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.     

Feedback Inhibition and Throughput Properties of an Integrate-and-Fire-or-Burst Network Model of Retinogeniculate Transmission

Computational modeling has played an important role in the dissection of the biophysical basis of rhythmic oscillations in thalamus that are associated with sleep and certain forms of epilepsy. In contrast, the dynamic filter properties of thalamic relay nuclei during states of arousal are not well understood. Here we present a modeling and simulation study of the throughput properties of the visually driven dorsal lateral geniculate nucleus (dLGN) in the presence of feedback inhibition from the perigeniculate nucleus (PGN). We employ thalamocortical (TC) and thalamic reticular (RE) versions of a minimal integrate-and-fire-or-burst type model and a one-dimensional, two-layered network architecture. Potassium leakage conductances control the neuromodulatory state of the network and eliminate rhythmic bursting in the presence of spontaneous input (i.e., wake up the network). The aroused dLGN/PGN network model is subsequently stimulated by spatially homogeneous spontaneous retinal input or spatio-temporally patterned input consistent with the activity of X-type retinal ganglion cells during full-field or drifting grating visual stimulation. The throughput properties of this visually-driven dLGN/PGN network model are characterized and quantified as a function of stimulus parameters such as contrast, temporal frequency, and spatial frequency. During low-frequency oscillatory full-field stimulation, feedback inhibition from RE neurons often leads to TC neuron burst responses, while at high frequency tonic responses dominate. Depending on the average rate of stimulation, contrast level, and temporal frequency of modulation, the TC and RE cell bursts may or may not be phase-locked to the visual stimulus. During drifting-grating stimulation, phase-locked bursts often occur for sufficiently high contrast so long as the spatial period of the grating is not small compared to the synaptic footprint length, i.e., the spatial scale of the network connectivity.     

Synaptic activation of metabotropic glutamate receptors regulates dendritic outputs of thalamic interneurons

Information gating through the thalamus is dependent on the output of thalamic relay neurons. These relay neurons receive convergent innervation from a number of sources, including GABA-containing interneurons that provide feed-forward inhibition. These interneurons are unique in that they have two distinct outputs: axonal and dendritic. In addition to conventional axonal outputs, these interneurons have presynaptic dendrites that may provide localized inhibitory influences. Our study indicates that synaptic activation of metabotropic glutamate receptors (mGluRs) increases inhibitory activity in relay neurons by increasing output of presynaptic dendrites of interneurons. Optic tract stimulation increases inhibitory activity in thalamic relay neurons in a frequency- and intensity-dependent manner and is attenuated by mGluR antagonists. Our data suggest that synaptic activation of mGluRs selectively alters dendritic output but not axonal output of thalamic interneurons. This mechanism could serve an important role in focal, feed-forward information processing in addition to dynamic information processing in thalamocortical circuits.     

Corticothalamic interactions in the transfer of visual information

Thalamic function does not stand apart, as a discrete processing step, from the cortical circuitry. The thalamus receives extensive feedback from the cortex and this influences the firing pattern, synchronization and sensory response mode of relay cells. A crucial question concerns the extent to which the feedback simply controls the state and transmission mode of relay cells and the extent to which the feedback participates in the specific processing of sensory information. Using examples from experiments examining the influence of feedback from the visual cortex to the lateral geniculate nucleus (LGN), we argue that thalamic mechanisms are selectively focused by visually driven feedback to optimize the thalamic contribution to segmentation and global integration. This involves effects on both the temporal and spatial parameters characterizing the responses of LGN cells and includes, for example, motion-driven feedback effects from MT (middle temporal visual area) relayed via layer 6 of V1 (primary 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.     

Thalamocortical control of feed-forward inhibition in awake somatosensory 'barrel' cortex

Intracortical inhibition plays a role in shaping sensory cortical receptive fields and is mediated by both feed-forward and feedback mechanisms. Feed-forward inhibition is the faster of the two processes, being generated by inhibitory interneurons driven by monosynaptic thalamocortical (TC) input. In principle, feed-forward inhibition can prevent targeted cortical neurons from ever reaching threshold when TC input is weak. To do so, however, inhibitory interneurons must respond to TC input at low thresholds and generate spikes very quickly. A powerful feed-forward inhibition would sharpen the tuning characteristics of targeted cortical neurons, and interneurons with sensitive and broadly tuned receptive fields could mediate this process. Suspected inhibitory interneurons (SINs) with precisely these properties are found in layer 4 of the somatosensory (S1) 'barrel' cortex of rodents and rabbits. These interneurons lack the directional selectivity seen in most cortical spiny neurons and in ventrobasal TC afferents, but are much more sensitive than cortical spiny neurons to low-amplitude whisker displacements. This paper is concerned with the activation of S1 SINs by TC impulses, and with the consequences of this activation. Multiple TC neurons and multiple S1 SINs were simultaneously studied in awake rabbits, and cross-correlation methods were used to examine functional connectivity. The results demonstrate a potent, temporally precise, dynamic and highly convergent/divergent functional input from ventrobasal TC neurons to SINs of the topographically aligned S1 barrel. Whereas the extensive pooling of convergent TC inputs onto SINs generates sensitive and broadly tuned inhibitory receptive fields, the potent TC divergence onto many SINs generates sharply synchronous activity among these elements. This TC feed-forward inhibitory network is well suited to provide a fast, potent, sensitive and broadly tuned inhibition of targeted spiny neurons that will suppress spike generation following all but the most optimal feed-forward excitatory inputs.     

Participation of Intracellular Ca2+ Stores in Ca2+ Signalling in Neurons of the Thalamic Laterodorsal Nucleus of Rats

Experiments were carried out on isolated neurons of the thalamic nucleus lateralis dorsalis (LD) from 12-day-old rats. According to the morphological characteristics, LD neurons were classified as relay thalamo-cortical units and interneurons. The concentration of free Ca²⁺ ions in the cytoplasm ([Ca²⁺] _i ) was measured by a fluorescent calcium indicator, fura-2AM. Application of 30 mM caffeine caused a transient change in the [Ca²⁺] _i in 8 of 15 and in 6 of 11 of the thalamo-cortical units and interneurons under study, respectively. After stimulation of a cell with application of 50 mM KCl, a caffeine-induced increase in the [Ca²⁺] _i was observed in all tested neurons. To study the contribution of Ca²⁺-induced Ca²⁺ release (CICR) to the calcium transient evoked by depolarization of the neuronal membrane, caffeine in a subthreshold concentration was pre-applied. After 50 mM KCl had been added to the medium following pre-application of 0.5 mM caffeine, the calcium transient amplitude in thalamo-cortical neurons increased by 51 ± 7% (n = 16). In interneurons this effect was not observed (n = 11). The data obtained allow us to hypothesize that CICR contributes to the depolarization-evoked calcium transient only in the relay (thalamo-cortical) neurons. Differences in the pattern of calcium signalling, which were detected in two types of neurons of the thalamic LD, can be a factor determining distinctions in the physiological characteristics of these neurons.     

Development of spatial coarse-to-fine processing in the visual pathway

The sequential analysis of information in a coarse-to-fine manner is a fundamental mode of processing in the visual pathway. Spatial frequency (SF) tuning, arguably the most fundamental feature of spatial vision, provides particular intuition within the coarse-to-fine framework: low spatial frequencies convey global information about an image (e.g., general orientation), while high spatial frequencies carry more detailed information (e.g., edges). In this paper, we study the development of cortical spatial frequency tuning. As feedforward input from the lateral geniculate nucleus (LGN) has been shown to have significant influence on cortical coarse-to-fine processing, we present a firing-rate based thalamocortical model which includes both feedforward and feedback components. We analyze the relationship between various model parameters (including cortical feedback strength) and responses. We confirm the importance of the antagonistic relationship between the center and surround responses in thalamic relay cell receptive fields (RFs), and further characterize how specific structural LGN RF parameters affect cortical coarse-to-fine processing. Our results also indicate that the effect of cortical feedback on spatial frequency tuning is age-dependent: in particular, cortical feedback more strongly affects coarse-to-fine processing in kittens than in adults. We use our results to propose an experimentally testable hypothesis for the function of the extensive feedback in the corticothalamic circuit.     

The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.     

A thalamo-cortical neural mass model for the simulation of brain rhythms during sleep

Cortico-thalamic interactions are known to play a pivotal role in many brain phenomena, including sleep, attention, memory consolidation and rhythm generation. Hence, simple mathematical models that can simulate the dialogue between the cortex and the thalamus, at a mesoscopic level, have a great cognitive value. In the present work we describe a neural mass model of a cortico-thalamic module, based on neurophysiological mechanisms. The model includes two thalamic populations (a thalamo-cortical relay cell population, TCR, and its related thalamic reticular nucleus, TRN), and a cortical column consisting of four connected populations (pyramidal neurons, excitatory interneurons, inhibitory interneurons with slow and fast kinetics). Moreover, thalamic neurons exhibit two firing modes: bursting and tonic. Finally, cortical synapses among pyramidal neurons incorporate a disfacilitation mechanism following prolonged activity. Simulations show that the model is able to mimic the different patterns of rhythmic activity in cortical and thalamic neurons (beta and alpha waves, spindles, delta waves, K-complexes, slow sleep waves) and their progressive changes from wakefulness to deep sleep, by just acting on modulatory inputs. Moreover, simulations performed by providing short sensory inputs to the TCR show that brain rhythms during sleep preserve the cortex from external perturbations, still allowing a high cortical activity necessary to drive synaptic plasticity and memory consolidation. In perspective, the present model may be used within larger cortico-thalamic networks, to gain a deeper understanding of mechanisms beneath synaptic changes during sleep, to investigate the specific role of brain rhythms, and to explore cortical synchronization achieved via thalamic influences.     

Optogenetic Stimulation of the Corticothalamic Pathway Affects Relay Cells and GABAergic Neurons Differently in the Mouse Visual Thalamus

The dorsal lateral geniculate nucleus (dLGN) serves as the primary conduit of retinal information to visual cortex. In addition to retinal input, dLGN receives a large feedback projection from layer VI of visual cortex. Such input modulates thalamic signal transmission in different ways that range from gain control to synchronizing network activity in a stimulus-specific manner. However, the mechanisms underlying such modulation have been difficult to study, in part because of the complex circuitry and diverse cell types this pathway innervates. To address this and overcome some of the technical limitations inherent in studying the corticothalamic (CT) pathway, we adopted a slice preparation in which we were able to stimulate CT terminal arbors in the visual thalamus of the mouse with blue light by using an adeno-associated virus to express the light-gated ion channel, ChIEF, in layer VI neurons. To examine the postsynaptic responses evoked by repetitive CT stimulation, we recorded from identified relay cells in dLGN, as well as GFP expressing GABAergic neurons in the thalamic reticular nucleus (TRN) and intrinsic interneurons of dLGN. Relay neurons exhibited large glutamatergic responses that continued to increase in amplitude with each successive stimulus pulse. While excitatory responses were apparent at postnatal day 10, the strong facilitation noted in adult was not observed until postnatal day 21. GABAergic neurons in TRN exhibited large initial excitatory responses that quickly plateaued during repetitive stimulation, indicating that the degree of facilitation was much larger for relay cells than for TRN neurons. The responses of intrinsic interneurons were smaller and took the form of a slow depolarization. These differences in the pattern of excitation for different thalamic cell types should help provide a framework for understanding how CT feedback alters the activity of visual thalamic circuitry during sensory processing as well as different behavioral or pathophysiological states.     

Active dendritic conductances dynamically regulate GABA release from thalamic interneurons

Inhibitory interneurons in the dorsal lateral geniculate nucleus (dLGN) process visual information by precisely controlling spike timing and by refining the receptive fields of thalamocortical (TC) neurons. Previous studies indicate that dLGN interneurons inhibit TC neurons by releasing GABA from both axons and dendrites. However, the mechanisms controlling GABA release are poorly understood. Here, using simultaneous whole-cell recordings from interneurons and TC neurons and two-photon calcium imaging, we find that synchronous activation of multiple retinal ganglion cells (RGCs) triggers sodium spikes that propagate throughout interneuron axons and dendrites, and calcium spikes that invade dendrites but not axons. These distinct modes of interneuron firing can trigger both a rapid and a sustained component of inhibition onto TC neurons. Our studies suggest that active conductances make LGN interneurons flexible circuit-elements that can shift their spatial and temporal properties of GABA release in response to coincident activation of functionally related subsets of RGCs.     

A spherical model for orientation and spatial-frequency tuning in a cortical hypercolumn

A theory is presented of the way in which the hypercolumns in primary visual cortex (V1) are organized to detect important features of visual images, namely local orientation and spatial-frequency. Given the existence in V1 of dual maps for these features, both organized around orientation pinwheels, we constructed a model of a hypercolumn in which orientation and spatial-frequency preferences are represented by the two angular coordinates of a sphere. The two poles of this sphere are taken to correspond, respectively, to high and low spatial-frequency preferences. In Part I of the paper, we use mean-field methods to derive exact solutions for localized activity states on the sphere. We show how cortical amplification through recurrent interactions generates a sharply tuned, contrast-invariant population response to both local orientation and local spatial frequency, even in the case of a weakly biased input from the lateral geniculate nucleus (LGN). A major prediction of our model is that this response is non-separable with respect to the local orientation and spatial frequency of a stimulus. That is, orientation tuning is weaker around the pinwheels, and there is a shift in spatial-frequency tuning towards that of the closest pinwheel at non-optimal orientations. In Part II of the paper, we demonstrate that a simple feed-forward model of spatial-frequency preference, unlike that for orientation preference, does not generate a faithful representation when amplified by recurrent interactions in V1. We then introduce the idea that cortico-geniculate feedback modulates LGN activity to generate a faithful representation, thus providing a new functional interpretation of the role of this feedback pathway. Using linear filter theory, we show that if the feedback from a cortical cell is taken to be approximately equal to the reciprocal of the corresponding feed-forward receptive field (in the two-dimensional Fourier domain), then the mismatch between the feed-forward and cortical frequency representations is eliminated. We therefore predict that cortico-geniculate feedback connections innervate the LGN in a pattern determined by the orientation and spatial-frequency biases of feed-forward receptive fields. Finally, we show how recurrent cortical interactions can generate cross-orientation suppression.     

Cortically-Controlled Population Stochastic Facilitation as a Plausible Substrate for Guiding Sensory Transfer across the Thalamic Gateway

The thalamus is the primary gateway that relays sensory information to the cerebral cortex. While a single recipient cortical cell receives the convergence of many principal relay cells of the thalamus, each thalamic cell in turn integrates a dense and distributed synaptic feedback from the cortex. During sensory processing, the influence of this functional loop remains largely ignored. Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. The synaptic bombardment of cortical origin was mimicked through the injection of a stochastic mixture of excitatory and inhibitory conductances, resulting in a gradable correlation level of afferent activity shared by thalamic cells. The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. This suggests that the transfer efficiency of relay cells could be selectively amplified when they become simultaneously desynchronized by the cortical feedback. When applied to the intact brain, this network regulation mechanism could direct an attentional focus to specific thalamic subassemblies and select the appropriate input lines to the cortex according to the descending influence of cortically-defined “priors”.     

Thalamocortical interactions

Glutamatergic pathways dominate information processing in the brain, but these are not homogeneous. They include two distinct types: Class 1, which carries the main information for processing, and Class 2, which serves a modulatory role. Identifying the Class 1 inputs in a circuit can lead to a better understanding of its function. Also, identifying Class 1 inputs to a thalamic nucleus tells us its main function (e.g. the lateral geniculate nucleus, or LGN, is the relay of retinal Class 1 input), and such identification leads to a division of thalamic relays into first and higher order: the former receives Class 1 inputs from subcortical sources; the latter, from layer 5 of cortex, which it then relays to another cortical area. When a cortical area directly connects with another, it often has a parallel, transthalamic connection through these higher order relays. This leads to a novel appreciation of cortical functioning and raises many new questions.     

A visual thalamocortical slice

We describe a thalamocortical slice preparation in which connectivity between the mouse lateral geniculate nucleus (LGN) and primary visual cortex (V1) is preserved. Through DiI injections in fixed brains we traced and created a three-dimensional model of the mouse visual pathways. From this computer model we designed a slice preparation that contains a projection from LGN to V1. We prepared brain slices with these predicted coordinates and demonstrated anatomical LGN-V1 connectivity in these slices after LGN tracer injections. We also revealed functional LGN-V1 connectivity by stimulating LGN electrically and detecting responses in layer 4 of V1 using calcium imaging, field potential recordings and whole-cell recordings. We also identified layer-4 neurons that receive direct thalamocortical input. Finally, we compared cortical activity after LGN stimulation with spontaneous cortical activity and found significant overlap of the spatiotemporal dynamics generated by both types of events.     

A simple model of retina-LGN transmission

To gain a deeper understanding of the transmission of visual signals from retina through the lateral geniculate nucleus (LGN), we have used a simple leaky integrate and-fire model to simulate a relay cell in the LGN. The simplicity of the model was motivated by two questions: (1) Can an LGN model that is driven by a retinal spike train recorded as synaptic (‘S’) potentials, but does not include a diverse array of ion channels, nor feedback inputs from the cortex, brainstem, and thalamic reticular nucleus, accurately simulate the LGN discharge on a spike-for-spike basis? (2) Are any special synaptic mechanisms, beyond simple summation of currents, necessary to model experimental recordings? We recorded cat relay cell responses to spatially homogeneous small or large spots, with luminance that was rapidly modulated in a pseudo-random fashion. Model parameters for each cell were optimized with a Simplex algorithm using a short segment of the recording. The model was then tested on a much longer, distinct data set consisting of responses to numerous repetitions of the noisy stimulus. For LGN cells that spiked in response to a sufficiently large fraction of retinal inputs, we found that this simplified model accurately predicted the firing times of LGN discharges. This suggests that modulations of the efficacy of the retino-geniculate synapse by pre-synaptic facilitation or depression are not necessary in order to account for the LGN responses generated by our stimuli, and that post-synaptic summation is sufficient.     

The Subcellular Distribution of T-Type Ca2+ Channels in Interneurons of the Lateral Geniculate Nucleus

Inhibitory interneurons (INs) in the lateral geniculate nucleus (LGN) provide both axonal and dendritic GABA output to thalamocortical relay cells (TCs). Distal parts of the IN dendrites often enter into complex arrangements known as triadic synapses, where the IN dendrite plays a dual role as postsynaptic to retinal input and presynaptic to TC dendrites. Dendritic GABA release can be triggered by retinal input, in a highly localized process that is functionally isolated from the soma, but can also be triggered by somatically elicited Ca²⁺-spikes and possibly by backpropagating action potentials. Ca²⁺-spikes in INs are predominantly mediated by T-type Ca²⁺-channels (T-channels). Due to the complex nature of the dendritic signalling, the function of the IN is likely to depend critically on how T-channels are distributed over the somatodendritic membrane (T-distribution). To study the relationship between the T-distribution and several IN response properties, we here run a series of simulations where we vary the T-distribution in a multicompartmental IN model with a realistic morphology. We find that the somatic response to somatic current injection is facilitated by a high T-channel density in the soma-region. Conversely, a high T-channel density in the distal dendritic region is found to facilitate dendritic signalling in both the outward direction (increases the response in distal dendrites to somatic input) and the inward direction (the soma responds stronger to distal synaptic input). The real T-distribution is likely to reflect a compromise between several neural functions, involving somatic response patterns and dendritic signalling.     

A multivariate population density model of the dLGN/PGN relay

Using a population density approach we study the dynamics of two interacting collections of integrate-and-fire-or-burst (IFB) neurons representing thalamocortical (TC) cells from the dorsal lateral geniculate nucleus (dLGN) and thalamic reticular (RE) cells from the perigeniculate nucleus (PGN). Each population of neurons is described by a multivariate probability density function that satisfies a conservation equation with appropriately defined probability fluxes and boundary conditions. The state variables of each neuron are the membrane potential and the inactivation gating variable of the low-threshold Ca²⁺ current I_T. The synaptic coupling of the populations and external excitatory drive are modeled by instantaneous jumps in the membrane potential of postsynaptic neurons. The population density model is validated by comparing its response to time-varying retinal input to Monte Carlo simulations of the corresponding IFB network composed of 100 to 1000 cells per population. In the absence of retinal input, the population density model exhibits rhythmic bursting similar to the 7 to 14 Hz oscillations associated with slow wave sleep that require feedback inhibition from RE to TC cells. When the TC and RE cell potassium leakage conductances are adjusted to represent cholingergic neuromodulation and arousal of the network, rhythmic bursting of the probability density model may either persists or be eliminated depending on the number of excitatory (TC to RE) or inhibitory (RE to TC) connections made by each presynaptic cell. When the probability density model is stimulated with constant retinal input (10–100 spikes/sec), a wide range of responses are observed depending on cellular parameters and network connectivity. These include asynchronous burst and tonic spikes, sleep spindle-like rhythmic bursting, and oscillations in population firing rate that are distinguishable from sleep spindles due to their amplitude, frequency, or the presence of tonic spikes. In this context of dLGN/PGN network modeling, we find the population density approach using 2,500 mesh points and resolving membrane voltage to 0.7 mV is over 30 times more efficient than 1000-cell Monte Carlo simulations. Action Editor: David Golomb     

Extended difference-of-Gaussians model incorporating cortical feedback for relay cells in the lateral geniculate nucleus of cat

A striking feature of the organization of the early visual pathway is the significant feedback from primary visual cortex to cells in the dorsal lateral geniculate nucleus (LGN). Despite numerous experimental and modeling studies, the functional role for this feedback remains elusive. We present a new firing-rate-based model for LGN relay cells in cat, explicitly accounting for thalamocortical loop effects. The established DOG model, here assumed to account for the spatial aspects of the feedforward processing of visual stimuli, is extended to incorporate the influence of thalamocortical loops including a full set of orientation-selective cortical cell populations. Assuming a phase-reversed push-pull arrangement of ON and OFF cortical feedback as seen experimentally, this extended DOG (eDOG) model exhibits linear firing properties despite non-linear firing characteristics of the corticothalamic cells. The spatiotemporal receptive field of the eDOG model has a simple algebraic structure in Fourier space, while the real-space receptive field, as well as responses to visual stimuli, are found by evaluation of an integral. As an example application we use the eDOG model to study effects of cortical feedback on responses to flashing circular spots and patch-grating stimuli and find that the eDOG model can qualitatively account for experimental findings.