Farhan A. Khawaja

Pattern Motion Selectivity of Spiking Outputs and Local Field Potentials in Macaque Visual Cortex

The dorsal pathway of the primate visual cortex is involved in the processing of motion signals that are useful for perception and behavior. Along this pathway, motion information is first measured by the primary visual cortex (V1), which sends specialized projections to extrastriate regions such as the middle temporal area (MT). Previous work with plaid stimuli has shown that most V1 neurons respond to the individual components of moving stimuli, whereas some MT neurons are capable of estimating the global motion of the pattern. In this work, we show that the majority of neurons in the medial superior temporal area (MST), which receives input from MT, have this pattern-selective property. Interestingly, the local field potentials (LFPs) measured simultaneously with the spikes often exhibit properties similar to that of the presumptive feedforward input to each area: in the high-gamma frequency band, the LFPs in MST are as component selective as the spiking outputs of MT, and MT LFPs have plaid responses that are similar to the spiking outputs of V1. In the lower LFP frequency bands (beta and low gamma), component selectivity is very common, and pattern selectivity is almost entirely absent in both MT and MST. Together, these results suggest a surprisingly strong link between the sensory tuning of cortical LFPs and afferent inputs, with important implications for the interpretation of imaging studies and for models of cortical function.

Hierarchical processing of complex motion along the primate dorsal visual pathway

Neurons in the medial superior temporal (MST) area of the primate visual cortex respond selectively to complex motion patterns defined by expansion, rotation, and deformation. Consequently they are often hypothesized to be involved in important behavioral functions, such as encoding the velocities of moving objects and surfaces relative to the observer. However, the computations underlying such selectivity are unknown. In this work we have developed a unique, naturalistic motion stimulus and used it to probe the complex selectivity of MST neurons. The resulting data were then used to estimate the properties of the feed-forward inputs to each neuron. This analysis yielded models that successfully accounted for much of the observed stimulus selectivity, provided that the inputs were combined via a nonlinear integration mechanism that approximates a multiplicative interaction among MST inputs. In simulations we found that this type of integration has the functional role of improving estimates of the 3D velocity of moving objects. As this computation is of general utility for detecting complex stimulus features, we suggest that it may represent a fundamental aspect of hierarchical sensory processing.

Brief motion stimuli preferentially activate surround-suppressed neurons in macaque visual area MT

Summary Intuitively one might think that larger objects should be easier to see, and indeed performance on visual tasks generally improves with increasing stimulus size [1,2]. Recently, a remarkable exception to this rule was reported [3]: when a high-contrast, moving stimulus is presented very briefly, motion perception deteriorates as stimulus size increases. This psychophysical surround suppression has been interpreted as a correlate of the neuronal surround suppression that is commonly found in the visual cortex [3–5]. However, many visual cortical neurons lack surround suppression, and so one might expect that the brain would simply use their outputs to discriminate the motion of large stimuli. Indeed previous work has generally found that observers rely on whichever neurons are most informative about the stimulus to perform similar psychophysical tasks [6]. Here we show that the responses of neurons in the middle temporal (MT) area of macaque monkeys provide a simple resolution to this paradox. We find that surround-suppressed MT neurons integrate motion signals relatively quickly, so that by comparison non-suppressed neurons respond poorly to brief stimuli. Thus, psychophysical surround suppression for brief stimuli can be viewed as a consequence of a strategy that weights neuronal responses according to how informative they are about a given stimulus. If this interpretation is correct, then it follows that any psychophysical experiment that uses brief motion stimuli will effectively probe the responses of MT neurons that have strong surround suppression.

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.

Responses of MST neurons to plaid stimuli

The estimation of motion information from retinal input is a fundamental function of the primate dorsal visual pathway. Previous work has shown that this function involves multiple cortical areas, with each area integrating information from its predecessors. Compared with neurons in the primary visual cortex (V1), neurons in the middle temporal (MT) area more faithfully represent the velocity of plaid stimuli, and the observation of this pattern selectivity has led to two-stage models in which MT neurons integrate the outputs of component-selective V1 neurons. Motion integration in these models is generally complemented by motion opponency, which refines velocity selectivity. Area MT projects to a third stage of motion processing, the medial superior temporal (MST) area, but surprisingly little is known about MST responses to plaid stimuli. Here we show that increased pattern selectivity in MST is associated with greater prevalence of the mechanisms implemented by two-stage MT models: Compared with MT neurons, MST neurons integrate motion components to a greater degree and exhibit evidence of stronger motion opponency. Moreover, when tested with more challenging unikinetic plaid stimuli, an appreciable percentage of MST neurons are pattern selective, while such selectivity is rare in MT. Surprisingly, increased motion integration is found in MST even for transparent plaid stimuli, which are not typically integrated perceptually. Thus the relationship between MST and MT is qualitatively similar to that between MT and V1, as repeated application of basic motion mechanisms leads to novel selectivities at each stage along the pathway.