Context-Sensitive Binding by the Laminar Circuits of V1 and V2: A Unified Model of Perceptual Grouping, Attention, and Orientation Contrast

A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific laminar circuits allow the responses of visual cortical neurons to be determined not only by the stimuli within their classical receptive fields, but also to be strongly influenced by stimuli in the extra-classical surround. This context-sensitive visual processing can greatly enhance the analysis of visual scenes, especially those containing targets that are low contrast, partially occluded, or crowded by distractors. We show how interactions of feedforward, feedback and horizontal circuitry can implement several types of contextual processing simultaneously, using shared laminar circuits. In particular, we present computer simulations which suggest how top-down attention and preattentive perceptual grouping, two processes that are fundamental for visual binding, can interact, with attentional enhancement selectively propagating along groupings of both real and illusory contours, thereby showing how attention can selectively enhance object representations. These simulations also illustrate how attention may have a stronger facilitatory effect on low contrast than on high contrast stimuli, and how pop-out from orientation contrast may occur. The specific functional roles which the model proposes for the cortical layers allow several testable neurophysiological predictions to be made. The results presented here simulate only the boundary grouping system of adult cortical architecture. However we also discuss how this model contributes to a larger neural theory of vision which suggests how intracortical and intercortical feedback help to stabilize development and learning within these cortical circuits. Although feedback plays a key role, fast feedforward processing is possible in response to unambiguous information. Model circuits are capable of synchronizing quickly, but context-sensitive persistence of previous events can influence how synchrony develops. Although these results focus on how the interblob cortical processing stream controls boundary grouping and attention, related modeling of the blob cortical processing stream suggests how visible surfaces are formed, and modeling of the motion stream suggests how transient responses to scenic changes can control long-range apparent motion and also attract spatial attention.Defense Advanced Research Projects agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI 94-01659, IRI 97-20333); ONR (N00014-92-J-1309, N00014-95-1-0657

Spatial context in the early visual system

Important visual objects in our everyday life, such as fellow people, passing cars or birds perhaps, are not point-like structures but often occupy considerable amounts of the visual field. However, each photoreceptor in our eyes samples just a tiny portion of the visual field and somehow the visual system should integrate these local signals. This process takes place mainly in the visual cortex and, while higher-order visual areas play an important role in perception of extended structures, it is now well established that visual neurons at the first cortical steps of seeing integrate broad spatial context into their responses. The main purpose of this thesis was to provide detailed information concerning the spatial structure of the mechanisms that underlie integration of spatial context in the early visual system. The opening study of this thesis showed that the antagonistic Gaussians structure that has been used for modeling context integration in single visual neurons provides a relatively accurate description of the process also in the human visual system. The first study introduced a novel method for connecting perceptual and neuroimaging measurements and this method was applied in the second study of this thesis. The second study showed that the human visual system integrates spatial context in terms of its visual field size instead of the size of its cortical representation. The third study showed that context is integrated over an unexpectedly large region of the visual field and that spatially distant context may sometimes increase the contrast response of the visual system. The closing study showed that orientation specificity of the integration of spatial context depends on distance both in single neurons in the macaque primary visual cortex and in human perception. The knowledge acquired in this thesis will be generally useful in applications that require understanding of the human visual system.Arkielämän kannalta tärkeät visuaaliset objektit kuten ihmiset, ohikiitävät autot ja kenties kissat, ovat harvoin pistemäisiä, mutta sen sijaan voivat peittää laajankin alueen näkökentästä. Näköaistinsolut prosessoivat kuvainformaatiota erittäin pieneltä näkökentän alueelta ja näköjärjestelmän tulee jollain tavoin yhdistää nämä paikalliset signaalit. Vaikka näköaivokuoren myöhäisten alueiden merkitys spatiaalisesti laajojen objektien havaitsemisessa onkin merkittävä, nykytietämyksen valossa on kiistatonta että myös varhaisten näköaivokuorten hermosolut integroivat spatiaalista kontekstia laajalta näkökentän alueelta. Tässä väitöskirjassa tutkitaan konteksti-integraation taustalla olevien mekanismien spatiaalista rakennetta varhaisessa näköjärjestelmässä. Väitöskirjan ensimmäisessä osatyössä osoitettiin että konteksti-integraatiota yksittäisissä hermosoluissa kuvaavat kahden antagonistisen Gaussilaisen mallit ovat melko hyviä kuvauksia konteksti-integraatiomekanismien spatiaalisesta rakenteesta myös ihmisen näköjärjestelmässä. Ensimmäisessä osatyössä kehitettiin menetelmä joka mahdollistaa havainto- ja aivokuvantamismittausten uudenlaisen yhdistämisen. Tätä menetelmää sovellettiin toisessa osatyössä, jonka päätulos oli konteksti-integraation riippuvuus ärsykkeen koosta näkökentässä sen sijaan että se olisi sidoksissa ärsykkeen edustuksen kokoon aivokuorella. Kolmannessa osatyössä osoitettiin, että kontekstia integroidaan huomattavan laajalta alueelta ja että spatiaalisesti etäinen konteksti saattaa toisinaan vahvistaa näköjärjestelmän kontrastivastetta. Neljäs tutkimus osoitti, että konteksti-integraation valikoivuus orientaatiolle riippuu etäisyydestä niin ihmisen näköhavainnoissa kuin makaki-apinan ensimmäisen näköaivokuoren soluissakin. Tämän väitöskirjan tuloksia voidaan hyödyntää sovelluksissa joissa tarvitaan tietoa ihmisen näköjärjestelmän toiminnasta

The neural basis of centre-surround interactions in visual motion processing

Perception of a moving visual stimulus can be suppressed or enhanced by surrounding context in adjacent parts of the visual field. We studied the neural processes underlying such contextual modulation with fMRI. We selected motion selective regions of interest (ROI) in the occipital and parietal lobes with sufficiently well defined topography to preclude direct activation by the surround. BOLD signal in the ROIs was suppressed when surround motion direction matched central stimulus direction, and increased when it was opposite. With the exception of hMT+/V5, inserting a gap between the stimulus and the surround abolished surround modulation. This dissociation between hMT+/V5 and other motion selective regions prompted us to ask whether motion perception is closely linked to processing in hMT+/V5, or reflects the net activity across all motion selective cortex. The motion aftereffect (MAE) provided a measure of motion perception, and the same stimulus configurations that were used in the fMRI experiments served as adapters. Using a linear model, we found that the MAE was predicted more accurately by the BOLD signal in hMT+/V5 than it was by the BOLD signal in other motion selective regions. However, a substantial improvement in prediction accuracy could be achieved by using the net activity across all motion selective cortex as a predictor, suggesting the overall conclusion that visual motion perception depends upon the integration of activity across different areas of visual cortex

From receptive profiles to a metric model of V1

In this work we show how to construct connectivity kernels induced by the receptive profiles of simple cells of the primary visual cortex (V1). These kernels are directly defined by the shape of such profiles: this provides a metric model for the functional architecture of V1, whose global geometry is determined by the reciprocal interactions between local elements. Our construction adapts to any bank of filters chosen to represent a set of receptive profiles, since it does not require any structure on the parameterization of the family. The connectivity kernel that we define carries a geometrical structure consistent with the well-known properties of long-range horizontal connections in V1, and it is compatible with the perceptual rules synthesized by the concept of association field. These characteristics are still present when the kernel is constructed from a bank of filters arising from an unsupervised learning algorithm.Comment: 25 pages, 18 figures. Added acknowledgement

The effects of noise on binocular rivalry waves: a stochastic neural field model

We analyse the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We first show how, in the absence of any noise, the system supports a propagating composite wave consisting of an invading activity front in one network co-moving with a retreating front in the other network. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how multiplicative noise in the activity variables leads to a diffusive–like displacement (wandering) of the composite wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. The multiplicative noise also renormalizes the mean speed of the wave. We use our analysis to calculate the first passage time distribution for a stochastic rivalry wave to travel a fixed distance, which we find to be given by an inverse Gaussian. Finally, we investigate the effects of noise in the depression variables, which under an adiabatic approximation leads to quenched disorder in the neural fields during propagation of a wave

Cortical Spike Synchrony as a Measure of Input Familiarity

J.G.O. was supported by the Ministerio de Economia y Competividad and FEDER (Spain, project FIS2015-66503-C3-1-P) and the ICREA Academia programme. E.U. acknowledges support from the Scottish Universities Life Sciences Alliance (SULSA) and HPC-Europa2.Peer reviewedPostprin

Neural Models of Motion Integration, Segmentation, and Probablistic Decision-Making

When brain mechanism carry out motion integration and segmentation processes that compute unambiguous global motion percepts from ambiguous local motion signals? Consider, for example, a deer running at variable speeds behind forest cover. The forest cover is an occluder that creates apertures through which fragments of the deer's motion signals are intermittently experienced. The brain coherently groups these fragments into a trackable percept of the deer in its trajectory. Form and motion processes are needed to accomplish this using feedforward and feedback interactions both within and across cortical processing streams. All the cortical areas V1, V2, MT, and MST are involved in these interactions. Figure-ground processes in the form stream through V2, such as the seperation of occluding boundaries of the forest cover from the boundaries of the deer, select the motion signals which determine global object motion percepts in the motion stream through MT. Sparse, but unambiguous, feauture tracking signals are amplified before they propogate across position and are intergrated with far more numerous ambiguous motion signals. Figure-ground and integration processes together determine the global percept. A neural model predicts the processing stages that embody these form and motion interactions. Model concepts and data are summarized about motion grouping across apertures in response to a wide variety of displays, and probabilistic decision making in parietal cortex in response to random dot displays.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624