Dynamics of neurons in the cat lateral geniculate nucleus: in vivo electrophysiology and computational modeling

Temporal Sensitivity for Achromatic and Chromatic Flicker across the Visual Cortex

The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic postreceptoral channels. The goal of the current study was to determine temporal sensitivity across the three postreceptoral channels in subcortical and cortical regions involved in human vision. We measured functional magnetic resonance imaging (fMRI) responses at 7 T from three participants (two males, one female) viewing a high-contrast, flickering, spatially uniform wide field (∼140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L + M + S, L - M, and S - (L + M) cone combinations. These measurements were used to create temporal sensitivity functions of the primary visual cortex (V1) across eccentricity and spatially averaged responses from the lateral geniculate nucleus (LGN), and the V2/V3, hV4, and V3A/B regions. fMRI responses reflected the known properties of the visual system, including higher peak temporal sensitivity to achromatic versus chromatic stimuli and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. The comparison of measured cortical responses to a model of the integrated retinal output to our stimuli demonstrates that extensive filtering and amplification are applied to postretinal signals.

Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales

The processing of sensory information, even at early stages, is influenced by the internal state of the animal. Internal states, such as arousal, are often characterized by relating neural activity to a single "level" of arousal, defined by a behavioral indicator such as pupil size. In this study, we expand the understanding of arousal-related modulations in sensory systems by uncovering multiple timescales of pupil dynamics and their relationship to neural activity. Specifically, we observed a robust coupling between spiking activity in the mouse dorsolateral geniculate nucleus (dLGN) of the thalamus and pupil dynamics across timescales spanning a few seconds to several minutes. Throughout all these timescales, 2 distinct spiking modes-individual tonic spikes and tightly clustered bursts of spikes-preferred opposite phases of pupil dynamics. This multi-scale coupling reveals modulations distinct from those captured by pupil size per se, locomotion, and eye movements. Furthermore, coupling persisted even during viewing of a naturalistic movie, where it contributed to differences in the encoding of visual information. We conclude that dLGN spiking activity is under the simultaneous influence of multiple arousal-related processes associated with pupil dynamics occurring over a broad range of timescales.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes

We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spiking pattern. The SNN includes excitatory and inhibitory neurons in some proportion, sustaining the excitation-inhibition balance of autonomous firing. The astrocytes accompanying each excitatory synapse provide a slow modulation of synaptic transmission strength. An information image was uploaded to the network in the form of excitatory stimulation pulses distributed in time reproducing the shape of the image. We found that astrocytic modulation prevented stimulation-induced SNN hyperexcitation and non-periodic bursting activity. Such homeostatic astrocytic regulation of neuronal activity makes it possible to restore the image supplied during stimulation and lost in the raster diagram of neuronal activity due to non-periodic neuronal firing. At a biological point, our model shows that astrocytes can act as an additional adaptive mechanism for regulating neural activity, which is crucial for sensory cortical representations.

Involvement of the thalamic reticular nucleus in prepulse inhibition of acoustic startle

Thalamic reticular nucleus (TRN) is a group of inhibitory neurons surrounding the thalamus. Due to its important role in sensory information processing, TRN is considered as the target nucleus for the pathophysiological investigation of schizophrenia and autism spectrum disorder (ASD). Prepulse inhibition (PPI) of acoustic startle response, a phenomenon that strong stimulus-induced startle reflex is reduced by a weaker prestimulus, is always found impaired in schizophrenia and ASD. But the role of TRN in PPI modulation remains unknown. Here, we report that parvalbumin-expressing (PV+) neurons in TRN are activated by sound stimulation of PPI paradigm. Chemogenetic inhibition of PV+ neurons in TRN impairs PPI performance. Further investigations on the mechanism suggest a model of burst-rebound burst firing in TRN-auditory thalamus (medial geniculate nucleus, MG) circuitry. The burst firing is mediated by T-type calcium channel in TRN, and rebound burst firing needs the participation of GABAB receptor in MG. Overall, these findings support the involvement of TRN in PPI modulation.

Thalamic state influences timing precision in the thalamocortical circuit

Sensory signals from the outside world are transduced at the periphery, passing through thalamus before reaching cortex, ultimately giving rise to the sensory representations that enable us to perceive the world. The thalamocortical circuit is particularly sensitive to the temporal precision of thalamic spiking due to highly convergent synaptic connectivity. Thalamic neurons can exhibit burst and tonic modes of firing that strongly influence timing within the thalamus. The impact of these changes in thalamic state on sensory encoding in the cortex, however, remains unclear. Here, we investigated the role of thalamic state on timing in the thalamocortical circuit of the vibrissa pathway in the anesthetized rat. We optogenetically hyperpolarized thalamus while recording single unit activity in both thalamus and cortex. Tonic spike-triggered analysis revealed temporally precise thalamic spiking that was locked to weak white-noise sensory stimuli, whereas thalamic burst spiking was associated with a loss in stimulus-locked temporal precision. These thalamic state-dependent changes propagated to cortex such that the cortical timing precision was diminished during the hyperpolarized (burst biased) thalamic state. Although still sensory driven, the cortical neurons became significantly less precisely locked to the weak white-noise stimulus. The results here suggests a state-dependent differential regulation of spike timing precision in the thalamus that could gate what signals are ultimately propagated to cortex.NEW & NOTEWORTHY The majority of sensory signals are transmitted through the thalamus. There is growing evidence of complex thalamic gating through coordinated firing modes that have a strong impact on cortical sensory representations. Optogenetic hyperpolarization of thalamus pushed it into burst firing that disrupted precise time-locked sensory signaling, with a direct impact on the downstream cortical encoding, setting the stage for a timing-based thalamic gate of sensory signaling.

Temporal information loss in the macaque early visual system

Stimuli that modulate neuronal activity are not always detectable, indicating a loss of information between the modulated neurons and perception. To identify where in the macaque visual system information about periodic light modulations is lost, signal-to-noise ratios were compared across simulated cone photoreceptors, lateral geniculate nucleus (LGN) neurons, and perceptual judgements. Stimuli were drifting, threshold-contrast Gabor patterns on a photopic background. The sensitivity of LGN neurons, extrapolated to populations, was similar to the monkeys' at low temporal frequencies. At high temporal frequencies, LGN sensitivity exceeded the monkeys' and approached the upper bound set by cone photocurrents. These results confirm a loss of high-frequency information downstream of the LGN. However, this loss accounted for only about 5% of the total. Phototransduction accounted for essentially all of the rest. Together, these results show that low temporal frequency information is lost primarily between the cones and the LGN, whereas high-frequency information is lost primarily within the cones, with a small additional loss downstream of the LGN.

Prefrontal cortex modulates firing pattern in the nucleus reuniens of the midline thalamus via distinct corticothalamic pathways

The thalamus has long been recognized for its role in relaying sensory information from the periphery, a function accomplished by its "first-order" nuclei. However, a second category of thalamic nuclei, termed "higher-order" nuclei, have been shown instead to mediate communication between cortical areas. The nucleus reuniens of the midline thalamus (RE) is a higher-order nucleus known to act as a conduit of reciprocal communication between the medial prefrontal cortex (mPFC) and hippocampus. While anatomical and behavioural studies of RE are numerous, circuit-based electrophysiological studies, particularly those examining the impact of cortical input and the thalamic reticular nucleus (TRN) on RE neuron firing, are sparse. To characterize RE neuron firing properties and dissect the circuit dynamics of the infralimbic subdivision of the mPFC (ilPFC), the TRN and RE, we used in vivo, extracellular, single-unit recordings in male Sprague Dawley rats and manipulated neural activity using targeted pharmacological manipulations, electrical stimulation and a projection-specific implementation of designer receptors exclusively activated by designer drugs (DREADDs). We show that ilPFC inhibition reduces multiple burst firing parameters in RE, whereas ilPFC stimulation drives burst firing and dampens tonic firing. In addition, TRN inhibition reduces the number of spontaneously active neurons in RE. Finally, inhibition of ilPFC terminals in RE selectively enhances a subset of burst firing parameters. These findings demonstrate that ilPFC input, both via direct projections and via the TRN, can modulate RE neuron firing pattern in nuanced and complex ways. They also highlight the ilPFC-TRN-RE circuit as a likely critical component of prefrontal-hippocampal interactions.

A novel mutual information estimator to measure spike train correlations in a model thalamocortical network

The impact of thalamic state on information transmission to the cortex remains poorly understood. This limitation exists due to the rich dynamics displayed by thalamocortical networks and because of inadequate tools to characterize those dynamics. Here, we introduce a novel estimator of mutual information and use it to determine the impact of a computational model of thalamic state on information transmission. Using several criteria, this novel estimator, which uses an adaptive partition, is shown to be superior to other mutual information estimators with uniform partitions when used to analyze simulated spike train data with different mean spike rates, as well as electrophysiological data from simultaneously recorded neurons. When applied to a thalamocortical model, the estimator revealed that thalamocortical cell T-type calcium current conductance influences mutual information between the input and output from this network. In particular, a T-type calcium current conductance of ~40 nS appears to produce maximal mutual information between the input to this network (conceptualized as afferent input to the thalamocortical cell) and the output of the network at the level of a layer 4 cortical neuron. Furthermore, at particular combinations of inputs to thalamocortical and thalamic reticular nucleus cells, thalamic cell bursting correlated strongly with recovery of mutual information between thalamic afferents and layer 4 neurons. These studies suggest that the novel mutual information estimator has advantages over previous estimators and that thalamic reticular nucleus activity can enhance mutual information between thalamic afferents and thalamorecipient cells in the cortex. NEW & NOTEWORTHY In this study, a novel mutual information estimator was developed to analyze information flow in a model thalamocortical network. Our findings suggest that this estimator is a suitable tool for signal transmission analysis, particularly in neural circuits with disparate firing rates, and that the thalamic reticular nucleus can potentiate ascending sensory signals, while thalamic recipient cells in the cortex can recover mutual information in ascending sensory signals that is lost due to thalamic bursting.

Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells

Visually evoked signals in the retina pass through the dorsal geniculate nucleus (dLGN) on the way to the visual cortex. This is however not a simple feedforward flow of information: there is a significant feedback from cortical cells back to both relay cells and interneurons in the dLGN. Despite four decades of experimental and theoretical studies, the functional role of this feedback is still debated. Here we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. For this model the responses are found by direct evaluation of two- or three-dimensional integrals allowing for fast and comprehensive studies of putative effects of different candidate organizations of the cortical feedback. Our analysis identifies a special mixed configuration of excitatory and inhibitory cortical feedback which seems to best account for available experimental data. This configuration consists of (i) a slow (long-delay) and spatially widespread inhibitory feedback, combined with (ii) a fast (short-delayed) and spatially narrow excitatory feedback, where (iii) the excitatory/inhibitory ON-ON connections are accompanied respectively by inhibitory/excitatory OFF-ON connections, i.e. following a phase-reversed arrangement. The recent development of optogenetic and pharmacogenetic methods has provided new tools for more precise manipulation and investigation of the thalamocortical circuit, in particular for mice. Such data will expectedly allow the eDOG model to be better constrained by data from specific animal model systems than has been possible until now for cat. We have therefore made the Python tool pyLGN which allows for easy adaptation of the eDOG model to new situations.

On route from the retina to primary visual cortex, visually evoked signals have to pass through the dorsal lateral geniculate nucleus (dLGN). However, this is not an exclusive feedforward flow of information as feedback exists from neurons in the cortex back to both relay cells and interneurons in the dLGN. The functional role of this feedback remains mostly unresolved. Here, we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. Our analysis indicates that a particular mix of excitatory and inhibitory cortical feedback agrees best with available experimental observations. In this configuration ON-center relay cells receive both excitatory and (indirect) inhibitory feedback from ON-center cortical cells (ON-ON feedback) where the excitatory feedback is fast and spatially narrow while the inhibitory feedback is slow and spatially widespread. In addition to the ON-ON feedback, the connections are accompanied by OFF-ON connections following a so-called phase-reversed (push-pull) arrangement. To facilitate further applications of the model, we have made the Python tool pyLGN which allows for easy modification and evaluation of the a priori quite general eDOG model to new situations.

Spike and burst coding in thalamocortical relay cells

Mammalian thalamocortical relay (TCR) neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA) and the Event-Triggered Covariance (ETC). This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms) and showed a clear distinction between spikes (selective for fluctuations) and bursts (selective for integration). The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (I_T) and the cyclic nucleotide modulated h current (I_h). The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two currents. Finally, the model was used to investigate the more realistic “high-conductance state”, where fluctuations are caused by (synaptic) conductance changes instead of current injection. Under “standard” conditions bursts are difficult to initiate, given the high degree of inactivation of the T-type calcium current. Strong and/or precisely timed inhibitory currents were able to remove this inactivation.

Neurons in the brain respond to (sensory) stimuli by generating electrical pulses called ‘spikes’ or ‘action potentials’. Spikes are organized in different temporal patterns, such as ‘bursts’ in which they occur at a high frequency followed by a period of silence. Bursts are ubiquitous in the nervous system: they occur in different parts of the brain and in different species. Different mechanisms that generate them have been pointed out. Why the nervous system uses bursts in its communication, or what type of information is represented by bursts, remains largely unknown. Here, we looked at bursting in thalamocortical relay (TCR) cells, neurons that form a bridge between early sensory processing and higher-order structures (cortex). These cells fire bursts as a result of the activation of two distinct subthreshold ionic currents: the T-type calcium current and the h-type current. We investigated experimentally and computationally what features in the input makes TCR cells respond with bursts, and what features with single spikes. Bursts are a response to low-frequency slowly increasing input; single spikes are a response to faster fluctuations. Moreover, bursts are rare and highly informative, in line with an earlier hypothesis that bursts could play a ‘wake-up call’ role in the nervous system.

The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions

The physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM; Heeger DJ. Vis Neurosci 9: 181-197, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.

Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits

Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons.

Information Coding through Adaptive Gating of Synchronized Thalamic Bursting

It has been posited that the regulation of burst/tonic firing in the thalamus could function as a mechanism for controlling not only how much but what kind of information is conveyed to downstream cortical targets. Yet how this gating mechanism is adaptively modulated on fast timescales by ongoing sensory inputs in rich sensory environments remains unknown. Using single-unit recordings in the rat vibrissa thalamus (VPm), we found that the degree of bottom-up adaptation modulated thalamic burst/tonic firing as well as the synchronization of bursting across the thalamic population along a continuum for which the extremes facilitate detection or discrimination of sensory inputs. Optogenetic control of baseline membrane potential in thalamus further suggests that this regulation may result from an interplay between adaptive changes in thalamic membrane potential and synaptic drive from inputs to thalamus, setting the stage for an intricate control strategy upon which cortical computation is built.

Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model

The thalamic reticular nucleus (TRN) is a shell of GABAergic neurons that surrounds the dorsal thalamus. Previous work has shown that TRN neurons send GABAergic projections to thalamocortical (TC) cells to form reciprocal, closed-loop circuits. This has led to the hypothesis that the TRN is responsible for oscillatory phenomena, such as sleep spindles and absence seizures. However, there is emerging evidence that open-loop circuits are also found between TRN and TC cells. The implications of open-loop configurations are not yet known, particularly when they include time-dependent nonlinearities in TC cells such as low-threshold bursting. We hypothesized that low-threshold bursting in an open-loop circuit could be a mechanism by which the TRN could paradoxically enhance TC activation, and that enhancement would depend on the relative timing of TRN vs. TC cell stimulation. To test this, we modeled small circuits containing TC neurons, TRN neurons, and layer 4 thalamorecipient cells in both open- and closed-loop configurations. We found that open-loop TRN stimulation, rather than universally depressing TC activation, increased cortical output across a broad parameter space, modified the filter properties of TC neurons, and altered the mutual information between input and output in a frequency-dependent and T-type calcium channel-dependent manner. Therefore, an open-loop model of TRN-TC interactions, rather than suppressing transmission through the thalamus, creates a tunable filter whose properties may be modified by outside influences onto the TRN. These simulations make experimentally testable predictions about the potential role for the TRN for flexible enhancement of cortical activation.

Interhemispheric interactions of the human thalamic reticular nucleus

The thalamic reticular nucleus is an important structure governing the recurrent interactions between the thalamus and cortex that may provide a substrate for unified perception. Despite the importance of the TRN, its activity has been scarcely investigated in vivo in animal models, and never in humans. Here we anatomically identify the human TRN using multiple registered and averaged proton density-weighted structural MRI scans and drive its functional activity with a dual phase-encoded stimulus. We characterize the retinotopic and temporal response properties in the visual sector of the TRN and measured an inhibitory relationship with the contralateral LGN. These observations provide a basis for further gross characterizations of the role of the TRN in human behavior.

Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons

Synaptic noise is thought to be a limiting factor for computational efficiency in the brain. In visual cortex (V1), ongoing activity is present in vivo, and spiking responses to simple stimuli are highly unreliable across trials. Stimulus statistics used to plot receptive fields, however, are quite different from those experienced during natural visuomotor exploration. We recorded V1 neurons intracellularly in the anaesthetized and paralyzed cat and compared their spiking and synaptic responses to full field natural images animated by simulated eye-movements to those evoked by simpler (grating) or higher dimensionality statistics (dense noise). In most cells, natural scene animation was the only condition where high temporal precision (in the 10–20 ms range) was maintained during sparse and reliable activity. At the subthreshold level, irregular but highly reproducible membrane potential dynamics were observed, even during long (several 100 ms) “spike-less” periods. We showed that both the spatial structure of natural scenes and the temporal dynamics of eye-movements increase the signal-to-noise ratio by a non-linear amplification of the signal combined with a reduction of the subthreshold contextual noise. These data support the view that the sparsening and the time precision of the neural code in V1 may depend primarily on three factors: (1) broadband input spectrum: the bandwidth must be rich enough for recruiting optimally the diversity of spatial and time constants during recurrent processing; (2) tight temporal interplay of excitation and inhibition: conductance measurements demonstrate that natural scene statistics narrow selectively the duration of the spiking opportunity window during which the balance between excitation and inhibition changes transiently and reversibly; (3) signal energy in the lower frequency band: a minimal level of power is needed below 10 Hz to reach consistently the spiking threshold, a situation rarely reached with visual dense noise.

Bursts and isolated spikes code for opposite movement directions in midbrain electrosensory neurons

Directional selectivity, in which neurons respond strongly to an object moving in a given direction but weakly or not at all to the same object moving in the opposite direction, is a crucial computation that is thought to provide a neural correlate of motion perception. However, directional selectivity has been traditionally quantified by using the full spike train, which does not take into account particular action potential patterns. We investigated how different action potential patterns, namely bursts (i.e. packets of action potentials followed by quiescence) and isolated spikes, contribute to movement direction coding in a mathematical model of midbrain electrosensory neurons. We found that bursts and isolated spikes could be selectively elicited when the same object moved in opposite directions. In particular, it was possible to find parameter values for which our model neuron did not display directional selectivity when the full spike train was considered but displayed strong directional selectivity when bursts or isolated spikes were instead considered. Further analysis of our model revealed that an intrinsic burst mechanism based on subthreshold T-type calcium channels was not required to observe parameter regimes for which bursts and isolated spikes code for opposite movement directions. However, this burst mechanism enhanced the range of parameter values for which such regimes were observed. Experimental recordings from midbrain neurons confirmed our modeling prediction that bursts and isolated spikes can indeed code for opposite movement directions. Finally, we quantified the performance of a plausible neural circuit and found that it could respond more or less selectively to isolated spikes for a wide range of parameter values when compared with an interspike interval threshold. Our results thus show for the first time that different action potential patterns can differentially encode movement and that traditional measures of directional selectivity need to be revised in such cases.

A minimal mechanistic model for temporal signal processing in the lateral geniculate nucleus

The receptive fields of cells in the lateral geniculate nucleus (LGN) are shaped by their diverse set of impinging inputs: feedforward synaptic inputs stemming from retina, and feedback inputs stemming from the visual cortex and the thalamic reticular nucleus. To probe the possible roles of these feedforward and feedback inputs in shaping the temporal receptive-field structure of LGN relay cells, we here present and investigate a minimal mechanistic firing-rate model tailored to elucidate their disparate features. The model for LGN relay ON cells includes feedforward excitation and inhibition (via interneurons) from retinal ON cells and excitatory and inhibitory (via thalamic reticular nucleus cells and interneurons) feedback from cortical ON and OFF cells. From a general firing-rate model formulated in terms of Volterra integral equations, we derive a single delay differential equation with absolute delay governing the dynamics of the system. A freely available and easy-to-use GUI-based MATLAB version of this minimal mechanistic LGN circuit model is provided. We particularly investigate the LGN relay-cell impulse response and find through thorough explorations of the model's parameter space that both purely feedforward models and feedback models with feedforward excitation only, can account quantitatively for previously reported experimental results. We find, however, that the purely feedforward model predicts two impulse response measures, the time to first peak and the biphasic index (measuring the relative weight of the rebound phase) to be anticorrelated. In contrast, the models with feedback predict different correlations between these two measures. This suggests an experimental test assessing the relative importance of feedforward and feedback connections in shaping the impulse response of LGN relay cells.

Coding movement direction by burst firing in electrosensory neurons

Directional selectivity, in which neurons respond strongly to an object moving in a given direction ("preferred") but respond weakly or not at all to an object moving in the opposite direction ("null"), is a critical computation achieved in brain circuits. Previous measures of direction selectivity have compared the numbers of action potentials elicited by each direction of movement, but most sensory neurons display patterning, such as bursting, in their spike trains. To examine the contribution of patterned responses to direction selectivity, we recorded from midbrain neurons in weakly electric fish and found that most neurons responded with a combination of both bursts and isolated spikes to moving object stimuli. In these neurons, we separated bursts and isolated spikes using an interspike interval (ISI) threshold. The directional bias of bursts was significantly higher than that of either the full spike train or the isolated spike train. To examine the encoding and decoding of bursts, we built biologically plausible models that examine 1) the upstream mechanisms that generate these spiking patterns and 2) downstream decoders of bursts. Our model of upstream mechanisms uses an interaction between afferent input and subthreshold calcium channels to give rise to burst firing that occurs preferentially for one direction of movement. We tested this model in vivo by application of calcium antagonists, which reduced burst firing and eliminated the differences in direction selectivity between bursts, isolated spikes, and the full spike train. Our model of downstream decoders used strong synaptic facilitation to achieve qualitatively similar results to those obtained using the ISI threshold criterion. This model shows that direction selective information carried by bursts can be decoded by downstream neurons using biophysically plausible mechanisms.

Cortical modulation of the transient visual response at thalamic level: a TMS study

The transient visual response of feline dorsal lateral geniculate nucleus (dLGN) cells was studied under control conditions and during the application of repetitive transcranial magnetic stimulation at 1 Hz (rTMS@1Hz) on the primary visual cortex (V1). The results show that rTMS@1Hz modulates the firing mode of Y cells, inducing an increase in burst spikes and a decrease in tonic firing. On the other hand, rTMS@1Hz modifies the spatiotemporal characteristics of receptive fields of X cells, inducing a delay and a decrease of the peak response, and a change of the surround/center amplitude ratio of RF profiles. These results indicate that V1 controls the activity of the visual thalamus in a different way in the X and Y pathways, and that this feedback control is consistent with functional roles associated with each cell type.

Spike timing and information transmission at retinogeniculate synapses

This study examines the rules governing the transfer of spikes between the retina and the lateral geniculate nucleus (LGN) with the goal of determining whether the most informative retinal spikes preferentially drive LGN responses and what role spike timing plays in the process. By recording from monosynaptically connected pairs of retinal ganglion cells and LGN neurons in vivo in the cat, we show that relayed spikes are more likely than nonrelayed spikes to be evoked by stimuli that match the receptive fields of the recorded cells and that an interspike interval-based mechanism contributes to the process. Relayed spikes are also more reliable in their timing and number where they often achieve the theoretical limit of minimum variance. As a result, relayed spikes carry more visual information per spike. Based on these results, we conclude that retinogeniculate processing increases sparseness in the neural code by selectively relaying the highest fidelity spikes to the visual cortex.

The episodic nature of spike trains in the early visual pathway

An understanding of the neural code in a given visual area is often confounded by the immense complexity of visual stimuli combined with the number of possible meaningful patterns that comprise the response spike train. In the lateral geniculate nucleus (LGN), visual stimulation generates spike trains comprised of short spiking episodes ("events") separated by relatively long intervals of silence, which establishes a basis for in-depth analysis of the neural code. By studying this event structure in both artificial and natural visual stimulus contexts and at different contrasts, we are able to describe the dependence of event structure on stimulus class and discern which aspects generalize. We find that the event structure on coarse time scales is robust across stimulus and contrast and can be explained by receptive field processing. However, the relationship between the stimulus and fine-time-scale features of events is less straightforward, partially due to a significant amount of trial-to-trial variability. A new measure called "label information" identifies structural elements of events that can contain ≤30% more information in the context of natural movies compared with what is available from the overall event timing. The first interspike interval of an event most robustly conveys additional information about the stimulus and is somewhat more informative than the event spike count and much more informative than the presence of bursts. Nearly every event is preserved across contrast despite changes in their fine-time-scale features, suggesting that--at least on a coarse level--the stimulus selectivity of LGN neurons is contrast invariant. Event-based analysis thus casts previously studied elements of LGN coding such as contrast adaptation and receptive field processing in a new light and leads to broad conclusions about the composition of the LGN neuronal code.

Intracortical connections are not required for oscillatory activity in the visual cortex

Synchronized oscillatory discharge in the visual cortex has been proposed to underlie the linking of retinotopically disparate features into perceptually coherent objects. These proposals have largely relied on the premise that the oscillations arise from intracortical circuitry. However, strong oscillations within both the retina and the lateral geniculate nucleus (LGN) have been reported recently. To evaluate the possibility that cortical oscillations arise from peripheral pathways, we have developed two plausible models of single cell oscillatory discharge that specifically exclude intracortical networks. In the first model, cortical oscillatory discharge near 50 Hz in frequency arises from the integration of signals from strongly oscillatory cells within the LGN. The model also predicts the incidence of 50-Hz oscillatory cells within the cortex. Oscillatory discharge around 30 Hz is explained in a second model by the presence of intrinsically oscillatory cells within cortical layer 5. Both models generate spike trains whose power spectra and mean firing rates are in close agreement with experimental observations of simple and complex cells. Considered together, the two models can largely account for the nature and incidence of oscillatory discharge in the cat's visual cortex. The validity of these models is consistent with the possibility that oscillations are generated independently of intracortical interactions. Because these models rely on intrinsic stimulus-independent oscillators within the retina and cortex, the results further suggest that oscillatory activity within the cortex is not necessarily associated with the processing of high-order visual information.

Intracortical connections are not required for oscillatory activity in the visual cortex

arises from the integration of signals from strongly oscillatory cells within the LGN. The model also predicts the incidence of 50-Hz oscillatory cells within the cortex. Oscillatory discharge around 30 Hz is explained in a second model by the presence of intrinsically oscillatory cells within cortical layer 5. Both models generate spike trains whose power spectra and mean firing rates are in close agreement with experimental observations of simple and complex cells. Considered together, the two models can largely account for the nature and incidence of oscillatory discharge in the cat's visual cortex. The validity of these models is consistent with the possibility that oscillations are generated independently of intracortical interactions. Because these models rely on intrinsic stimulus-independent oscillators within the retina and cortex, the results further suggest that oscillatory activity within the cortex is not necessarily associated with the processing of high-order visual information.

Functional mechanisms shaping lateral geniculate responses to artificial and natural stimuli

Functional models of the early visual system should predict responses not only to simple artificial stimuli but also to sequences of complex natural scenes. An ideal testbed for such models is the lateral geniculate nucleus (LGN). Mechanisms shaping LGN responses include the linear receptive field and two fast adaptation processes, sensitive to luminance and contrast. We propose a compact functional model for these mechanisms that operates on sequences of arbitrary images. With the same parameters that fit the firing rate responses to simple stimuli, it predicts the bulk of the firing rate responses to complex stimuli, including natural scenes. Further improvements could result by adding a spiking mechanism, possibly one capable of bursts, but not by adding mechanisms of slow adaptation. We conclude that up to the LGN the responses to natural scenes can be largely explained through insights gained with simple artificial stimuli.

Information measure for analyzing specific spiking patterns and applications to LGN bursts

Neural spiking responses can include a variety of spiking patterns. However, neither the mere presence of the patterns nor the pattern's frequency indicates that the pattern conveys distinct stimulus information. Here, we present an in-depth analysis of a Pattern Information measure, which quantifies how informative it is to distinguish a particular pattern of spikes from either a single spike or an another pattern. (1) We show how a shuffle-controlled estimation method minimizes the impact of sampling bias. (2) We describe how the Pattern Information could arise from time-varying firing rates, and we demonstrate an analysis to determine whether Pattern Information associated with a particular pattern captures structure not contained in the time-varying firing rate. (3) Because patterns may contain several spikes or inter-spike intervals, we extend the Pattern Information measure to determine whether the complete pattern carries information distinct from sub-patterns containing only a fraction of these spikes or intervals. (4) The Pattern Information is applied to determine whether a plurality of patterns carry distinct stimulus information from one another. In particular, we demonstrate these concepts using data from cells of the lateral geniculate nucleus (LGN), thereby extending previous analysis demonstrating that distinguishes between bursts of spikes and single spikes providing visual information.

Thalamic filtering of retinal spike trains by postsynaptic summation

At many synapses in the central nervous system, spikes within high-frequency trains have a better chance of driving the postsynaptic neuron than spikes occurring in isolation. We asked what mechanism accounts for this selectivity at the retinogeniculate synapse. The amplitude of synaptic potentials was remarkably constant, ruling out a major role for presynaptic mechanisms such as synaptic facilitation. Instead, geniculate spike trains could be predicted from retinal spike trains on the basis of postsynaptic summation. This simple form of integration explains the response differences between a geniculate neuron and its main retinal driver, and thereby determines the flow of visual information to cortex.

Different roles for AMPA and NMDA receptors in transmission at the immature retinogeniculate synapse

The relay of information at the retinogeniculate synapse, the connection between retina and visual thalamus, begins days before eye opening and is thought to play an important role in the maturation of neural circuits in the thalamus and visual cortex. Remarkably, during this period of development, the retinogeniculate synapse is immature, with single retinal ganglion cell inputs evoking an average peak excitatory postsynaptic current (EPSC) of only about 40 pA compared with 800 pA in mature synapses. Yet, at the mature synapse, EPSCs >400 pA are needed to drive relay neuron firing. This raises the question of how small-amplitude EPSCs can drive transmission at the immature retinogeniculate synapse. Here we find that several features of the immature synapse, compared with the mature synapse, contribute to synaptic transmission. First, although the peak amplitude of EPSC is small, the decay time course of both alpha-amino-3-hydroxy-5-methyl-4isoxazolepropionic acid receptor (AMPAR) and N-methyl-d-aspartate receptor (NMDAR) currents is significantly slower. The prolonged time course of NMDAR currents is a result of the presence of both NR2B and NR2C/D subunits. In addition, the extended presence of neurotransmitter released prolongs the synaptic current time course. Second, reduced sensitivity to magnesium block results in significantly greater synaptic charge transfer through NMDAR. Third, AMPAR currents contribute to the spike latency, but not to temporal precision, at the immature synapse. Furthermore, intrinsic excitability is greater. These properties enable immature synapses with predominantly NMDARs and little or no AMPARs to contribute to the relay of information from retina to visual cortex.

The role of cortical feedback in the generation of the temporal receptive field responses of lateral geniculate nucleus neurons: a computational modelling study

The influence of cortical feedback on thalamic visual responses has been a source of much discussion in recent years. In this study we examine the possible role of cortical feedback in shaping the spatiotemporal receptive field (STRF) responses of thalamocortical (TC) cells in the lateral geniculate nucleus (LGN) of the thalamus. A population-based computational model of the thalamocortical network is used to generate a representation of the STRF response of LGN TC cells within the corticothalamic feedback circuit. The cortical feedback is shown to have little influence on the spatial response properties of the STRF organization. However, the model suggests that cortical feedback may play a key role in modifying the experimentally observed biphasic temporal response property of the STRF, that is, the reversal over time of the polarity of ON and OFF responses of the centre and surround of the receptive field, in particular accounting for the experimentally observed mismatch between retinal cells and TC cells in respect of the magnitude of the second (rebound) phase of the temporal response. The model results also show that this mismatch may result from an anti-phase corticothalamic feedback mechanism.

Retinogeniculate Transmission in Wakefulness

Despite popular belief that the primary function of the thalamus is to “gate” sensory inputs by state, few studies have attempted to directly characterize the efficacy of such gating in the awake, behaving animal. I measured the efficacy of retinogeniculate transmission in the awake cat by taking advantage of the fact that many neurons in the lateral geniculate nucleus (LGN) are dominated by a single retinal input, and that this input produces a distinct event known as the S-potential. Retinal input failed to produce an LGN action potential half of the time. However, success or failure was powerfully tied to the recency of the S-potential. Short intervals tend to be successful and long intervals unsuccessful. For four of 12 neurons, the probability that a given S-potential could cause a spike exceeded 90% if that S-potential was preceded by an S-potential within the previous 10 ms (100 Hz). Whereas this temporal influence on efficacy has been demonstrated extensively in anesthetized animals, wakefulness is different in several ways. Overall efficacy is better in wakefulness than in anesthesia, the durations of facilitating effects are briefer in wakefulness, efficacy of long intervals is superior in wakefulness, and the temporal dependence can be briefly disrupted by altering background illumination. The last two observations may be particularly significant. Increased success at long intervals in wakefulness provides additional evidence that the spike code of the anesthetized animal is not the spike code of the awake animal. Altering retinogeniculate efficacy by altering visual conditions undermines the influence inter-S-potential interval might have in determining efficacy in the real world. Finally, S-potential amplitude, duration, and even slope are dynamic and systematic within wakefulness; providing further support that the S-potential is the extracellular signature of the retinal EPSP.

Signal detection of salient visual features by the early visual pathway

The role of the lateral geniculate nucleus (LGN) of the thalamus in visual encoding remains an open question. Visual stimulation of the LGN produces two distinct types of responses: tonic and burst. It has been suggested that these two modes of response could serve to transmit high fidelity features of the visual world (tonic) or robustly detect salient features of the visual world (burst). Here, we use a combination of experimental and simulated LGN responses to natural scene movies to investigate the specificity of burst generation, and their role in signaling salient features of the visual scene. LGN responses to excitatory stimulus features were simulated with and without bursts and analyzed using signal detection theory. We find that bursts enhance detection of the onset of excitatory features as compared to purely tonic firing, and that algorithms inspired by this type of framework can enhance the transmission of visual information in situations with limited bandwidth.

Thalamic burst mode and inattention in the awake LGNd

Awake mammals are often inattentive in familiar environments, but must still respond appropriately to relevant visual stimulation. Such "inattentive vision" has received little study, perhaps due to difficulties in controlling eye position in this state. In rabbits, eye position is exceedingly stable in both alert and inattentive states. Here, we exploit this stability to examine temporal filtering of visual information in LGNd neurons as rabbits alternate between EEG-defined states. Within a single second of shifting from alert to an inattentive state, both peak temporal frequency and bandwidth were sharply reduced, and burst frequency increased dramatically. However, spatial dimensions of receptive field centers showed no significant state dependence. We conclude that extremely rapid and significant changes in temporal filtering and bursting occur in the LGNd as awake subjects shift between alert and inattentive states.

Visual control of burst priming in the anesthetized lateral geniculate nucleus

Thalamic relay cells fire bursts of action potentials. Once a long hyperpolarization "primes" (deinactivates) the T-type calcium channel, a depolarizing input will "trigger" a calcium spike with a burst of action potentials. During sleep, bursts are frequent, rhythmic, and nonvisual. Bursts have been observed in alert animals, and burst timing is known to carry visual information under light anesthesia. We extend this finding by showing that bursts without visual triggers are rare. Nevertheless, if the channel were primed at random with respect to the stimulus, then bursts would have the same visual significance as single spikes. We find, however, that visual signals influence when the channel is primed. First, natural time-varying stimuli evoke more bursts than white noise. Second, specific visual stimuli reproducibly elicit bursts, whereas others reliably elicit single spikes. Therefore, visual information is encoded by the selective tagging of some responses as bursts. The visual information attributable to visual priming (as distinct from the information attributable to visual triggering of the bursts) was two bits per burst on average. Although bursts are reportedly rare in alert animals, this must be investigated as a function of visual stimulus. Moreover, we propose methods to measure the extent of both visual triggering and visual priming of bursts. Whether or not bursts are rare, our methods could help determine whether bursts in alert animals carry a distinct visual signal.

Response of the difference-of-Gaussians model to circular drifting-grating patches

Forty years ago R.W. Rodieck introduced the Difference-of-Gaussians (DOG) model, and this model has been widely used by the visual neuroscience community to quantitatively account for spatial response properties of cells in the retina and lateral geniculate nucleus following visual stimulation. Circular patches of drifting gratings are now regularly used as visual stimuli when probing the early visual system, but for this stimulus type the mathematical evaluation of the DOG-model response is significantly more complicated than for moving bars, full-field drifting gratings, or circular flashing spots. Here we derive mathematical formulas for the DOG-model response to centered circular patch gratings. The response is found to be given as the difference between two summed series, where each term in the series involves the confluent hypergeometric function. This function is available in commonly used mathematical software, and the results should thus be readily applicable. Example results illustrate how a strong surround suppression in area-summation curves for iso-luminant circular spots may be reversed into a surround enhancement for circular patch gratings. They also show that the spatial-frequency response changes from band-pass to low-pass when going from the full-field grating situation to the situation where the patch covers only the receptive-field center.

Do we know what the early visual system does?

We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single "standard model" for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.

Higher-order thalamic relays burst more than first-order relays

There is a strong correlation between the behavior of an animal and the firing mode (burst or tonic) of thalamic relay neurons. Certain differences between first- and higher-order thalamic relays (which relay peripheral information to the cortex versus information from one cortical area to another, respectively) suggest that more bursting might occur in the higher-order relays. Accordingly, we recorded bursting behavior in single cells from awake, behaving rhesus monkeys in first-order (the lateral geniculate nucleus, the ventral posterior nucleus, and the ventral portion of the medial geniculate nucleus) and higher-order (pulvinar and the medial dorsal nucleus) thalamic relays. We found that the extent of bursting was dramatically greater in the higher-order than in the first-order relays, and this increased bursting correlated with lower spontaneous activity in the higher-order relays. If bursting effectively signals the introduction of new information to a cortical area, as suggested, this increased bursting may be more important in corticocortical transmission than in transmission of primary information to cortex.

Frequency-dependent modulation of retinogeniculate transmission by serotonin

The relay of visual information converging in the lateral geniculate nucleus (LGN) en route to the visual cortex is modulated by projections from brainstem nuclei. The release of serotonin, one mediator of these effects, has been shown to act at a presynaptic site to inhibit neurotransmitter release at the retinogeniculate synapse, the connection between retinal ganglion cells and thalamocortical relay neurons in the LGN. To understand how serotonergic inhibition of synaptic transmission influences the transfer of information at this synapse, we examined the EPSCs and firing responses of relay neurons to 5-carboxytryptamine (5-CT), a 5-HT1 receptor agonist that preferentially activates the presynaptic over postsynaptic modulatory effects of serotonin. Bath application of 5-CT inhibits synaptic strength, relieves synaptic depression, and reduces the total synaptic charge transferred at the retinogeniculate synapse in mouse LGN brain slices. In contrast, 5-CT does not significantly alter the membrane potential response of relay neurons to trains of intracellular current injections. Here we show that presynaptic serotonergic modulation results in a frequency-dependent inhibition of relay neuron firing. At low-frequency stimulation, 5-CT markedly reduces charge transfer at the retinogeniculate synapse, thus inhibiting relay neuron firing. However, inhibition of firing by 5-CT is diminished during high-frequency stimulation, because relief from synaptic depression partially offsets the reduction in charge transfer. Thus, presynaptic serotonergic inhibition plays a powerful role in modulating the frequency range of visual information transmitted via the retinogeniculate synapse such that high-frequency inputs are more reliably transmitted than low-frequency inputs.

Orientation tuning, but not direction selectivity, is invariant to temporal frequency in primary visual cortex

The activity of neurons in primary visual cortex is influenced by the orientation, contrast, and temporal frequency of a visual stimulus. This raises the question of how these stimulus properties interact to shape neuronal responses. While past studies have shown that the bandwidth of orientation tuning is invariant to stimulus contrast, the influence of temporal frequency on orientation-tuning bandwidth is unknown. Here, we investigate the influence of temporal frequency on orientation tuning and direction selectivity in area 17 of ferret visual cortex. For both simple cells and complex cells, measures of orientation-tuning bandwidth (half-width at half-maximum response) are approximately 20-25 degrees across a wide range of temporal frequencies. Thus cortical neurons display temporal-frequency invariant orientation tuning. In contrast, direction selectivity is typically reduced, and occasionally reverses, at nonpreferred temporal frequencies. These results show that the mechanisms contributing to the generation of orientation tuning and direction selectivity are differentially affected by the temporal frequency of a visual stimulus and support the notion that stability of orientation tuning is an important aspect of visual processing.

Visual response properties of burst and tonic firing in the mouse dorsal lateral geniculate nucleus

Thalamic relay cells fire action potentials in two modes: burst and tonic. Previous studies in cats have shown that these two modes are associated with significant differences in the visual information carried by spikes in the dorsal lateral geniculate nucleus (dLGN). Here we describe the visual response properties of burst and tonic firing in the mouse dLGN. Extracellular recordings of activity in single geniculate cells were performed under halothane and nitrous oxide anesthesia in vivo. After confirming that the criteria used to isolate burst spikes from these recordings identify firing events with properties described for burst firing in other species and preparations, we show that burst firing in the mouse dLGN occurs during visual stimulation. We then compare burst and tonic firing across a wide range of visual response characteristics. While the two firing modes do not differ with respect to spatial summation or spatial frequency tuning, they show significant differences in the temporal domain. Burst spikes are phase advanced relative to their tonic counterparts. Burst firing is also more rectified, possesses sharper temporal frequency tuning, and prefers lower temporal frequencies than tonic firing. In addition, contrast-response curves are more step-like for burst responses. Finally, we present analyses that describe the stimulus detection abilities and spike timing reliability of burst and tonic firing.

Encoding of natural scene movies by tonic and burst spikes in the lateral geniculate nucleus

The role of the lateral geniculate nucleus (LGN) of the thalamus in visual encoding remains an open question. Here, we characterize the function of tonic and burst spikes in cat LGN X-cells in signaling features of natural stimuli. A significant increase in bursting was observed during natural stimulation (relative to white noise stimulation) and was linked to the strong correlation structure of the natural scene movies. Burst responses were triggered by specific stimulus events consisting of a prolonged inhibitory stimulus, followed by an excitatory stimulus, such as the movement of an object into the receptive field. LGN responses to natural scene movies were predicted using an integrate-and-fire (IF) framework and compared with experimentally observed responses. The standard IF model successfully predicted LGN responses to natural scene movies during tonic firing, indicating a linear relationship between stimulus and response. However, the IF model typically underpredicted the LGN response during periods of bursting, indicating a nonlinear amplification of the stimulus in the actual response. The addition of a burst mechanism to the IF model was necessary to accurately predict the entire LGN response. These results suggest that LGN bursts are an important part of the neural code, providing a nonlinear amplification of stimulus features that are typical of the natural environment.

Parallel processing of sensory input by bursts and isolated spikes

Burst firing is commonly observed in many sensory systems and is proposed to transmit information reliably. Although a number of biophysical burst mechanisms have been identified, the relationship between burst dynamics and information transfer is uncertain. Electrosensory pyramidal cells have a well defined backpropagation-dependent burst mechanism. We used in vivo, in vitro, and modeling approaches to investigate pyramidal cell responses to mimics of behaviorally relevant sensory input. We found that within a given spike train, bursts are biased toward low-frequency events while isolated spikes simultaneously code for the entire frequency range. We also demonstrated that burst dynamics are essential for optimal feature detection but are not required for stimulus estimation. We conclude that burst and spike dynamics can segregate a single spike train into two parallel and complementary streams of information transfer.

Derivation and analysis of basic computational operations of thalamocortical circuits

Shared anatomical and physiological features of primary, secondary, tertiary, polysensory, and associational neocortical areas are used to formulate a novel extended hypothesis of thalamocortical circuit operation. A simplified anatomically based model of topographically and nontopographically projecting ("core" and "matrix") thalamic nuclei, and their differential connections with superficial, middle, and deep neocortical laminae, is described. Synapses in the model are activated and potentiated according to physiologically based rules. Features incorporated into the models include differential time courses of excitatory versus inhibitory postsynaptic potentials, differential axonal arborization of pyramidal cells versus interneurons, and different laminar afferent and projection patterns. Observation of the model's responses to static and time-varying inputs indicates that topographic "core" circuits operate to organize stored memories into natural similarity-based hierarchies, whereas diffuse "matrix" circuits give rise to efficient storage of time-varying input into retrievable sequence chains. Examination of these operations shows their relationships with well-studied algorithms for related functions, including categorization via hierarchical clustering, and sequential storage via hash- or scatter-storage. Analysis demonstrates that the derived thalamocortical algorithms exhibit desirable efficiency, scaling, and space and time cost characteristics. Implications of the hypotheses for central issues of perceptual reaction times and memory capacity are discussed. It is conjectured that the derived functions are fundamental building blocks recurrent throughout the neocortex, which, through combination, gives rise to powerful perceptual, motor, and cognitive mechanisms.

Auditory Thalamus Bursts in Anesthetized and Non-Anesthetized States: Contribution to Functional Properties

Over the last 10 years, high-frequency bursts of action potentials have been the subject of intense researches to understand their potential role in information encoding. Based on recordings from auditory thalamus neurons ( n = 302) collected during anesthesia (pentobarbital, urethan, or ketamine/xylazine), waking (W), and slow-wave sleep (SWS), we investigated how bursts participate to frequency tuning, intensity-function, response latency (and latency variability), and stimulus detectability. Although present in all experimental conditions, bursts never dominated the cells mode of discharge: the highest proportion was found during ketamine/xylazine anesthesia (22%), the lowest during waking (4.5%). In all experimental conditions, bursts preferentially occurred at or around the cells best frequency (BF), thus increasing the frequency selectivity. This effect was observed at both the intensities producing the highest and the lowest evoked responses. Testing the intensity-functions indicated that for most of the cells, there was no systematic relationship between burst proportion and responses strength. Under several conditions (W, SWS, and urethan), when cells exhibited bursts >20%, the variability of their response latency was reduced in burst mode compared with single-spike mode. During W, this effect was accompanied by a reduction of the response latency. Finally, a receiver operating characteristic analysis indicated no particular relation between bursts and stimulus detectability. Compared with single-spike mode, which is present for broader frequency ranges, the prominence of bursts at the BF should contribute to filter information reaching the targets of medial geniculate cells at both cortical and subcortical levels.

Different roles for simple-cell and complex-cell inhibition in V1

Previously, we proposed a model of the circuitry underlying simple-cell responses in cat primary visual cortex (V1) layer 4. We argued that the ordered arrangement of lateral geniculate nucleus inputs to a simple cell must be supplemented by a component of feedforward inhibition that is untuned for orientation and responds to high temporal frequencies to explain the sharp contrast-invariant orientation tuning and low-pass temporal frequency tuning of simple cells. The temporal tuning also requires a significant NMDA component in geniculocortical synapses. Recent experiments have revealed cat V1 layer 4 inhibitory neurons with two distinct types of receptive fields (RFs): complex RFs with mixed ON/OFF responses lacking in orientation tuning, and simple RFs with normal, sharp-orientation tuning (although, some respond to all orientations). We show that complex inhibitory neurons can provide the inhibition needed to explain simple-cell response properties. Given this complex cell inhibition, antiphase or "push-pull" inhibition from tuned simple inhibitory neurons acts to sharpen spatial frequency tuning, lower responses to low temporal frequency stimuli, and increase the stability of cortical activity.

Receptive field structure of burst and tonic firing in feline lateral geniculate nucleus

There are two recognised modes of firing activity in thalamic cells, burst and tonic. A low-threshold (LT) burst (referred to from now on as 'burst') comprises a small number of high-frequency action potentials riding the peak of a LT Ca(2+) spike which is preceded by a silent hyperpolarised state > 50 ms. This is traditionally viewed as a sleep-like phenomenon, with a shift to tonic mode at wake-up. However, bursts have also been seen in the wake state and may be a significant feature for full activation of recipient cortical cells. Here we show that for visual stimulation of anaesthetised cats, burst firing is restricted to a reduced area within the receptive field centre of lateral geniculate nucleus cells. Consistently, the receptive field size of all the recorded neurons decreased in size proportionally to the percentage of spikes in bursts versus tonic spikes, an effect that is further demonstrated with pharmacological manipulation. The role of this shrinkage may be distinct from that also seen in sleep-like states and we suggest that this is a mechanism that trades spatial resolution for security of information transfer.