Synchronization between the end stages of the dorsal and the ventral visual stream

Abstract

Verhoef B, Vogels R, Janssen P. Synchronization between the end stages of the dorsal and the ventral visual stream. J Neurophysiol 105: 2030 -2042, 2011. First published February 16, 2011 doi:10.1152/jn.00924.2010.-The end stage areas of the ventral (IT) and the dorsal (AIP) visual streams encode the shape of disparitydefined three-dimensional (3D) surfaces. Recent anatomical tracer studies have found direct reciprocal connections between the 3D-shape selective areas in IT and AIP. Whether these anatomical connections are used to facilitate 3D-shape perception is still unknown. We simultaneously recorded multi-unit activity (MUA) and local field potentials in IT and AIP while monkeys discriminated between concave and convex 3D shapes and measured the degree to which the activity in IT and AIP synchronized during the task. We observed strong beta-band synchronization between IT and AIP preceding stimulus onset that decreased shortly after stimulus onset and became modulated by stereo-signal strength and stimulus contrast during the later portion of the stimulus period. The beta-coherence modulation was unrelated to task-difficulty, regionally specific, and dependent on the MUA selectivity of the pairs of sites under study. The beta-spikefield coherence in AIP predicted the upcoming choice of the monkey. Several convergent lines of evidence suggested AIP as the primary source of the AIP-IT synchronized activity. The synchronized beta activity seemed to occur during perceptual anticipation and when the system has stabilized to a particular perceptual state but not during active visual processing. Our findings demonstrate for the first time that synchronized activity exists between the end stages of the dorsal and ventral stream during 3D-shape discrimination. three-dimensional shape perception; synchronization TO UNDERSTAND THE FUNCTIONING of brain networks, one must know the properties of its constituting elements and the interconnections between them. Traditional neuroscience has mainly focused on the functional properties of brain elements (e.g., feature tuning of neurons or the functional role of brain regions). However, recently there has been an increased interest in the brain's "connectome" (Sporns et al. 2005), i.e., the neural connections at the micro-, meso-, and macroscale.

Stimulus repetition affects both strength and synchrony of macaque inferior temporal cortical activity

“…Indeed, there was an enhanced synchronization in this band after the adapter stimulus presentation followed by desynchronization, which decreased with repetition. This is reminiscent of the stimulus-driven desynchronization between LIP and IT activity observed by Verhoef et al (2011) in the beta band during a depth discrimination task, which increased with stimulus strength. Thus the greater beta/low gamma desynchronization for the adapter compared with the test stimulus might reflect a greater saliency of the former stimulus.…”

“…To control for the contribution of spiking rate differences when comparing the coherence values for two different stimuli, e.g., adapter and test stimuli, we equated the firing rates for the two stimuli before computing the spectra (Gregoriou et al 2009;Verhoef et al 2011). For each site and condition, we equated the average firing rate computed in 1-ms bins within an interval of 1,000 ms that started 250 ms before stimulus onset by randomly removing spikes of the corresponding bin for the stimulus with a larger firing rate at that bin.…”

“…Details about implants and surgery can be found in Kaliukhovich and Vogels (2011) and are only summarized briefly here. The placement of the plastic recording chamber was guided with a preoperative MRI scan and verified with MRI scans obtained at the beginning and between recording sessions.…”

Selectivity for Three-Dimensional Shape and Grasping-Related Activity in the Macaque Ventral Premotor Cortex

“…Furthermore, the population latency of the neuronal selectivity in F5a (75-85 ms) was slightly longer than that of AIP (50 -70 ms) (Srivastava et al, 2009;Theys et al, 2012), but nevertheless shorter than in IT (100 -120 ms) (Janssen et al, 1999;Verhoef et al, 2011). F5a neurons tended to preserve their selectivities across fewer positions in depth (median number of positions, 3) compared to AIP (median number of positions, 4), suggesting that mean disparity exerts a stronger influence in F5a than in AIP.…”

“…AIP neurons, in contrast, encode 3D information in a faster, coarser, and more metric (as opposed to the categorical coding in IT) manner (Srivastava et al, 2009). The correlation between AIP activity and perceptual choice emerges late and after the decision has been formed when monkeys categorize 3D shape (Verhoef et al, 2011), and reversible inactivation of 3D-shape-selective AIP sites produces a grasping deficit but no deficit in 3D-shape categorization (Verhoef et al, 2009). Here, the preponderance of 3D-shape-selective F5a neurons that respond during object grasping also indicates a different role for higher-order disparity selective neurons, i.e., object analysis for the purpose of grasping.…”