PT  - JOURNAL ARTICLE
AU  - Yasmine El-Shamayleh
AU  - Romesh D. Kumbhani
AU  - Neel T. Dhruv
AU  - J. Anthony Movshon
TI  - Visual Response Properties of V1 Neurons Projecting to V2 in Macaque
AID  - 10.1523/JNEUROSCI.2753-13.2013
DP  - 2013 Oct 16
TA  - The Journal of Neuroscience
PG  - 16594--16605
VI  - 33
IP  - 42
4099  - http://www.jneurosci.org/content/33/42/16594.short
4100  - http://www.jneurosci.org/content/33/42/16594.full
SO  - J. Neurosci.2013 Oct 16; 33
AB  - Visual area V2 of the primate cortex receives the largest projection from area V1. V2 is thought to use its striate inputs as the basis for computations that are important for visual form processing, such as signaling angles, object borders, illusory contours, and relative binocular disparity. However, it remains unclear how selectivity for these stimulus properties emerges in V2, in part because the functional properties of the inputs are unknown. We used antidromic electrical stimulation to identify V1 neurons that project directly to V2 (10% of all V1 neurons recorded) and characterized their electrical and visual responses. V2-projecting neurons were concentrated in the superficial and middle layers of striate cortex, consistent with the known anatomy of this cortico-cortical circuit. Most were fast conducting and temporally precise in their electrical responses, and had broad spike waveforms consistent with pyramidal regular-spiking excitatory neurons. Overall, projection neurons were functionally diverse. Most, however, were tuned for orientation and binocular disparity and were strongly suppressed by large stimuli. Projection neurons included those selective and invariant to spatial phase, with roughly equal proportions. Projection neurons found in superficial layers had longer conduction times, broader spike waveforms, and were more responsive to chromatic stimuli; those found in middle layers were more strongly selective for motion direction and binocular disparity. Collectively, these response properties may be well suited for generating complex feature selectivity in and beyond V2.