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.     

Low response variability in simultaneously recorded retinal, thalamic, and cortical neurons

The response of a cortical cell to a repeated stimulus can be highly variable from one trial to the next. Much lower variability has been reported of retinal cells. We recorded visual responses simultaneously from three successive stages of the cat visual system: retinal ganglion cells (RGCs), thalamic (LGN) relay cells, and simple cells in layer 4 of primary visual cortex. Spike count variability was lower than that of a Poisson process at all three stages but increased at each stage. Absolute and relative refractory periods largely accounted for the reliability at all three stages. Our results show that cortical responses can be more reliable than previously thought. The differences in reliability in retina, LGN, and cortex can be explained by (1) decreasing firing rates and (2) decreasing absolute and relative refractory periods.     

Simultaneous Recording of Input and Output of Lateral Geniculate Neurones

TO understand the way in which the cat dorsal lateral geniculate nucleus (LGN) processes visual information it would be useful to know the number and type of retinal inputs to individual LGN neurones. Using electrical stimulation of the optic nerve Bishop et al.¹concluded that an impulse in a single optic nerve fibre is sufficient to excite a single LGN neurone. From the appearance of excitatory postsynaptic potentials (EPSPs) recorded essentially intracellularly, Creutzfeldt suggested that LGN neurones are driven by perhaps one² or a few³ retinal ganglion cells. Hubel and Wiesel⁴ proposed models of convergence of several retinal inputs on single LGN neurones based on analyses of receptive fields. Guillery⁵ produced anatomical evidence that some types of LGN neurones receive inputs from several different retinal fibres. Now we report direct observations which were made by recording simultaneously from single LGN neurones and from individual retinal ganglion cells which provided excitatory input to them. We shall not consider inhibitory influences, which are currently under study.     

Feedforward origins of response variability underlying contrast invariant orientation tuning in cat visual cortex

Contrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.     

Changes in signal transmission by neurons of the cat lateral geniculate nucleus by acute deafferentation and early degeneration.

1. The responses of single principal cells of the cat lateral geniculate nucleus (LGN) were recorded extracellulary from the optic radiation (OR) axons or intracellularly from the LGN. Electrical stimuli at different frequencies were applied to the optic tract (OT) to test the transneuronal and the synaptic signal transmission in the LGN. 2. The effect of acute deafferentation (by photocoagulation of the retinal receptive field) or of synaptic degeneration induced 2-4 days prior to the recording time on the LGN neuron signal transfer was studied. Immediately after deafferentation, the synaptic signal transfer by LGN neurons exhibits signs of hyperexcitability leading to multiple neuronal discharges. This acute deafferentation hyperexicitability is probably caused mainly by the disapperance of lateral inhibition mediated by LGN interneurons. The deafferentation hyperexcitability disappeared during electrical stimulation of the OT at frequencies greater than 10/sec. 3. With progressing degeneration of the synaptic terminals during the 2nd to 4th day after interruption of the optic nerve axoplasmic flow, the synaptic signal transfer by LGN neurons gradually deteriorates and ceases at the end of the fourth day. The signs of this deterioration (larger temporal scatter, increased exhaustability and reduced upper frequency limit of the transneuronal signal transmission and gradual reduction of the EPSP amplitude in D-neurons) were quantitatively investigated. 4. The neurophysiological data obtained at different levels of synaptic terminal degeneration are well correlated with morphological changes found within the degenerating synaptic terminals.     

Rapid plasticity of visual responses in the adult lateral geniculate nucleus

Compared to the developing visual system, where neuronal plasticity has been well characterized at multiple levels, little is known about plasticity in the adult, particularly within subcortical structures. We made intraocular injections of 2-amino-4-phosphonobutyric acid (APB) in adult cats to block visual responses in On-center retinal ganglion cells and examined the consequences on visual responses in the lateral geniculate nucleus (LGN) of the thalamus. In contrast to current views of retinogeniculate organization, which hold that On-center LGN neurons should become silent with APB, we find that ～50% of On-center neurons rapidly develop Off-center responses. The time course of these emergent responses and the actions of APB in the retina indicate the plasticity occurs within the LGN. These results suggest there is greater divergence of retinogeniculate connections than previously recognized and that functionally silent, nonspecific retinal inputs can serve as a substrate for rapid plasticity in the adult.     

A Burst-Based “Hebbian” Learning Rule at Retinogeniculate Synapses Links Retinal Waves to Activity-Dependent Refinement

Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN). Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with “Hebbian” development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity.     

A Neuron Model with Spatially Distributed Synaptic Input

I have assembled a neuron model simulating contiguous patches of nerve cell membrane. With this model I have examined the functional significance of different spatial and temporal distributions of synaptic inputs. The model consists of two terminal electronic analogue circuits with inputs controlled by a LINC computer. One terminal represents the inside of a membrane patch, the other represents the outside. Two circuit designs are used: one simulates spike-generating regions of the neuron, the other simulates subthreshold activity in inexcitable regions. To simulate a neuron, patches are assembled in various spatial arrangements by suitable connection to the “intracellular” nodes. Thus the relation of neuron geometry to aspects of spatiotemporal summation of synaptic inputs can be investigated readily. Performance of the model is assessed by comparison with results from microelectrode studies in the cochlear nucleus of the cat. In particular, the peristimulus time (PST) histogram and averaged membrane potential are used for quantitative comparison. The model suggests that the geometry of the neuron's receptive surface can account for a wide variety of physiologically observed behavior, particularly in response to dynamic stimuli.     

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.     

A burst-based "Hebbian" learning rule at retinogeniculate synapses links retinal waves to activity-dependent refinement

Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN). Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with “Hebbian” development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity.     

Corticofugal feedback can reduce the visual latency of responses to antagonistic stimuli

 A biophysically realistical model of the primary visual pathway is designed, including feedback connections from the visual cortex to the lateral geniculate nucleus (LGN) – the so-called corticofugal pathway. The model comprises up to 10 000 retina and LGN cells divided into the ON and the OFF pathway according to their contrast response characteristics. An additional 6000 cortical simple cells are modeled. Apart from the direct excitatory afferent pathway we include strong mutual inhibition between the ON and the OFF subsystems. In addition, we propose a novel type of paradoxical corticofugal connection pattern which links ON dominated cortical simple cells to OFF-center LGN cells and vice versa. In accordance with physiological findings these connections are weakly excitatory and do not interfere with the steady-state responses to constant illumination, because during the steady-state inhibition arising from the active pathway effectively silences the nonstimulated pathway. At the moment of a contrast reversal the effect of the paradoxical connection pattern comes into play and the depolarization of the previously silent channel is accelerated, leading to a latency reduction of up to 4 ms using moderate synaptic weights. With increased weights reductions of more than 10 ms can be achieved. We introduce different synaptic characteristics for the feedback (AMPA, NMDA, AMPA+NMDA) and show that the strongest latency reduction is obtained for a combination of the membrane channels (i.e., AMPA+NMDA). The effect of the proposed paradoxical connection pattern is self-regulating; because the levels of inhibition and paradoxical excitation are always driven by the same inputs (strong inhibition is counterbalanced by a stronger paradoxical excitation and vice versa). In addition, the latency reduction for a contrast inversion which ends at a small absolute contrast level (small contrast step) is stronger than the reduction for an inversion with large final contrast (large contrast step). This leads to a more pronounced reduction in the reaction times for weak stimuli. Thus, reaction time differences for different contrast steps are smoothed out. Received: 22 January 1996/Accepted in revised form: 20 May 1996     

Reciprocal inhibition and slow calcium decay in perigeniculate interneurons explain changes of spontaneous firing of thalamic cells caused by cortical inactivation

The role of cortical feedback in the thalamocortical processing loop has been extensively investigated over the last decades. With an exception of several cases, these searches focused on the cortical feedback exerted onto thalamo-cortical relay (TC) cells of the dorsal lateral geniculate nucleus (LGN). In a previous, physiological study, we showed in the cat visual system that cessation of cortical input, despite decrease of spontaneous activity of TC cells, increased spontaneous firing of their recurrent inhibitory interneurons located in the perigeniculate nucleus (PGN). To identify mechanisms underlying such functional changes we conducted a modeling study in NEURON on several networks of point neurons with varied model parameters, such as membrane properties, synaptic weights and axonal delays. We considered six network topologies of the retino-geniculo-cortical system. All models were robust against changes of axonal delays except for the delay between the LGN feed-forward interneuron and the TC cell. The best representation of physiological results was obtained with models containing reciprocally connected PGN cells driven by the cortex and with relatively slow decay of intracellular calcium. This strongly indicates that the thalamic reticular nucleus plays an essential role in the cortical influence over thalamo-cortical relay cells while the thalamic feed-forward interneurons are not essential in this process. Further, we suggest that the dependence of the activity of PGN cells on the rate of calcium removal can be one of the key factors determining individual cell response to elimination of cortical input.     

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.     

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.     

Competitive interactions between retinal ganglion cells during prenatal development

In the mammalian visual system, retinal ganglion cell axons terminate within the LGN in a series of alternating eye-specific layers. These layers are not present initially during development. In the cat they emerge secondarily following a prenatal period in which originally intermixed inputs from the two eyes gradually segregate from each other to give rise to the characteristic set of layers by birth. Many lines of evidence suggest that activity-dependent competitive interactions between ganglion cell axons from the two eyes for LGN neurons play an important role in the final patterning of retinogeniculate connections. Studies of the branching patterns of individual ganglion cell axons suggest that during the period when inputs from the two eyes are intermixed, axons from one eye send side branches into territory later occupied exclusively by axons from the other eye. Ultrastructural studies indicate that these branches in fact are sites of synaptic contacts, which are later eliminated since the side branches disappear as axons form their mature terminal arbors in appropriate territory. In vitro microelectrode recordings from LGN neurons indicate that they can receive convergent synaptic excitation from electrical stimulation of the optic nerves before but not after the eye-specific layers form, suggesting that at least some of the synaptic contacts seen at the ultrastructural level are functonal. Finally, experiments in which tetrodotoxin was infused intracranially during the two week period during which the eye-specific layers normally form demonstrate that it is possible to prevent, or at least delay, the formation of the layers. Accordingly, individual axons fail to develop their restricted terminal arbor branching pattern and instead branch widely throughout the LGN. These results indicate that all of the machinery necessary for synaptic function and competition is present during fetal life. Moreover, it is highly likely that neuronal activity is required for the formation of the eye-specific layers. If so, then activity would have to be present in the form of spontaneously generated action potentials, since vision is not possible at these early ages. Thus, the functioning of the retinogeniculate system many weeks before it is put to the use for which it is ultimately designed may contribute to the final patterning of connections present in the adult.     

Developmental remodeling of the retinogeniculate synapse

Anatomical rearrangement of retinogeniculate connections contributes to the refinement of synaptic circuits in the developing visual system, but the underlying changes in synaptic function are unclear. Here, we study such changes in mouse brain slices. Each geniculate cell receives a surprisingly large number of retinal inputs (>20) well after eye-specific zones are formed. All but one to three of these inputs are eliminated over a 3-week period spanning eye opening. Remaining inputs are strengthened approximately 50-fold, in part through an increase in quantal size, but primarily through an increase in the number of release sites. Changes in release probability do not contribute significantly. Thus, a redistribution of release sites from many inputs to few inputs at this late developmental stage contributes to the precise receptive fields of thalamic relay neurons.     

Neuronal and synaptic organization of the lateral geniculate nucleus of the tree shrew,Tupaia glis

Summary The ultrastructural study of the lateral geniculate nucleus (LGN) of the tree shrew (Tupaia glis) revealed two types of neurons: (1) a large thalamocortical relay cell (TCR), which may bear cilia, and (2) a small Golgi type-II interneuron (IN) with an invaginated nucleus. The narrow rim of pale cytoplasm of the IN contains fewer lysosomes and fewer Nissl bodies than the cytoplasm of the TCR. The IN perikarya, which in some cases establish somatosomatic contacts, frequently contain flattened or pleomorphic synaptic vesicles. The ratio of TCR to IN is 31.Three types of axon terminals were observed in the LGN. Two of them contain round synaptic vesicles but differ in size. The large RL boutons undergo dark degeneration after enucleation; they are the terminals of retino-geniculate fibers. The smaller RS boutons show dark degeneration after ablation of the visual cortex; they are the terminals of the cortico-geniculate fibers. The third type of bouton (F₁ does not degenerate after either intervention. The boutons of this type are filled with flattened vesicles and are believed to be intrageniculate terminals. F₂-profiles were interpreted as presynaptic dendrites of the IN. The characteristic synaptic glomeruli found in the LGN contain in their center an optic terminal. These optic terminals establish synaptic contacts with dendrites or spine-like dendritic protrusions of TCRs as well as with presynaptic dendrites. Synaptic triads were also seen. The distribution of the individual types of synaptic contacts in layers 3 and 4 was determined. Layer 4 contains only one third of the retino-geniculate synapses and of the synaptic contacts of F₁-terminals.     

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.     

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids

The visual response of a cell in the primary visual cortex (V1) to a drifting grating stimulus at the cell’s preferred orientation decreases when a second, perpendicular, grating is superimposed. This effect is called masking. To understand the nonlinear masking effect, we model the response of Macaque V1 simple cells in layer 4Cα to input from magnocellular Lateral Geniculate Nucleus (LGN) cells. The cortical model network is a coarse-grained reduction of an integrate-and-fire network with excitation from LGN input and inhibition from other cortical neurons. The input is modeled as a sum of LGN cell responses. Each LGN cell is modeled as the convolution of a spatio-temporal filter with the visual stimulus, normalized by a retinal contrast gain control, and followed by rectification representing the LGN spike threshold. In our model, the experimentally observed masking arises at the level of LGN input to the cortex. The cortical network effectively induces a dynamic threshold that forces the test grating to have high contrast before it can overcome the masking provided by the perpendicular grating. The subcortical nonlinearities and the cortical network together account for the masking effect. Melinda Koelling is formerly from Center for Neural Science and Courant Institute, New York University.