Direction- and Velocity-Specific Responses from beyond the Classical Receptive Field in the Middle Temporal Visual Area (MT)

Abstract

The true receptive field of more than 90% of neurons in the middle temporal visual area (MT) extends well beyond the classical receptive field (crf), as mapped with conventional bar or spot stimuli, and includes a surrounding region that is 50 to 100 times the area of the crf. These extensive surrounds are demonstrated by simultaneously stimulating the crf and the surround with moving stimuli. The surrounds commonly have directional and velocity-selective influences that are antagonistic to the response from the crf. The crfs of MT neurons are organized in a topographic representation of the visual field. Thus MT neurons are embedded in an orderly visuotopic array, but are capable of integrating local stimulus conditions within a global context. The extensive surrounds of MT neurons may be involved in figure-ground discrimination, preattentive vision, perceptual constancies, and depth perception through motion cues.

Occipital network for figure/ground organization

“…MT is one of the primary output pathways for layer six neurons of these early retinotopic regions (Rockland and Van Hoesen 1994;Rockland and Knutson 2000). Neurophysiologically, a role for MT/MST in Wgure/ground assignment for structure-from-motion has been suggested for the past two decades (Allman et al 1985;Olavarria et al 1992;Eifuku and Wurtz 1999;Born 2000;Born and Bradley 2005). Rapid feedback to V1 from areas with large receptive Welds, such as V2 or MT, was proposed in many cases Lamme 1995;Zipser et al 1996;Lee et al 1998;Nothdurft et al 1999Nothdurft et al , 2000Hupé et al 2001;Craft et al 2007).…”

On motion detection through a multi-layer neural network architecture

“…Current biological data suggest that there are several levels in motion analysis in the visual system (Albright, 1992;Allman, Miezin, & McGuinness, 1985;Andersen & Siegel, 1990;Morrone, Burr, & Vaina, 1995).…”

The complementary brain: unifying brain dynamics and modularity

“…Classical computational models of motion detection involving Reichardt-like or motion-energy mechanisms have focused on the recovery of local motion directions [33][34][35] . Cells in motion processing areas like MT, however, are sensitive to both the direction and the speed of moving patterns 20,36 . Indeed, both direction and speed estimates are needed to track moving objects.…”