Contributions of indirect pathways to visual response properties in macaque middle temporal area MT.

The primate visual cortex exhibits a remarkable degree of interconnectivity. Each visual area receives an average of 10 to 15 inputs, many of them from cortical areas with overlapping, but not identical, functional properties. In this study, we assessed the functional significance of this anatomical parallelism to the middle temporal area (MT) of the macaque visual cortex. MT receives major feedforward inputs from areas V1, V2, and V3, but little is known about the properties of each of these pathways. We previously demonstrated that reversible inactivation of V2 and V3 causes a disproportionate degradation of tuning for binocular disparity of MT neurons, relative to direction tuning (Ponce et al., 2008). Here we show that MT neurons continued to encode speed and size information during V2/3 inactivation; however, many became significantly less responsive to fast speeds and others showed a modest decrease in surround suppression. These changes resemble previously reported effects of reducing stimulus contrast (Pack et al., 2005; Krekelberg et al., 2006), but we show here that they differ in their temporal dynamics. We find no evidence that the indirect pathways selectively target different functional regions within MT. Overall, our findings suggest that the indirect pathways to MT primarily convey modality-specific information on binocular disparity, but that they also contribute to the processing of stimuli moving at fast speeds.

Stimulus-dependent modulation of suppressive influences in MT.

Surround suppression contributes to important functions in visual processing, such as figure-ground segregation; however, this benefit comes at the cost of decreased neuronal sensitivity. Studies of receptive fields at several levels of the visual hierarchy have demonstrated that surround suppression is reduced for low contrast stimuli, thereby improving neuronal sensitivity. We investigated whether this reduction of surround suppression reflects a general processing strategy to boost sensitivity for weak signals by summing them over a larger region of the visual field (spatial integration) or if the reduction is limited to specialized stimulus conditions. To do this, we used stochastic motion stimuli to measure surround suppression in area MT of alert macaque monkeys. While varying stimulus size we also varied the strength of two other critical stimulus features: contrast and coherence (i.e., the proportion of dots moving in the preferred direction of the neuron). We found that reducing stimulus contrast weakened surround suppression, but reducing stimulus coherence had the opposite effect, indicating that diminished surround suppression is not a universal response to stimuli of low signal-to-noise. This can be partially explained by our other finding, which is that surrounds in MT are very broadly direction tuned. Instead of producing a reduction of surround suppression that would improve the ability of the neuron to integrate preferred direction motion, low coherence stimuli activated the broadly tuned surrounds relatively better than the centers, which are generally more direction selective. Our results are consistent with a normalization mechanism of surround suppression that pools broadly across multiple stimulus dimensions.

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.

Contrast dependence of suppressive influences in cortical area MT of alert macaque.

Visual neurons are often characterized in terms of their tuning for various stimulus properties, such as shape, color, and velocity. Generally, these tuning curves are further modulated by the overall intensity of the stimulus, such that increasing the contrast increases the firing rate, up to some maximum. In this paper, we describe the tuning of neurons in the middle temporal area (MT or V5) of macaque visual cortex for moving stimuli of varying contrast. We find that, for some MT neurons, tuning curves for stimulus direction, speed, and size are shaped in part by suppressive influences that are present at high stimulus contrast but weak or nonexistent at low contrast. For most neurons, the suppression is direction-specific and strongest for large, slow-moving stimuli. The surprising consequence of this phenomenon is that some MT neurons actually fire more vigorously to a large low-contrast stimulus than to one of high contrast. These results are consistent with recent perceptual observations, as well as with information-theoretic models, which hypothesize that the visual system seeks to reduce redundancy at high contrast while maintaining sensitivity at low contrast.