Do fast retinal oscillations play a role in vision? A study in the anesthetized and awake cat

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(1)U N I V E R S I DA D E F E D E R A L P RO G R A M A. DE. DO. RIO GRANDE. PÓS-GRADUAÇÃO. EM. DO. N O RT E . N E U RO C I Ê N C I A S . I N S T I T U TO D O ! C É R E B RO. ! ! ! ! DO. FA S T R E T I N A L O S C I L L AT I O N S P L AY A RO L E I N V I S I O N ? . A S T U DY I N T H E A N E S T H E T I Z E D A N D AWA K E C AT . ! ! G I O V A N N E. R O S S O . ! ! ! ! ! ! ! ! ! Natal, 2015 .

(2) ! U N I V E R S I DA D E F E D E R A L P RO G R A M A. DE. DO. RIO GRANDE. PÓS-GRADUAÇÃO. EM. DO. N O RT E . N E U RO C I Ê N C I A S . I N S T I T U TO D O ! C É R E B RO. . DO. ! ! ! !. FA S T R E T I N A L O S C I L L AT I O N S P L AY A RO L E I N V I S I O N ? . A S T U DY I N T H E A N E S T H E T I Z E D A N D AWA K E C AT . ! ! ! G I O V A N N E. R O S S O . ! TRABALHO APRESENTADO AO PROGRAMA DE PÓS -G RADUAÇÃO EM NEUROCIÊNCIAS DA U NIVERSIDADE F EDERAL DO R IO G RANDE DO NORTE COMO REQUISITO PARCIAL PARA A OBTENÇÃO DO . GRAU DE MESTRE. !. O R I E N TA D O R : P ro f . D r. S E R G I O N E U E N S C H WA N D E R . N EUROBIOLOGIA. DE. S ISTEMAS. E. ! ! ! ! Natal, 2015 . C OGNIÇÃO .

(3) U N I V E R S I DA D E F E D E R A L P RO G R A M A. DE. DO. RIO GRANDE. PÓS-GRADUAÇÃO. EM. DO. N O RT E . N E U RO C I Ê N C I A S . I N S T I T U TO D O ! C É R E B RO. . DO. ! ! !. FA S T R E T I N A L O S C I L L AT I O N S P L AY A RO L E I N V I S I O N ? . A S T U DY I N T H E A N E S T H E T I Z E D A N D AWA K E C AT . ! ! ! G I O V A N N E. R O S S O . ! D ISSERTAÇÃO APRESENTADA AO PROGRAMA DE PÓS -G RADUAÇÃO EM NEUROCIÊNCIAS. DA. U NIVERSIDADE F EDERAL DO R IO G RANDE DO NORTE. COMO REQUISITO PARCIAL PARA A OBTENÇÃO DO. G RAU DE MESTRE . . ÁREA DE CONCENTRAÇÃO : NEUROBIOLOGIA DE S ISTEMAS E C OGNIÇÃO.. ! !. APROVADA EM:. 16.11.2015. B A N C A E X A M I N A D O R A : . P ROF . D R . SERGIO NEUENSCHWANDER. P ROF . D R . CLAUDIO QUEIROZ. P ROF . D R . JEROME BARON .

(4) ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! E XPERIMENTS ARE THE ONLY MEANS OF KNOWLEDGE AT OUR DISPOSAL . T HE REST IS POETRY , IMAGINATION .. . !. M AX P LANCK .

(5) ABSTRACT. 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 OFFcomponents 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. .

(6) RESUMO. 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 nãoanestesiados, 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 potenciaisde-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..

(7) 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. .

(8) LIST. 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. .

(9) SUMMARY. ! ABSTRACT RESUMO LIST. AND KEY WORDS. …………..…….…….…………………. E PA L A V R A S - C H A V E. …………..…….…….………………. O F F I G U R E S A N D TA B L E S. 05. 06. ………….….….….………………… 08 . S U M M A R Y ……………………..…….….….….…………………… 10. I N T R O D U C T I O N ……………………..…….….….….……………… 11 1.1 M AT I S S E S C I S S O R S ……………………………………..……… 11. 1.3 O S 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. …………………………………………………. 19. 1.4 G R O U N D Z E R O. 2. O B J E C T I V E S Sp e c i f i c g o a l s. ……………………..……..….….………………. 21. ……….……….……………….……….……………. 21. 3. M E T H O D S ………………………………………………………… 23 3.1 E X P E R I M E N TA L S E S S I O N S …………..…..…..…..…..…..…..…..…. 23. 3. 1. 1 S U R G I C A L P R O C E D U R E S ……………………………….. 24. 3. 1. 2 R E C O R D I N G S ……………………………………….…. 26. 3. 1. 3 D ATA 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. D ATA A N A LY S I S …………………………………………………… 31 . 4. R E 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. O S C I L L AT I O N D Y N A M I C S ……………….………………………. 39. 4.3. D E P E N D E N C I E S O N H A L O T H A N E ……….………………………. 41. 4.4. N O - H A L O T H A N E C O N D I T I O N …………………………………… 41. 4.5. R E C O R D I N G S I N T H E A W A K E C AT ………….…… …………………. 42. 4.5. S T 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. C O N C L U S I O N ………………………………………………………… 48. 7. R E F E R E N C E S ………………...……………………………………… 49 .

(10) 8. T A B L E S ……………………...……………………………………… 56. 9. F I N A N C I A L. S U P P O R T ……….…………………………………………. 57. 10. A C K N O W L E D G M E N T S ……….……………………………………… 58. !. ! !.

(11) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . . "1 1. ! ! 1.. INTRODUCTION. 1.1 M AT 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..

(12) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 2. Figure 1. Seeing Matisse. The Cut-Outs exhibition, Tate Modern, London, April 2014. Photograph by Guy Bell. © REX.. 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 higherorder 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)..

(13) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 3. 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).. !.

(14) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 4. 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 highdensity, 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.

(15) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 5. 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..

(16) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 6. 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 O S 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 Ve r z e a n o, 1 9 6 7 ; A r n e t t , 1 9 7 5 ; N e u e n s c h w a n d e r a n d S i n g e r, 1 9 9 6 ; 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-.

(17) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 7. 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?. !.

(18) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . SCOPE. AUDIO. TAPE. REC. SPIKE. CLASS. CRT. XCORRE. "1 8. 32 HZ. PRE-AMP MIRROR. BOARD. PLOT VIDEO. GEN. TV. MONITOR. -500. 500. 0. 32 HZ. LAUFER AND VERZEANO, 1967 A R N E T T, 1 9 7 5. -50. 0. Time (ms). 50. 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).. RETINA. RETINA. LGN 200 ms. 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..

(19) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "1 9. 1. 1. 2. 2 3°. 3°. 109 Hz. 104 Hz. 111 Hz. 106 Hz. -80. 0. Time (ms). 80. 104 Hz. -80. 0. 80. Time (ms). 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).. 1.3 G R 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.

(20) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 0. 12°. HALOTHANE. 1.0%. Time (ms). 80. cgl04c0501 5-5. cgl04c0501 5-5. cgl04c0502 5-5. cgl04c0502 5-5. cgl04c0503 5-5. cgl04c0503 5-5. 0. 80. HALOTHANE. 0.4%. 0. -80 80. 0 0.40 0.0. -80. Time. 300 ms. 100. 0. 1.0. 2.0. Spikes/s. 0.2%. Coincidences. HALOTHANE. 3.0. Time (s). 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).. 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). .

(21) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . 2.. "2 1. OBJECTIVES. ! 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 slidingwindow correlation analysis and multiaper spectrum and coherence of single-cell spiking responses.. !. Sp e c i f i c g o al s. ! • 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..

(22) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 2. • 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.. ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !.

(23) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . 3.. "2 3. METHODS. 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 E X 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)..

(24) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . 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).. Frame column Device guiding. bars Guide tube positioning scale L-shape head. holder X-Y Table Adaptor Recording. chamber AP-positioning knob. 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.. "2 4.

(25) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 5. 3.1. 1 S U 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 HorsleyClarke 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.

(26) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . Narishige microdrive Fixation ring. Microdrive. piston. "2 6. L-shape arm. (steel). Pin connector Cable. Grid (nylon) Plate (Plexyglas) Needle 0.3 mm (steel) 2X Needle 0.6 mm. (steel). Heat shrinking. tube Soldering pellet Piston (glass). Quartz electrode. 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.. 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.

(27) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 7. 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 R E 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.

(28) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 8. Electrode coarse. positoning scale Electrode coarse. positoning knob Microdrive L-shape arm Fixation ring Glass piston Grid Pexyglas plate Guide tube Stopper AP-Guide tube positioning knob. 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. 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.

(29) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "2 9. 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 D ATA 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.

(30) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 0. information of the temporal structure of the ongoing responses was also very useful to guide the experiments.. G R AY- L EV E L. BI N ARY. L I GH T PATC H. 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.. ! 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 i mu l u s p re s e n t a t i o n w a s c o n t ro l l e d by t h e A c t i ve S t i m s o f t w a re (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.

(31) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 1. were centered on the receptive fields altogether (only in selected cases the stimuli were centered on individual receptive fields).. 3.4. D ATA A N A LY S I S. Our analysis is focused on evaluating the oscillatory behavior of singlecells 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 crosscorrelations 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.

(32) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 2. 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, ...,. . Numerically,. . } with the. -th. is computed as the. slepian taper, denoted by. 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:. C yx ( f ) = where . Sx ( f ). time series . and . xn ( t ). Sy ( f ). and . Syx ( f ) Sx ( f ) Sy ( f ). are the multitapered power spectrum estimates of the. yn ( t ). averaged over n repetitions, respectively, and . Syx ( f ). 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.

(33) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 3. 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. .

(34) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . 4.. "3 4. R E 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,.

(35) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 5. 11° cgl03e12 5a-5a. Time (ms). 80. 0. 1a. 0.5 0.0. -80. ON-cell. cgl03e12 5b-5b. 80. 0. 1b. 0.5 0.0. -80. spikes/s. 0.3 0.0. -80 500 ms. Time. Coincidences. 0. 10. OFF-cell. cgl03e12 5g-5g. 80. 1c ON-cell. 500 ms. 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.. 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-.

(36) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . nal004l04 17a, 17b, 18a, 18b. RETINA. ON-cells. 0 0.2 0.0. -80. Time (ms). RETINA. OFF-cells. 0.0 -80. nal004l04 17a, 17b, 18a, 18b. 80. 1b - 2a. Coincidences. 1a - 2b. 0.3. 0.3. 0 0.2 0.0. -80. Coincidences. Time (ms). 80. 0.0 -80. Time. "3 6. 1.0. 1.9 ms. 0. 80. 0.0 10. 40. 80. 1.0. -0.8 ms. 0. 74 Hz. 80. 120. 78 Hz. 0.0 10. Time (ms). 40. 80. 120. Frequency (Hz). 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 ONcells 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.. 50. 1a - 1a. 0. - 50. shk011j02 3a, 3b, 3c, 3d. shk011j02 3a, 3b, 3c, 3d. 78 Hz. 0. - 50. 1b. -0.2 ms. 78 Hz. 2.2 ms. 79 Hz. 1.2 ms. 78 Hz. 1a - 1b. 1c. 1a - 1c. 1d. 1a - 1d. 0.2. 0.1 0.25. 0.0. 0.0. 0.2 0.0. Time. 1a - (1b,1c,1d). 0.2 0.0. Time. Coincidences. (1b,1c,1d). Coincidences. 1.2 ms. 78 Hz. 0.25. -50. 0. 50. Time (ms). 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.. Coincidences. LGN. shk011j02 3a, 3b, 3c, 3d. Time (ms). 1a. Time (ms). 50.

(37) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "3 7. 1a - 2a Luminance. 1a ON-cell RETINA. nal004k02 17a, 17c. Time (ms). 0.9 80. 0.6. Size 0.3. nal004l01 17a 18b. 2°. 0 -80. 1°. 4°. 2a ON-cell RETINA. 6°. nal004k02 18c. 1°. 8°. 10°. 0.1 0.0. C oincidences. 12°. Time. 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).. 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..

(38) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . nal004l04 17a, 18b (2). 80. 0.2 0.0. nal004l04 17a, 18b (3). 80. 0.2 0.0. Time. 80 20. 40 82. 75. 70 120. 80. 0.0. 20. 20. 40 83. 73. 72. 1.0. 0. -80. 0.0 1.0. 0. -80. Freq (Hz). Coincidences. 0.0. -80. 120. Rate (sp/s). RETINA. 0.2. Coincidences. ON-cells. 0. Coincidences. Time (ms). 1a - 2b. 1.0. Joint rate (sp/s). nal004l04 17a, 18b (4). 80. "3 8. 120. 80. 0.0. 40 84. 73. 40. 81. 120. Frequency (Hz). Time. 500 ms. 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.. 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.. ! ! !.

(39) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . cgl07a03 17a (3). cgl07a03 17b (3). 80. 1b. 0. OFF-cell. 0.2. cgl07a02 17ab. 0.0. -80 cgl07a03 17a, 17b (3). 80. (1a, 1b). 0. RETINA. 0.2 0.0. -80. Time. 80. 40 120. 80. 40 120. 80 50. 40. Time. 500 ms. Rate (sp/s). 0.0. -80. Freq (Hz). 0.1. Coincidences. 0. Coincidences. cgl07a02 17a. 120. Coincidences. 1a ON-cell. Time (ms). 80. "3 9. Figure 17. ON- and the OFF-oscillations are independent. Cross-correlation sliding window analysis for two cells of opposite polarity recorded in the retina.. 4.2. O S C I L L AT I O N D Y 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)..

(40) Do fast retinal oscillations play a role in vision? by Giovanne Rosso . "4 0. 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 OFFcells. 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 sizewalk 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.. 20°. 20° cgl03e07 5 (2). 0. -80 80. cgl03e07 5 (3). 80. Time (ms) cgl03e06 5 (2). 0. HALOTHANE. 1.0%. 0. -80 80. cgl03e06 5 (3). 0.6%. 0. -80. -80 cgl03e08 5 (2). 0 0.3 0.0. -80. Time. 500 ms. cgl03e08 5 (3). 80. Coincidences. 80. 0 0.3 0.0. -80. Time. 500 ms. Coincidences. Time (ms). 80. 0.2%. 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..