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.

Tsui JMG, Hunter JN, Born RT, Pack CC. The role of V1 surround suppression in MT motion integration. J Neurophysiol 103: 3123-3138, 2010. First published March 24, 2010 doi:10.1152/jn.00654.2009. 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.

Nervous systems adapt to the prevailing sensory environment, and the consequences of this adaptation can be observed in the responses of single neurons and in perception. Given the variety of timescales underlying events in the natural world, determining the temporal characteristics of adaptation is important to understanding how perception adjusts to its sensory environment. Previous work has shown that neural adaptation can occur on a timescale of milliseconds, but perceptual adaptation has generally been studied over relatively long timescales, typically on the order of seconds. This disparity raises important questions. Can perceptual adaptation be observed at brief, functionally relevant timescales? And if so, how do its properties relate to the rapid adaptation seen in cortical neurons? We address these questions in the context of visual motion processing, a perceptual modality characterized by rapid temporal dynamics. We demonstrate objectively that 25 ms of motion adaptation is sufficient to generate a motion aftereffect, an illusory sensation of movement experienced when a moving stimulus is replaced by a stationary pattern. This rapid adaptation occurs regardless of whether the adapting motion is perceived. In neurophysiological recordings from the middle temporal area of primate visual cortex, we find that brief motion adaptation evokes directionselective responses to subsequently presented stationary stimuli. A simple model shows that these neural responses can explain the consequences of rapid perceptual adaptation. Overall, we show that the motion aftereffect is not merely an intriguing perceptual illusion, but rather a reflection of rapid neural and perceptual processes that can occur essentially every time we experience motion.T he nervous system constantly adapts to the statistics of its sensory inputs, and such adaptation has important perceptual consequences (1, 2). Examples include the desensitization of the somatosensory system to constant stimuli (e.g., clothing) and the visual system's adjustments to prevailing light levels. Adaptation affects both neural activity during constant stimulation and neural responses to subsequent stimuli (1). Given the variety of timescales underlying events in the natural world, determining the temporal characteristics of adaptation is a key step in understanding sensory perception. Traditionally, perceptual adaptation is thought to occur over long time periods, with the adapting stimuli being presented for seconds or longer. Neurophysiological work, however, has shown that adaptation occurs at a variety of timescales and can be observed following stimulus exposures as brief as tens of milliseconds (1, 3-7). This rapid adaptation has strong implications for neural coding of sensory stimuli (5,6,8), which renders the relative lack of evidence about brief perceptual adaptation puzzling. Here we consider this question in the context of visual motion processing. Because of the highly dynamic nature of moving stimuli, rapid adaptation is potentially of great relev...

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