia by halothane (or isoflurane) and by ketamine (control
experiments).
Figure 6. Oscillatory responses vanish in absence of halothane. The horizontal stripes in the sliding window analysis plots (left) reveal the oscillatory modulation of the responses, which very strong for a halothane concentration of 1.0%. Notice that removing the halothane leads to a slight increase in response levels (histograms, right). Oscillation frequency, 72 Hz. The stimulus was a bright disc presented over the RFs, with luminance increasing linearly. Stimulus size, 12°(from Freitag, 2013; Figure 20).
12°
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Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "21
2. OB J E C T I V E S
!The primary goal of this study was to test whether fast retinal oscillations
are present or not in conditions compatible with natural seeing. This involved (1)
recording directly from the retina of the anesthetized cat to study spiking
responses to dynamical stimuli, such as natural scenes movies and varying-size
stimuli and (2) obtain data from the alert cat, removed from any influences of
anesthetic agents.
Recently we have shown that halothane and isoflurane are responsible for
the generation of fast rhythms in the retina. This first study, however, was limited
to an autocorrelation analysis of multiunit responses in the LGN. Here, we aim to
extend and refine these results by recording single-cell activity simultaneously
from the retina and the LGN. Comparisons will be made for recordings under
halothane (isoflurane) and ketamine anesthesia, and also for recordings under
ketamine anesthesia without previous exposition to halothane (ketamine-only
condition). Finally, these results will be compared to data obtained in the alert
cat.
Quantification of the oscillatory dynamics will be based on a sliding-
window correlation analysis and multiaper spectrum and coherence of single-cell
spiking responses.
!Speci f ic goals
!• To compare the oscillatory behavior of the retinal responses under
halothane (or isoflurane) and ketamine anesthesia;
• To verify at the single-cell level whether breaking of stimulus continuity
disrupts synchronous oscillatory responses;
• To verify at the single-cell whether synchronous oscillatory responses are
also present in responses when probed with dynamical stimuli, such as
natural scene movies and size-varying stimuli.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "22
• To record LGN responses in the cat under ketamine anesthesia without
previous exposition to another anesthetic (ketamine-only condition).
• To record LGN responses in the awake cat.
!!!!!!!!!!!!!!!!!!!!
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "23
3. ME T H O D S
Adult cats from our colony (BSIC-Instituto do Cérebro - UFRN) were
used in this study (N= 5).
All experimental procedures were approved by the ethical committee for
animal experimentation of the Universidade Federal do Rio Grande do Norte
(CEUA-UFRN protocol nº 019/2012) and were in compliance with the guidelines
of the European Community for the care and use of laboratory animals
(European Union directive 86/ 609/EEC).
3.1 EX P E R I M E N TA L S E S S I O N S
In a first set of acute experiments, recordings were made from the LGN
and the retina of anesthetized and paralyzed cats (N= 3). Different anesthetics
were used during the same experimental session. Generally we started a session
with ketamine (induction), followed by halothane, which subsequently could be
replaced by isoflurane or combined with ketamine. Ketamine was always applied
if halothane or isoflurane were to be absent (usually less than 1 hour periods),
assuring a surgical plane of anesthesia during all procedures. In these experiments
the cats were not recovered at the end of the recordings, which typically lasted
for 96 hours (4 continuous days).
In addition to this group we were able to record from the LGN of cats
(N= 2) without any immediate exposition to halothane (or isoflurane). For this, a
recording chamber was chronically implanted on the skull. Typically, these cats
were submitted to multiple recording sessions (~ 10 sessions), which lasted for 3
to 4 hours. In one series of experiments, recordings started after ketamine
anesthesia, the ketamine-only condition (since previously the cat received no
other anesthetic than ketamine). In another series, recordings were made in the
awake cat (N= 1), without influence of any anesthetic agent, the awake condition.
To this aim, one cat was habituated over several months to sit quietly with its
head fixed for 2 to 3 hours (Figure 10). During the training and recording
sessions cat food rewards were always given abundantly. In 2 occasions, we were
able to sample data from the same LGN recording sites for all three conditions
(awake, ketamine-only, halothane).
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "24
Figure 7. An alert cat during a recording session. In our study one cat (shk) was trained to sit quietly while having the head fixed. We were able to obtain stable recordings from the LGN over a few hours. Notice that the cat was fixed by the two recording chambers. In general cat with their heads fixed stare at the monitor, making possible to coarsely map the RFs (see example in Figure XX).
Figure 8. Head fixation apparatus and recording device X-Y table. The head of the cat was held by two identical chambers chronically implanted on the skull (only the recording chamber is shown). The fixation system had a long column (see Figure 10), in which a L-shape plate was mounted (model shown to the left). A bored cylindrical adapter was screwed to the recording chamber (14 mm in diameter, 1.0 mm thread). The X-Y table and recording device were than attached to the L-plate with this adapter (see Figure 12). 3D modeling by Heitor Bernardino de Oliveira, Instituto do Cérebro - UFRN, Natal.
X-Y Table
Device guiding bars
Guide tube positioning scale
Frame column
L-shape headholder
Adaptor
AP-positioning knob
Recordingchamber
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "25
3.1 .1 SU R G I C A L P R O C E D U R E S
For the acute recordings a single large recording chamber (15 mm in
diameter) was surgically cemented on the skull at the beginning of the
experiment. Generally, this procedure took a few hours to be completed. After
that, the cranium was opened, the dura removed and the cortex above the LGN
exposed. Electrodes were than positioned into the LGN (centered on Horsley-
Clarke coordinates AP 6 to 7, ML 9 to 10), and the recording sessions started.
Before the surgical procedures, the cats received atropine sulphate
(Atropion, Ariston, Brazil, 0.1 mg/kg i.m.) and were sedated with Xylazine
(Xylazin, Syntec, Brasil, 0.25 mg/kg i.m.) combined with Ketamine (Cetamin,
Syntec, Brasil, 10 mg/kg, i.m.). The cats were than intubated (Braun cuffed
endotracheal tube, Germany, 3.5 to 4.0 mm) and artificially ventilated. Anesthesia
was maintained with 0.8 to 1.2% halothane (Halotano, Hoechst do Brasil) in a
mixture of oxygen (30% to 40%) and nitrous oxide. The volume of the respiration
pump (35 to 45 ml) and the respiration frequency (14 to 20 stokes/ min) were
adjusted to yield a ventilation pressure of 7-10 mbar and expiratory CO2 in the
range of 2.6 to 3.5%. A rectal thermometer connected to a heating pad unit was
used to maintain body temperature at 38°C. Relevant parameters for life support
(EKG, temperature, expiratory CO2 and SpO2 trends, inspiratory and expiratory
halothane and oxygen concentrations) were monitored continuously by means of
a patient monitor (Dash 3000, linked to a Smart anesthesia multi-gas unit, GE
Heathcare, USA). Fluid loss was compensated by infusion of saline solution
(Braun infusion pump, Germany, 6 ml/h i.v.).
In order to record from the retinal ganglion cells we employed the
intraocular recording technique originally developed by B. G. Cleand in Camberra
during his seminal work in the retina (Cleland et al.,1971), and posteriorly
modified by Heinz Wässle in Konstanz (Wässle and Peichel, 1979). We used a
modified stereotaxic frame (Wässle, 1975), which left the orbit of the cat free,
thus, making easy the placement of the recording device. After opening the skin
laterally to the canthus, the conjunctiva around the eye ball was cut and the
sclera exposed. A steel ring was then fixated to the sclera just behind the limbus
by means of 5 to 7 modified Donati stitches. The stitches were distributed
equally around the globe, assuring a strong bound between the sclera and the
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "26
ring, which was hold in place by a long articulated horizontal arm connected to
the stereotaxic apparatus. By releasing a single screw, one could rotate the ring
to a desired position, and consequently the eye. We used a fundus camera (Zeiss,
Germany) to determine the best position of the eye as a function of the retinal
landmarks (the area centralis and the optic disc) which were projected on the
computer screen used for visual stimulation. A bored plate fixed to the ring
supported the recording device, so no pressure was applied to the eye. After
opening the sclera with a cauterizer (Fine Science Tools, Germany), the
electrodes (mounted in individual guide tubes) were inserted into the eye though
a cannula (1.2 x 10 mm). The apparatus had a spherical bearing allowing angular
rotations of the cannula in the posterior chamber of the eye. In this way, with
help of the fundus camera, we could aim the electrodes to almost any desired
Figure 9. Schematic representation of the electrodes and guide tubes. The quartz electrode is connected to the glass piston and the cable with a soldering pellet (melted by a hot air blower). A staple can be used for the L-shape arm element. Notice that the electrodes can be loaded into the guide tubes from above, simplifying exchanges. Electrode length, 100 mm. Distance between the grid and guide tube, 45 mm. Glass piston, 30 mm, diameter of 2.7 mm. For clarity elements are not drawn with the same scale. Developed jointly by Bruss Lima, Sergio Neuenschwander, Jerome Baron and Johanna Klon-Lipok at the Max-Planck Institute for Brain Research, Frankfurt.
Piston (glass)
Soldering pellet
Fixation ring
Narishige microdrive
Microdrivepiston
Needle 0.6 mm(steel)
Quartz electrode
Needle 0.3 mm (steel) 2X
Heat shrinkingtube
Grid (nylon)
Plate (Plexyglas)
Pin connector
Cable
L-shape arm(steel)
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "27
location in the retina. This technique yielded very stable recordings from the
retinal ganglion cells. Experiments were discontinued only when the optics of the
eye start to deteriorate, what usually happened in 2 to 3 days.
For the semi-chronical recordings two small titanium chambers (6 mm in
diameter) were surgically implanted on the skull at the position of the LGN in
the two hemispheres, respectively. The chambers were identical, but only one of
the two was actually used for the recordings. After opening the skin and exposing
the cranial vault, 10 to 13 self-tapping titanium screws (Synthes standard cortex
screws, Germany, 2.0 mm) were placed into the bone following a horizontal plane
just above the zygomatic arc. Acrylic cement (Paladur, Heraeus Kulzer, Germany)
was then spread in successive layers, to build a prothesis anchoring the chambers
and fixation screws. We observed a one-month recovery period before starting
the recording sessions. Typically recording session were scheduled one every 1-2
weeks. Implanted cats were not hindered by the prothesis. Local infections were
controlled by daily cleaning the skin borders with saline and topic oxygenated
water. These cats led a normal life among the others in the colony, with no signs
of discomfort or distress (one of our cats is already implanted for more than 1
and 1/2 year).
3.1 .2 RE C O R D I N G S
This study is entirely based on extra-cellular recordings of action
potentials (multi-unit and single cell activity).
We used quartz-electrodes (tungsten-platinum fiber electrodes insulated
by quartz, Thomas Recording, Germany, 80 μm in diameter). These electrodes are
known to have a good signal to noise ratio, and are rigid enough to penetrate the
brain (or the vitreous) undeviatingly.
In all experiments we employed a customized recording device (designed
by Sergio Neuenschwander at the Max-Planck Institute for Brain Research,
Frankfurt). Essentially it consists of 5 oil hydraulic microdrives (MO-95, Narishige,
Japan) mounted in a movable platform (Figure 12). The quartz electrodes are
placed in single guide tubes, which are mounted into a grid (determines the
spacing of the electrodes). A glass capillary mounted at the end of the guide
tubes serves as a piston for moving the electrodes. These pistons are connected
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "28
to their respective drivers by teflon elements. Our recording device allows for
the placement of the guide tubes to a desired depth (all together, with their
electrodes). The electrodes, in turn, can be moved independently (fine
displacements controlled by the microdrive units) or as a group (coarse
displacements controlled by a vertical screw). As shown in Figure 13 the guide
tubes consists of two thin needles (Ehrhardt Supra, Germany, 0.3 x 23 mm)
mounted inside a thicker cannula (Braun 100 Sterican, Germany, 0.6 x 60 mm)
and glued in place with an instant adhesive (Super Bonder, Loctite, Brasil). The
thin needle provides a a good cutting edge when moving the guide tubes through
the tissue.
The recording device was fit with a X-Y positioning system (part of the
Narishige MO-95 recording system), allowing for systematic positioning of the
electrodes in the horizontal plane (see Figure 13). This was particularly useful for
localizing the LGN. Our recordings were aimed at the region of central
representation of the visual field (less than 10 degrees of eccentricity).
For the recordings from the LGN, the guide tubes were first placed 5 to 7
mm above the the nucleus and than moved slowly, one by one, until lamina A was
Figure 10. Recording device. Our device allowed for independent positioning of the guide tubes and the electrodes. It was mounted on a X-Y table which was attached to the head-holder plate by a cylindrical adapter (See Figure 11). Device structure was made in PEEK. Designed by Sergio Neuenschwander at the Max-Planck Institute for Brain Research, Frankfurt. 3D modeling by Heitor Bernardino de Oliveira, Instituto do Cérebro - UFRN, Natal
Microdrive
Electrode coarsepositoning scale
Electrode coarsepositoning knob
Fixation ring
Grid
Glass piston
Guide tube
AP-Guide tube positioning knob
Pexyglas plate
Stopper
L-shape arm
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "29
found (robust reposes to the contralateral eye). Typically 3 to 4 electrodes were
used for the LGN recordings, both in the anesthetized and alert cats.
For the intraocular recordings we used a similar approach. The guide tubes
penetrated the vitreous in the posterior camera, and were placed a few
millimeters above the retina. Than they were moved individually under visual and
acoustic control (listening to the recorded spiking activity), until they reached
the retinal ganglion cell layer. Usually 2 to 3 electrodes were used for the
recordings in the retina.
In all experiments in which inhalation anesthesia was applied (either acute
or semi-chronical) eye movements were blocked by the intravenous infusion of a
paralyzing agent (pancuronium bromide, Nova Farma, Brazil, loading dose of 0.5
mg/kg i.v., maintenance dose of 0.25 mg/kg/h i.v.). After paralysis, the pupils were
dilated with topical application of atropine sulfate (Atropine-POS, Ursapharm,
Germany, 1%) and the nictitating membrane retracted (Neosynephrin, Ursapharm,
Germany, 5%). The cornea was protected with contact lenses containing artificial
pupils of 2 mm diameter. The eyes were focused on the stimulus monitor with
add of correcting lenses whenever necessary (Rodenstock manual refractometer,
Germany).
3.1 .3 DATA A C Q U I S I T I O N
Spiking activity from neuronal groups (MUA) were recorded after
amplification and band-pass filtering of the compound signals (0.7 – 6.0 KHz)
with a 32-channel Plexon modified preamplifier and a HST16025 headset (Plexon
Inc, Dallas, TX, USA). Data acquisition made with the SPASS software (written in
LabVIEW by Sergio Neuenschwander at the Max Planck Institute for Brain
Research), based on M-series NI acquisition boards (National Instruments, USA).
Signals were sampled at 32 kS/s with an additional 10 X onboard amplification.
Spikes were detected after a simple amplitude threshold algorithm, typically set
to twice the noise level.
The SPASS software provides modules for on-line visualization of the spike
waveforms, response trends and on-going autocorrelation function. Because our
analysis is focused at the single-cell level, we generally adjusted the position of
the electrodes to yield maximal responses and big spike waveforms. The online
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "30
information of the temporal structure of the ongoing responses was also very
useful to guide the experiments.
!!!!3.2 . V I S U A L S T I M U L I
Visual stimuli were presented on a 21” CRT monitor (Hitachi, CM803ET),
placed about 57 cm from the cat. Refresh rate was set to 100 Hz (except for the
protocols used for evaluation of stimulus entrainment, see Results section) at a
resolution of 1024 x 768 pixels (1.0° of visual field corresponded to 25 pixels).
S t imulus presentat ion was contro l led by the Act iveSt im sof tware
(www.activestim.com). Protocols consisted of a series of 10 to 250 repetitions
(according to the number of conditions of each stimulus protocol). For all
protocols, the different stimulus conditions were presented in a random order.
At the beginning of the recording sessions, RFs were searched with a
variety of stimuli, such as black and white cardboard, the experimenter’s hands
(Figure 7) and a handheld DC-light projector. If robust responses were found we
proceeded to an automatic mapping of the RFs (Fiorani et al., 2014; see a
comparison of various mapping methods in Pipa et al., 2012). Essentially this
procedure consisted in presenting a high-contrast bar (10 X 1000 pixels) at 16
different directions of movement (step of 22.5°). RF maps were obtained by
computing a response matrix with 10 ms resolution, corresponding to
approximately 0.2° in visual angle (see example of Figure XX). Generally, stimuli
LIGHT PATCHGRAY-LEVEL BINARY
Figure 11. Visual stimuli used in the experiments in awake cats. Stimuli were large covering circa of 20° of visual angle centered at the computer screen. Gray-level natural scene movies had 200 luminance values. Binary natural scene movies were displayed with 2 luminance values (black and white). All stimuli were smoothed spatially to avoid responses to high contrast borders. Circle indicates typical RF position relative to the stimulus.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "31
were centered on the receptive fields altogether (only in selected cases the
stimuli were centered on individual receptive fields).
3.4 . DATA A N A LY S I S
Our analysis is focused on evaluating the oscillatory behavior of single-
cells responses (SUA), which could be grouped to yield a small population signal
of same response polarity (ON or OFF-cells MUA). In our analysis we used the
NEUROSYNC package developed in LabVIEW (National Instruments, USA) by
Sergio Neuenschwander and Jerome Baron. Additionally, we used Matlab
(MathWorks, USA) routines of the Chronux (www.chronux.org), an open-source
analysis software (see discussion in Mitra, 2007), which were embedded in the
LabVIEW environment. Spike sorting was carried out with SpikeOne (a LabVIEW
program written by Sergio Neuenschwander) relying on principal component
analysis of the spike waveforms and k-means clustering analysis (Machine
Learning LabVIEW toolkit). Numerous visualization and analytical tools, such as
the refractory period seen in autocorrelograms, were available to further guide
the refinement of the sorting (merging of clusters, exclusion of spike waveforms).
The oscillatory behavior of the responses was first assessed in the time
domain. For all data we carried out an average sliding window correlation analysis
(200 ms window in 50 ms steps), so we could follow the oscillatory behavior of
single-cells over time. This analysis proved to be very useful for the sorting
refinement, since the ON and OFF components could be easily identified in the
responses (see example in Figure 14). Trends and discontinuities in the oscillation
strength, frequency, phase were quantified by computing average auto- and cross-
correlations of SUA and MUA within 500 ms windows (sometimes we used
shorter windows as indicated in the figures).
Quantification of oscillation strength and frequency were made in the
spectral domain. We use the multitaper Chronux functions mtspectrumpb and
coherncypb for spectral analysis and coherence, respectively.
In brief, multitapering methods attempt to reduce the variance of spectral
estimates by multiplying the data with several orthogonal tapers (slepian
functions). Therefore, the frequency decomposition of the data yields
independent spectral estimates which is less sensitive to noise. The multitapered
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "32
power spectrum of a time series is defined for a given frequency as an average
across all repetitions and tapers:
!!!!
where
!!
is the discrete Fourier transform of the product of the measured time series
sequence { ��� , n = 1, 2, ..., ��� } with the ��� -th slepian taper, denoted by
��� . Numerically, ��� is computed as the FFT of the product. In our
analysis data were padded with zeros to the length of 2048 before the Fourier
transform. Five slepian tapers were used. Thus, we obtained a spectral resolution
of ±5 Hz and ±15 Hz for a 500 ms and a 200 ms window, respectively.
Synchronization of the oscillatory responses was evaluate by the
coherence, defined as:
where ��� and ��� are the multitapered power spectrum estimates of the
time series ��� and ��� averaged over n repetitions, respectively, and ���
is the cross-power of these two time series. Coherence provides a normalized
metric of linear dependencies between two processes, scaling from 0.0 to 1.0.
For a noiseless data, a coherence value of 1.0 should be obtained at all
frequencies if two processes are linearly related (i.e., their amplitude covary and
Sx f( ) Sy f( )
xn t( ) yn t( ) Syx f( )
Cyx f( ) =Syx f( )
Sx f( )Sy f( )
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "33
they share a constant phase relationship). If the two processes are completely
independent, coherence should be equal to 0.0.
The 95% confidence bounds for the spectral estimates were determined
by the jack-knife method across tapers and trials, as implemented in the Chronux
software.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "34
4. RE S U LT S
In a first set of experiments, carried out in cats anesthetized with
halothane, we describe at the single-cell level the characteristics of oscillatory
responses in the LGN. We employed dynamical stimuli, such as varying-size bright
discs and movies, to follow the synchronization behavior of the responses over
time (e.g., oscillation strength and frequency). Our single cell analysis allowed us
to follow independently the ON and OFF-components along the responses.
In a second set of data, we present the effects of varying the
concentration level of halothane. Occasionally we also employed isoflurane, an
halogenated anesthetic similar to halothane. As a control, we compare the effects
of ketamine, either combined to halothane (or isoflurane) or after the halothane
withdrawing test.
By recording directly from the retinal ganglion cells with intraocular
electrodes, we show direct evidence whether halothane affects the generation of
oscillations within the retina (and not at the thalamic level). In a few cases
recordings were carried out simultaneously with the LGN, enabling us to follow
the effects of anesthesia a the two levels, retina and thalamus.
In a last series of experiments, data were obtained in absence of
halothane. In two cats, recordings were made from the LGN under ketamine
anesthesia, without previous exposition to halothane (the ketamine-only
condition). Finally, we present LGN data obtained in a freely viewing cat.
4.1 . S I N G L E-C E L L A N A LY S I S
Single-cell responses in the LGN are often oscillatory. In Figure 12,
recordings were made from Lamina A of an anesthetized cat with halothane. A
sliding window correlation analysis reveals very strong oscillations for cell
responses of both ON and OFF-polarities. The light stimulus evoked strong
responses in one ON-cell (1a), which persisted for a few hundred milliseconds.
Notice, however, that oscillations are absent at the very transient component of
the responses to the onset of the stimulus (seen as a sharp peak in the response
traces). This was characteristic in most of the recordings (see examples in
Figures 13, 14 and 15). Likely, oscillations may take up to 100 msec to build,
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "35
persisting afterwards in the late components of the responses. Interestingly, the
responses of the OFF-cells to the offset of the light stimulus appeared
instantaneously, without the characteristic non-oscillatory component of the
ON-cells (Figure 12, unit 1b; Figure 3, units 1b-2a in the retina). These
differences were consistent among many of our recordings, despite the
considerable smoothing inherent to our sliding analysis, which may hide sharp
transitions along the responses (typically we used a widow of 200 msec with a
step of 20 msec). Contrary to previous observations from MUA responses
(Neuenschwander et al., 1999), our single-cell analysis revealed no significant
differences in oscillation frequencies for the ON- and OFF-cell responses (see
examples in Figures 12 and 13), in accord with the findings of Ito et al., 2010).
Likely, fast oscillations in the retina arises from interactions among
neighboring retinal ganglion cells. A strong evidence is shown in Figure 14.
Recordings were made in the retina under halothane anesthesia. Auto and cross-
0.5
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Figure 12. Single-cell responses in the LGN are often oscillatory. Strong oscillatory responses were observed for single-cells of both ON- and OFF-polarity (upper and middle sliding correlation analysis plots). Notice that not every cell oscillates. The response of the ON-cell shown in the lower plot, although robust and sustained, has no signs of temporal structure. Response traces are shown to the right. Responses to a bright disc flashed over the RFs. Stimulus size, 11°. Anesthesia, halothane.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "36
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80Time (ms) Frequency (Hz)Time
1a - 2bR E T I N A
ON-cells
1b - 2aR E T I N A
OFF-cells
Figure 13. Synchronization of ON and OFF-cell responses. Simultaneous recordings from 2 pairs of cells in the retina. Each pair of units were obtained from separated channels. Synchronization of the ON-cells are shown above, while the OFF-cells below. Left panels, average sliding window analysis. Middle panels, average cross-correlation function computed within a 500 ms window (indicated by the black bar in the sliding correlation plot). Right panels, multitaper coherence analysis. ON-cell oscillation frequency, 74 Hz. OFF-cell oscillation frequency, 78 Hz. Responses to a bright disc flashed over the RFs. Stimulus size, ~20°. Anesthesia, halothane.
Tim
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s)
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- 50
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Tim
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s)
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shk011j02 3a, 3b, 3c, 3d shk011j02 3a, 3b, 3c, 3d shk011j02 3a, 3b, 3c, 3d
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inci
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1a
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(1b,1c,1d)
TimeTime
LGN
Figure 14. Fast retinal oscillations arise from population interactions. Data obtained from 4 cells recorded simultaneously from the same electrode. Left panels, sliding autocorrelation functions. Right panels, cross-correlation functions between unit 1a and each one of the 3 other units (1a-1b, 1a-1c and 1a-1d). Observe that for the individual neurons oscillatory patterns were often weak and discontinuous. The central bin in the crosscorrelogram is equal zero because superimposed spikes were discarded in the spike sorting process. Oscillation frequency, 78 Hz. Responses to a light circle. Stimulus size, ~20°. Anesthesia, halothane.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "37
correlation analysis show that even though individual cells may exhibit weak or
discontinuous oscillatory patterns, at the population level, oscillations are strong
and stable (oscillation frequency, 78 Hz). This means that, despite firing in an
strong oscillatory manner, the individual cells may skip many cycles, a feature also
described in the cortex (Nikolic, 2013).
However, it needs to be emphasized that not all cells of same polarity
contributed to the oscillations seen in the MUA signals. A clear example is shown
in Figure 12 (unit 1c). While one of the two ON-cells recorded exhibited a very
strong oscillation, the other showed no signs of oscillatory patterning, even
though the two response is equally robust. Interestingly these two cells have
clearly different response profiles (unit Ic exhibits a sustained response
compatible with a X-cel, while unit 1b exhibits a transient response, compatible
with Y-cell). Although beyond the scope of this study it would be interesting to
see whether the different functional types (X or Y-cells) are capable of
synchronizing their responses, depending on the characteristics of the stimulus.
nal004l01 17a 18b
Tim
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s)
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Coi
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0.9
2°
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1a - 2aSize
1°
nal004k02 18c
nal004k02 17a, 17c
1aON-cellRETINA
ON-cell2a
RETINA
1°
Figure 15. Stimulus size and luminance modulate synchronous oscillations in single-cell responses of the retina. Cross-correlation sliding window analysis show a strong correlation between the size and the stimulus and oscillation strength. Data obtained for 3 different luminance levels (175, 80, 50 Lux).
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "38
As previously described for MUA responses (Neuenschwander et al.,
1999), synchronous oscillations in the retina and the LGN were very sensitive to
these size of the stimulus. In Figure 15, a strong correlation between stimulus
size and oscillation strength. We used 6 different sizes of the stimulus at 3
luminance levels (175, 80 and 50 Lux, corresponding to contrast ratios of 0.9, 0.6
and 0.3). From the plots in Figure 15, it is obvious that oscillation strength
increased non linearly as a function of stimulus size. At a relatively high luminance
level (50 Lux in our experiments, contrast of 0.3) only a circle size greater than
6° degrees sufficed to trigger oscillatory responses. Likely, a critical size value had
to be reached for the spreading of oscillation among activated mass of retinal
ganglion cells.
In our experiments, synchronization was always accompanied by
oscillations. For a pair of cells Depending on the stimulus conditions, the
coherence values could be surprisingly high, near the maximal value of 1.0 (see
examples in Figure 13 and 16), indicating that spikes exhibited very consistent
phase relations.
!!!
40 120Time
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120
40
TimeFrequency (Hz)
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(Hz)
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R E T I N AON-cells
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nal004l04 17a, 18b (2)
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t ra
te (
sp/s
)
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Rat
e (s
p/s
)
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20
Figure 16. Modulation of the oscillatory to a size-walk stimulus. The size-varying stimulus led to a very strong modulation of the responses. The coherence between the two cells was much less sensitive to the variation in size, not following the rates.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "39
4.2 . OS C I L L AT I O N DY N A M I C S
To test how robust would be an oscillation-based encoding mechanism in
the retina, we followed the oscillation dynamics (strength, frequency and phase)
of responses to dynamical stimuli, such as size- or luminance-varying bright discs
(random walks) or natural scene movies. In the experiment shown in Figure 16,
we used 3 different size-varying functions for a bright disc (size-walk stimuli)
presented over the RFs of two ON-cells in the retina. As expected, the size-walk
stimulus led to a very strong modulation of the responses. Interestingly, the
coherence between the two cells was much less sensitive to the variation in size,
definitively not following the rates (see middle panels in Figure 16). Moreover,
the oscillation frequency tend to decrease smoothly after the onset of the
oscillations (starting around 200 msec after the appearance of the stimulus). This
decay in frequency was probably due to a single global oscillatory process,
because in general there was no discontinues or transients in frequency or phase
(see frequency plots in Figures 16). It has been observed in virtually in all data, in
the retina and LGN, and can be considered as a hallmark of the fast retinal
oscillations (see also examples in Figures 13 and 15).
Time
80
120
40
Time
80
120
40
Freq
(Hz)
80
120
40
1a
(1a, 1b)R E T I N A
ON-cell
1bOFF-cell
500 ms
0
80
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cgl07a03 17a (3)
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0.1
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Coi
ncid
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s
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Rat
e (s
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Figure 17. ON- and the OFF-oscillations are independent. Cross-correlation sliding window analysis for two cells of opposite polarity recorded in the retina.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "40
However, depending on the size history of the stimulus (and consequently
on the size history of the population of active cells), the oscillation process could
be reset. In Figure 16, when the stimulus decreases in size so extremely that the
cell responses cease (see arrowhead in the frequency plot), there is a jump in the
oscillation frequency for the upcoming response (from 73 to 81 Hz), at the very
moment the stimulus reaches de novo a critical size.
Resets in global ongoing oscillations were found both for ON and OFF-
cells. An intriguing example is shown in Figure 17. In this case the size-walk
stimulus was centered at a point outside the RFs of two cells recorded in the
retina. The cells had opposite polarity and overlapping RFs. Thus, when the size-
walk stimulus invaded the RFs the ON-cell fired while the OFF-cell silenced. The
inverse occurred for when the stimulus left the RFs. This explain why the
responses barely overlapped. There were a few resets in the oscillations for both
the ON and the OFF-responses. Remarkably, the oscillations resets were
independent of each other, indicating that the ON- and the OFF-oscillations do
not share a common input.
T imeT ime
1.0%
0.6%
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cgl03e07 5 (2)
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HALOTHANE
Figure 18. Retinal oscillations in LGN vanish in absence of halothane. Left panels, sliding window correlation for responses to a natural scene movie. Right panels, responses to a large patch of light. Observe that the effects on oscillation strength do not correlate linearly with the concentration levels of halothane (already at 0.6% oscillations ceased almost entirely). Firing rates are slightly augmented after halothane withdraw, indicating that halothane causes a slight depression in the general activity of the retinogeniculate system.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "41
4.3 . DE P E N D E N C I E S O N H A L O T H A N E
As described recently for MUA responses (Freitag, 2013), single-cell
oscillations are unambiguously correlated to the level of halothane anesthesia.
Figure 18 documents how varying the halothane concentration affected
the oscillatory behavior for SUA recordings in the LGN for responses to a natal
scene movie and a large patch of light. Observe that the effects on oscillation
strength do not correlate linearly with the concentration levels of halothane
(already at 0.6% oscillations ceased almost entirely). Firing rates are slightly
augmented after halothane withdraw, indicating that halothane causes a slight
depression in the general activity of the retinogeniculate system. As indicated in
the Methods section, it is important to mention that before removing the
halothane, we supplemented the anesthesia with ketamine.
We found evidence that isoflurane, an anesthetic agent with similar
pharmacological properties to halothane, is also capable of inducing strong
oscillations in the retinogeniculate responses (data not shown).
Taken together, these findings indicate that halogenated anesthetics have a
profound effect in the temporal patterning of single cell responses.
4.4 . NO-H A L O T H A N E C O N D I T I O N
In a series of experiments, data were obtained in the complete absence of
halothane (N= 2 cats). For this, recordings were made from the LGN under
ketamine, without immediate exposition to halothane (the ketamine-only
condition).
Tim
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cgl03d11 4a-4b
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cgl03d04 4b
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LGN
ON-cell1b
LGN
2°
804010 120
804010 120
92 Hz
Frequency (Hz)
0.0
1.0
0.0
1.0
Figure 19. Oscillations are absent during ketamine anesthesia. Ketamine was given without previous exposition to halothane (ketamine-only condition). Notice that very strong synchronous oscillations appear after administration of halothane (0.6 %). Coherence is shown to the right. Oscillation frequency 92 Hz. Pair of ON-cells in the LGN. Overlapping RFs.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "42
Figure 19 shows an example for responses in the LGN of two cells with
overlapping RFs. Synchronous oscillations that were completely absent from the
responses in the ketamine-only conditions, appeared strong as usual when
halothane is administered to the cat.
4.5 . RE C O R D I N G S I N T H E AWA K E C AT
Finally, in last series of experiments in one awake cat (shk) we could verify
whether fast retinal oscillations are present during a freely viewing condition.
As indicated in Figure 21, in absence of halothane the strong oscillations
in the LGN responses disappear.
Notably, in a series of sessions we were able to record LGN responses in
an awake cat, which was subsequently anesthetized with halothane, keeping the
same recording site (Figure 22). Oscillations were completely absent in the
awake condition and appeared strong as usual during the halothane anesthesia.
!
Time (ms) Frequency (Hz)Time804010 120
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shk005e01 4a, 4b, 4c, 4d, 4f
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0.0
11
KETAMINEONLY
AWAKE
1.0%HALOTHANE
20°
(1a, 1b, 1c, 1d)
LGNON-ce l l s
Figure 20. In the awake cat, fast retinal oscillations are absent. Analysis was made for jointly responses of 4 ON-cells recorded simultaneously in the LGN, lamina A. Notice that the oscillations are completely absent from the responses for the awake cat and for the ketamine-only conditions. Following administration of halothane characteristically strong oscillations appear. Sliding window autocorrelation functions are shown to the left. Spectral analysis is shown to the right. Oscillation frequency 86 Hz. Overlapping RFs (plots are not shown).
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "43
!!
Time (ms) Frequency (Hz)Time804010 120
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(KETAMINE)
AWAKE
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(1a, 1b) - (1c, 1d)
LGNON-ce l l s
(1a, 1b) - (1c, 1d)
LGNON-ce l l s
20°
Figure 21. Recordings in the LGN of an alert cat and during halothane anesthesia. Jointly responses from 2 pairs of ON-cells recorded simultaneously in lamina A1of the LGN. In this experiment, we were able to record LGN responses in an awake cat (shk), which was subsequently anesthetized with halothane (same recording site). Notice that exorbitantly strong oscillations appear following administration of halothane (1.0%). The central bin in the crosscorrelogram is equal zero because superimposed spikes were discarded in the spike sorting process. Coherence is shown to the right. Oscillation frequency 72 Hz. Overlapping RFs (plots are not shown). Correlograms are shown with a time lag ranging from -50 to 50 ms.
Time
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84
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HALOTHANE1.0%
75 Hz
100 Hz
120 Hz
20° 20°
Figure 22. Entrainment of responses to the refresh of a CRT monitor display.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "44
4.2 . ST I M U L U S E N T R A I N M E N T
In many recordings in the awake cat we have seen strong entrainment to
the periodic refresh of the monitor. Figure 22 compares the responses to
different CRT refresh frequencies (75 Hz, 100 Hz and 120 Hz) for the awake cat
and during halothane anesthesia. Observe that the recordings made in the awake
cat show strong entrainment with oscillation frequency coinciding precisely with
the refresh frequency, without any signs of decay. In the contrary, during the
anesthesia, strong oscillations are seen with about the same frequency (around
85 Hz). Surprisingly, these strong oscillatory patterns generated internally
overrides completely the oscillatory inputs (due to the refresh of the CRT
screen). Overall these findings show that responses in the retina of the cat during
natural conditions can be temporally precise, even without any oscillatory
patterning being generated internally.
!!!!!!!!!!!!!!!!
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "45
5. DI S C U S S I O N
The primary goal of this study was to test whether fast retinal oscillations
are present or not in conditions compatible with natural seeing. For this we
recorded directly from the retina of the anesthetized cat to study spiking
responses to dynamical stimuli, such as natural scenes movies and varying-size
stimuli (size- and luminance random walks). Finally, we obtained data from the
alert cat, removed from any influences of anesthetic agents.
It is well known that oscillations originated in the retina are transmitted
to the LGN and to the cortex (Doty and Kimura, 1963; Laufer and Verzeano,
1967; Arnett, 1975; Neuenschwander et al., 1996; Castelo-Branco et al., 1998). In
the study of Neuenschwander et al. (1996) synchronization of oscillatory
responses was observed for large distances in the retina (up to 20°), and could
be observed for LGN cells receiving inputs from the same eye, independent
whether the cells were located in the same LGN or in the LGNs of the two
hemispheres. Oscillatory patterns in the LGN can propagate to the cortex, as
demonstrated directly by simultaneous recordings from the retina, LGN and
areas A17 and A18 (Castelo-Branco et al., 1988).
An important aspect in the organization of the retinogeniculate system is
the reliability of information transfer. Retinal afferents to the LGN consist of
thick axons involving richly branched terminal arbors with boutons densely
distributed in terminal clusters (Sherman and Guillery, 2006). This organization
confers great robustness for the retinogeniculate transmission. Analysis of retinal
excitatory post-synaptic potentials (EPSPs) associated with LGN spike waveforms
(S-Potentials) shows that most LGN neurons have one retinal ganglion cell input
that accounts for nearly all LGN spikes sent to visual cortex (Sincich et al., 2007).
Thus, it is not surprising to see that the retinal fast oscillations are faithfully
transmitted through the retinogeniculate pathway up to the LGN (Figure 4).
It has been known that the size of simple stimuli modulates responses in
the early visual system (Barlow et al., 1954; Hubel and Wiesel, 1961). Small spots
of light flashed over the RF center evoke strong responses. However, when the
stimulus reaches the surround regions, the responses decreases. Therefore,
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "46
response levels are unlikely to be appropriate for encoding the size of the
stimulus.
An attractive alternative hypothesis could be that global characteristics
such as s ize and continuity are represented by a temporal code .
Neuenschwander and collaborators have shown in the LGN and the retina of the
cat that oscillation strength is correlated with stimulus size, using light rectangles
flashed over the RFs (Neuenschwander et al., 1999; Stephens et al., 2006). Our
study extended findings, showing that oscillations may encode the size of even
surfaces in natural images. As shown in Figure 18, oscillations in response to
natural scene stimuli appeared only for short epochs, when large connected
segments in the image (e.g., surfaces or the faces of a geometrical object)
covered the RFs. Qualitatively, we can see that the critical blob size for triggering
oscillations is very large. In this sense, encoding of size would be in place only
after a certain threshold is exceeded.
We found abundant evidence, with a variety of visual stimuli, that retinal
oscillations in the cat are dependent on halothane anesthesia, and are absent
during ketamina anesthesia or in natural conditions (Figures 18 to 21). Early
studies on temporal coding in the retinogeniculate system have used anesthetized
animals as experimental model, applying as anesthetic agent either sodium
thiopental (Doty and Kimura, 1963; Laufer and Verzeano, 1967; Reinagel and Reid,
2000; Butts et al., 2007; Desbordes et al., 2008), halothane (Neuenschwander et
al., 1996; Castelo-Branco et al., 1998) or isoflurane (Ito et al., 2010). Halogenated
anesthetics, such as halothane, are known to act directly on GABAA receptors
through an agonist effect by prolonging the decay of inhibitory postsynaptic
currents and increasing IPSP amplitudes (Li et al., 2000; Nishikawa and Maclver,
2000). Halothane is a general inhalation anesthetic used for induction and
maintenance of general anesthesia. It reduces the blood pressure and frequently
decreases the pulse rate and depresses respiration. The anesthetic also induces
muscle relaxation and reduces pains sensitivity by altering tissue excitability. It
does so by decreasing the extent of gap junction mediated cell-cell coupling and
altering the activity of the channels that underlie the action potential. Halothane
causes general anesthesia due to its actions on multiple ion channels, which
ultimately depresses nerve conduction, breathing, cardiac contractility and
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "47
reduces the consumption of oxygen up to 15%. Halothane was also shown to
facilitate evoked gamma in the rat visual cortex (Imas et al., 2004).
The gaseous anesthetic halothane have long been known to reduce gap
junction function (Rozental et al., 2000). The gap junctions or the electrical
synapses are known to mediate the retina’s ability to respond flexibly. Changes in
light intensity have been shown to regulate electrical synapses in at least three
places, between rods and cones, between horizontal cells, and between AII
amacrine cells (Kazumichi Shimizu and Mark Stopfer, 2013).
In this study, we show that isoflurane also evoked oscillatory responses
with the same temporal characteristics as halothane. Thus, our findings can be
generalized to halogenated anesthetics. This is important since these two agents
have been routinely used in many studies of temporal coding at various levels in
the sensory systems (e.g., Neuenschwander and Singer, 1996; Ito et al. 2010).
Finally, a few studies have reported that retinal oscillations occur also for
non-anesthetized and paralyzed cats and monkeys (after transpontine
transection) (Doty and Kimura, 1963), which is at odds with our results. In these
early experiments, however, the stimulus conditions were very different from
ours. Visual stimulation was generally made by illuminating the whole visual field
using light flashes (Doty and Kimura, 1963; Laufer and Verzeano, 1967). It remains
to be investigated whether whole-field stimulation (with a DC-light) are able to
entrain oscillations in the retina.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "48
6. CO N C L U S I O N
In this study we show that fast retinal oscillations in the cat (recorded
both, directly from the retina and/ or the lateral geniculate nucleus) depend
strongly on halothane (or isoflurane) anesthesia, and are absent under natural
conditions, such as freely viewing natural scenes or artificial stimuli. These
findings raise serious doubts about the role of fast retinal oscillations on visual
processing. It is likely that fast rhythms in the retina arise from an imbalance
between excitation and inhibition produced by the anesthesia. Interestingly,
recordings from the awake cat demonstrate that retinal ganglion cell responses
may be entrained by fast periodic inputs as fast as 120 Hz (CRT monitor refresh
rate), indicating that the visual system of the cat is capable of representing very
fast events. Thus, although periodic rhythms are absent from retinal ganglion cell
responses under natural conditions, responses can be temporally precise.
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "49
7. RE F E R E N C E S
Ahissar, E., Sosnik, R., Haidarliu, S. (2000). Transformation from temporal to rate coding in a somatosensory thalamocortical pathway. Nature. 406, 302 – 306;
Alonso, J.M., Usrey, W.M., Reid, R.C. (1996). Precisely correlated firing in cells of the lateral geniculate. Nature. 383 (1996) 815–819;
Andolina, I.M., Jones, H.E., Wang, W., Sillito, A.M. (2007). Corticothalamic feedback enhances stimulus response precision in the visual system. PNAS. 104, 1685 – 1690;
Arai, I., Yamada, Y., Asaka, T., Tachibana, M. (2004). Light-Evoked Oscillatory Discharges in Retinal Ganglion Cells Are Generated by Rhythmic Synaptic Inputs. J. Neurophysiol. 92, 715 – 725;
Ariel, M., Daw, N.W., Rader, R.K. (1983). Rhythmicity in rabbit retinal ganglion cell responses. Vis. Re. 23, 1485 – 1493;
Arnett, D.W. (1975). Correlation analysis of units recorded in the cat dorsal lateral geniculate nucleus. Exp. Brain Res. 24 (1975) 111–130;
Barlow, H. B., Fitzhugh, R., Kuffler, S.W. (1954). Resting discharge and dark adaptation in the cat, J. Physiol. (Lond.), 25 28–9P;
Bishop, G.H. (1933). Fiber groups in the optic nerve. American Journal of Physiology. 106, 460 – 470;
Bishop, P.O., Levick, W.R., Williams, W.O. (1964). Statistical Analysis of the Dark Discharge of Lateral Geniculate Neurones. J. Physiol. 170: 598 - 612;
Butts, D.A., Weng, C., Jin, J., Yeh, C., Lesica, N.A., Alonso, J.M., Stanley, G.B. (2007). Temporal precision in the neural code and the timescales of natural vision. Nature. 449, 92 – 96;
Buzsáki, G. and Wang, X.J. (2012). Mechanisms of Gamma Oscillations. Annu. Rev. Neurosci. 35, 203 – 25;
Casagrande, V.A. and Kaas, J.H. (1994). The afferent, intrinsic, and efferent connections of primary visual cortex in primates. Cerebral Cortex. 10, 201 – 259;
Castelo-Branco, M., Goebel, R., Neuenschwander, S., Singer, W. (2000). Neural synchrony correlates with surface segregation rules. Nature. 405, 685 – 689;
Castelo-Branco, M., Neuenschwander, S., Singer, W. (1998). Synchronization of visual responses between the cortex, lateral geniculate nucleus, and retina in the anesthetized cat. The Journal of Neuroscience. 18, 6395 – 6410;
Dan, Y., Alonso, J.M., Usrey, W.M., Reid, R.C. (1998). Coding of visual information by precisely correlated spikes in the lateral geniculate nucleus, Nat Neurosci. 1, 501–507;
Desbordes, G., Jin, J., Weng, C., Lesica, N.A., Stanley, G.B., Alonso, J.M. (2008). Timing Precision in Population Coding of Natural Scenes in the Early Visual System. Plos Biology. 6, 2672 – 2682;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "50
Doty, R.W., and Kimura, D.S. (1963). Oscillatory Potentials in the Visual System of Cats and Monkeys. J. Physiol. 168, 205 – 218;
Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., Reitboeck, H.J. (1988). Coherent Oscillations: A Mechanism of Feature Linking in the Visual Cortex? Biological Cybernetics. 60, 121 – 130;
Engel, A.K., Fries, P., Singer, W. (2001). Dynamic predictions: oscillations and synchronization in top-down processing. Nature. 2, 704 – 716;
Engel, A.K., König, P. and Singer, W. (1991). Direct physiological evidence for scene segmentation by temporal coding. Proc. Natl. Acad. Sci. USA 88, 9136 – 9140;
Enroth-Cugell, C., and Robson, J.G. (1966). The contrast sensitivity of retinal ganglion cells of the cat. J. Physiol. 187, 517 – 552;
Fries, P., Reynolds, J.H., Rorie, A.E., Desimone, R. (2001). Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention. Science. 291, 1560 – 1563;
Fries, P. (2009). Neuronal gamma-band synchronization as a fundamental process in cortical computation, Annu. Rev. Neurosci. 32, 209–224;
Fröhlich, F. W. (1914). Beiträge zur allgemeinen Physiologie der Sinnesorgane. Psychologische Physiologie Sinnesorganische II. Abteilung Sinnesphysiologische, 48, 28–164;
Gasser, H.S. and Erlanger, J. (1929). Role of fiber size in establishment of nerve block by pressure or cocaine. Amer. J. Physiol. 88, 581–591;
Gattass, R., Nascimento-Silva, S., Soares, J.G.M., Lima, B., Jansen, A.K., Diogo, A.C.M., Farias, M.F., Marcondes, M., Botelho, E.P., Mariani, O.S., Azzi, J., Fiorani, M. (2005). Cortical visual areas in monkeys: location, topography, connections, columns, plasticity and cortical dynamics. Phil. Trans. R. Soc. B. 360, 709 –731;
Gollisch, T. and Meister, M. (2008). Rapid Neural Coding in the Retina with Relative Spike Latencies. Science. 319: 1108 - 1111;
Gotch F. (1903). The time relations of the photo-electric changes in the eyeball of the frog. J Physiol. 29(4-5):388–410;
Gray, C.M. and Viana Di Prisco, G. (1997). Stimulus-dependent neuronal oscillations and local synchronization in striate cortex of the alert cat, J Neurosci. 17, 3239–3253;
Gray, C.M. and Singer, W. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Natl. Acad. Sci. USA. 86, 1698 – 1702;
Gray, C. M., König P., Engel A. K., Singer W. (1989). Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties, Nature. 338, 334–337;
Granit, R., Therman, P.O. (1935). Excitation and inhibition in the retina and in the optic nerve, J. Physiol. (Lond.). 83, 359–381;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "51
Hasenstaub, A., Shu, Y., Haider, B., Kraushaar, U., Duque, A., McCormick. (2005). Inhibitory Postsynaptic Potentials Carry Synchronized Frequency Information in Active Cortical Networks. Neuron. 47, 423 – 435;
Haslinger, R., Pipa, G., Lima, B., Singer, W., Brown, E.N., Neuenschwander, S. (2012). Context Matters: The Illusive Simplicity of Macaque V1 PLoS ONE. 7 (2012) e39699;
He, D.S., Burt, J.M. (2000). Mechanism and Selectivity of the Effects of Halothane on Gap Junction Channel Function. Circulation Research. 86, 104 – 109;
Herculano-Houzel, S., Munk, M. H., Neuenschwander, S., Singer, W. (1999) Precisely synchronized oscillatory firing patterns require electroencephalographic activation, Journal of Neuroscience. 19, 3992–4010;
Hoffmann, K.P., Stone, J., Sherman, M.S. (1972). Relay of Receptive-Field Properties in Dorsal Lateral Geniculate Nucleus of the Cat. J. Neurophysiol. 35, 518 – 521;
Hormuzdi, S.G., Filippov, M.A., Mitropoulou, G., Monyer, H., Bruzzone, R. (2004). Electrical synapses: a dynamic signaling system that shapes the activity of neuronal networks. Biochimica et Biophysica Acta. 1662, 113 – 137;
Hubel, D.H., Wiesel, T.N. (1961). Integrative action in the cat’s lateral geniculate body. J. Physiol. 155, 385 – 398;
Hubel, D.H., Wiesel, T.N. (1962). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J. Physiol. 160, 106 – 154;
Hughes, T.E., Grünert, U., Karten, H.J. (1991). Receptors in the retina of the cat: an immunohistochemical study of wholemounts, sections, and dissociated cells. Vis. Neurosci. 6, 229 – 238;
Imas, O.A., Ropella, K.M., Wood, J.D., Hudetz, A.G. (2004). Halothane augments event-related γ oscillations in rat visual cortex. Neuroscience. 123, 269 – 278;
Ishikane, H., Gangi, M., Honda, S., Tachibana, M. (2005). Synchronized retinal oscillations encode essential information for escape behavior in frogs. Nature Neuroscience. 8, 1087 – 1095;
Ishikane, H., Kawana, A., Tachibana, M. (1999). Short- and long-range synchronous activities in dimming detectors of the frog retina. Visual Neuroscience. 16, 1001 – 1014;
Ito, H., Maldonado, P.E., Gray, C.M. (2010). Dynamics of Stimulus-Evoked Timing Correlations in the Cat Lateral Geniculate Nucleus. J. Neurophysiol. 104, 3276 – 3292;
Kirschfeld, K. (1992). Oscillations in the insect brain: do they correspond to the cortical gamma-waves of vertebrates? Proc. Natl. Acad. Sci. USA. 15, 4764 – 4768;
Koepsell, K., Wang, X., Vaingankar, V., Wei, Y., Wang, Q., Rathbun, D.L., Usrey, W.M., Hirsch, J.A., Sommer, F. (2009). Retinal oscillations carry visual information to cortex. Frontiers in systems neuroscience. 3, 1 – 18;
Koepsell, K., Wang, X., Hirsch, J.A., Sommer, F.T. (2010). Exploring the function of neural oscillations in early sensory systems. Frontiers in Neuroscience. 4, 53 – 61;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "52
König, P. (1994) A method for the quantification of synchrony and oscillatory properties of neuronal activity. J Neurosci Methods 54:31–37;
Kotani, N. and Akaike, N. (2013). The effects of volatile anesthetics on synaptic and extrasynaptic GABA-induced neurotransmission. Brain Research Bulletin. 93, 69 – 79;
Kreiter, A.K. and Singer W. (1996). Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey, J Neurosci. 16 2381–2396;
Krasowski, M.D. and Harrison, N.L. (1999). General anaesthetic actions on ligand-gated ion channels. Cell Mol Life Sci. 55, 1278 – 1303;
Kratz, K.E., Webb, S.V., Sherman, S.M. (1978). Electrophysiological classification of X- and Y- cells in the cat’s lateral geniculate nucleus. Vision Res. 18, 489 – 492;
Kuffler, S. (1953). Discharge patterns and functional organization of mammalian retina, J Neurophysiol. 16 37–68;
Laufer, M. and Verzeano, M. (1967). Periodic activity in the visual system of the cat. Vision Res. 7, 215 – 229;
Laurent, G. (2002). Olfactory networks dynamics and the coding of multidimensional signals. Nature. 3, 884 – 895;
Li, X., Czajkowski, C., Pearce, R.A. (2000). Rapid and Direct Modulation of Receptors by Halothane. Anestheology. 92, 1366 – 1375;
Lima, B., Singer, W., Chen, N., Neuenschwander, S. (2009). Synchronization Dynamics in Response to Plaid Stimuli in Monkey V1. Cerebral Cortex. 20, 1556 – 1573;
Lima, B., Singer, W., Neuenschwander, S. (2011). Gamma Responses Correlate with Temporal Expectation in Monkey Primary Visual Cortex. The Journal of Neuroscience. 31, 15919 – 15931;
Livingstone, M. and Hubel, D. (1988). Segregation of Form, Color, Movement, and Depth: Anatomy, Physiology, and Perception. Science. 240, 740 – 749;
Merker, B. (2013). Activation, not cognition, is the functional key to cortical gamma oscillations. Neuroscience and Biobehavioral Reviews. 37, 401 – 417;
Munk, M. H., Roelfsema, P. R., König, P., Engel, A. K., Singer, W. (1996). Role of reticular activation in the modulation of intracortical synchronization, Science. 272, 271–274;
Nassi, J.J., Callaway, E.M. (2009). Parallel Processing Strategies of the Primate Visual System. Nature Rev. Neurosci. 10, 360 – 372;
Neuenschwander, S., Castelo-Branco, M., Baron, J., Singer, W. (2002). Feed-forward synchronization: propagation of temporal patterns along the retinothalamocortical pathway. Phil. Trans. R. Soc. Lond. B. 357, 1869 – 1876;
Neuenschwander, S., Castelo-Branco, M., Singer, W. (1999). Synchronous oscillations in the cat retina. Vision Research. 39, 2485 – 2497;
Neuenschwander, S., Singer, W. (1996). Long-range synchronization of oscillatory light responses in the cat retina and lateral geniculate nucleus. Nature. 379, 728 – 733;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "53
Nishikawa, K. and Maclver, M.B. (2000). Membrane and Synaptic Actions of Halothane on Rat Hippocampal Pyramidal Neurons and Inhibitory Interneurons. The Journal of Neuroscience. 20, 5915 – 5923;
Palanca, B.J.A. and DeAngelis, B.J.A. (2005). Does neuronal synchrony underlie visual feature grouping? Neuron. 46, 333–346;
Pipa, G., Chen, Z., Neuenschwander, S., Lima, B., Brown, E.N. (2012). Mapping of Visual Receptive Fields by Tomographic Reconstruction, Neural Computation. 24, 2543–2578;
Press. W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P. (1986). Numerical Recipes in C – The Art of Scientific Computing. Cambridge University Press;
Quiroga, R.Q., Nadasdy, Z., Ben-Shaul, Y. (2004). Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Computation. 16, 1661 – 1687;
Reich, D.S., Victor, J.D., Knight, B.W., Ozaki, T., Kaplan, W. (1997). Response Variability and Timing Precision of Neuronal Spike Trains in Vivo. J. Neurophysiol. 77, 2836 – 2841;
Reinagel, P. and Reid, C. (2000). Temporal Coding of Visual Information in the Thalamus. The Journal of Neuroscience. 20, 5392 – 5400;
Roberts, W.M. and Rutherford, M.A. (2008). Linear and nonlinear processing in hair cells. The Journal of Experimental Biology. 211, 1775 – 1780;
Roelfsema, P., Lamme, V.A.F., Spekreijse, H. (2004). Synchrony and covariation of firing rates in the primary visual cortex during contour grouping. Nature Neuroscience. 7, 982 – 991;
Rosa, M.G.P. and Tweedale, R. (2005). Brain maps, great and small: lessons from comparative studies of primate visual cortical organization. Phil.Trans.R.Soc.B. 360, 665 – 691;
Saito, H.A. (2004). Morphology of physiologically identified X-, Y-, and W-type retinal ganglion cells of the cat. Journal of Comparative Neurology. 221, 279 – 288;
Sherman, S.M. and Guillery, R.W. (2006). Exploring the thalamus and its role in cortical function. Sec. Edition. The MIT Press. Cambridge, Massachusetts. London, England;
Sherman, S.M., Guillery, R.W. (2002). The role of the thalamus in the flow of information to the cortex. Phil. Trans. R. Soc. Lond. B. 357, 1695 – 1708;
Sillito, A.M., Cudeiro, J., Jones, H.E. (2006). Always returning: feedback and sensory processing in visual córtex and thalamus. Trends in Neurosciences. 29, 307 – 316;
Sincich, L.C., Adams, D.L., Economides, J.R., Horton J.C. (2007). Transmission of spike trains at the retinogeniculate synapse, J Neurosci. 27, 2683–2692;
Singer, W. (1999). Neuronal Synchrony: A versatile Code for the Definition of Relations? Neuron. 24, 49-65;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "54
Söhl, G., Maxeiner, S., Willecke, K. (2005). Expression and functions of neuronal gap junctions. Nature. 6, 191 – 200;
Stephens, G.J., Neuenschwander, S., George, J.S., Singer, W., Kenyon, G.T. (2006). See globally, spike locally: oscillations in a retinal model encode large visual features. Biol. Cybern. 95, 327 – 348;
Steriade, M., Contreras, D., Amzica, F., Timofeev, I. (1996). Synchronization of Fast (30 – 40 Hz) Spontaneous Oscillations in Intrathalamic and Thalamocortical Networks. The Journal of Neuroscience. 16, 2788 – 2808;
Stanley, G.B., Jin, J., Wang, Y., Desbordes, G., Wang, Q., Black, M.J. , Alonso, J-M (2012). Visual orientation and directional selectivity through thalamic synchrony. Journal of Neuroscience, 32 (2012) 9073–9088.
Stone J. (1983). Parallel processing in the Visual System. New York: Plenum Press; Thiele, A. and Stoner, G. (2003). Neuronal synchrony does not correlate with motion
coherence in cortical area MT. Nature. 421, 366 – 370; Tolhurst, D.J. (1973). Separate channels for the analysis of the shape and the
movement of a moving visual stimulus. J. Physiol. 231, 385 – 402; Uhlhaas, P.J., Pipa, G., Neuenschwander, S., Wibral, M., Singer, W. (2011). A new
look at gamma? High- (>60 Hz) γ-band activity in cortical networks: Function, mechanisms and impairment. Progress in Biophysics and Molecular Biology. 105, 14-28;
Usrey, M.W. (2002). Spike timing and visual processing in the retinogeniculocortical pathway. Phil. Trans. R. Soc. Lond. B. 357, 1729 – 1737;
Usrey, W.M., Reppas, J.B., Reid, R.C. (1998). Paired-spike interactions and synaptic efficacy of retinal inputs to the thalamus. Nature. 395, 384 – 387;
Vardi, N., Masarachia, P., Sterling, P. (1992). Immunoreactivity to Receptor in the Outer Plexiform Layer of the Cat Retina. The Journal of Comparative Neurology. 320, 394 – 397;
Von der Malsburg, C. (1981). The Correlation Theory of Brain Function. Internal Report 81-2, Dept. of Neurobiology, Max-Planck Institute for Biophysical Chemistry, Göttingern, Germany;
Wang, X. and Buzsáki, G. (1996). Gamma Oscillation by Synaptic Inhibition in a Hippocampal Interneuronal Network Model. The Journal of Neuroscience. 16, 6402 – 6413;
Wentlandt, K., Samoilova, M., Carlen, P.L., El Beheiry, H. (2006). General Anesthetics Inhibit Gap Junction Communication in Cultured Organotypic Hippocampal Slices. Anesth. Analg. 102, 1692 – 1698;
Womelsdorf, T., Schoffelen, J.M., Oostenveld, R., Singer, W., Desimone, R., Engel, A., Fries, P. (2007). Modulation of Neuronal Interactions Through Neuronal Synchronization. Science. 316, 1609 – 1612;
Wunderle, T., Eriksson, D., Schmidt, K.E. (2013). Multiplicative Mechanism of Lateral Interactions Revealed by Controlling Interhemispheric Input. Cerebral Cortex. 23, 900 – 912;
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "55
Yeh, C., Stoelzel, C.R., Alonso, J.M. (2003). Two different types of Y cells in the cat Lateral Geniculate Nucleus. J. Neurophysiol. 90, 1852 – 1864.
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8. TA B L E S
Table 1 . Summary of number of recording sites and all stimulus protocols used in this study.C
atR
eco
rdin
g A
rea
Tecn
iqu
eA
nes
thes
iaM
apR
FC
ircl
eSi
zeA
nn
ula
rMas
kG
rati
ngs
Size
Wal
kLu
min
ance
Wal
kLa
bP
anM
edik
amen
tTo
tal
Nr.
of
MU
As
Rec
ord
ing
Site
s
Shak
iLG
NSe
mi-C
hron
icAw
ake
71
641
73
20
81
11
Shak
iLG
NSe
mi-C
hron
icKe
tam
ine
only
12
14
12
3
Shak
iLG
NSe
mi-C
hron
icHa
loth
ane
+ Ke
tam
ine
41
101
52
61
8
Nala
LGN
Sem
i-Chr
onic
Keta
min
e on
ly5
15
11
23
7
Nala
LGN
Acut
eKe
tam
ine
24
56
17
51
21
Nala
LGN
Acut
eHa
loth
ane+
Ke
tam
ine
110
14
32
52
67
81
2
Nala
LGN
Acut
eHa
loth
ane
42
34
13
39
12
Nala
Retin
aAc
ute
Keta
min
e4
52
11
24
13
Nala
Retin
aAc
ute
Halo
than
e+
Keta
min
e1
93
22
32
04
61
2
Nala
Retin
aAc
ute
Halo
than
e4
23
41
32
91
1
cgl0
7LG
NAc
ute
Halo
than
e1
22
11
77
3
cgl0
7LG
NAc
ute
Halo
than
e +
Keta
min
e1
23
31
cgl0
7LG
NAc
ute
Keta
min
e1
22
55
1
cgl0
7Re
tina
Acut
eHa
loth
ane
12
21
17
71
cgl0
7Re
tina
Acut
eHa
loth
ane
+ Ke
tam
ine
12
33
1
cgl0
7Re
tina
Acut
eKe
tam
ine
12
25
52
cgl0
4LG
NAc
ute
Halo
than
e18
410
46
42
12
92
4
cgl0
4LG
NAc
ute
Halo
than
e +
Keta
min
e*1
11
13
33
cgl0
4LG
NAc
ute
Keta
min
e*2
26
3
cgl0
3LG
NAc
ute
Halo
than
e9
76
72
98
71
5
cgl0
3LG
NAc
ute
Keta
min
e3
25
15
6
cgl0
3LG
NAc
ute
Isoflu
rane
11
26
3
*was
hout
pro
coto
ls
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "57
9. F I N A N C I A L S U P P O RT
During this work Giovanne Rosso was supported by CAPES (Master‘s
Degree Scholarship). Our laboratory (Vislab, ICe-UFRN) was supported by the
Federal University of Rio Grande do Norte-UFRN, CNPq (BMBF-CNPq 490127/
2011-8, CNPq Universal 478060/2012-2, CNPq PQ 308190/2012-2) and by a
collaboration between the Brain Institute-UFRN and the Max-Planck Institute for
Brain Research, Frankfurt.
This thesis was produced as part of the activities of FAPESP Center for
Neuromathematics (FAPESP 2013/ 07699-0, São Paulo Research Foundation).
!
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "58
!!
10. AC K N O W L E D G M E N T S
Many thanks to my advisor Sergio Neuenschwander. Things may go wrong,
but as he always says „we need to fight“. After all, there is no free lunch. Sergio is
a great experimentalist, not only because of his knowledge and skills, but mostly
because of the way he lives and loves science. Thanks for the patience and for
believing on me, whenever I hesitated.
I also wish to thank Kerstin Schmidt, Jerome Baron, Bruss Lima, Ed
Tehovinik, Luiz Lana and Johanna Klon-Lipok for the suggestions, discussions,
ideas and support given during this scientific journey.
Thanks to Dr. med. vet. Josy Pontes for help and care with the cats. Many
thanks to Heitor de Oliveira for his wonderful 3D renderings and design of
mechanical stuff essential to this work. Special thanks to Witilla for her care and
commitment in the animal house. Thanks also to Marilene, Monik, Roseleide and
Eronildo for help in many occasions.
I also wish to thank Katia-Simone Rocha, Stephany Campanelli, Dardo
Ferreiro for the discussions, criticisms and friendship.
Many thanks to Prof. Jerome Baron and Prof. Claudio Queiroz for kindly
accepting to evaluate my thesis work, and Akaline Araújo for her secretary work
at the PG-Neuro, UFRN.
Finally I wish to thanks my family for continuous support. Thank you Dad
and Mom for the attention and love. Guilherme, my brother, thank you for the
dedication and commitment. Vô Clarindo, thanks for being always a great father,
grandfather and a friend. I wish you could be here.
!!!!!
Do fast ret inal osci l lat ions play a role in v is ion? by Giovanne Rosso "59
!!!!!!!!!!!!!!!!!
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