Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex

An Indexing Theory for Working Memory Based on Fast Hebbian Plasticity

Working memory (WM) is a key component of human memory and cognition. Computational models have been used to study the underlying neural mechanisms, but neglected the important role of short-term memory (STM) and long-term memory (LTM) interactions for WM. Here, we investigate these using a novel multiarea spiking neural network model of prefrontal cortex (PFC) and two parietotemporal cortical areas based on macaque data. We propose a WM indexing theory that explains how PFC could associate, maintain, and update multimodal LTM representations. Our simulations demonstrate how simultaneous, brief multimodal memory cues could build a temporary joint memory representation as an “index” in PFC by means of fast Hebbian synaptic plasticity. This index can then reactivate spontaneously and thereby also the associated LTM representations. Cueing one LTM item rapidly pattern completes the associated uncued item via PFC. The PFC–STM network updates flexibly as new stimuli arrive, thereby gradually overwriting older representations.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism.

SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

From one moment to the next, in an ever-changing world, and awash in a deluge of sensory data, the brain fluidly guides our actions throughout an astonishing variety of tasks. Processing this ongoing bombardment of information is a fundamental problem faced by its underlying neural circuits. Given that the structure of our actions along with the organization of the environment in which they are performed can be intuitively decomposed into sequences of simpler patterns, an encoding strategy reflecting the temporal nature of these patterns should offer an efficient approach for assembling more complex memories and behaviors. We present a model that demonstrates how activity could propagate through recurrent cortical microcircuits as a result of a learning rule based on neurobiologically plausible time courses and dynamics. The model predicts that the interaction between several learning and dynamical processes constitute a compound mnemonic engram that can flexibly generate sequential step-wise increases of activity within neural populations.

How Does the Cerebral Cortex Work? Development, Learning, Attention, and 3-D Vision by Laminar Circuits of Visual Cortex

A key goal of behavioral and cognitive neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress toward explaining how the visual cortex sees. Visual cortex, like many parts of perceptual and cognitive neocortex, is organized into six main layers of cells, as well as characteristic sublamina. Here it is proposed how these layered circuits help to realize processes of development, learning, perceptual grouping, attention, and 3-D vision through a combination of bottom-up, horizontal, and top-down interactions. A main theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. These results thus begin to unify three fields: infant cortical development, adult cortical neurophysiology and anatomy, and adult visual perception. The identified cortical mechanisms promise to generalize to explain how other perceptual and cognitive processes work.

Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks

Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is still unclear how distinct local network states, which are intrinsically generated by synaptic interactions within each layer, would affect the ability of FFN to transmit information. Here we investigate the impact of such network states on propagating transient synchrony (synfire) and firing rate by a combination of numerical simulations and analytical approach. Specifically, local network dynamics is attributed to the competition between excitatory and inhibitory neurons within each layer. Our results show that concomitant with different local network states, the performance of signal propagation differs dramatically. For both synfire propagation and firing rate propagation, there exists an optimal local excitability state, respectively, that optimizes the performance of signal propagation. Furthermore, we find that long-range connections strongly change the dependence of spiking activity propagation on local network state and propose that these two factors work jointly to determine information transmission across distributed networks. Finally, a simple mean field approach that bridges response properties of long-range connectivity and local subnetworks is utilized to reveal the underlying mechanism.

Neocortical inhibitory activities and long-range afferents contribute to the synchronous onset of silent states of the neocortical slow oscillation

During slow-wave sleep, neurons of the thalamocortical network are engaged in a slow oscillation (<1 Hz), which consists of an alternation between the active and the silent states. Several studies have provided insights on the transition from the silent, which are essentially periods of disfacilitation, to the active states. However, the conditions leading to the synchronous onset of the silent state remain elusive. We hypothesized that a synchronous input to local inhibitory neurons could contribute to the transition to the silent state in the cat suprasylvian gyrus during natural sleep and under ketamine-xylazine anesthesia. After partial and complete deafferentation of the cortex, we found that the silent state onset was more variable among remote sites. We found that the transition to the silent state was preceded by a reduction in excitatory postsynaptic potentials and firing probability in cortical neurons. We tested the impact of chloride-mediated inhibition in the silent-state onset. We uncovered a long-duration (100-300 ms) inhibitory barrage occurring about 250 ms before the silent state onset in 3-6% of neurons during anesthesia and in 12-15% of cases during natural sleep. These inhibitory activities caused a decrease in cortical firing that reduced the excitatory drive in the neocortical network. That chain reaction of disfacilitation ends up on the silent state. Electrical stimuli could trigger a network silent state with a maximal efficacy in deep cortical layers. We conclude that long-range afferents to the neocortex and chloride-mediated inhibition play a role in the initiation of the silent state.

Conductance-based refractory density model of primary visual cortex

A layered continual population model of primary visual cortex has been constructed, which reproduces a set of experimental data, including postsynaptic responses of single neurons on extracellular electric stimulation and spatially distributed activity patterns in response to visual stimulation. In the model, synaptically interacting excitatory and inhibitory neuronal populations are described by a conductance-based refractory density approach. Populations of two-compartment excitatory and inhibitory neurons in cortical layers 2/3 and 4 are distributed in the 2-d cortical space and connected by AMPA, NMDA and GABA type synapses. The external connections are pinwheel-like, according to the orientation of a stimulus. Intracortical connections are isotropic local and patchy between neurons with similar orientations. The model proposes better temporal resolution and more detailed elaboration than conventional mean-field models. In comparison to large network simulations, it excludes a posteriori statistical data manipulation and provides better computational efficiency and minimal parametrization.

Laminar firing and membrane dynamics in four visual areas exposed to two objects moving to occlusion

It is not known how visual cortical neurons react to several moving objects and how their firing to the motion of one object is affected by neurons firing to another moving object. Here we combine imaging of voltage sensitive dye (VSD) signals, reflecting the population membrane potential from ferret visual areas 17, 18, 19, and 21, with laminar recordings of multiunit activity, (MUA), when two bars moved toward each other in the visual field, occluded one another, and continued on in opposite directions. Two zones of peak MUA, mapping the bars' motion, moved toward each other along the area 17/18 border, which in the ferret maps the vertical meridian of the field of view. This was reflected also in the VSD signal, at both the 17/18 border as well as at the 19/21 border with a short delay. After some 125 ms at the area 19/21 border, the VSD signal increased and became elongated in the direction of motion in front of both of the moving representations. This was directly followed by the phase of the signal reversing and travelling back from the 19/21 border toward the 17/18 border, seemingly without respect for retinotopic boundaries, where it arrived at 150 ms after stimulus onset. At this point the VSD signal in front of the moving bar representations along the 17/18 border also increased and became elongated in the direction of object motion; the signal now being the linear sum of what has been observed in response to single moving bars. When the neuronal populations representing the bars were some 600 μm apart on the cortex, the dye signal and laminar MUA decreased strongly, with the MUA scaling to that of a single bar during occlusion. Despite a short rebound of the dye signal and MUA, the MUA after the occlusion was significantly depressed. The interactions between the neuronal populations mapping the bars' position, and the neurons in between these populations were, apart from 19/21 to 17/18 interaction, mainly lateral-horizontal; first excitatory and inducing firing at the site of future occlusion, then inhibitory just prior to occlusion. After occlusion the neurons that had fired already to the first bar showed delayed and prolonged inhibition in response to the second bar. Thus, the interactions that were particular to the occlusion condition in these experiments were local and inhibitory at short cortical range, and delayed and inhibitory after the occlusion when the bars moved further apart.

Cortical gamma oscillations: the functional key is activation, not cognition

Cortical oscillatory synchrony in the gamma range has been attracting increasing attention in cognitive neuroscience ever since being proposed as a solution to the so-called binding problem. This growing literature is critically reviewed in both its basic neuroscience and cognitive aspects. A physiological "default assumption" regarding these oscillations is introduced, according to which they signal a state of physiological activation of cortical tissue, and the associated need to balance excitation with inhibition in particular. As such these oscillations would belong among a variety of generic neural control operations that enable neural tissue to perform its systems level functions, without implementing those functions themselves. Regional control of cerebral blood flow provides an analogy in this regard, and gamma oscillations are tightly correlated with this even more elementary control operation. As correlates of neural activation they will also covary with cognitive activity, and this typically suffices to account for the covariation between gamma activity and cognitive task variables. A number of specific cases of gamma synchrony are examined in this light, including the original impetus for attributing cognitive significance to gamma activity, namely the experiments interpreted as evidence for "binding by synchrony". This examination finds no compelling reasons to assign functional roles to oscillatory synchrony in the gamma range beyond its generic functions at the level of infrastructural neural control.

Mapping cortical representations of the rodent forepaw and hindpaw with BOLD fMRI reveals two spatial boundaries

Electrical stimulation of the rat forepaw and hindpaw was employed to study the spatial distribution of BOLD fMRI. Averaging of multiple fMRI sessions significantly improved the spatial stability of the BOLD signal and enabled quantitative determination of the boundaries of the BOLD fMRI maps. The averaged BOLD fMRI signal was distributed unevenly over the extent of the map and the data at the boundaries could be modeled with major and minor spatial components. Comparison of three-dimensional echo-planar imaging (EPI) fMRI at isotropic 300 μm resolution demonstrated that the border locations of the major spatial component of BOLD signal did not overlap between the forepaw and hindpaw maps. Interestingly, the border positions of the minor BOLD fMRI spatial components extended significantly into neighboring representations. Similar results were found for cerebral blood volume (CBV) weighted fMRI obtained using iron oxide particles, suggesting that the minor spatial components may not be due to vascular mislocalization typically associated with BOLD fMRI. Comparison of the BOLD fMRI maps of the forepaw and hindpaw to histological determination of these representations using cytochrome oxidase (CO) staining demonstrated that the major spatial component of the BOLD fMRI activation maps accurately localizes the borders. Finally, 2-3 weeks following peripheral nerve denervation, cortical reorganization/plasticity at the boundaries of somatosensory limb representations in adult rat brain was studied. Denervation of the hindpaw caused a growth in the major component of forepaw representation into the adjacent border of hindpaw representation, such that fitting to two components no longer led to a better fit as compared to using one major component. The border of the representation after plasticity was the same as the border of its minor component in the absence of any plasticity. It is possible that the minor components represent either vascular effects that extend from the real neuronal representations or the neuronal communication between neighboring regions. Either way the results will be useful for studying mechanisms of plasticity that cause alterations in the boundaries of neuronal representations.

Cross-sensory modulation of primary sensory cortex is developmentally regulated by early sensory experience

The presence of cross-sensory influences on neuronal responses in primary sensory cortex has been observed previously using several different methods. To test this idea in rat S1 barrel cortex, we hypothesized that auditory stimuli combined with whisker stimulation ("cross-sensory" stimuli) may modify response levels to whisker stimulation. Since the brain has been shown to have a remarkable capacity to be modified by early postnatal sensory activity, manipulating postnatal sensory experiences would be predicted to alter the degree of cross-sensory interactions. To test these ideas, we raised rats with or without whisker deprivation and with or without postnatal exposure to repeated auditory clicks. We recorded extracellular responses under urethane anesthesia from barrel cortex neurons in response to principal whisker stimulation alone, to auditory click stimulation alone, or to a cross-sensory stimulus. The responses were compared statistically across different stimulus conditions and across different rearing groups. Barrel neurons did not generate action potentials in response to auditory click stimuli alone in any rearing group. However, in cross-sensory stimulus conditions the response magnitude was facilitated in the 0-15 ms post-whisker-stimulus epoch in all rearing conditions, whereas modulation of response magnitude in a later 15-30 ms post-whisker-stimulus epoch was significantly different in each rearing condition. The most significant cross-sensory effect occurred in rats that were simultaneously whisker deprived and click reared. We conclude that there is a modulatory type of cross-sensory auditory influence on normal S1 barrel cortex, which can be enhanced by early postnatal experiences.

Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition

Both ongoing and natural stimulus driven neuronal activity are dominated by transients. Selective gating of these transients is mandatory for proper brain function and may, in fact, form the basis of millisecond-fast decision making and action selection. Here we propose that neuronal networks may exploit timing differences between correlated excitation and inhibition (temporal gating) to control the propagation of spiking activity transients. When combined with excitation-inhibition balance, temporal gating constitutes a powerful mechanism to control the propagation of mixtures of transient and tonic neural activity components.

Functional consequences of correlated excitatory and inhibitory conductances in cortical networks

Neurons in the neocortex receive a large number of excitatory and inhibitory synaptic inputs. Excitation and inhibition dynamically balance each other, with inhibition lagging excitation by only few milliseconds. To characterize the functional consequences of such correlated excitation and inhibition, we studied models in which this correlation structure is induced by feedforward inhibition (FFI). Simple circuits show that an effective FFI changes the integrative behavior of neurons such that only synchronous inputs can elicit spikes, causing the responses to be sparse and precise. Further, effective FFI increases the selectivity for propagation of synchrony through a feedforward network, thereby increasing the stability to background activity. Last, we show that recurrent random networks with effective inhibition are more likely to exhibit dynamical network activity states as have been observed in vivo. Thus, when a feedforward signal path is embedded in such recurrent network, the stabilizing effect of effective inhibition creates an suitable substrate for signal propagation. In conclusion, correlated excitation and inhibition support the notion that synchronous spiking may be important for cortical processing.

Voltage-sensitive dye imaging: Technique review and models

In this review, we present the voltage-sensitive dye imaging (VSDI) method. The possibility offered for in vivo (and in vitro) brain imaging is unprecedented in terms of spatial and temporal resolution. However, the unresolved multi-component origin of the optical signal encourages us to perform a detailed analysis of the method limitation and the existing models. We propose a biophysical model at a mesoscopic scale in order to understand and interpret this signal.

A model of non-linear interactions between cortical top-down and horizontal connections explains the attentional gating of collinear facilitation

Past physiological and psychophysical experiments have shown that attention can modulate the effects of contextual information appearing outside the classical receptive field of a cortical neuron. Specifically, it has been suggested that attention, operating via cortical feedback connections, gates the effects of long-range horizontal connections underlying collinear facilitation in cortical area V1. This article proposes a novel mechanism, based on the computations performed within the dendrites of cortical pyramidal cells, that can account for these observations. Furthermore, it is shown that the top-down gating signal into V1 can result from a process of biased competition occurring in extrastriate cortex. A model based on these two assumptions is used to replicate the results of physiological and psychophysical experiments on collinear facilitation and attentional modulation.

Astrocytes discriminate and selectively respond to the activity of a subpopulation of neurons within the barrel cortex

Sensory information from single whiskers in rodents projects to defined morphological units in the cortex, the barrels. We found that astrocytes selectively respond with an increase in the cytosolic Ca(2+) concentration to activation of layer 4 neurons, the input cells of the barrel columns. The neuronal Ca(2+) signal also spread across barrel column borders mainly in layer 2/3, but the glutamate-mediated astrocyte response stayed restricted to the barrel column. In contrast, when interfering with inhibitory pathways by blocking either purinergic, adenosine or gamma-aminobutyric acid(A) receptors, the stimulation activated a Ca(2+) response in a much larger astrocyte population no longer restricted to the borders of the barrel column. We also observed spontaneous and evoked Ca(2+) activity in the synaptic target cells of layer 4 neurons, the layer 2/3 pyramidal cells, but again, we never recorded Ca(2+) responses in astrocytes following activity in this neuronal population. Our data show that astrocytes can discriminate and selectively respond to the activity of a subpopulation of excitatory neurons within a given brain region. This selectivity in the astrocyte response describes a new level of complexity and integration in the reaction of astrocytes to neuronal activity.

Dopaminergic modulation of local network activity in rat prefrontal cortex

Dopamine modulates prefrontal cortex excitability in complex ways. Dopamine's net effect on local neuronal networks is therefore difficult to predict based on studies on pharmacologically isolated excitatory or inhibitory connections. In the present work, we have studied the effects of dopamine on evoked activity in acute rat brain slices when both excitation and inhibition are intact. Whole cell recordings from layer II/III pyramidal cells under conditions of normal synaptic transmission showed that bath-applied dopamine (30 microM) increased the outward inhibitory component of composite postsynaptic currents, whereas inward excitatory currents were not significantly affected. Optical imaging with the voltage-sensitive dye N-(3-(triethylammonium)propyl)-4-(4-(p-diethylaminophenyl)buta-dienyl)pyridinium dibromide revealed that bath application of dopamine significantly decreased the amplitude, duration, and lateral spread of activity in local cortical networks. This effect of dopamine was observed both with single and train (5 at 20 Hz) stimuli. The effect was mimicked by the D1-like receptor agonistR(+)-6-chloro-7,8-dihydroxy-1-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine hydrobromide (1 microM) and was blocked by R(+)-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine hydrochloride (10 microM), a selective antagonist for D1-like receptors. The D2-like receptor agonist quinpirole (10 microM) had no significant effect on evoked dye signals. Our results suggest that dopamine's effect on inhibition dominates over that on excitation under conditions of normal synaptic transmission. Such neuromodulation by dopamine may be important for maintenance of stability in local neuronal networks in the prefrontal cortex.

Negatively correlated firing: the functional meaning of lateral inhibition within cortical columns

Lateral inhibition is a well documented aspect of neural architecture in the main sensory systems. Existing accounts of lateral inhibition focus on its role in sharpening distinctions between inputs that are closely related. However, these accounts fail to explain the functional role of inhibition in cortical columns, such as those in V1, where neurons have similar response properties. In this paper, we outline a model of position tracking using cortical columns of integrate-and-fire and Hodgkin-Huxley-type neurons which respond optimally to a particular location, to show that negatively correlated firing patterns arise from lateral inhibition in cortical columns and that this provides a clear benefit for population coding in terms of stability, accuracy, estimation time and neural resources.

Spatial Patterns of Excitation and Inhibition Evoked by Lateral Connectivity in Layer 2/3 of Rat Barrel Cortex

In the rat barrel cortex, neurons in layer 4 are topographically arranged in a precise columnar structure, and the excitatory feed-forward input from layer 4 to layer 2/3 projects almost exclusively within the home barrel column. Here we analyzed the lateral connectivity that links neighboring columns in layer 2/3, which is necessary for integrating information across whiskers. We examined the spatial distributions of three different functional types of lateral connections in layer 2/3 of the rat barrel cortex: glutamate receptor-mediated excitatory connections, GABA(A) receptor-mediated inhibitory connections and GABA(B) receptor-mediated inhibitory connections. Synaptic potentials of pyramidal neurons, which are measures of the strength of connections, were evoked by a horizontal array of stimulation electrodes. The synaptic potentials and their decrease with distance from the stimulation site were measured in two types of slices whose planes were parallel to or orthogonal to barrel rows. Excitatory and GABA(B) receptor-mediated inhibitory connections were stronger along barrel rows than across them, whereas GABA(A) receptor-mediated inhibitory connections did not show such a tendency. These results indicate that lateral connectivity in layer 2/3 varies on the basis of not only excitatory polarity but also receptor subtypes.

Laminar cortical dynamics of 3D surface perception: stratification, transparency, and neon color spreading

The 3D LAMINART neural model is developed to explain how the visual cortex gives rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes. Such percepts are sensitive to whether contiguous image regions have the same contrast polarity and ocularity. The model predicts how like-polarity competition at V1 simple cells in layer 4 may cause these percepts when it interacts with other boundary and surface processes in V1, V2, and V4. The model also explains how: the Metelli Rules cause transparent percepts, bistable transparency percepts arise, and attention influences transparency reversal.

On-chip visual perception of motion: A bio-inspired connectionist model on FPGA

Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented. The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering. The architecture is constituted by three main modules that perform spatial, temporal, and excitatory-inhibitory connectionist processing. The biomimetic architecture is modeled, simulated and validated in VHDL. The synthesis results on a Field Programmable Gate Array (FPGA) device show the potential achievement of real-time performance at an affordable silicon area.

The "silent" surround of V1 receptive fields: theory and experiments

The spiking response of a primary visual cortical cell to a stimulus placed within its receptive field can be up- and down-regulated by the simultaneous presentation of objects or scenes placed in the "silent" regions which surround the receptive field. We here review recent progresses that have been made both at the experimental and theoretical levels in the description of these so-called "Center/Surround" modulations and in the understanding of their neural basis. Without denying the role of a modulatory feedback from higher cortical areas, recent results support the view that some of these phenomena result from the dynamic interplay between feedforward projections and horizontal intracortical connectivity in V1. Uncovering the functional role of the contextual periphery of cortical receptive fields has become an area of active investigation. The detailed comparison of electrophysiological and psychophysical data reveals strong correlations between the integrative behavior of V1 cells and some aspects of "low-level" and "mid-level" conscious perception. These suggest that as early as the V1 stage, the visual system is able to make use of contextual cues to recover local visual scene properties or correct their interpretation. Promising ideas have emerged on the importance of such a strategy for the coding of visual scenes, and the processing of static and moving objects.

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.

Fast synchronization of perceptual grouping in laminar visual cortical circuits

Perceptual grouping is well known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints in which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

Spatiotemporal patterns of excitation and inhibition evoked by the horizontal network in layer 2/3 of ferret visual cortex

The horizontal network in visual cortex layer 2/3 is implicated in numerous psychophysical and physiological properties. To investigate the spatial and temporal distribution of excitation and inhibition evoked by this network, we used voltage-sensitive dyes to image the responses to focal electrical stimulation in tangential slices of ferret visual cortex layer 2/3. The resulting optical patterns included a diffuse zone of activation near the stimulation site and numerous ovoid domains throughout the slice. In contrast to the fixed anatomy of the horizontal connections, substantial shifts in both space and time were evident in the distribution of population-based neuronal activity during stimulus trains. Both of these shifts relied on inhibitory synaptic potentials, suggesting that inhibition driven by horizontal connections sculpts the distribution of activity in this cortical network.