Nobuhiko Wagatsuma

Layer-Dependent Attentional Processing by Top-down Signals in a Visual Cortical Microcircuit Model

A vast amount of information about the external world continuously flows into the brain, whereas its capacity to process such information is limited. Attention enables the brain to allocate its resources of information processing to selected sensory inputs for reducing its computational load, and effects of attention have been extensively studied in visual information processing. However, how the microcircuit of the visual cortex processes attentional information from higher areas remains largely unknown. Here, we explore the complex interactions between visual inputs and an attentional signal in a computational model of the visual cortical microcircuit. Our model not only successfully accounts for previous experimental observations of attentional effects on visual neuronal responses, but also predicts contrasting differences in the attentional effects of top-down signals between cortical layers: attention to a preferred stimulus of a column enhances neuronal responses of layers 2/3 and 5, the output stations of cortical microcircuits, whereas attention suppresses neuronal responses of layer 4, the input station of cortical microcircuits. We demonstrate that the specific modulation pattern of layer-4 activity, which emerges from inter-laminar synaptic connections, is crucial for a rapid shift of attention to a currently unattended stimulus. Our results suggest that top-down signals act differently on different layers of the cortical microcircuit.

Spatial attention in early vision for the perception of border ownership

Spatial attention alters contrast gain in early visual areas, which might affect the determination of border ownership (BO) that indicates the direction of figure with respect to the border. We investigated the role of spatial attention applied to early vision in the determination of BO with a computational model that consists of V1, V2, and posterior parietal (PP) modules. Attention alters contrast gain in the V1 module so that it enhances local contrast. The V2 module determines BO based on the surrounding contrast extracted by the V1 module. The simulation results showed that the attention significantly modulates BO; BO is even flipped in figures with ambiguous BO while BO is stable for unambiguous figures such as a simple square. To evaluate the model quantitatively, we carried out psychophysical experiments to measure the effects of attention in the perception of BO and compared the results with those from corresponding simulations. The model showed good agreement with human perception including the determination of BO for ambiguous random-block stimuli. These results indicate that the activity of BO-selective neurons could be modulated significantly by spatial attention that alters local contrast gain in V1, which may account in part for automatic, bi-stable perception in ambiguous figures.

Spike synchrony generated by modulatory common input through NMDA-type synapses

Common excitatory input to neurons increases their firing rates and the strength of the spike correlation (synchrony) between them. Little is known, however, about the synchronizing effects of modulatory common input. Here, we show that modulatory common input with the slow synaptic kinetics of N-methyl-d-aspartate (NMDA) receptors enhances firing rates and also produces synchrony. Tight synchrony (correlations on the order of milliseconds) always increases with modulatory strength. Unexpectedly, the relationship between strength of modulation and strength of loose synchrony (tens of milliseconds) is not monotonic: The strongest loose synchrony is obtained for intermediate modulatory amplitudes. This finding explains recent neurophysiological results showing that in cortical areas V1 and V2, presumed modulatory top-down input due to contour grouping increases (loose and tight) synchrony but that additional modulatory input due to top-down attention does not change tight synchrony and actually decreases loose synchrony. These neurophysiological findings are understood from our model of integrate-and-fire neurons under the assumption that contour grouping as well as attention lead to additive modulatory common input through NMDA-type synapses. In contrast, circuits with common projections through model α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors did not exhibit the paradoxical decrease of synchrony with increased input. Our results suggest that NMDA receptors play a critical role in top-down response modulation in the visual cortex.

Feature-based attention in early vision for the modulation of figure-ground segregation.

We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma et al., 2008). These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1–V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F–G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object.

Modeling Attention-Induced Reduction of Spike Synchrony in the Visual Cortex

The mean firing rate of a border-ownership selective (BOS) neuron encodes where a foreground figure relative to its classical receptive field. Physiological experiments have demonstrated that top-down attention increases firing rates and decreases spike synchrony between them. To elucidate mechanisms of attentional modulation on rates and synchrony of BOS neurons, we developed a spiking neuron network model: BOS neurons receive synaptic input which reflects visual input. The synaptic input strength is modulated multiplicatively by the activity of Grouping neurons whose activity represents the object’s location and mediates top-down attentional projection to BOS neurons. Model simulations agree with experimental findings, showing that attention to an object increases the firing rates of BOS neurons representing it while decreasing spike synchrony between pairs of such neurons. Our results suggest that top-down attention multiplicatively emphasizes synaptic current due to bottom-up visual inputs.

Effect of Spatial Attention in Early Vision for the Modulation of the Perception of Border-Ownership

We propose a computational model consisting of mutually linked V1, V2, and PP modules. The model reproduces the effect of attention in the determination of border-ownership (BO) that tells which side of the contour owns the border. The V2 module determines BO based on surrounding contrast extracted by the V1 module that could be influenced by top-down spatial attention from the PP module. We carried out the simulations of the model with random-block ambiguous figures to test whether spatial attention alters BO for these meaningless stimuli. To compare quantitatively these results with human perception, we carried out psychophysical experiments corresponding to the simulations. The results of these two showed good agreement in that the perception of BO was flipped when altering the location of spatial attention. These results suggest that spatial attention is a crucial factor for the modulation of figure direction in meaningless figures, and that the effects of spatial attention in early visual area are crucial for the modulation of figure direction.

Independence of space-based and feature-based attention in the determination of figure direction

Introduction Visual attention enhances our perception and even alters the perception of figures, as we often see in ambiguous figures. We investigated computationally the role of spatial attention in early vision for the perception of direction-offigure (DOF). Spatial attention alters local contrast gain in early vision, thus apparent local contrast will be modulated. If the local contrast is the basis for the determination of border-ownership (BO) that tells which side of a contour owns the border [1,2], BO will be modulated based on the local contrast that is altered by the attention. If the effect of attention is significant, the activity of BOselective cells will be facilitated/suppressed so that the DOF will be flipped.

Interactions elicited by the contradiction between figure direction discrimination and figure-ground segregation

Figure-ground (FG) segregation that separates an object from the rest of the image is a fundamental problem in vision science. A majority of neurons in monkey V2 showed the selectivity to border ownership (BO) that indicates which side of a contour owns the border. Although BO could be a precursor of FG segregation, the contribution of BO to FG segregation has not been clarified. Because FG segregation is the perception of the global region that belongs to an object, whereas BO determination provides the local direction of figure (DOF) along a contour, a spatial integration of BO might be expected for the generation of FG. To understand the mechanisms underlying the perception of figural regions, we investigated the interaction between the local BO determination and the global FG segregation through the quantitative analysis of the visual perception and the spatiotemporal characteristics of eye movements. We generated a set of novel stimuli in which translucency induces local DOF along the contour and global FG independently so that DOF and FG could be either consistent or contradictory. The perceptual responses showed better performance in DOF discrimination than FG segregation, supporting distinct mechanisms for the DOF discrimination and the FG segregation. We examined whether the contradiction between DOF and FG modulates the eye movement while participants judged DOF and FG. The duration of the first eye fixation was modulated by the contradiction during FG segregation but not DOF discrimination, suggesting a sequential processing from the BO determination to the FG segregation. These results of human perception and eye fixation provide important clues for understanding the visual processing for FG segregation.

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision.

Layer dependent neural modulation of a realistic layered-microcircuit model in visual cortex based on bottom-up and top-down signals

Visual attention allocates the information processing resources of the brain to selected sensory inputs to reduce the processing load. Here, we carried out a large-scale simulation with a layered-microcircuit model of the visual cortex based on current knowledge of cortical neurobiology to explore the complex interaction between bottom-up visual input and top-down attentional signals. The microcircuit model corresponds to two columns of visual cortex. Each column consists of about 40,000 integrate-and-fire neurons comprising layers 2/3, 4, 5 and 6 [1]. These columns interact via lateral inhibition from layer 2/3 excitatory neurons in one column to layer 2/3 inhibitory neurons in the other, so that the full network comprises in total around 80,000 neurons and 300 million synapses. Excitatory and inhibitory neurons in layer 4 of the model receive visual inputs mimicking vertical and horizontal bars. Top-down attention was projected to layers 2/3 and 5 to facilitate the visual processing. In order to investigate the mechanism of visual processing and the attentional effect in the layered-microcircuit model, we compared the response of the model to physiological results for neural and attentional modulation [2]. Our model successfully reproduced previous experimental observations of stimulus presentation and attentional effects on visual neuronal responses in layers 2/3 and 5 (Figure ​(Figure1).1). Moreover, the model predicts contrasting differences in the effects of attention between cortical layers: attention to a preferred stimulus of a column enhances neuronal responses of layers 2/3 and 5, the output station of cortical microcircuits, whereas attention suppresses neuronal activities of layer 4, the input station of cortical microcircuits. Further simulations with our model suggest that the specific attentional modulation pattern of layer 4 activity emerges from inter-laminar synaptic connections within the cortical microcircuit and is crucial for the microcircuit to rapidly shift attention to a stimulus different from the one currently attended to. Our multicolumnar model is a canonical microcircuit model for the dynamic selection of multiple sensory inputs to the visual cortices, and makes several testable predictions about the layer-dependence of the response modulations. Figure 1 The population firing rates of excitatory (filled bars) and inhibitory (empty bars) neurons are shown for each layer of a column for various combinations of visual and attentional inputs. The preferred stimulus of the column is bordered white. An attended ...