Retinal oscillations carry visual information to cortex

Dynamic modulation of mouse thalamocortical visual activity by salient sounds

Visual responses of the primary visual cortex (V1) are altered by sound. Sound-driven behavioral arousal suggests that, in addition to direct inputs from the primary auditory cortex (A1), multiple other sources may shape V1 responses to sound. Here, we show in anesthetized mice that sound (white noise, ≥70dB) drives a biphasic modulation of V1 visually driven gamma-band activity, comprising fast-transient inhibitory and slow, prolonged excitatory (A1-independent) arousal-driven components. An analogous yet quicker modulation of the visual response also occurred earlier in the visual pathway, at the level of the dorsolateral geniculate nucleus (dLGN), where sound transiently inhibited the early phasic visual response and subsequently induced a prolonged increase in tonic spiking activity and gamma rhythmicity. Our results demonstrate that sound-driven modulations of visual activity are not exclusive to V1 and suggest that thalamocortical inputs from the dLGN to V1 contribute to shaping V1 visual response to sound.

On the Functional Role of Gamma Synchronization in the Retinogeniculate System of the Cat

Fast gamma oscillations, generated within the retina, and transmitted to the cortex via the lateral geniculate nucleus (LGN), are thought to carry information about stimulus size and continuity. This hypothesis relies mainly on studies conducted under anesthesia and the extent to which it holds under more naturalistic conditions remains unclear. Using multielectrode recordings of spiking activity in the retina and the LGN of both male and female cats, we show that visually driven gamma oscillations are absent for awake states and are highly dependent on halothane (or isoflurane). Under ketamine, responses were nonoscillatory, as in the awake condition. Response entrainment to the monitor refresh was commonly observed up to 120 Hz and was superseded by the gamma oscillatory responses induced by halothane. Given that retinal gamma oscillations are contingent on halothane anesthesia and absent in the awake cat, such oscillations should be considered artifactual, thus playing no functional role in vision.SIGNIFICANCE STATEMENT Gamma rhythms have been proposed to be a robust encoding mechanism critical for visual processing. In the retinogeniculate system of the cat, many studies have shown gamma oscillations associated with responses to static stimuli. Here, we extend these observations to dynamic stimuli. An unexpected finding was that retinal gamma responses strongly depend on halothane concentration levels and are absent in the awake cat. These results weaken the notion that gamma in the retina is relevant for vision. Notably, retinal gamma shares many of the properties of cortical gamma. In this respect, oscillations induced by halothane in the retina may serve as a valuable preparation, although artificial, for studying oscillatory dynamics.

Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system

Oscillations of neural activity permeate sensory systems. In the visual system, broadband gamma oscillations (30-80 Hz) are thought to act as a communication mechanism underlying perception. However, these oscillations show widely varying frequency and phase, providing constraints for coordinating spike timing across areas. Here, we examined Allen Brain Observatory data and performed causal experiments to show that narrowband gamma (NBG) oscillations (50-70 Hz) propagate and synchronize throughout the awake mouse visual system. Lateral geniculate nucleus (LGN) neurons fired precisely relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG neurons across areas showed a higher likelihood of functional connectivity and stronger visual responses; remarkably, NBG neurons in LGN, preferring bright (ON) versus dark (OFF), fired at distinct NBG phases aligned across the cortical hierarchy. NBG oscillations may thus serve to coordinate spike timing across brain areas and facilitate communication of distinct visual features during perception.

The brain time toolbox, a software library to retune electrophysiology data to brain dynamics

Human thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue that this goal is impeded by the time format of our data-clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up and undergo abrupt changes, introducing a disharmony between the brain's internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the data's new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific enquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.

Perturbation of Spike Timing Benefits Neural Network Performance on Similarity Search

Perturbation has a positive effect, as it contributes to the stability of neural systems through adaptation and robustness. For example, deep reinforcement learning generally engages in exploratory behavior by injecting noise into the action space and network parameters. It can consistently increase the agent's exploration ability and lead to richer sets of behaviors. Evolutionary strategies also apply parameter perturbations, which makes network architecture robust and diverse. Our main concern is whether the notion of synaptic perturbation introduced in a spiking neural network (SNN) is biologically relevant or if novel frameworks and components are desired to account for the perturbation properties of artificial neural systems. In this work, we first review part of the locality-sensitive hashing (LSH) of similarity search, the FLY algorithm, as recently published in Science, and propose an improved architecture, time-shifted spiking LSH (TS-SLSH), with the consideration of temporal perturbations of the firing moments of spike pulses. Experiment results show promising performance of the proposed method and demonstrate its generality to various spiking neuron models. Therefore, we expect temporal perturbation to play an active role in SNN performance.

The superior colliculus/lateral posterior thalamic nuclei in mice rapidly transmit fear visual information through the theta frequency band

Animals perceive threat information mainly from vision, and the subcortical visual pathway plays a critical role in the rapid processing of fear visual information. The superior colliculus (SC) and lateral posterior (LP) nuclei of the thalamus are key components of the subcortical visual pathway; however, how animals encode and transmit fear visual information is unclear. To evaluate the response characteristics of neurons in SC and LP thalamic nuclei under fear visual stimuli, extracellular action potentials (spikes) and local field potential signals were recorded under looming and dimming visual stimuli. The results showed that both SC and LP thalamic nuclei were strongly responsive to looming visual stimuli but not sensitive to dimming visual stimuli. Under the looming visual stimulus, the theta (θ) frequency bands of both nuclei showed obvious oscillations, which markedly enhanced the synchronization between neurons. The functional network characteristics also indicated that the network connection density and information transmission efficiency were higher under fear visual stimuli. These findings suggest that both SC and LP thalamic nuclei can effectively identify threatening fear visual information and rapidly transmit it between nuclei through the θ frequency band. This discovery can provide a basis for subsequent coding and decoding studies in the subcortical visual pathways.

Effects of tACS-Like Electrical Stimulation on Correlated Firing of Retinal Ganglion Cells: Part III

Purpose

Transcranial alternating current stimulation (tACS) is a stimulation protocol used for learning enhancement and mitigation of cognitive dysfunction. Correlated firing has been postulated to be a meta-code that links neuronal spike responses associated with a single entity and may be an important component of high-level cognitive functions. Thus, changes in the covariance firing structure of CNS neurons such as retinal ganglion cells are one potential mechanism by which tACS can exert its effects.

Materials and Methods

We used microelectrode arrays to record light-evoked spike responses of 24 retinal ganglion cells in 7 rabbit eyecup preparations and analyzed the covariance between 30 pairs of neighboring retinal ganglion cells before, during, and after 10-minute application of alternating currents of 1 microampere at 10 or 20 Hz.

Results

tACS stimulation significantly changed the covariance structure of correlated firing in 60% of simultaneously recorded retinal ganglion cells. Application of tACS in the retinal preparation increased cross-covariance in 26% of cell pairs, an effect usually associated with increased light-evoked ganglion cell firing. tACS associated decreases in cross-covariance occurred in 37% of cell pairs. Increased covariance was more common in response to the first, 10-minute application of tACS in isolated retina preparation. Changes in covariance were rare after repeated stimulation, and more likely to result in decreased covariance.

Conclusion

Retinal ganglion cell correlated firing is modulated by 1 microampere tACS currents showing that electrical stimulation can significantly and persistently change the structure of the correlated firing of simultaneously recorded rabbit retinal ganglion cells.

Measuring Temporal and Spatial Variability of Red Blood Cell Velocity in Human Retinal Vessels

Purpose

The retinal circulation regulates blood flow through various internal and external factors; however, it is unclear how locally these factors act within the retinal microcirculation. We measured the temporal and spatial variability of blood velocity in small retinal vessels using a dual-beam adaptive optics scanning laser ophthalmoscope.

Methods

In young healthy subjects (n = 3), temporal blood velocity variability was measured in a local vascular region consisting of an arteriole, capillary, and venule repeatedly over 2 days. Data consisted of 10 imaging periods separated into two sessions: (1) five 6-minute image acquisition periods with 30-minute breaks, and (2) five 6-minute image acquisition periods with 10-minute breaks. In another group of young healthy subjects (n = 5), spatial distribution of velocity variability was measured by imaging three capillary segments during three 2-minute conditions: (1) baseline imaging condition (no flicker), (2) full-field flicker, and (3) no flicker condition again.

Results

Blood velocities were measurable in all subjects with a reliability of about 2%. The coefficient of variation (CV) was used as an estimate of the physiological variability of each vessel. Over 2 days, the average CV in arterioles was 7% (±2%); in capillaries, it was 19% (±6%); and, in venules, it was 8% (±2%). During flicker stimulation, the average capillary CV was 16% during baseline, 15% during flicker stimulation, and 18% after flicker stimulation.

Conclusions

Capillaries in the human retina exhibit spatial and temporal variations in blood velocity. This inherent variation in blood velocity places limits on studying the vascular regulation of individual capillaries, and the study presented here serves as a foundation for future endeavors.

Parallel Neural Multiprocessing with Gamma Frequency Latencies

The Poisson variability in cortical neural responses has been typically modeled using spike averaging techniques, such as trial averaging and rate coding, since such methods can produce reliable correlates of behavior. However, mechanisms that rely on counting spikes could be slow and inefficient and thus might not be useful in the brain for computations at timescales in the 10 millisecond range. This issue has motivated a search for alternative spike codes that take advantage of spike timing and has resulted in many studies that use synchronized neural networks for communication. Here we focus on recent studies that suggest that the gamma frequency may provide a reference that allows local spike phase representations that could result in much faster information transmission. We have developed a unified model (gamma spike multiplexing) that takes advantage of a single cycle of a cell's somatic gamma frequency to modulate the generation of its action potentials. An important consequence of this coding mechanism is that it allows multiple independent neural processes to run in parallel, thereby greatly increasing the processing capability of the cortex. System-level simulations and preliminary analysis of mouse cortical cell data are presented as support for the proposed theoretical model.

Visual Information Processing in the Ventral Division of the Mouse Lateral Geniculate Nucleus of the Thalamus

Even though the lateral geniculate nucleus of the thalamus (LGN) is associated with form vision, that is not its sole role. Only the dorsal portion of LGN (dLGN) projects to V1. The ventral division (vLGN) connects subcortically, sending inhibitory projections to sensorimotor structures, including the superior colliculus (SC) and regions associated with certain behavioral states, such as fear (Monavarfeshani et al., 2017; Salay et al., 2018). We combined computational, physiological, and anatomical approaches to explore visual processing in vLGN of mice of both sexes, making comparisons to dLGN and SC for perspective. Compatible with past, qualitative descriptions, the receptive fields we quantified in vLGN were larger than those in dLGN, and most cells preferred bright versus dark stimuli (Harrington, 1997). Dendritic arbors spanned the length and/or width of vLGN and were often asymmetric, positioned to collect input from large but discrete territories. By contrast, arbors in dLGN are compact (Krahe et al., 2011). Consistent with spatially coarse receptive fields in vLGN, visually evoked changes in spike timing were less precise than for dLGN and SC. Notably, however, the membrane currents and spikes of some cells in vLGN displayed gamma oscillations whose phase and strength varied with stimulus pattern, as for SC (Stitt et al., 2013). Thus, vLGN can engage its targets using oscillation-based and conventional rate codes. Finally, dark shadows activate SC and drive escape responses, whereas vLGN prefers bright stimuli. Thus, one function of long-range inhibitory projections from vLGN might be to enable movement by releasing motor targets, such as SC, from suppression.SIGNIFICANCE STATEMENT Only the dorsal lateral geniculate nucleus (dLGN) connects to cortex to serve form vision; the ventral division (vLGN) projects subcortically to sensorimotor nuclei, including the superior colliculus (SC), via long-range inhibitory connections. Here, we asked how vLGN processes visual information, making comparisons with dLGN and SC for perspective. Cells in vLGN versus dLGN had wider dendritic arbors, larger receptive fields, and fired with lower temporal precision, consistent with a modulatory role. Like SC, but not dLGN, visual stimuli entrained oscillations in vLGN, perhaps reflecting shared strategies for visuomotor processing. Finally, most neurons in vLGN preferred bright shapes, whereas dark stimuli activate SC and drive escape behaviors, suggesting that vLGN enables rapid movement by releasing target motor structures from inhibition.

Visual responses in the dorsal lateral geniculate nucleus at early stages of retinal degeneration in rd1 PDE6β mice

Inherited retinal degenerations encompass a wide range of diseases that result in the death of rod and cone photoreceptors, eventually leading to irreversible blindness. Low vision survives at early stages of degeneration, at which point it could rely on residual populations of rod/cone photoreceptors as well as the inner retinal photoreceptor, melanopsin. To date, the impact of partial retinal degeneration on visual responses in the primary visual thalamus (dorsal lateral geniculate nucleus, dLGN) remains unknown, as does their relative reliance on surviving rod and cone photoreceptors vs. melanopsin. To answer these questions, we recorded visually evoked responses in the dLGN of anesthetized rd¹ mice using in vivo electrophysiology at an age (3-5 wk) at which cones are partially degenerate and rods are absent. We found that excitatory (ON) responses to light had lower amplitude and longer latency in rd¹ mice compared with age-matched visually intact controls; however, contrast sensitivity and spatial receptive field size were largely unaffected at this early stage of degeneration. Responses were retained when those wavelengths to which melanopsin is most sensitive were depleted, indicating that they were driven primarily by surviving cones. Inhibitory responses appeared absent in the rd¹ thalamus, as did light-evoked gamma oscillations in firing. This description of fundamental features of the dLGN visual response at this intermediate stage of retinal degeneration provides a context for emerging attempts to restore vision by introducing ectopic photoreception to the degenerate retina.NEW & NOTEWORTHY This study provides new therapeutically relevant insights to visual responses in the dorsal lateral geniculate nucleus during progressive retinal degeneration. Using in vivo electrophysiology, we demonstrate that visual responses have lower amplitude and longer latency during degeneration, but contrast sensitivity and spatial receptive fields remain unaffected. Such visual responses are driven predominantly by surviving cones rather than melanopsin photoreceptors. The functional integrity of this visual pathway is encouraging for emerging attempts at visual restoration.

Differentially synchronized spiking enables multiplexed neural coding

Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.

Oscillations in Spontaneous and Visually Evoked Neuronal Activity in the Superficial Layers of the Cat's Superior Colliculus

Oscillations are ubiquitous features of neuronal activity in sensory systems and are considered as a substrate for the integration of sensory information. Several studies have described oscillatory activity in the geniculate visual pathway, but little is known about this phenomenon in the extrageniculate visual pathway. We describe oscillations in evoked and background activity in the cat's superficial layers of the superior colliculus, a retinorecipient structure in the extrageniculate visual pathway. Extracellular single-unit activity was recorded during periods with and without visual stimulation under isoflurane anesthesia in the mixture of N₂O/O₂. Autocorrelation, FFT and renewal density analyses were used to detect and characterize oscillations in the neuronal activity. Oscillations were common in the background and stimulus-evoked activity. Frequency range of background oscillations spanned between 5 and 90 Hz. Oscillations in evoked activity were observed in about half of the cells and could appear in two forms —stimulus-phase-locked (10–100 Hz), and stimulus-phase-independent (8–100 Hz) oscillations. Stimulus-phase-independent and background oscillatory frequencies were very similar within activity of particular neurons suggesting that stimulus-phase-independent oscillations may be a form of enhanced “spontaneous” oscillations. Stimulus-phase-locked oscillations were present in responses to moving and flashing stimuli. In contrast to stimulus-phase-independent oscillations, the strength of stimulus-phase-locked oscillations was positively correlated with stimulus velocity and neuronal firing rate. Our results suggest that in the superficial layers of the superior colliculus stimulus-phase-independent oscillations may be generated by the same mechanism(s) that lie in the base of “spontaneous” oscillations, while stimulus-phase-locked oscillations may result from interactions within the intra-collicular network and/or from a phase reset of oscillations present in the background activity.

Thalamocortical Communication in the Awake Mouse Visual System Involves Phase Synchronization and Rhythmic Spike Synchrony at High Gamma Frequencies

In the neocortex, communication between neurons is heavily influenced by the activity of the surrounding network, with communication efficacy increasing when population patterns are oscillatory and coherent. Less is known about whether coherent oscillations are essential for conveyance of thalamic input to the neocortex in awake animals. Here we investigated whether visual-evoked oscillations and spikes in the primary visual cortex (V1) were aligned with those in the visual thalamus (dLGN). Using simultaneous recordings of visual-evoked activity in V1 and dLGN we demonstrate that thalamocortical communication involves synchronized local field potential oscillations in the high gamma range (50-90 Hz) which correspond uniquely to precise dLGN-V1 spike synchrony. These results provide evidence of a role for high gamma oscillations in mediating thalamocortical communication in the visual pathway of mice, analogous to beta oscillations in primates.

Clinical Impact of Spontaneous Hyperactivity in Degenerating Retinas: Significance for Diagnosis, Symptoms, and Treatment

Hereditary retinal degenerations result from varied pathophysiologic mechanisms, all ultimately characterized by photoreceptor dysfunction and death. Hence, much research on these diseases has concentrated on the outer retina. Over the past decade or so increasing attention has focused on concomitant changes in complex inner retinal neural circuits that process visual signals for transmission to the brain. One striking abnormality develops before the ultimately profound anatomic disruption of the inner retina. Highly elevated spontaneous activity was first demonstrated in central nervous system visual centers in vivo by Dräger and Hubel (1978), and subsequently has been confirmed in vitro, now in multiple animal models and by multiple investigators (see other contributions to this Research Topic). What evidence exists that this phenomenon occurs in human patients with retinal degeneration, and what is the ultimate effect of spontaneous hyperactivity in the output neurons, the retinal ganglion cells? Here I summarize abnormalities of visual perception among patients with retinal degeneration that may arise from hyperactivity. Next, I consider the disruption of neural encoding and anatomic connectivity that may result within the retina and in downstream visual centers of the brain. I then consider how specific characteristics of hyperactivity may distinguish various forms or stages of retinal degeneration, potentially helping in the near future to refine diagnosis and/or treatment choices for different patients. Finally, I review how consideration of these features may help optimize pharmacologic, gene, stem cell, prosthetic or other therapies to forestall visual loss or restore sight.

Gamma and infra-slow oscillations shape neuronal firing in the rat subcortical visual system

KEY POINTS

Neuronal oscillations observed in sensory systems are physiological carriers of information about stimulus features. Rhythm in the infra-slow range, originating from the retina, was previously found in the firing of subcortical visual system nuclei involved in both image and non-image forming functions. The present study shows that the firing of neurons in the lateral geniculate nucleus is also governed by gamma oscillation (∼35 Hz) time-locked to high phase of infra-slow rhythm that codes the intensity of transient light stimulation. We show that both physiological rhythms are synchronized within and between ipsilateral nuclei of the subcortical visual system and are dependent on retinal activity. The present study shows that neurophysiological oscillations characterized by various frequencies not only coexist in the subcortical visual system, but also are subjected to complex interference and synchronization processes.

ABSTRACT

The physiological function of rhythmic firing in the neuronal networks of sensory systems has been linked with information coding. Also, neuronal oscillations in different frequency bands often change as a signature of brain state or sensory processing. Infra-slow oscillation (ISO) in the neuronal firing dependent on the retinal network has been described previously in the structures of the subcortical visual system. In the present study, we show for the first time that firing of ISO neurons in the lateral geniculate nucleus is also characterized by a harmonic discharge pattern (i.e. action potentials are separated by the intervals governed by fundamental frequency in the gamma range: ∼35 Hz). A similar phenomenon was recently described in the suprachiasmatic nuclei of the hypothalamus: the master biological clock. We found that both gamma and ISO rhythms were synchronized within and between ipsilateral nuclei of the subcortical visual system and were dependent on the retinal activity of the contralateral eye. These oscillatory patterns were differentially influenced by transient and prolonged light stimulation with respect to both frequency change direction and sustainability. The results of the present study show that the firing pattern of neurons in the subcortical visual system is shaped by oscillations from infra-slow and gamma frequency bands that are plausibly generated by the retinal network. Additionally, the results demonstrate that both rhythms are not a distinctive feature of image or non-image forming visual systems but, instead, they comprise two channels carrying distinctive properties of photic information.

On Synchronizing Coupled Retinogeniculocortical Pathways: A Toy Model

A Newman-Watts graph is formed by including random links in a regular lattice. Here, the emergence of synchronization in coupled Newman-Watts graphs is studied. The whole neural network is considered as a toy model of mammalian visual pathways. It is composed by four coupled graphs, in which a coupled pair represents the lateral geniculate nucleus and the visual cortex of a cerebral hemisphere. The hemispheres communicate with each other through a coupling between the graphs representing the visual cortices. This coupling makes the role of the corpus callosum. The state transition of neurons, supposed to be the nodes of the graphs, occurs in discrete time and it follows a set of deterministic rules. From periodic stimuli coming from the retina, the neuronal activity of the whole network is numerically computed. The goal is to find out how the values of the parameters related to the network topology affect the synchronization among the four graphs.

Gap junction plasticity as a mechanism to regulate network-wide oscillations

Cortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap junction coupling. Gap junctions are ubiquitous in cortex between GABAergic interneurons. Moreover, recent experiments indicate their strength can be modified in an activity-dependent manner, similar to chemical synapses. We hypothesized that activity-dependent gap junction plasticity acts as a mechanism to regulate oscillations in the cortex. We developed a computational model of gap junction plasticity in a recurrent cortical network based on recent experimental findings. We showed that gap junction plasticity can serve as a homeostatic mechanism for oscillations by maintaining a tight balance between two network states: asynchronous irregular activity and synchronized oscillations. This homeostatic mechanism allows for robust communication between neuronal assemblies through two different mechanisms: transient oscillations and frequency modulation. This implies a direct functional role for gap junction plasticity in information transmission in cortex.

Micro-calibration of space and motion by photoreceptors synchronized in parallel with cortical oscillations: A unified theory of visual perception

A fundamental function of the visual system is detecting motion, yet visual perception is poorly understood. Current research has determined that the retina and ganglion cells elicit responses for motion detection; however, the underlying mechanism for this is incompletely understood. Previously we proposed that retinogeniculo-cortical oscillations and photoreceptors work in parallel to process vision. Here we propose that motion could also be processed within the retina, and not in the brain as current theory suggests. In this paper, we discuss: 1) internal neural space formation; 2) primary, secondary, and tertiary roles of vision; 3) gamma as the secondary role; and 4) synchronization and coherence. Movement within the external field is instantly detected by primary processing within the space formed by the retina, providing a unified view of the world from an internal point of view. Our new theory begins to answer questions about: 1) perception of space, erect images, and motion, 2) purpose of lateral inhibition, 3) speed of visual perception, and 4) how peripheral color vision occurs without a large population of cones located peripherally in the retina. We explain that strong oscillatory activity influences on brain activity and is necessary for: 1) visual processing, and 2) formation of the internal visuospatial area necessary for visual consciousness, which could allow rods to receive precise visual and visuospatial information, while retinal waves could link the lateral geniculate body with the cortex to form a neural space formed by membrane potential-based oscillations and photoreceptors. We propose that vision is tripartite, with three components that allow a person to make sense of the world, terming them "primary, secondary, and tertiary roles" of vision. Finally, we propose that Gamma waves that are higher in strength and volume allow communication among the retina, thalamus, and various areas of the cortex, and synchronization brings cortical faculties to the retina, while the thalamus is the link that couples the retina to the rest of the brain through activity by gamma oscillations. This novel theory lays groundwork for further research by providing a theoretical understanding that expands upon the functions of the retina, photoreceptors, and retinal plexus to include parallel processing needed to form the internal visual space that we perceive as the external world.

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks

Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

Subcortical Source and Modulation of the Narrowband Gamma Oscillation in Mouse Visual Cortex

Primary visual cortex exhibits two types of gamma rhythm: broadband activity in the 30–90 Hz range and a narrowband oscillation seen in mice at frequencies close to 60 Hz. We investigated the sources of the narrowband gamma oscillation, the factors modulating its strength, and its relationship to broadband gamma activity. Narrowband and broadband gamma power were uncorrelated. Increasing visual contrast had opposite effects on the two rhythms: it increased broadband activity, but suppressed the narrowband oscillation. The narrowband oscillation was strongest in layer 4 and was mediated primarily by excitatory currents entrained by the synchronous, rhythmic firing of neurons in the lateral geniculate nucleus (LGN). The power and peak frequency of the narrowband gamma oscillation increased with light intensity. Silencing the cortex optogenetically did not abolish the narrowband oscillation in either LGN firing or cortical excitatory currents, suggesting that this oscillation reflects unidirectional flow of signals from thalamus to cortex.

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Mouse V1 exhibits a pronounced narrowband gamma oscillation close to 60 Hz

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This oscillation is strongest in layer 4 and specific to excitatory currents

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It increases with arousal and light intensity and decreases with visual contrast

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It is seen in lateral geniculate neurons, regardless of V1 activity

Modulation of Fast Narrowband Oscillations in the Mouse Retina and dLGN According to Background Light Intensity

Background light intensity (irradiance) substantially impacts the visual code in the early visual system at synaptic and single-neuron levels, but its influence on population activity is largely unexplored. We show that fast narrowband oscillations, an important feature of population activity, systematically increase in amplitude as a function of irradiance in both anesthetized and awake, freely moving mice and at the level of the retina and dorsal lateral geniculate nucleus (dLGN). Narrowband coherence increases with irradiance across large areas of the dLGN, but especially for neighboring units. The spectral sensitivity of these effects and their substantial reduction in melanopsin knockout animals indicate a contribution from inner retinal photoreceptors. At bright backgrounds, narrowband coherence allows pooling of single-unit responses to become a viable strategy for enhancing visual signals within its frequency range.

Synaptic Contributions to Receptive Field Structure and Response Properties in the Rodent Lateral Geniculate Nucleus of the Thalamus

Comparative physiological and anatomical studies have greatly advanced our understanding of sensory systems. Many lines of evidence show that the murine lateral geniculate nucleus (LGN) has unique attributes, compared with other species such as cat and monkey. For example, in rodent, thalamic receptive field structure is markedly diverse, and many cells are sensitive to stimulus orientation and direction. To explore shared and different strategies of synaptic integration across species, we made whole-cell recordings in vivo from the murine LGN during the presentation of visual stimuli, analyzed the results with different computational approaches, and compared our findings with those from cat. As for carnivores, murine cells with classical center-surround receptive fields had a "push-pull" structure of excitation and inhibition within a given On or Off subregion. These cells compose the largest single population in the murine LGN (∼40%), indicating that push-pull is key in the form vision pathway across species. For two cell types with overlapping On and Off responses, which recalled either W3 or suppressed-by-contrast ganglion cells in murine retina, inhibition took a different form and was most pronounced for spatially extensive stimuli. Other On-Off cells were selective for stimulus orientation and direction. In these cases, retinal inputs were tuned and, for oriented cells, the second-order subunit of the receptive field predicted the preferred angle. By contrast, suppression was not tuned and appeared to sharpen stimulus selectivity. Together, our results provide new perspectives on the role of excitation and inhibition in retinothalamic processing.

SIGNIFICANCE STATEMENT

We explored the murine lateral geniculate nucleus from a comparative physiological perspective. In cat, most retinal cells have center-surround receptive fields and push-pull excitation and inhibition, including neurons with the smallest (highest acuity) receptive fields. The same is true for thalamic relay cells. In mouse retina, the most numerous cell type has the smallest receptive fields but lacks push-pull. The most common receptive field in rodent thalamus, however, is center-surround with push-pull. Thus, receptive field structure supersedes size per se for form vision. Further, for many orientation-selective cells, the second-order component of the receptive field aligned with stimulus preference, whereas suppression was untuned. Thus, inhibition may improve spatial resolution and sharpen other forms of selectivity in rodent lateral geniculate nucleus.

Cortical gamma band synchronization through somatostatin interneurons

Gamma band rhythms may synchronize distributed cell assemblies to facilitate information transfer within and across brain areas, yet their underlying mechanisms remain hotly debated. Most circuit models postulate that soma-targeting parvalbumin-positive GABAergic neurons are the essential inhibitory neuron subtype necessary for gamma rhythms. Using cell-type-specific optogenetic manipulations in behaving animals, we show that dendrite-targeting somatostatin (SOM) interneurons are critical for a visually induced, context-dependent gamma rhythm in visual cortex. A computational model independently predicts that context-dependent gamma rhythms depend critically on SOM interneurons. Further in vivo experiments show that SOM neurons are required for long-distance coherence across the visual cortex. Taken together, these data establish an alternative mechanism for synchronizing distributed networks in visual cortex. By operating through dendritic and not just somatic inhibition, SOM-mediated oscillations may expand the computational power of gamma rhythms for optimizing the synthesis and storage of visual perceptions.

An evolving view of retinogeniculate transmission

The thalamocortical (TC) relay neuron of the dorsoLateral Geniculate Nucleus (dLGN) has borne its imprecise label for many decades in spite of strong evidence that its role in visual processing transcends the implied simplicity of the term "relay". The retinogeniculate synapse is the site of communication between a retinal ganglion cell and a TC neuron of the dLGN. Activation of retinal fibers in the optic tract causes reliable, rapid, and robust postsynaptic potentials that drive postsynaptics spikes in a TC neuron. Cortical and subcortical modulatory systems have been known for decades to regulate retinogeniculate transmission. The dynamic properties that the retinogeniculate synapse itself exhibits during and after developmental refinement further enrich the role of the dLGN in the transmission of the retinal signal. Here we consider the structural and functional substrates for retinogeniculate synaptic transmission and plasticity, and reflect on how the complexity of the retinogeniculate synapse imparts a novel dynamic and influential capacity to subcortical processing of visual information.

Snapshots of the Brain in Action: Local Circuit Operations through the Lens of γ Oscillations

γ oscillations (20-80 Hz) are associated with sensory processing, cognition, and memory, and focused attention in animals and humans. γ activity can arise from several neural mechanisms in the cortex and hippocampus and can vary across circuits, behavioral states, and developmental stages. γ oscillations are nonstationary, typically occurring in short bouts, and the peak frequency of this rhythm is modulated by stimulus parameters. In addition, the participation of excitatory and inhibitory neurons in the γ rhythm varies across local circuits and conditions, particularly in the cortex. Although these dynamics present a challenge to interpreting the functional role of γ oscillations, these patterns of activity emerge from synaptic interactions among excitatory and inhibitory neurons and thus provide important insight into local circuit operations.

Degeneration stage-specific response pattern of retinal ganglion cell spikes in rd10 mouse retina

It is known that with retinal degeneration there is rewiring of retinal networks. Consequently, electrical stimulation of the degenerating retina produces responses that differ according to the stage of retinal degeneration. We sought to delineate a degeneration stage-specific parameter for the response pattern of retinal ganglion cell (RGC) spikes as a strategy for stage-specific electrical stimulation for perceptual efficiency of prosthetic vision devices. Electrically-evoked RGC spikes were recorded at different degeneration stages in the rd10 mouse model for human retinitis pigmentosa (RP). Retinal explants mounted on an 8×8 multi-electrode array were stimulated by applying 1 Hz cathodic-phase first biphasic current pulses. RGC firing rate during the first 100 ms post-stimulus was compared to that during the 100-1000 ms period and a response ratio of 100 ms (RR100 ms) was calculated through the different postnatal weeks. Our results show that during post-stimulus 100-1000 ms, the degree of correlation between pulse amplitude and evoked RGC spikes drastically decreases at PNW 4.5. This pattern was closely matched by the RR100 ms curve at this stage. We conclude that the RR100 ms might be a good indicator of the therapeutic potential of a retinal electrical prosthesis.

How inhibitory circuits in the thalamus serve vision

Inhibitory neurons dominate the intrinsic circuits in the visual thalamus. Interneurons in the lateral geniculate nucleus innervate relay cells and each other densely to provide powerful inhibition. The visual sector of the overlying thalamic reticular nucleus receives input from relay cells and supplies feedback inhibition to them in return. Together, these two inhibitory circuits influence all information transmitted from the retina to the primary visual cortex. By contrast, relay cells make few local connections. This review explores the role of thalamic inhibition from the dual perspectives of feature detection and information theory. For example, we describe how inhibition sharpens tuning for spatial and temporal features of the stimulus and how it might enhance image perception. We also discuss how inhibitory circuits help to reduce redundancy in signals sent downstream and, at the same time, are adapted to maximize the amount of information conveyed to the cortex.

A Spiking Neural Network System for Robust Sequence Recognition

This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software.

Aberrant Activity in Degenerated Retinas Revealed by Electrical Imaging

In this review, I present and discuss the current understanding of aberrant electrical activity found in the ganglion cell layer (GCL) of rod-degenerated (rd) mouse retinas. The reported electrophysiological properties revealed by electrical imaging using high-density microelectrode arrays can be subdivided between spiking activity originating from retinal ganglion cells (RGCs) and local field potentials (LFPs) reflecting strong trans-membrane currents within the GCL. RGCs in rd retinas show increased and rhythmic spiking compared to age-matched wild-type retinas. Fundamental spiking frequencies range from 5 to 15 Hz in various mouse models. The rhythmic RGC spiking is driven by a presynaptic network comprising AII amacrine and bipolar cells. In the healthy retina this rhythm-generating circuit is inhibited by photoreceptor input. A unique physiological feature of rd retinas is rhythmic LFP manifested as spatially-restricted low-frequency (5-15 Hz) voltage changes. Their spatiotemporal characterization revealed propagation and correlation with RGC spiking. LFPs rely on gap-junctional coupling and are shaped by glycinergic and by GABAergic transmission. The aberrant RGC spiking and LFPs provide a simple readout of the functionality of the remaining retinal circuitry which can be used in the development of improved vision restoration strategies.

Visual Functions of the Thalamus

The thalamus is the heavily interconnected partner of the neocortex. All areas of the neocortex receive afferent input from and send efferent projections to specific thalamic nuclei. Through these connections, the thalamus serves to provide the cortex with sensory input, and to facilitate interareal cortical communication and motor and cognitive functions. In the visual system, the lateral geniculate nucleus (LGN) of the dorsal thalamus is the gateway through which visual information reaches the cerebral cortex. Visual processing in the LGN includes spatial and temporal influences on visual signals that serve to adjust response gain, transform the temporal structure of retinal activity patterns, and increase the signal-to-noise ratio of the retinal signal while preserving its basic content. This review examines recent advances in our understanding of LGN function and circuit organization and places these findings in a historical context.

Pattern segmentation with activity dependent natural frequency shift and sub-threshold resonance

Understanding the mechanisms underlying distributed pattern formation in brain networks and its content driven dynamical segmentation is an area of intense study. We investigate a theoretical mechanism for selective activation of diverse neural populations that is based on dynamically shifting cellular resonances in functionally or structurally coupled networks. We specifically show that sub-threshold neuronal depolarization from synaptic coupling or external input can shift neurons into and out of resonance with specific bands of existing extracellular oscillations, and this can act as a dynamic readout mechanism during information storage and retrieval. We find that this mechanism is robust and suggest it as a general coding strategy that can be applied to any network with oscillatory nodes.

Simultaneous recordings from the primary visual cortex and lateral geniculate nucleus reveal rhythmic interactions and a cortical source for γ-band oscillations

Oscillatory synchronization of neuronal activity has been proposed as a mechanism to modulate effective connectivity between interacting neuronal populations. In the visual system, oscillations in the gamma-frequency range (30-100 Hz) are thought to subserve corticocortical communication. To test whether a similar mechanism might influence subcortical-cortical communication, we recorded local field potential activity from retinotopically aligned regions in the lateral geniculate nucleus (LGN) and primary visual cortex (V1) of alert macaque monkeys viewing stimuli known to produce strong cortical gamma-band oscillations. As predicted, we found robust gamma-band power in V1. In contrast, visual stimulation did not evoke gamma-band activity in the LGN. Interestingly, an analysis of oscillatory phase synchronization of LGN and V1 activity identified synchronization in the alpha (8-14 Hz) and beta (15-30 Hz) frequency bands. Further analysis of directed connectivity revealed that alpha-band interactions mediated corticogeniculate feedback processing, whereas beta-band interactions mediated geniculocortical feedforward processing. These results demonstrate that although the LGN and V1 display functional interactions in the lower frequency bands, gamma-band activity in the alert monkey is largely an emergent property of cortex.

Recurrent connections form a phase-locking neuronal tuner for frequency-dependent selective communication

The brain requires task-dependent interregional coherence of information flow in the anatomically connected neural network. However, it is still unclear how a neuronal group can flexibly select its communication target. In this study, we revealed a hidden routing mechanism on the basis of recurrent connections. Our simulation results based on the spike response model show that recurrent connections between excitatory and inhibitory neurons modulate the resonant frequency of a local neuronal group, and that this modulation enables a neuronal group to receive selective information by filtering a preferred frequency component. We also found that the recurrent connection facilitates the successful routing of any necessary information flow between neuronal groups through frequency-dependent resonance of synchronized oscillations. Taken together, these results suggest that recurrent connections act as a phase-locking neuronal tuner which determines the resonant frequency of a local group and thereby controls the preferential routing of incoming signals.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

A linear model for characterization of synchronization frequencies of neural networks

The synchronization frequency of neural networks and its dynamics have important roles in deciphering the working mechanisms of the brain. It has been widely recognized that the properties of functional network synchronization and its dynamics are jointly determined by network topology, network connection strength, i.e., the connection strength of different edges in the network, and external input signals, among other factors. However, mathematical and computational characterization of the relationships between network synchronization frequency and these three important factors are still lacking. This paper presents a novel computational simulation framework to quantitatively characterize the relationships between neural network synchronization frequency and network attributes and input signals. Specifically, we constructed a series of neural networks including simulated small-world networks, real functional working memory network derived from functional magnetic resonance imaging, and real large-scale structural brain networks derived from diffusion tensor imaging, and performed synchronization simulations on these networks via the Izhikevich neuron spiking model. Our experiments demonstrate that both of the network synchronization strength and synchronization frequency change according to the combination of input signal frequency and network self-synchronization frequency. In particular, our extensive experiments show that the network synchronization frequency can be represented via a linear combination of the network self-synchronization frequency and the input signal frequency. This finding could be attributed to an intrinsically-preserved principle in different types of neural systems, offering novel insights into the working mechanism of neural systems.

Comparison of basal oscillatory rhythm of retinal activities in rd1 and rd10 mice

Among the many animal models of retinitis pigmentosa (RP), the most extensively characterized animal is the rd1 mouse. Recent studies showed that the neurophysiological properties of rd1 retinas differ significantly from those of normal retina; the presence of an oscillatory rhythmic activity (~10 Hz) both in retinal ganglion cell (RGC) spikes and field potentials (slow wave component, SWC). However, lesser studies have been done regarding electrical characteristics of rd10 retina, carrying the mutation of same rod-PDE gene and showing a later onset degeneration of photoreceptors. Therefore, in this study, we compared the oscillatory rhythm in RGC spike and SWC between rd1 and rd10 mice in different postnatal ages to understand neural code used by two diseased retinas to communicate with the brain. Extracellular action potentials are recorded by 8 × 8 MEA from the RGC in the in vitro whole mount retina. 4 and 8 weeks in rd1 mice and 4, 10, 15, and 20 weeks in rd10 mice were used (n=3 for each postnatal age). From the raw waveform of retinal recording, RGC Spikes and SWC were isolated by using 200 Hz high-pass filter and 20 Hz low-pass filter, respectively. Fourier transform was performed for detection of oscillatory rhythm in RGC spikes and SWC. In rd1 mice, there is no statistical difference between the frequency of SWC and spike in 4 weeks [p>0.05; spike 9.3 ± 0.9 Hz (n=40), SWC 9.3 ± 1.5 Hz (n=25)] and 8 weeks [p>0.05; spike 10.0 ± 1.3 Hz (n=87), SWC 10.9 ± 1.7 Hz (n=25)]. While in rd10 mice there is no statistical differences among the SWC through 4 ~ 20 weeks, significant differences were observed between the frequency of RGC spike and SWC and also among RGC spikes [4 weeks (p<0.001): spike 5.5 ± 1.3 Hz (n=59), SWC 10.8 ± 3.1 Hz (n=14); 10 weeks (p<0.001): spike 6.8 ± 3.8 Hz (n=79), SWC 10.3 ± 2.6 Hz (n=25); 15 weeks (p<0.05): spike 3.9 ± 0.7 Hz (n=33), SWC 9.9 ± 1.2 Hz (n=25); 20 weeks (p<0.05): spike 4.4 ± 1.2 Hz (n=53), SWC 9.8 ± 1.2 Hz (n=25)].

Spontaneous Oscillatory Rhythm in Retinal Activities of Two Retinal Degeneration (rd1 and rd10) Mice

Previously, we reported that besides retinal ganglion cell (RGC) spike, there is ~ 10 Hz oscillatory rhythmic activity in local field potential (LFP) in retinal degeneration model, rd1 mice. The more recently identified rd10 mice have a later onset and slower rate of photoreceptor degeneration than the rd1 mice, providing more therapeutic potential. In this study, before adapting rd10 mice as a new animal model for our electrical stimulation study, we investigated electrical characteristics of rd10 mice. From the raw waveform of recording using 8×8 microelectrode array (MEA) from in vitro-whole mount retina, RGC spikes and LFP were isolated by using different filter setting. Fourier transform was performed for detection of frequency of bursting RGC spikes and oscillatory field potential (OFP). In rd1 mice, ~10 Hz rhythmic burst of spontaneous RGC spikes is always phase-locked with the OFP and this phase-locking property is preserved regardless of postnatal ages. However, in rd10 mice, there is a strong phase-locking tendency between the spectral peak of bursting RGC spikes (~5 Hz) and the first peak of OFP (~5 Hz) across different age groups. But this phase-locking property is not robust as in rd1 retina, but maintains for a few seconds. Since rd1 and rd10 retina show phase-locking property at different frequency (~10 Hz vs. ~5 Hz), we expect different response patterns to electrical stimulus between rd1 and rd10 retina. Therefore, to extract optimal stimulation parameters in rd10 retina, first we might define selection criteria for responding rd10 ganglion cells to electrical stimulus.

Synchrony makes neurons fire in sequence, and stimulus properties determine who is ahead

The synchronized activity of cortical neurons often features spike delays of several milliseconds. Usually, these delays are considered too small to play a role in cortical computations. Here, we use simultaneous recordings of spiking activity from up to 12 neurons to show that, in the cat visual cortex, the pairwise delays between neurons form a preferred order of spiking, called firing sequence. This sequence spans up to ∼ 15 ms and is referenced not to external events but to the internal cortical activity (e.g., beta/gamma oscillations). Most importantly, the preferred sequence of firing changed consistently as a function of stimulus properties. During beta/gamma oscillations, the reliability of firing sequences increased and approached that of firing rates. This suggests that, in the visual system, short-lived spatiotemporal patterns of spiking defined by consistent delays in synchronized activity occur with sufficient reliability to complement firing rates as a neuronal code.

Inhibitory circuits for visual processing in thalamus

Synapses made by local interneurons dominate the intrinsic circuitry of the mammalian visual thalamus and influence all signals traveling from the eye to cortex. Here we draw on physiological and computational analyses of receptive fields in the cat's lateral geniculate nucleus to describe how inhibition helps to enhance selectivity for stimulus features in space and time and to improve the efficiency of the neural code. Further, we explore specialized synaptic attributes of relay cells and interneurons and discuss how these might be adapted to preserve the temporal precision of retinal spike trains and thereby maximize the rate of information transmitted downstream.

Estimating Neuronal Information: Logarithmic Binning of Neuronal Inter-Spike Intervals

Neurons communicate via the relative timing of all-or-none biophysical signals called spikes. For statistical analysis, the time between spikes can be accumulated into inter-spike interval histograms. Information theoretic measures have been estimated from these histograms to assess how information varies across organisms, neural systems, and disease conditions. Because neurons are computational units that, to the extent they process time, work not by discrete clock ticks but by the exponential decays of numerous intrinsic variables, we propose that neuronal information measures scale more naturally with the logarithm of time. For the types of inter-spike interval distributions that best describe neuronal activity, the logarithm of time enables fewer bins to capture the salient features of the distributions. Thus, discretizing the logarithm of inter-spike intervals, as compared to the inter-spike intervals themselves, yields histograms that enable more accurate entropy and information estimates for fewer bins and less data. Additionally, as distribution parameters vary, the entropy and information calculated from the logarithm of the inter-spike intervals are substantially better behaved, e.g., entropy is independent of mean rate, and information is equally affected by rate gains and divisions. Thus, when compiling neuronal data for subsequent information analysis, the logarithm of the inter-spike intervals is preferred, over the untransformed inter-spike intervals, because it yields better information estimates and is likely more similar to the construction used by nature herself.

Independent encoding of grating motion across stationary feature maps in primary visual cortex visualized with voltage-sensitive dye imaging

In early visual cortex different stimulus parameters are represented in overlaid feature maps. Such functioning was extensively explored by the use of drifting gratings characterized by orientation, spatial-temporal frequency, and direction of motion. However surprisingly, the direct cortical visuotopic drift of the gratings' stripy pattern has never been detected simultaneously to these stationary feature maps. It therefore remains to be demonstrated how physical signals of grating motion across the cortex are represented independently of other parametric maps and thus, how multi-dimensional input is processed independently to enable effective read-out further downstream. Taking advantage of the high spatial and temporal resolution of voltage-sensitive dye imaging, we here show the real-time encoding of position and orientation. By decomposing the cortical responses to drifting gratings we visualize the typical emergence of stationary orientation maps in which specific domains exhibited highest amplitudes. Simultaneously to these patchy maps, we demonstrate coherently propagating waves of activity that precisely matched the actual movement of the gratings in space and time, most dominantly for spatial frequencies lower than the preferred range. Thus, the primary visual cortex multiplexes information about retinotopic motion by additional temporal modulation of stationary orientation signals. These signals may be used to variably extract coarse-grained object motion and form information at higher visual processing stages.

Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing

Synapses made by local interneurons dominate the thalamic circuits that process signals traveling from the eye downstream. The anatomical and physiological differences between interneurons and the (relay) cells that project to cortex are vast. To explore how these differences might influence visual processing, we made intracellular recordings from both classes of cells in vivo. Macroscopically, all receptive fields were similar, made of two concentrically arranged subregions in which dark and bright stimuli elicited responses of the reverse sign. Microscopically, however, the responses of the two types of cells had opposite profiles. Excitatory stimuli drove trains of single EPSPs in relay cells but graded depolarizations in interneurons. By contrast, suppressive stimuli evoked smooth hyperpolarizations in relay cells but unitary IPSPs in interneurons. Computational analyses suggested that these complementary patterns of response help preserve information encoded within the fine timing of retinal spikes and increase the amount of information transmitted to cortex.

The gamma slideshow: object-based perceptual cycles in a model of the visual cortex

While recent studies have shed light on the mechanisms that generate gamma (>40 Hz) oscillations, the functional role of these oscillations is still debated. Here we suggest that the purported mechanism of gamma oscillations (feedback inhibition from local interneurons), coupled with lateral connections implementing “Gestalt” principles of object integration, naturally leads to a decomposition of the visual input into object-based “perceptual cycles,” in which neuron populations representing different objects within the scene will tend to fire at successive cycles of the local gamma oscillation. We describe a simple model of V1 in which such perceptual cycles emerge automatically from the interaction between lateral excitatory connections (linking oriented cells falling along a continuous contour) and fast feedback inhibition (implementing competitive firing and gamma oscillations). Despite its extreme simplicity, the model spontaneously gives rise to perceptual cycles even when faced with natural images. The robustness of the system to parameter variation and to image complexity, together with the paucity of assumptions built in the model, support the hypothesis that perceptual cycles occur in natural vision.

Recoding of sensory information across the retinothalamic synapse

The neural code that represents the world is transformed at each stage of a sensory pathway. These transformations enable downstream neurons to recode information they receive from earlier stages. Using the retinothalamic synapse as a model system, we developed a theoretical framework to identify stimulus features that are inherited, gained, or lost across stages. Specifically, we observed that thalamic spikes encode novel, emergent, temporal features not conveyed by single retinal spikes. Furthermore, we found that thalamic spikes are not only more informative than retinal ones, as expected, but also more independent. Next, we asked how thalamic spikes gain sensitivity to the emergent features. Explicitly, we found that the emergent features are encoded by retinal spike pairs and then recoded into independent thalamic spikes. Finally, we built a model of synaptic transmission that reproduced our observations. Thus, our results established a link between synaptic mechanisms and the recoding of sensory information.

Dynamics of stimulus-evoked spike timing correlations in the cat lateral geniculate nucleus

Precisely synchronized neuronal activity has been commonly observed in the mammalian visual pathway. Spike timing correlations in the lateral geniculate nucleus (LGN) often take the form of phase synchronized oscillations in the high gamma frequency range. To study the relations between oscillatory activity, synchrony, and their time-dependent properties, we recorded activity from multiple single units in the cat LGN under stimulation by stationary spots of light. Autocorrelation analysis showed that approximately one third of the cells exhibited oscillatory firing with a mean frequency ∼80 Hz. Cross-correlation analysis showed that 30% of unit pairs showed significant synchronization, and 61% of these pairs consisted of synchronous oscillations. Cross-correlation analysis assumes that synchronous firing is stationary and maintained throughout the period of stimulation. We tested this assumption by applying unitary events analysis (UEA). We found that UEA was more sensitive to weak and transient synchrony than cross-correlation analysis and detected a higher incidence (49% of cell pairs) of significant synchrony (unitary events). In many unit pairs, the unitary events were optimally characterized at a bin width of 1 ms, indicating that neural synchrony has a high degree of temporal precision. We also found that approximately one half of the unit pairs showed nonstationary changes in synchrony that could not be predicted by the modulation of firing rates. Population statistics showed that the onset of synchrony between LGN cells occurred significantly later than that observed between retinal afferents and LGN cells. The synchrony detected among unit pairs recorded on separate tetrodes tended to be more transient and have a later onset than that observed between adjacent units. These findings show that stimulus-evoked synchronous activity within the LGN is often rhythmic, highly nonstationary, and modulated by endogenous processes that are not tightly correlated with firing rate.

Binding by asynchrony: the neuronal phase code

Neurons display continuous subthreshold oscillations and discrete action potentials (APs). When APs are phase-locked to the subthreshold oscillation, we hypothesize they represent two types of information: the presence/absence of a sensory feature and the phase of subthreshold oscillation. If subthreshold oscillation phases are neuron-specific, then the sources of APs can be recovered based on the AP times. If the spatial information about the stimulus is converted to AP phases, then APs from multiple neurons can be combined into a single axon and the spatial configuration reconstructed elsewhere. For the reconstruction to be successful, we introduce two assumptions: that a subthreshold oscillation field has a constant phase gradient and that coincidences between APs and intracellular subthreshold oscillations are neuron-specific as defined by the "interference principle." Under these assumptions, a phase-coding model enables information transfer between structures and reproduces experimental phenomenons such as phase precession, grid cell architecture, and phase modulation of cortical spikes. This article reviews a recently proposed neuronal algorithm for information encoding and decoding from the phase of APs (Nadasdy, 2009). The focus is given to the principles common across different systems instead of emphasizing system specific differences.

Synaptic plasticity controls sensory responses through frequency-dependent gamma oscillation resonance

Synchronized gamma frequency oscillations in neural networks are thought to be important to sensory information processing, and their effects have been intensively studied. Here we describe a mechanism by which the nervous system can readily control gamma oscillation effects, depending selectively on visual stimuli. Using a model neural network simulation, we found that sensory response in the primary visual cortex is significantly modulated by the resonance between “spontaneous” and “stimulus-driven” oscillations. This gamma resonance can be precisely controlled by the synaptic plasticity of thalamocortical connections, and cortical response is regulated differentially according to the resonance condition. The mechanism produces a selective synchronization between the afferent and downstream neural population. Our simulation results explain experimental observations such as stimulus-dependent synchronization between the thalamus and the cortex at different oscillation frequencies. The model generally shows how sensory information can be selectively routed depending on its frequency components.

In the nervous system, a network of neurons shows interesting population activities. One example is a various frequency of synchronized oscillations which are thought to be important to sensory functions. In particular, it has been reported that gamma frequency rhythms (30∼70Hz) in the cortex can significantly regulate the responses to visual stimuli. In this study, we further investigate the mechanism by which the nervous system can control the effect of gamma oscillation on the modulation of neural responses. We found that the sensory response of the visual cortex strongly depends on the extent of synchronization between external stimulus rhythms and spontaneous gamma oscillations in the cortical network. Furthermore, the simulation results show that the plasticity of the neural circuit can modulate the frequency of spontaneous gamma oscillations, thus readily controlling neural population responsiveness. This finding is related to the question of how the brain efficiently interprets external input signals under various conditions, using its internal neural connectivity. Our study provides insight into this question.

Sensory input drives multiple intracellular information streams in somatosensory cortex

Stable perception arises from the interaction between sensory inputs and internal activity fluctuations in cortex. Here we analyzed how different types of activity contribute to cortical sensory processing at the cellular scale. We performed whole-cell recordings in the barrel cortex of anesthetized rats while applying ongoing whisker stimulation and measured the information conveyed about the time-varying stimulus by different types of input (membrane potential) and output (spiking) signals. We found that substantial, comparable amounts of incoming information are carried by two types of membrane potential signal: slow, large (up-down state) fluctuations, and faster (>20 Hz), smaller-amplitude synaptic activity. Both types of activity fluctuation are therefore significantly driven by the stimulus on an ongoing basis. Each stream conveys essentially independent information. Output (spiking) information is contained in spike timing not just relative to the stimulus but also relative to membrane potential fluctuations. Information transfer is favored in up states relative to down states. Thus, slow, ongoing activity fluctuations and finer-scale synaptic activity generate multiple channels for incoming and outgoing information within barrel cortex neurons during ongoing stimulation.