Temporal Dynamics of Binocular Display Processing with Corticogeniculate Interactions

A neural model of binocular vision is developed to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing. The model shows how feedforward and feedback interactions among LGN ON and OFF cells and cortical simple, complex, and hypercomplex cells can simulate binocular summation, the Pulfrich effect, and the fusion of delayed anticorrelated stereograms. Model retinal ON and OFF cells are linked by an opponent process capable of generating antagonistic rebounds from OFF cells after offset of an ON cell input. Spatially displaced ON and OFF cells excite simple cells. Opposite polarity simple cells compete before their half-wave rectified outputs excite complex cells. Complex cells binocularly match like-polarity simple cell outputs before pooling half-wave rectified signals frorn opposite polarities. Competitive feedback among complex cells leads to sharpening of disparity selectivity and normalizes cell activity. Slow inhibitory interneurons help to reset complex cells after input offset. The Pulfrich effect occurs because the delayed input from the one eye fuses with the present input from the other eye to create a disparity. Binocular summation occurs for stimuli of brief duration or of low contrast because competitive normalization takes time, and cannot occur for very brief or weak stimuli. At brief SOAs, anticorrelatecd stereograms can be fused because the rebound mechanism ensures that the present image to one eye can fuse with the afterimage from a previous image to the other eye. Corticogeniculate feedback embodies a matching process that enhances the speed and temporal accuracy of complex cell disparity tuning. Model mechanisms interact to control the stable development of sharp disparity tuning.Air Force Office of Scientific Research (F19620-92-J-0499, F49620-92-J-0334, F49620-92-J-0225); Office of Naval Research (N00014-95-1-0409, N00014-95-l-0657, N00014-92-J-1015, N00014-91-J-4100

Interaction of excitation and inhibition in processing of pure tone and amplitude-modulated stimuli in the medial superior olive of the mustached bat

1. In mammals with good low-frequency hearing, the medial superior olive (MSO) processes interaural time or phase differences that are important cues for sound localization. Its cells receive excitatory projections from both cochlear nuclei and are thought to function as coincidence detectors. The response patterns of MSO neurons in most mammals are predominantly sustained. In contrast, the MSO in the mustached bat is a monaural nucleus containing neurons with phasic discharge patterns. These neurons receive projections from the contralateral anteroventral cochlear nucleus (AVCN) and the ipsilateral medial nucleus of the trapezoid body (MNTB). 2. To further investigate the role of the MSO in the bat, the responses of 252 single units in the MSO to pure tones and sinusoidal amplitude-modulated (SAM) stimuli were recorded. The results confirmed that the MSO in the mustached bat is tonotopically organized, with low frequencies in the dorsal part and high frequencies in the ventral part. The 61-kHz region is overrepresented. Most neurons tested (88%) were monaural and discharged only in response to contralateral stimuli. Their response could not be influenced by stimulation of the ipsilateral ear. 3. Only 11% of all MSO neurons were spontaneously active. In these neurons the spontaneous discharge rate was suppressed during the stimulus presentation. 4. The majority of cells (85%) responded with a phasic discharge pattern. About one-half (51%) responded with a level-independent phasic ON response. Other phasic response patterns included phasic OFF or phasic ON-OFF, depending on the stimulus frequency. Neurons with ON-OFF discharge patterns were most common in the 61-kHz region and absent in the high-frequency region. 5. Double tone experiments showed that at short intertone intervals the ON response to the second stimulus or the OFF response to the first stimulus was inhibited. 6. In neuropharmacological experiments, glycine applied to MSO neurons (n = 71) inhibited any tone-evoked response. In the presence of the glycine antagonist strychnine the response patterns changed from phasic to sustained (n = 35) and the neurons responded to both tones presented in double tone experiments independent of the intertone interval (n = 5). The effects of strychnine were reversible. 7. Twenty of 21 neurons tested with sinusoidally amplitude-modulated (SAM) signals exhibited low-pass or band-pass filter characteristics. Tests with SAM signals also revealed a weak temporal summation of inhibition in 13 of the 21 cells tested.(ABSTRACT TRUNCATED AT 400 WORDS) </jats:p

Noninvasive optical inhibition with a red-shifted microbial rhodopsin

Optogenetic inhibition of the electrical activity of neurons enables the causal assessment of their contributions to brain functions. Red light penetrates deeper into tissue than other visible wavelengths. We present a red-shifted cruxhalorhodopsin, Jaws, derived from Haloarcula (Halobacterium) salinarum (strain Shark) and engineered to result in red light–induced photocurrents three times those of earlier silencers. Jaws exhibits robust inhibition of sensory-evoked neural activity in the cortex and results in strong light responses when used in retinas of retinitis pigmentosa model mice. We also demonstrate that Jaws can noninvasively mediate transcranial optical inhibition of neurons deep in the brains of awake mice. The noninvasive optogenetic inhibition opened up by Jaws enables a variety of important neuroscience experiments and offers a powerful general-use chloride pump for basic and applied neuroscience.McGovern Institute for Brain Research at MIT (Razin Fellowship)United States. Defense Advanced Research Projects Agency. Living Foundries Program (HR0011-12-C-0068)Harvard-MIT Joint Research Grants Program in Basic NeuroscienceHuman Frontier Science Program (Strasbourg, France)Institution of Engineering and Technology (A. F. Harvey Prize)McGovern Institute for Brain Research at MIT. Neurotechnology (MINT) ProgramNew York Stem Cell Foundation (Robertson Investigator Award)National Institutes of Health (U.S.) (New Innovator Award 1DP2OD002002)National Institute of General Medical Sciences (U.S.) (EUREKA Award 1R01NS075421)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1RC1MH088182)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Science Foundation (U.S.) (Career Award CBET 1053233)National Science Foundation (U.S.) (Grant EFRI0835878)National Science Foundation (U.S.) (Grant DMS0848804)Society for Neuroscience (Research Award for Innovation in Neuroscience)Wallace H. Coulter FoundationNational Institutes of Health (U.S.) (RO1 MH091220-01)Whitehall FoundationEsther A. & Joseph Klingenstein Fund, Inc.JPB FoundationPIIF FundingNational Institute of Mental Health (U.S.) (R01-MH102441-01)National Institutes of Health (U.S.) (DP2-OD-017366-01)Massachusetts Institute of Technology. Simons Center for the Social Brai

Nat Neurosci

Optogenetic inhibition of the electrical activity of neurons enables the causal assessment of their contributions to brain functions. Red light penetrates deeper into tissue than other visible wavelengths. We present a red-shifted cruxhalorhodopsin, Jaws, derived from Haloarcula (Halobacterium) salinarum (strain Shark) and engineered to result in red light-induced photocurrents three times those of earlier silencers. Jaws exhibits robust inhibition of sensory-evoked neural activity in the cortex and results in strong light responses when used in retinas of retinitis pigmentosa model mice. We also demonstrate that Jaws can noninvasively mediate transcranial optical inhibition of neurons deep in the brains of awake mice. The noninvasive optogenetic inhibition opened up by Jaws enables a variety of important neuroscience experiments and offers a powerful general-use chloride pump for basic and applied neuroscience.1DP2NS082126/DP/NCCDPHP CDC HHS/United States1DP2OD002002/OD/NIH HHS/United States1R01DA029639/DA/NIDA NIH HHS/United States1R01NS067199/NS/NINDS NIH HHS/United States1R01NS075421/NS/NINDS NIH HHS/United States1R01NS081716/NS/NINDS NIH HHS/United States1R01NS087950/NS/NINDS NIH HHS/United States1R21NS078660/NS/NINDS NIH HHS/United States1RC1MH088182/MH/NIMH NIH HHS/United States5R00MH085944/MH/NIMH NIH HHS/United StatesDP2 DK102256/DK/NIDDK NIH HHS/United StatesDP2 NS082126/NS/NINDS NIH HHS/United StatesDP2-OD-017366-01/OD/NIH HHS/United StatesP30 ES002109/ES/NIEHS NIH HHS/United StatesR00 EY018407/EY/NEI NIH HHS/United StatesR01 EY022951/EY/NEI NIH HHS/United StatesR01 EY022951/EY/NEI NIH HHS/United StatesR01 MH091220-01/MH/NIMH NIH HHS/United StatesR01 MH102365/MH/NIMH NIH HHS/United StatesR01 MH102365/MH/NIMH NIH HHS/United StatesR01 MH102441/MH/NIMH NIH HHS/United StatesR01-MH102441-01/MH/NIMH NIH HHS/United States2014-10-03T00:00:00Z24997763PMC418421

Local and global interneuron function in the retina

Brain regions consist of intricate neuronal circuits with diverse interneuron types. In order to gain mechanistic insights into brain function, it is essential to understand the computational purpose of the different types of interneurons. How does a single interneuron type shape the input-output transformation of a given brain region? Here I investigated how different interneuron types of the retina contribute to retinal computations. I developed approaches to systematically and quantitatively investigate the function of retinal interneurons by combining precise circuit perturbations with a system-wide read-out of activity. I studied the functional roles of a locally acting interneuron type, starburst amacrine cells, and of a globally acting type, horizontal cells. In Chapter 1, I show how a defined genetic perturbation in starburst amacrine cells, the mutation of the FRMD7 gene, leads to specific effects in the direction-selective output channels of the retina. Our findings provide a link between a specific neuronal computation and a human disease, and present an entry point for understanding the molecular pathways responsible for generating neuronal circuit asymmetries. Chapter 2 addresses how mutated FRMD7 in starburst cells and the genetic ablation of starburst cells affect the computation of visual motion in the retina and in primary visual cortex. Chapter 3 addresses how horizontal cells mediate rod depolarization under bright daylight conditions. In Chapter 4, I combined the precise, yet retina-wide, perturbation of horizontal cells with a system-level readout of the retinal output. I uncovered that horizontal cells can differentially shape the response dynamics of individual retinal output channels. Our combined experimental and theoretical work shows how the inhibitory feedback at the first visual synapse shapes functional diversity in the retina

Closed-loop experiments to investigate spatial contrast integration in the retina

The fundamental goal of all neuronal processing is to make optimal decisions, and thereby to generate optimal behavior. To this end, the brain performs at each point in time millions of parallel computations. Right now, your brain might weigh thoroughly if it is worth to continue reading this thesis or not. In the end however, weighing is not enough: a decision has to be made. Such a decision is an intrinsically nonlinear process. If two possibilities are nearly equally evaluated, a small change in your considerations might lead to the acceptance of one alternative, and the rejection of the other. Furthermore, not all considerations have to contribute linearly to the decision. For example, a lack of time might certainly keep you from reading this thesis, while having excess spare time might still not make you read it. Such a nonlinear weighing of considerations does not only occur on the conscious level, but all the time in the individual neuronal circuits of the brain. Each neuron can be interpreted as a decision unit, computing whether to spike or not. It typically receives multiple parallel streams of information, and based on these generates its own neuronal output. The inputs resemble the considerations taken into account, while the output conveys the decision to subsequent circuits. How the decision is made is therefore determined by the way the inputs are combined into the neuronal output. In particular, individual inputs might contribute either linearly or nonlinearly to the decision. Thus, in order to understand which role a neuron plays in information processing, we have to assess the nonlinearities involved in the integration of different neuronal inputs. In this thesis, we study this ubiquitous signal integration in the output neurons of the amphibian retina, the retinal ganglion cells. Thereby we hope to gain a better understanding of the general mechanisms underlying signal integration in the circuits of the brain. This will also help us elucidate the functions of the retina in particular. Because of the high similarity of the retinas among all vertebrates, by studying the amphibian retina we also learn to better understand human vision. The amphibian retina is particularly suited to study the nonlinear integration of neuronal signals, because each single ganglion cell receives distinct inputs originating from tens to hundreds of photoreceptors. Indeed, ganglion cells do not just linearly average these inputs, but combine them in a nonlinear fashion. It turned out that it is precisely this nonlinearity which allows specific ganglion cells to decide whether particular features were present in their visual input. Hence, an understanding of how the retina encodes images into neuronal activity requires an understanding of how the spatially distinct light stimuli, that each cell experiences, are combined into the output of this very cell. This is the question of spatial integration which we address in the following. Many facts about this question are already available on a cellular level. Today we know which cell types mediate the signals from the photoreceptors to the ganglion cell, and we know much about the connections between the involved cells. Furthermore, in recent studies the transmission functions of some of the involved circuit elements were measured. In particular, it turned out that many of the processing steps are highly nonlinear. Although all these details are known, a detailed phenomenological description of spatial integration is still lacking. Most current models assume a linear integration, and thereby simply neglect the nonlinearities occurring on the cellular level. In this thesis, we attempt to fill the gap and strive for a functional characterization of spatial integration, and in particular of the involved nonlinearities. We pursued the investigation by performing electrophysiological experiments on retinal ganglion cells. In particular, we measured the neuronal output with an array of electrodes. While measuring, we presented videos containing well-defined light stimuli to the retina. We performed the experiments in a closed-loop approach which allowed us to assess the neuronal response online and use the results to determine the subsequently shown stimuli. The visual area, over which a ganglion cell pools its input, is called the receptive field of the cell. It has been known for almost 60 years that the receptive fields of many ganglion cells are organized in a center-surround structure. In the receptive field center, the cell is most sensitive to visual stimulation. Depending on the cell, it preferentially responds to either a brightening (ON cell) or a darkening (OFF cell) of the image. In contrast, the response in the receptive field surround is weaker, and it is of opposite sign than the center response. Taking this structural segregation of the receptive field into account, we divided our experiments into two parts. First, we determined how different stimuli are combined within the receptive field center. Afterwards, we focused on the integration of stimuli in the center and the surround. Throughout this thesis, we used a specific approach to study spatial integration. This approach is the measurement of so-called iso-response stimuli. Instead of showing predefined stimuli and measuring the neuronal outputs, we did the experiments the other way round: we predefined the output, and then searched for those stimuli which yielded the chosen response. The result of such a measurement was a set of stimuli which all triggered the same neuronal response in a given ganglion cell. Thereby, the cell’s response was either defined as the number of elicited spikes (iso-rate stimuli), or the first-spike latency (iso-latency stimuli). Iso-response stimuli allowed us to directly assess the nonlinearities involved in signal integration in retinal ganglion cells

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing

Neural Circuits and Synapses for Early Stage Visual Processing.

Ganglion cells are the output neurons of the retina and send visual information through the optic nerve to various targets in the brain. There are ~20 types of ganglion cell, and most types encode contrast, the variance in light intensity around the mean level. This thesis investigates how retinal circuits and synapses encode contrast. At the first level of light processing, cone photoreceptors release glutamate onto ON and OFF bipolar cells, which respond to objects brighter or darker than the background and release glutamate onto the corresponding type of ganglion cell. This thesis demonstrates how excitatory and inhibitory synapses work in concert to encode light information in three ganglion cell types: ON Alpha, OFF Alpha, and OFF Delta cells. First, I demonstrate that excitatory synapses adapt following prolonged stimulation. Following a switch from high to low contrast, a ganglion cell rapidly decreases its responsiveness and recovers slowly over several seconds. This slow adaptation arises from reduced glutamate release from presynaptic bipolar cells. Glutamate released from bipolar cells binds to α-amino-3-hydroxyl-5- methyl-4-isoxazole-propionate (AMPA) and N-methyl-D-aspartic acid (NMDA) receptors on ganglion cell dendrites. NMDA-mediated responses were present in multiple ganglion cell types but absent in one type, the ON Alpha cell. OFF Alpha and Delta cells used NMDA receptors for encoding different contrast ranges: the full range (Alpha), including near-threshold responses, versus a high range (Delta). The Delta cell expresses the NR2B subunit, consistent with an extra-synaptic NMDA receptor location that is activated by glutamate spillover during high contrast stimulation. The contrast-independent role for NMDA receptors in OFF Alpha cells correlated with two circuit properties: high contrast sensitivity and low presynaptic basal glutamate release. In addition to excitatory glutamate synapses, OFF ganglion cells are driven by the removal of synaptic inhibition (disinhibition). Experiments implicate the AII amacrine cell, better known for its role in rod vision, as a critical circuit element through the following pathway: cone -> ON cone bipolar cell -> AII cell -> OFF ganglion cell. These results show a new role for disinhibition in the retina and suggest a new role for the AII amacrine cell in daylight vision.Ph.D.NeuroscienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64637/1/manookin_1.pd

Retinal OFF ganglion cells allow detection of quantal shadows at starlight

Perception of light in darkness requires no more than a handful of photons, and this remarkable behavioral performance can be directly linked to a particular retinal circuit???the retinal ON pathway. However, the neural limits of shadow detection in very dim light have remained unresolved. Here, we unravel the neural mecha-nisms that determine the sensitivity of mice (CBA/CaJ) to light decrements at the lowest light levels by measuring signals from the most sensitive ON and OFF retinal ganglion cell types and by correlating their sig-nals with visually guided behavior. We show that mice can detect shadows when only a few photon absorp-tions are missing among thousands of rods. Behavioral detection of such ???quantal???shadows relies on the retinal OFF pathway and is limited by noise and loss of single-photon signals in retinal processing. Thus, in the dim-light regime, light increments and decrements are encoded separately via the ON and OFF retinal pathways, respectively.Peer reviewe

Modeling direction selectivity of simple cells in striate visual cortex within the framework of the canonical microcircuit

Nearly all models of direction selectivity (DS) in visual cortex are based on feedforward connection schemes, where geniculate input provides all excitatory synaptic input to both pyramidal and inhibitory neurons. Feedforward inhibition then suppresses feedforward excitation for nonoptimal stimuli. Anatomically, however, the majority of asymmetric, excitatory, synaptic contacts onto cortical cells is provided by other cortical neurons, as embodied in the Canonical Microcircuit of Douglas and Martin (1991). In this view, weak geniculate input is strongly amplified in the preferred direction by the action of intracortical excitatory connections, while in the null direction inhibition reduces geniculate-induced excitation. We investigate analytically and through biologically realistic computer simulations the functioning of a cortical network based on massive excitatory, cortico-cortical feedback. The behavior of this network is compared to physiological data as well as to the behavior of a purely feedforward model of DS based on nonlagged input. Our model explains a number of puzzling features of direction selective simple cells, including the small somatic input conductance changes that have been measured experimentally during stimulation in the null direction, and the persistence of DS while fully blocking inhibition in a single cell. Although the operation at the heart of our network is amplification, the network passes the linearity test of (Jagadeesh et al., 1993). We make specific predictions concerning the effect of selective blockade of cortical inhibition on the velocity-response curve