Dynamics of directional selectivity in MT receptive field centre and surround

Primate extrastriate cortical area MST: a gateway between sensation and cognition

Primate visual cortex consists of dozens of distinct brain areas, each providing a highly specialized component to the sophisticated task of encoding the incoming sensory information and creating a representation of our visual environment that underlies our perception and action. One such area is the medial superior temporal cortex (MST), a motion-sensitive, direction-selective part of the primate visual cortex. It receives most of its input from the middle temporal (MT) area, but MST cells have larger receptive fields and respond to more complex motion patterns. The finding that MST cells are tuned for optic flow patterns has led to the suggestion that the area plays an important role in the perception of self-motion. This hypothesis has received further support from studies showing that some MST cells also respond selectively to vestibular cues. Furthermore, the area is part of a network that controls the planning and execution of smooth pursuit eye movements and its activity is modulated by cognitive factors, such as attention and working memory. This review of more than 90 studies focuses on providing clarity of the heterogeneous findings on MST in the macaque cortex and its putative homolog in the human cortex. From this analysis of the unique anatomical and functional position in the hierarchy of areas and processing steps in primate visual cortex, MST emerges as a gateway between perception, cognition, and action planning. Given this pivotal role, this area represents an ideal model system for the transition from sensation to cognition.

Neural Selectivity for Visual Motion in Macaque Area V3A

The processing of visual motion is conducted by dedicated pathways in the primate brain. These pathways originate with populations of direction-selective neurons in the primary visual cortex, which projects to dorsal structures like the middle temporal (MT) and medial superior temporal (MST) areas. Anatomical and imaging studies have suggested that area V3A might also be specialized for motion processing, but there have been very few studies of single-neuron direction selectivity in this area. We have therefore performed electrophysiological recordings from V3A neurons in two macaque monkeys (one male and one female) and measured responses to a large battery of motion stimuli that includes translation motion, as well as more complex optic flow patterns. For comparison, we simultaneously recorded the responses of MT neurons to the same stimuli. Surprisingly, we find that overall levels of direction selectivity are similar in V3A and MT and moreover that the population of V3A neurons exhibits somewhat greater selectivity for optic flow patterns. These results suggest that V3A should be considered as part of the motion processing machinery of the visual cortex, in both human and non-human primates.

Visual Motion Processing in Macaque V2

In the primate visual system, direction-selective (DS) neurons are critical for visual motion perception. While DS neurons in the dorsal visual pathway have been well characterized, the response properties of DS neurons in other major visual areas are largely unexplored. Recent optical imaging studies in monkey visual cortex area 2 (V2) revealed clusters of DS neurons. This imaging method facilitates targeted recordings from these neurons. Using optical imaging and single-cell recording, we characterized detailed response properties of DS neurons in macaque V2. Compared with DS neurons in the dorsal areas (e.g., middle temporal area [MT]), V2 DS neurons have a smaller receptive field and a stronger antagonistic surround. They do not code speed or plaid motion but are sensitive to motion contrast. Our results suggest that V2 DS neurons play an important role in figure-ground segregation. The clusters of V2 DS neurons are likely specialized functional systems for detecting motion contrast.

Suppressive mechanisms in visual motion processing: From perception to intelligence

Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and individuals with schizophrenia-a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores.

Diverse suppressive influences in area MT and selectivity to complex motion features

Neuronal selectivity results from both excitatory and suppressive inputs to a given neuron. Suppressive influences can often significantly modulate neuronal responses and impart novel selectivity in the context of behaviorally relevant stimuli. In this work, we use a naturalistic optic flow stimulus to explore the responses of neurons in the middle temporal area (MT) of the alert macaque monkey; these responses are interpreted using a hierarchical model that incorporates relevant nonlinear properties of upstream processing in the primary visual cortex (V1). In this stimulus context, MT neuron responses can be predicted from distinct excitatory and suppressive components. Excitation is spatially localized and matches the measured preferred direction of each neuron. Suppression is typically composed of two distinct components: (1) a directionally untuned component, which appears to play the role of surround suppression and normalization; and (2) a direction-selective component, with comparable tuning width as excitation and a distinct spatial footprint that is usually partially overlapping with excitation. The direction preference of this direction-tuned suppression varies widely across MT neurons: approximately one-third have overlapping suppression in the opposite direction as excitation, and many other neurons have suppression with similar direction preferences to excitation. There is also a population of MT neurons with orthogonally oriented suppression. We demonstrate that direction-selective suppression can impart selectivity of MT neurons to more complex velocity fields and that it can be used for improved estimation of the three-dimensional velocity of moving objects. Thus, considering MT neurons in a complex stimulus context reveals a diverse set of computations likely relevant for visual processing in natural visual contexts.

The complex structure of receptive fields in the middle temporal area

Neurons in the middle temporal area (MT) are often viewed as motion detectors that prefer a single direction of motion in a single region of space. This assumption plays an important role in our understanding of visual processing, and models of motion processing in particular. We used extracellular recordings in area MT of awake, behaving monkeys (M. mulatta) to test this assumption with a novel reverse correlation approach. Nearly half of the MT neurons in our sample deviated significantly from the classical view. First, in many cells, direction preference changed with the location of the stimulus within the receptive field. Second, the spatial response profile often had multiple peaks with apparent gaps in between. This shows that visual motion analysis in MT has access to motion detectors that are more complex than commonly thought. This complexity could be a mere byproduct of imperfect development, but can also be understood as the natural consequence of the non-linear, recurrent interactions among laterally connected MT neurons. An important direction for future research is to investigate whether these in homogeneities are advantageous, how they can be incorporated into models of motion detection, and whether they can provide quantitative insight into the underlying effective connectivity.

Neural correlates of induced motion perception in the human brain

A physically stationary stimulus surrounded by a moving stimulus appears to move in the opposite direction. There are similarities between the characteristics of this phenomenon of induced motion and surround suppression of directionally selective neurons in the brain. Here, functional magnetic resonance imaging was used to investigate the link between the subjective perception of induced motion and cortical activity. The visual stimuli consisted of a central drifting sinusoid surrounded by a moving random-dot pattern. The change in cortical activity in response to changes in speed and direction of the central stimulus was measured. The human cortical area hMT+ showed the greatest activation when the central stimulus moved at a fast speed in the direction opposite to that of the surround. More importantly, the activity in this area was the lowest when the central stimulus moved in the same direction as the surround and at a speed such that the central stimulus appeared to be stationary. The results indicate that the activity in hMT+ is related to perceived speed modulated by induced motion rather than to physical speed or a kinetic boundary. Early visual areas (V1, V2, V3, and V3A) showed a similar pattern; however, the relationship to perceived speed was not as clear as that in hMT+. These results suggest that hMT+ may be a neural correlate of induced motion perception and play an important role in contrasting motion signals in relation to their surrounding context and adaptively modulating our motion perception depending on the spatial context.

Combining feature selection and integration--a neural model for MT motion selectivity

Background

The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features.

Methodology/Principal Findings

Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem.

Conclusions/Significance

We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour.

Implied Motion Activation in Cortical Area MT Can Be Explained by Visual Low-level Features

To investigate form-related activity in motion-sensitive cortical areas, we recorded cell responses to animate implied motion in macaque middle temporal (MT) and medial superior temporal (MST) cortex and investigated these areas using fMRI in humans. In the single-cell studies, we compared responses with static images of human or monkey figures walking or running left or right with responses to the same human and monkey figures standing or sitting still. We also investigated whether the view of the animate figure (facing left or right) that elicited the highest response was correlated with the preferred direction for moving random dot patterns. First, figures were presented inside the cell's receptive field. Subsequently, figures were presented at the fovea while a dynamic noise pattern was presented at the cell's receptive field location. The results show that MT neurons did not discriminate between figures on the basis of the implied motion content. Instead, response preferences for implied motion correlated with preferences for low-level visual features such as orientation and size. No correlation was found between the preferred view of figures implying motion and the preferred direction for moving random dot patterns. Similar findings were obtained in a smaller population of MST cortical neurons. Testing human MT+ responses with fMRI further corroborated the notion that low-level stimulus features might explain implied motion activation in human MT+. Together, these results suggest that prior human imaging studies demonstrating animate implied motion processing in area MT+ can be best explained by sensitivity for low-level features rather than sensitivity for the motion implied by animate figures.

The role of V1 surround suppression in MT motion integration

Neurons in the primate extrastriate cortex are highly selective for complex stimulus features such as faces, objects, and motion patterns. One explanation for this selectivity is that neurons in these areas carry out sophisticated computations on the outputs of lower-level areas such as primary visual cortex (V1), where neuronal selectivity is often modeled in terms of linear spatiotemporal filters. However, it has long been known that such simple V1 models are incomplete because they fail to capture important nonlinearities that can substantially alter neuronal selectivity for specific stimulus features. Thus a key step in understanding the function of higher cortical areas is the development of realistic models of their V1 inputs. We have addressed this issue by constructing a computational model of the V1 neurons that provide the strongest input to extrastriate cortical middle temporal (MT) area. We find that a modest elaboration to the standard model of V1 direction selectivity generates model neurons with strong end-stopping, a property that is also found in the V1 layers that provide input to MT. With this computational feature in place, the seemingly complex properties of MT neurons can be simulated by assuming that they perform a simple nonlinear summation of their inputs. The resulting model, which has a very small number of free parameters, can simulate many of the diverse properties of MT neurons. In particular, we simulate the invariance of MT tuning curves to the orientation and length of tilted bar stimuli, as well as the accompanying temporal dynamics. We also show how this property relates to the continuum from component to pattern selectivity observed when MT neurons are tested with plaids. Finally, we confirm several key predictions of the model by recording from MT neurons in the alert macaque monkey. Overall our results demonstrate that many of the seemingly complex computations carried out by high-level cortical neurons can in principle be understood by examining the properties of their inputs.

Attention reshapes center-surround receptive field structure in macaque cortical area MT

Directing spatial attention to a location inside the classical receptive field (cRF) of a neuron in macaque medial temporal area (MT) shifts the center of the cRF toward the attended location. Here we investigate the influence of spatial attention on the profile of the inhibitory surround present in many MT neurons. Two monkeys attended to the fixation point or to 1 of 2 random dot patterns (RDPs) placed inside or next to the cRF, whereas a third RDP (the probe) was briefly presented in quick succession across the cRF and surround. The probe presentation responses were used to compute a map of the excitatory receptive field and its inhibitory surround. Attention systematically reshapes the receptive field profile, independently shifting both center and surround toward the attended location. Furthermore, cRF size is changed as a function of relative distance to the attentional focus: attention inside the cRF shrinks it, whereas directing attention next to the cRF expands it. In addition, we find systematic changes in surround inhibition and cRF amplitude. This nonmultiplicative push-pull modulation of the receptive field's center-surround structure optimizes processing at and near the attentional focus to strengthen the representation of the attended stimulus while reducing influences from distractors.

Fast-scale adaptive changes of directional tuning in fly tangential cells are explained by a static nonlinearity

The response of vertebrate motion-sensitive neurons to a directional stimulus is affected by the direction of the stimulus that immediately preceded it. These nonlinear effects are also observed for orientation tuning and are typically interpreted as fast-scale adaptive changes. We verified that similar effects are observed for spiking tangential cells in the fly lobula plate. We also investigated the spatial selectivity of these effects by presenting multiple patches at different positions within the receptive field,and found that the effects are strictly local.

We modelled the data using elementary operators (linear filters and threshold nonlinearities). A satisfactory account of the results is obtained when an early static nonlinearity acts on the outputs of multiple front-end filters that are subsequently pooled in a spatially restricted manner by the tangential cell. In line with recent studies, these findings emphasize the importance of testing simple nonlinear models before attempting more elaborate interpretations of fast-scale adaptive phenomena in single neurons. We discuss a potential neural implementation of the model based on medullar projections to the lobula plate.

Adaptive surround modulation in cortical area MT

Visual motion perception relies on two opposing operations: integration and segmentation. Integration overcomes motion ambiguity in the visual image by spatial pooling of motion signals, whereas segmentation identifies differences between adjacent moving objects. For visual motion area MT, previous investigations have reported that stimuli in the receptive field surround, which do not elicit a response when presented alone, can nevertheless modulate responses to stimuli in the receptive field center. The directional tuning of this "surround modulation" has been found to be mainly antagonistic and hence consistent with segmentation. Here, we report that surround modulation in area MT can be either antagonistic or integrative depending upon the visual stimulus. Both types of modulation were delayed relative to response onset. Our results suggest that the dominance of antagonistic modulation in previous MT studies was due to stimulus choice and that segmentation and integration are achieved, in part, via adaptive surround modulation.

Spatial Summation, End Inhibition and Side Inhibition in the Middle Temporal Visual Area (MT)

We investigated the responses of single neurons in the middle temporal area (MT) of anesthetized marmoset monkeys to sine-wave gratings of various lengths and widths. For the vast majority of MT cells maximal responses were obtained on presentation of gratings of specific dimensions, which were typically asymmetrical along the length and width axes. The strength of end inhibition was dependent on the width of the stimulus, with many cells showing clear end inhibition only when wide gratings were used. Conversely, the strength of side inhibition was dependent on stimulus length. Furthermore, for over one third of MT cells length summation properties could not be defined without consideration of stimulus width and vice versa. These neurons, which we refer to as “length–width inseparable” (LWI) cells, were rare in layer 4. The majority of LWI neurons was strongly inhibited by wide-field stimuli and responded preferentially to gratings that were elongated, along either the length or width dimensions. However, rather than forming a homogeneous and entirely distinct group, LWI cells represented the upper end of a continuum of complexity in spatial summation response properties, which characterized the population of MT cells. Only a minority of MT neurons (22.3%) showed no evidence of inhibition by wide-field stimuli, with this type of response being common among layer 5 cells. These results demonstrate distinct patterns of spatial selectivity in MT, supporting the notion that neurons in this area can perform various roles in terms of grouping and segmentation of motion signals.

Temporal dynamics of 2D and 3D shape representation in macaque visual area V4

We studied the temporal dynamics of shape representation in area V4 of the alert macaque monkey. Analyses were based on two large stimulus sets, one equivalent to the 2D shape stimuli used in a previous study of V2, and the other a set of stereoscopic 3D shape stimuli. As in V2, we found that information conveyed by individual V4 neurons about the stimuli tended to be maximal during the initial transient response and generally lower, albeit statistically significant, afterwards. The population response was substantially correlated from one stimulus to the next during the transients, and decorrelated as responses decayed. V4 responses showed significantly longer latencies than in V2, especially for the 3D stimulus set. Recordings from area V1 in a single animal revealed temporal dynamic patterns in response to the 2D shape stimuli that were largely similar to those in V2 and V4. Together with earlier results, these findings provide evidence for a distributed process of coarse-to-fine representation of shape stimuli in the visual cortex.

Behavioral Receptive Field for Ocular Following in Humans: Dynamics of Spatial Summation and Center-Surround Interactions

Visual neurons integrate information over a finite part of the visual field with high selectivity. This classical receptive field is modulated by peripheral inputs that play a role in both neuronal response normalization and contextual modulations. However, the consequences of these properties for visuomotor transformations are yet incompletely understood. To explore those, we recorded short-latency ocular following responses in humans to large center-only and center-surround stimuli. We found that eye movements are triggered by a mechanism that integrates motion over a restricted portion of the visual field, the size of which depends on stimulus contrast and increases as a function of time after response onset. We also found evidence for a strong nonisodirectional center-surround organization, responsible for normalizing the central, driving input so that motor responses are set to their most linear contrast dynamics. Such response normalization is delayed about 20 ms relative to tracking onset, gradually builds up over time, and is partly tuned for surround orientation/direction. These results outline the spatiotemporal organization of a behavioral receptive field, which might reflect a linear integration among subpopulations of cortical visual motion detectors.