Direction selectivity of excitation and inhibition in simple cells of the cat primary visual cortex

Direction selectivity in simple cells of primary visual cortex, defined from their spike responses, cannot be predicted using linear models. It has been suggested that the shunting inhibition evoked by visual stimulation is responsible for the nonlinear component of direction selectivity. Cortical inhibition would suppress a neuron's firing when stimuli move in the nonpreferred direction, but would allow responses to stimuli in the preferred direction. Models of direction selectivity based solely on input from the lateral geniculate nucleus, however, propose that the nonlinear response is caused by spike threshold. By extracting excitatory and inhibitory components of synaptic inputs from intracellular records obtained in vivo, we demonstrate that excitation and inhibition are tuned for the same direction, but differ in relative timing. Further, membrane potential responses combine in a linear fashion. Spike threshold, however, quantitatively accounts for the nonlinear component of direction selectivity, amplifying the direction selectivity of spike output relative to that of synaptic inputs.     

Covariation between Spike and LFP Modulations Revealed with Focal and Asynchronous Stimulation of Receptive Field Surround in Monkey Primary Visual Cortex

A focal visual stimulus outside the classical receptive field (RF) of a V1 neuron does not evoke a spike response by itself, and yet evokes robust changes in the local field potential (LFP). This subthreshold LFP provides a unique opportunity to investigate how changes induced by surround stimulation leads to modulation of spike activity. In the current study, two identical Gabor stimuli were sequentially presented with a variable stimulus onset asynchrony (SOA) ranging from 0 to 100 ms: the first (S1) outside the RF and the second (S2) over the RF of primary visual cortex neurons, while trained monkeys performed a fixation task. This focal and asynchronous stimulation of the RF surround enabled us to analyze the modulation of S2-evoked spike activity and covariation between spike and LFP modulation across SOA. In this condition, the modulation of S2-evoked spike response was dominantly facilitative and was correlated with the change in LFP amplitude, which was pronounced for the cells recorded in the upper cortical layers. The time course of covariation between the SOA-dependent spike modulation and LFP amplitude suggested that the subthreshold LFP evoked by the S1 can predict the magnitude of upcoming spike modulation.     

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.     

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.     

Steps in the production of motoneuron spikes

1. Spikes evoked in spinal motoneurons by antidromic stimulation normally present an inflection in their rising phase. A similar inflection is present in spikes evoked by direct stimulation with short pulses. 2. In either case the inflection becomes less prominent if the motoneuron membrane is depolarized and more prominent when it is hyperpolarized. Both antidromic and direct spikes may fall from the level of the inflection thus evoking a "small spike" only if sufficient hyperpolarization is applied. Similar events occur when antidromic or direct spikes are evoked in the aftermath of a preceding spike. 3. Spikes evoked by direct stimuli applied shortly after firing of a "small spike" may also become partially blocked at a critical stimulus interval. At shorter intervals, however, spike size again increases and no inflection can be detected in the rising phase. 4. When a weak direct stimulus evokes a small spike only, a stronger stimulus may evoke a full spike. Curves of the strength of the stimuli required for eliciting small or full spikes have been constructed in a number of conditions. 5. To explain the results it is assumed that threshold of the major portions of the soma membrane is higher than the threshold of the axon, the transition occurring over a finite area near the axon hillock. Following antidromic or direct stimulation, soma excitation is then initiated in the region of the axon hillock. Spread of activity towards the soma occurs at first slowly and with low safety factor. At this stage block may be easily evoked. Safety factor for propagation increases rapidly as the growing impulse involves larger and larger areas of the soma membrane so that, once the critical areas are excited, activation of the remaining portions of the soma membrane will suddenly occur.     

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.     

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.     

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     

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.     

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.     

Contrast invariance in the human lateral occipital complex depends on attention

The human visual system has a remarkable ability to successfully operate under a variety of challenging viewing conditions. For example, our object-recognition capabilities are largely unaffected by low-contrast (e.g., foggy) environments. The basis for this ability appears to be reflected in the neural responses in higher cortical visual areas that have been characterized as being invariant to changes in luminance contrast: neurons in these areas respond nearly equally to low-contrast as compared to high-contrast stimuli. This response pattern is fundamentally different than that observed in earlier visual areas such as primary visual cortex (V1), which is highly dependent on contrast. How this invariance is achieved in higher visual areas is largely unknown. We hypothesized that directed spatial attention is an important prerequisite of the contrast-invariant responses in higher visual areas and tested this with functional MRI (fMRI) while subjects directed their attention either toward or away from contrast-varying shape stimuli. We found that in the lateral occipital complex (LOC), a visual area important for processing shape information, attention changes the form of the contrast response function (CRF). By directing attention away from the shape stimuli, the CRF in the LOC was similar to that measured in V1. We describe a number of mechanisms that could account for this important function of attention.     

Influence of the motor cortex on lateral geniculate responses evoked in the cat by contralateral superior colliculus stimulation

It is shown that in nembutal anesthetized cats, a single stimulation of motor cortex (MC) causes a response in lateral geniculate nucleus (LGN). The development of this response had a conditioning effect on the LGN response evoked by stimulation of the contralateral superior colliculus (SC), markedly inhibiting it. The degree of this inhibition depended on the time interval between the cortical conditioning stimulation and the tectal test stimulation. A single conditioning MC stimulation did not noticeably change the LGN responses evoked by a light stimulus, but markedly inhibited visual responses from deep SC layers (those regions which on stimulation gave rise to LGN responses). From the results, it is suggested that the MC monitors the execution of tectal influences on LGN function at the tectal level rather than the geniculate level, and it is precisely by this means that it regulates saccadic suppression of LGN function, in the realization of which, as presumed earlier, the SC takes part.A. I. Karaev Institute of Physiology, Azerbaijan Academy of Sciences, Baku. Translated from Neirofiziologiya, Vol. 24, No. 4, July–August 1992.     

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1’s function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.     

Postinhibitory unit response of crustacean stretch receptors after direct and recurrent inhibition

The postinhibitory response of a slowly adapting neuron was investigated in experiments on an isolated preparation of crustacean stretch receptor and abdominal nerve chain. The structural features of this preparation are such that this response can be regarded as the response of the postsynaptic membrane to synaptic inhibition and not the action of synaptic excitation. IPSPs arise in the slowly adapting neuron in response to stimulation of the abdominal nerve chain (direct inhibition) or to excitation of the neuron itself (recurrent inhibition). The postinhibitory response consists of the development of action potentials or an increase in their amplitude and frequency. The magnitude of the response is determined by the duration of the inhibition and the state of the neuron membrane. The postinhibitory response was strongest when IPSPs were superposed on cathodal depression. IPSPs and an intracellular hyperpolarizing current evoke similar postinhibitory responses. Repetitive excitation of an inhibitory neuron may result in the appearance of a regular spike discharge from a previously inactive neuron through the mechanism of the postinhibitory response. Activation of a chain of recurrent inhibition increases the duration of the postinhibitory response evoked by direct inhibition or by a hyperpolarizing current. The existence of a chain of recurrent inhibition prevents the cessation of firing by a neuron during increasing cathodal depression. A mechanism of postinhibitory rebound lies at the basis of this phenomenon.     

研究: 外膝状体神经元的亮度反应与感受野ON-OFF反应的关系

外膝体是视觉信息进入新皮层的主要通路,其编码亮度信息的神经机制还不清楚.我们采用随机呈现的连续快速变化(50 Hz)的均匀亮度刺激,显著地提高了猫外膝体神经元对均匀亮度的反应强度,通过反相关算法抽提出神经元的亮度反应函数.约81%的神经元的亮度反应函数为单调性上升或下降,有19%的神经元亮度反应函数为V型.通过分析这些神经元对亮度上升和下降的反应强度与感受野ON和OFF反应强度的关系,表明83%的神经元对亮度的反应模式是由其感受野ON-OFF反应的相对强度决定的,其余17%则与其感受野ON-OFF区的兴奋和抑制的变化相关.这些结果揭示了外膝体神经元编码亮度变化的机制.     

The neurochemical basis of recurrent inhibition in the reflex arch of the defensive reaction]

Mechanisms of habituation in the network of identified neurones were investigated in isolated preparation of central nervous system in the snail Helix. It has been found that intracellularly induced spike discharge in premotor command neurones decreases synaptic responses to repeated nerve stimulation in all recorded command neurones. Application of the neuropeptide FMRFamide elicits similar changes in the network. Taking into account that the investigated command neurones contain FMRFamide, as was shown immunochemically, it is possible to assume the existence of recurrent inhibition in the network underlying avoidance reactions. This recurrent inhibition causes habituation of the network output in the cases when the repeated stimuli do not evoke sensitization via activation of serotonergic cells.     

Learning receptive field properties of complex cells in V1

There are two distinct classes of cells in the primary visual cortex (V1): simple cells and complex cells. One defining feature of complex cells is their spatial phase invariance; they respond strongly to oriented grating stimuli with a preferred orientation but with a wide range of spatial phases. A classical model of complete spatial phase invariance in complex cells is the energy model, in which the responses are the sum of the squared outputs of two linear spatially phase-shifted filters. However, recent experimental studies have shown that complex cells have a diverse range of spatial phase invariance and only a subset can be characterized by the energy model. While several models have been proposed to explain how complex cells could learn to be selective to orientation but invariant to spatial phase, most existing models overlook many biologically important details. We propose a biologically plausible model for complex cells that learns to pool inputs from simple cells based on the presentation of natural scene stimuli. The model is a three-layer network with rate-based neurons that describes the activities of LGN cells (layer 1), V1 simple cells (layer 2), and V1 complex cells (layer 3). The first two layers implement a recently proposed simple cell model that is biologically plausible and accounts for many experimental phenomena. The neural dynamics of the complex cells is modeled as the integration of simple cells inputs along with response normalization. Connections between LGN and simple cells are learned using Hebbian and anti-Hebbian plasticity. Connections between simple and complex cells are learned using a modified version of the Bienenstock, Cooper, and Munro (BCM) rule. Our results demonstrate that the learning rule can describe a diversity of complex cells, similar to those observed experimentally.     

Effects of Stimulation of the Periaqueductal Gray and <Emphasis Type="Italic">Locus Coeruleus</Emphasis> on Postsynaptic Reactions of Cat Somatosensory Cortex Neurons Activated by Nociceptors

In cats, we studied the influences of stimulation of the periaqueductal gray (PAG) and locus coeruleus (LC) on postsynaptic processes evoked in neurons of the somatosensory cortex by stimulation of nociceptive (intensive stimulation of the tooth pulp) and non-nociceptive (moderate stimulations of the infraorbital nerve and ventroposteromedial nucleus of the thalamus) afferent inputs. Twelve cells activated exclusively by nociceptors and 16 cells activated by both nociceptive and non-nociceptive influences (hereafter, nociceptive and convergent neurons, respectively) were recorded intracellularly. In neurons of both groups, responses to nociceptive stimulation (of sufficient intensity) looked like an EPSP-spike-IPSP (the latter, of significant duration, up to 200 msec) complex. Electrical stimulation of the PAG (which could itself evoke activation of the cortical neurons under study) resulted in long-term suppression of synaptic responses evoked by excitation of nociceptors (inhibition reached its maximum at a test interval of 600 to 800 msec). We observed a certain parallelism between conditioning influences of PAG activation and effects of systemic injections of morphine. Isolated stimulation of LC by a short high-frequency train of stimuli evoked primary excitatory responses (complex EPSPs) in a part of the examined cortical neurons, while in other cells high-amplitude and long-lasting IPSP (up to 120 msec) were observed. Independently of the type of the primary response to PAG stimulation, the latter resulted in long-term (several seconds) suppression of the responses evoked in cortical cells by stimulation of the nociceptive inputs. The mechanisms of modulatory influences coming from opioidergic and noradrenergic brain systems to somatosensory cortex neurons activated due to excitation of high-threshold (nociceptive) afferent inputs are discussed.Neirofiziologiya/Neurophysiology, Vol. 37, No. 1, pp. 61–73, January–February, 2005.     

Dynamic encoding of natural luminance sequences by LGN bursts

In the lateral geniculate nucleus (LGN) of the thalamus, visual stimulation produces two distinct types of responses known as tonic and burst. Due to the dynamics of the T-type Ca ²⁺ channels involved in burst generation, the type of response evoked by a particular stimulus depends on the resting membrane potential, which is controlled by a network of modulatory connections from other brain areas. In this study, we use simulated responses to natural scene movies to describe how modulatory and stimulus-driven changes in LGN membrane potential interact to determine the luminance sequences that trigger burst responses. We find that at low resting potentials, when the T channels are de-inactivated and bursts are relatively frequent, an excitatory stimulus transient alone is sufficient to evoke a burst. However, to evoke a burst at high resting potentials, when the T channels are inactivated and bursts are relatively rare, prolonged inhibitory stimulation followed by an excitatory transient is required. We also observe evidence of these effects in vivo, where analysis of experimental recordings demonstrates that the luminance sequences that trigger bursts can vary dramatically with the overall burst percentage of the response. To characterize the functional consequences of the effects of resting potential on burst generation, we simulate LGN responses to different luminance sequences at a range of resting potentials with and without a mechanism for generating bursts. Using analysis based on signal detection theory, we show that bursts enhance detection of specific luminance sequences, ranging from the onset of excitatory sequences at low resting potentials to the offset of inhibitory sequences at high resting potentials. These results suggest a dynamic role for burst responses during visual processing that may change according to behavioral state.