Neuroelectromagnetic correlates of perceptual closure processes

Perceptual closure refers to the coherent perception of an object under circumstances when the visual information is incomplete. Although the perceptual closure index observed in electroencephalography reflects that an object has been recognized, the full spatiotemporal dynamics of cortical source activity underlying perceptual closure processing remain unknown so far. To address this question, we recorded magnetoencephalographic activity in 15 subjects (11 females) during a visual closure task and performed beamforming over a sequence of successive short time windows to localize high-frequency gamma-band activity (60–100 Hz). Two-tone images of human faces (Mooney faces) were used to examine perceptual closure. Event-related fields exhibited a magnetic closure index between 250 and 325 ms. Time-frequency analyses revealed sustained high-frequency gamma-band activity associated with the processing of Mooney stimuli; closure-related gamma-band activity was observed between 200 and 300 ms over occipitotemporal channels. Time-resolved source reconstruction revealed an early (0–200 ms) coactivation of caudal inferior temporal gyrus (cITG) and regions in posterior parietal cortex (PPC). At the time of perceptual closure (200–400 ms), the activation in cITG extended to the fusiform gyrus, if a face was perceived. Our data provide the first electrophysiological evidence that perceptual closure for Mooney faces starts with an interaction between areas related to processing of three-dimensional structure from shading cues (cITG) and areas associated with the activation of long-term memory templates (PPC). Later, at the moment of perceptual closure, inferior temporal cortex areas specialized for the perceived object are activated, i.e., the fusiform gyrus related to face processing for Mooney stimuli.

Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.