‘Vector white noise’: a technique for mapping the motion receptive fields of direction-selective visual neurons

A technique is described and tested for mapping the sensitivities and preferred directions of motion at different locations within the receptive fields of direction-selective motion-detecting visual neurons. The procedure is to record the responses to a number of visual stimuli, each stimulus presentation consisting of a set of short, randomly-oriented, moving bars arranged in a square grid. Each bar moves perpendicularly to its long axis. The vector describing the sensitivity and preferred direction of motion at each grid location is obtained as a sum of the unit vectors defining the directions of motion of the bars in each of the stimuli at that location, weighted by the strengths of the corresponding responses. The resulting vector field specifies the optimum flow field for the neuron. The advantage of this technique over the conventional approach of probing the receptive field sequentially at each grid location is that the parallel nature of the stimulus is sensitive to nonlinear interactions (such as shunting inhibition for mutual facilitation) between different regions of the visual field. The technique is used to determine accurately the motion receptive fields of direction-selective motion detecting neurons in the optic lobes of insects. It is potentially applicable to motion-sensitive neurons with highly structured receptive fields, such as those in the optic tectum of the pigeon or in area MST of the monkey.     

Organization of receptive fields of motion-senstitive neurons in the cat pulvinar

The distribution of 70 visually sensitive neurons in the cat pulvinar sensitive to motion in the receptive fields was studied. The experimental results showed that components with directional characteristics are present in the structure of these fields of both direction-selective and unselective neurons. In the receptive fields of direction-selective neurons the directional elements of the substructure have identical preferred directions, which coincide with the preferred directions of response to stimulus movement over the entire receptive field. The organization of receptive fields of direction-selective neurons of the visual association structure thus does not differ significantly from that of analogous fields of visual projection neurons. Directional elements of the receptive fields of direction-unselective neurons were found to have different preferred directions, thereby providing a basis for organization of the nondirectional response of the neuron to a stimulus moving across the entire receptive field.L. A. Orbeli Institute of Physiology, Academy of Sciences of the Armenian SSR, Erevan. Translated from Neirofiziologiya, Vol. 14, No. 4, pp. 339–346, July–August, 1982.     

Receptive-field modification in rat visual cortex induced by paired visual stimulation and single-cell spiking

Experience-dependent plasticity of visual cortical receptive fields (RFs) involves synaptic modifications in the underlying neural circuits, but the site and mechanism of these modifications remain to be elucidated. Using in vivo whole-cell recordings, we show that pairing visual stimulation at a given retinal location with spiking of a single neuron in developing rat visual cortex induces rapid RF modifications. The time course of the response to the visual stimulus at the paired RF location is altered, with an enhancement of the response preceding the spike time and a reduction following the spike. Such bidirectional modification is consistent with spike timing-dependent plasticity. Response modification also occurs at nearby locations, the direction and magnitude of which are correlated with the change at the paired location. In addition, changes at unpaired locations show a negative correlation with the initial strength of the response, which may facilitate rapid modification of the spatial RF profile.     

Spike suppression in a local cortical circuit induced by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) noninvasively interferes with human cortical function, and is widely used as an effective technique for probing causal links between neural activity and cognitive function. However, the physiological mechanisms underlying TMS-induced effects on neural activity remain unclear. We examined the mechanism by which TMS disrupts neural activity in a local circuit in early visual cortex using a computational model consisting of conductance-based spiking neurons with excitatory and inhibitory synaptic connections. We found that single-pulse TMS suppressed spiking activity in a local circuit model, disrupting the population response. Spike suppression was observed when TMS was applied to the local circuit within a limited time window after the local circuit received sensory afferent input, as observed in experiments investigating suppression of visual perception with TMS targeting early visual cortex. Quantitative analyses revealed that the magnitude of suppression was significantly larger for synaptically-connected neurons than for isolated individual neurons, suggesting that intracortical inhibitory synaptic coupling also plays an important role in TMS-induced suppression. A conventional local circuit model of early visual cortex explained only the early period of visual suppression observed in experiments. However, models either involving strong recurrent excitatory synaptic connections or sustained excitatory input were able to reproduce the late period of visual suppression. These results suggest that TMS targeting early visual cortex disrupts functionally distinct neural signals, possibly corresponding to feedforward and recurrent information processing, by imposing inhibitory effects through intracortical inhibitory synaptic connections.     

Role of GABAA-Mediated Inhibition and Functional Assortment of Synapses onto Individual Layer 4 Neurons in Regulating Plasticity Expression in Visual Cortex

Layer 4 (L4) of primary visual cortex (V1) is the main recipient of thalamocortical fibers from the dorsal lateral geniculate nucleus (LGN_d). Thus, it is considered the main entry point of visual information into the neocortex and the first anatomical opportunity for intracortical visual processing before information leaves L4 and reaches supra- and infragranular cortical layers. The strength of monosynaptic connections from individual L4 excitatory cells onto adjacent L4 cells (unitary connections) is highly malleable, demonstrating that the initial stage of intracortical synaptic transmission of thalamocortical information can be altered by previous activity. However, the inhibitory network within L4 of V1 may act as an internal gate for induction of excitatory synaptic plasticity, thus providing either high fidelity throughput to supragranular layers or transmittal of a modified signal subject to recent activity-dependent plasticity. To evaluate this possibility, we compared the induction of synaptic plasticity using classical extracellular stimulation protocols that recruit a combination of excitatory and inhibitory synapses with stimulation of a single excitatory neuron onto a L4 cell. In order to induce plasticity, we paired pre- and postsynaptic activity (with the onset of postsynaptic spiking leading the presynaptic activation by 10ms) using extracellular stimulation (ECS) in acute slices of primary visual cortex and comparing the outcomes with our previously published results in which an identical protocol was used to induce synaptic plasticity between individual pre- and postsynaptic L4 excitatory neurons. Our results indicate that pairing of ECS with spiking in a L4 neuron fails to induce plasticity in L4-L4 connections if synaptic inhibition is intact. However, application of a similar pairing protocol under GABA_ARs inhibition by bath application of 2μM bicuculline does induce robust synaptic plasticity, long term potentiation (LTP) or long term depression (LTD), similar to our results with pairing of pre- and postsynaptic activation between individual excitatory L4 neurons in which inhibitory connections are not activated. These results are consistent with the well-established observation that inhibition limits the capacity for induction of plasticity at excitatory synapses and that pre- and postsynaptic activation at a fixed time interval can result in a variable range of plasticity outcomes. However, in the current study by virtue of having two sets of experimental data, we have provided a new insight into these processes. By randomly mixing the assorting of individual L4 neurons according to the frequency distribution of the experimentally determined plasticity outcome distribution based on the calculated convergence of multiple individual L4 neurons onto a single postsynaptic L4 neuron, we were able to compare then actual ECS plasticity outcomes to those predicted by randomly mixing individual pairs of neurons. Interestingly, the observed plasticity profiles with ECS cannot account for the random assortment of plasticity behaviors of synaptic connections between individual cell pairs. These results suggest that connections impinging onto a single postsynaptic cell may be grouped according to plasticity states.     

Independent Component Analysis in Spiking Neurons

Although models based on independent component analysis (ICA) have been successful in explaining various properties of sensory coding in the cortex, it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such computation. Here, we propose a biologically plausible mechanism for ICA-like learning with spiking neurons. Our model combines spike-timing dependent plasticity and synaptic scaling with an intrinsic plasticity rule that regulates neuronal excitability to maximize information transmission. We show that a stochastically spiking neuron learns one independent component for inputs encoded either as rates or using spike-spike correlations. Furthermore, different independent components can be recovered, when the activity of different neurons is decorrelated by adaptive lateral inhibition.     

The Possible Role of Spike Patterns in Cortical Information Processing

When the same visual stimulus is presented across many trials, neurons in the visual cortex receive stimulus-related synaptic inputs that are reproducible across trials (S) and inputs that are not (N). The variability of spike trains recorded in the visual cortex and their apparent lack of spike-to-spike correlations beyond that implied by firing rate fluctuations, has been taken as evidence for a low S/N ratio. A recent re-analysis of in vivo cortical data revealed evidence for spike-to-spike correlations in the form of spike patterns. We examine neural dynamics at a higher S/N in order to determine what possible role spike patterns could play in cortical information processing. In vivo-like spike patterns were obtained in model simulations. Superpositions of multiple sinusoidal driving currents were especially effective in producing stable long-lasting patterns. By applying current pulses that were either short and strong or long and weak, neurons could be made to switch from one pattern to another. Cortical neurons with similar stimulus preferences are located near each other, have similar biophysical properties and receive a large number of common synaptic inputs. Hence, recordings of a single neuron across multiple trials are usually interpreted as the response of an ensemble of these neurons during one trial. In the presence of distinct spike patterns across trials there is ambiguity in what would be the corresponding ensemble, it could consist of the same spike pattern for each neuron or a set of patterns across neurons. We found that the spiking response of a neuron receiving these ensemble inputs was determined by the spike-pattern composition, which, in turn, could be modulated dynamically as a means for cortical information processing.     

Developing velocity sensitivity in a model neuron by local synaptic plasticity

Sensor neurons, like those in the visual cortex, display specific functional properties, e.g., tuning for the orientation, direction and velocity of a moving stimulus. It is still unclear how these properties arise from the processing of the inputs which converge at a given cell. Specifically, little is known how such properties can develop by ways of synaptic plasticity. In this study we investigate the hypothesis that velocity sensitivity can develop at a neuron from different types of synaptic plasticity at different dendritic sub-structures. Specifically we are implementing spike-timing dependent plasticity at one dendritic branch and conventional long-term potentiation at another branch, both driven by dendritic spikes triggered by moving inputs. In the first part of the study, we show how velocity sensitivity can arise from such a spatially localized difference in the plasticity. In the second part we show how this scenario is augmented by the interaction between dendritic spikes and back-propagating spikes also at different dendritic branches. Recent theoretical (Saudargiene et al. in Neural Comput 16:595–626, 2004) and experimental (Froemke et al. in Nature 434:221–225, 2005) results on spatially localized plasticity suggest that such processes may play a major role in determining how synapses will change depending on their site. The current study suggests that such mechanisms could be used to develop the functional specificities of a neuron.     

Spike-timing-dependent plasticity leads to gamma band responses in a neural network

Early gamma band responses of the human electroencephalogram have been identified as an early interface linking top-down and bottom-up processing. This was based on findings that observed strong sensitivity of this signal to stimulus size and at the same time, to processes of attention and memory. Here, we simulate these findings in a simple random network of biologically plausible spiking neurons. During a learning phase, different stimuli were presented to the network and the synaptic connections were modified according to a spike-timing-dependent plasticity learning rule. In a subsequent test phase, we stimulated the network with (i) patterns of different sizes to simulate bottom-up effects and (ii) with patterns that were or were not presented during the learning phase. The network displayed qualitatively similar behavior as early gamma band responses measured from the scalp of human subjects: there was a general increase in response strength with increasing stimulus size and stronger responses for learned stimuli. We demonstrated that within one neural architecture early gamma band responses can be modulated both by bottom-up factors and by basal learning mechanisms mediated via spike-timing-dependent plasticity.     

Inhibitory synchrony as a mechanism for attentional gain modulation

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential (LFP) in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neuron's firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. When inhibitory synchrony increased, the coherence of spiking model neurons with the synaptic input increased, but the firing rate either increased or remained the same. The mean number of synchronous inhibitory inputs was a key determinant of the shape of the firing rate versus current (f-I) curves. For a large number of inhibitory inputs (approximately 50), the f-I curve saturated for large I and an increase in input synchrony resulted in a shift of sensitivity-the model neuron responded to weaker inputs I. For a small number (approximately 10), the f-I curves were non-saturating and an increase in input synchrony led to an increase in the gain of the response-the firing rate in response to the same input was multiplied by an approximately constant factor. The firing rate modulation with inhibitory synchrony was highest when the input network oscillated in the gamma frequency range. Thus, the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.     

Activity-dependent regulation of receptive field properties of cat area 17 by supervised Hebbian learning.

Most algorithms currently used to model synaptic plasticity in self-organizing cortical networks suppose that the change in synaptic efficacy is governed by the same structuring factor, i.e., the temporal correlation of activity between pre- and postsynaptic neurons. Functional predictions generated by such algorithms have been tested electrophysiologically in the visual cortex of anesthetized and paralyzed cats. Supervised learning procedures were applied at the cellular level to change receptive field (RF) properties during the time of recording of an individual functionally identified cell. The protocols were devised as cellular analogs of the plasticity of RF properties, which is normally expressed during a critical period of postnatal development. We summarize here evidence demonstrating that changes in covariance between afferent input and postsynaptic response imposed during extracellular and intracellular conditioning can acutely induce selective long-lasting up- and down-regulations of visual responses. The functional properties that could be modified in 40% of cells submitted to differential pairing protocols include ocular dominance, orientation selectivity and orientation preference, interocular orientation disparity, and the relative dominance of ON and OFF responses. Since changes in RF properties can be induced in the adult as well, our findings also suggest that similar activity-dependent processes may occur during development and during active phases of learning under the supervision of behavioral attention or contextual signals. Such potential for plasticity in primary visual cortical neurons suggests the existence of a hidden connectivity expressing a wider functional competence than the one revealed at the spiking level. In particular, in the spatial domain the sensory synaptic integration field is larger than the classical discharge field. It can be shaped by supervised learning and its subthreshold extent can be unmasked by the pharmacological blockade of intracortical inhibition.     

Multiple topological representation self-organized by spike-timing-dependent synaptic learning rule

Position-and-scale-free representations of shapes are acquired by neurons in the inferior temporal (IT) cortex. So each neuron receives information from the whole visual field. Familiar shapes are extremely restricted from all the possible shapes on the whole visual field. So they must be clustered in the shape space to have mixed structure of continuity and discreteness. We demonstrate that multiple representation can be acquired in a spike-based model for topological maps based on the spike-timing-dependent synaptic plasticity (STDP), subjected to a set of inputs on multiple rings, which is a simple example of mixed structure. In this representation, the position on each ring is represented by a center of active neurons and the difference of rings is represented by a detailed pattern of active neurons. Neurons in the same region exhibit high activities for an input on the other ring. The result is consistent with the fact observed in IT cortex that neighboring neurons exhibit different preferences while the region of active neurons is continuously shifted for continuous changes of object.     

Orientation sensitive properties of visually driven neurons in extrastriate area 21a of cat cortex

Orientation sensitive properties of extrastriate area 21a neurons were investigated. Special attention was paid to the qualitative characteristics of neuron responses to the different orientations of visual stimulus motion across neuron classical receptive fields (CRF). The results of experiments have shown that a group of neurons (31%) in area 21a with specialized responses to moving visual stimuli changed their direction selective (DS) characteristics depending on the orientation of the stimulus movement. Some neurons reveal an abrupt drop of the direction sensitivity index (DI) to certain orientation (58%), and some show significant increase of DI at one of applied orientations of stimulus motion (22%). Detailed investigation of response patterns of non-directional neurons to different orientations of stimulus motion have revealed clear-cut qualitative differences, such as different regularities in the distribution of inter-peak inhibitory intervals in the response pattern in dependence of the orientation of stimulus motion. The investigation of neuron CRF stationary functional organization did not reveal correlations between RF's spatial functional organization, and that of qualitative modulations of neuron response patterns. A suggestion was put forward, that visual information central processing of orientation discrimination is a complex integrative process that includes quantitative as well as qualitative transformations of neuron activity.     

A network of spiking neurons that can represent interval timing: mean field analysis

Despite the vital importance of our ability to accurately process and encode temporal information, the underlying neural mechanisms are largely unknown. We have previously described a theoretical framework that explains how temporal representations, similar to those reported in the visual cortex, can form in locally recurrent cortical networks as a function of reward modulated synaptic plasticity. This framework allows networks of both linear and spiking neurons to learn the temporal interval between a stimulus and paired reward signal presented during training. Here we use a mean field approach to analyze the dynamics of non-linear stochastic spiking neurons in a network trained to encode specific time intervals. This analysis explains how recurrent excitatory feedback allows a network structure to encode temporal representations.     

Modeling the role of gap junctions between excitatory neurons in the developing visual cortex

Recent experiments in the developing mammalian visual cortex have revealed that gap junctions couple excitatory cells and potentially influence the formation of chemical synapses. In particular, cells that were coupled by a gap junction during development tend to share an orientation preference and are preferentially coupled by a chemical synapse in the adult cortex, a property that is diminished when gap junctions are blocked. In this work, we construct a simplified model of the developing mouse visual cortex including spike-timing-dependent plasticity of both the feedforward synaptic inputs and recurrent cortical synapses. We use this model to show that synchrony among gap-junction-coupled cells underlies their preference to form strong recurrent synapses and develop similar orientation preference; this effect decreases with an increase in coupling density. Additionally, we demonstrate that gap-junction coupling works, together with the relative timing of synaptic development of the feedforward and recurrent synapses, to determine the resulting cortical map of orientation preference.     

Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity

In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational studies of sensory processing in neocortical network models equipped with synaptic plasticity.     

Selectivity of visual cortical neurons of rabbits to magnitude of moving stimuli

Unit responses of the rabbit visual cortex were investigated in relation to size of visual stimuli moving in their receptive field. With an increase in size of the stimulus in a direction perpendicular to the direction of movement ("width" of the stimulus) an initial increase in the intensity of the unit response through spatial summation of excitory effects is followed by a decrease through lateral inhibition. This inhibition is observed between zones of the receptive field which behave as activating when tested by a stimulus of small size. Each neuron has its own "preferred" size of stimuli evoking its maximal activation. No direct correlation is found between the "preferred" stimulus size and the size of the receptive field. With a change in stimulus size in the direction of movement ("length" of the stimulus) the responses to stimuli of optimal size may be potentiated through mutual facilitation of the effects evoked by the leading and trailing edges of the stimulus and weakened in response to stimuli of large size. The selective behavior of the neurons with respect to stimulus size is intensified in the case of coordinated changes in their length and width. It is postulated that the series of neurons responding to stimuli of different "preferred" dimensions may constitute a system classifying stimuli by their size.A. N. Severtsov Institute of Evolutionary Morphology and Ecology of Animals, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 4, No. 6, pp. 636–644, November–December, 1972.     

Spatiotemporal specificity of neuronal activity directs the modification of receptive fields in the developing retinotectal system

The precise temporal relation between pre- and postsynaptic activity modulates the strength of synaptic connections. Despite its extensive characterization in vivo and in vitro, the degree to which spike timing-dependent plasticity can shape receptive field properties is unclear. We use in vivo patch-clamp recordings of tectal neurons in developing Xenopus tadpoles to control the precise timing of action potentials with respect to the arrival of a subset of visual inputs evoked by local light stimulation on the retina. The pattern of visual inputs onto a tectal neuron was tracked over time by rapid reverse correlation mapping of receptive fields. Spike timing-dependent potentiation or depression of a subset of synapses reliably shifts the spatial receptive fields toward or away from the trained subregion of visual space, respectively. These results demonstrate that natural patterns of activity evoked by sensory stimuli play an instructive role in the developing nervous system.     

Development of spatiotemporal receptive fields of simple cells: II. Simulation and analysis

In part I of this article a correlation based model for the developmental process of spatiotemporal receptive fields has been introduced. In this model the development is described as an activity-dependent competition between four types of input from the lateral geniculate nucleus onto a cortical cell, viz. non-lagged ON and OFF and lagged ON and OFF inputs. In the present paper simulation results and a first analysis are presented for this model. We study the developmental process both before and after eye-opening and compare the results with experimental data from reverse correlation measurements. The outcome of the developmental process is determined mainly by the spatial and the temporal correlations between the different inputs. In particular, if the mean correlation between non-lagged and lagged inputs is weak, receptive fields with a widely varying degree of direction selectivity emerge. However, spatiotemporal receptive fields may show rotation of their preferred orientation as a function of response delay. Even if the mean correlation between two types of temporal input is not weak, direction-selective receptive fields may emerge because of an intracortical interaction between different cortical maps. In an environment of moving lines or gratings, direction-selective receptive fields develop only if the distribution of the directions of motion presented during development shows some anisotropy. In this case, a continuous map of preferred direction is also shown to develop. Received: 18 June 1997 / Accepted: 16 September 1997     

Responses of neurons of the extrastriate cortex of the cat brain to moving stimuli of different forms

We examined responses of neurons of the field 21b of the cat brain cortex to presentation of moving visual stimuli of different forms. Characteristics of the responses of about 54% of the studied neurons showed that in these cases configurations of the contours of moving stimuli were to a certain extent discriminated. Most neurons selectively reacting to changes in the form of the stimulus were dark-sensitive units (they generated optimum responses to presentation of dark visual stimuli on the light background). Detailed examination of the spatial infrastructure of receptive fields (RFs) of the neurons and comparison of this structure with the selectivity of neuronal responses showed that there is no significant correlation between static organization of the RF and responses of the neuron to the movements of stimuli of different forms. We hypothesize that the dynamic infrastructure of the RF and the combined activity of functional groups of neurons, whose RFs spatially overlap the RF of the neuron under study, play a definite role in the mechanisms responsible for neuronal discrimination of the form of the visual stimulus. Neirofiziologiya/Neurophysiology, Vol. 38, No. 1, pp. 61–71, January–February, 2006.