PT  - JOURNAL ARTICLE
AU  - Yuwei Cui
AU  - Liu D. Liu
AU  - Farhan A. Khawaja
AU  - Christopher C. Pack
AU  - Daniel A. Butts
TI  - Diverse Suppressive Influences in Area MT and Selectivity to Complex Motion Features
AID  - 10.1523/JNEUROSCI.0203-13.2013
DP  - 2013 Oct 16
TA  - The Journal of Neuroscience
PG  - 16715--16728
VI  - 33
IP  - 42
4099  - http://www.jneurosci.org/content/33/42/16715.short
4100  - http://www.jneurosci.org/content/33/42/16715.full
SO  - J. Neurosci.2013 Oct 16; 33
AB  - 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.