Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales |
| |
Authors: | Knoblauch Andreas Palm Günther |
| |
Institution: | (1) Department of Neural Information Processing, University of Ulm, 89069 Ulm, Germany, DE |
| |
Abstract: | We present further simulation results of the model of two reciprocally connected visual areas proposed in the first paper
Knoblauch and Palm (2002) Biol Cybern 87:151–167]. One area corresponds to the orientation–selective subsystem of the primary
visual cortex, the other is modeled as an associative memory representing stimulus objects according to Hebbian learning.
We examine the scene-segmentation capability of our model on larger time and space scales, and relate it to experimental findings.
Scene segmentation is achieved by attention switching on a time-scale longer than the gamma range. We find that the time-scale
can vary depending on habituation parameters in the range of tens to hundreds of milliseconds. The switching process can be
related to findings concerning attention and biased competition, and we reproduce experimental poststimulus time histograms
(PSTHs) of single neurons under different stimulus and attentional conditions. In a larger variant the model exhibits traveling
waves of activity on both slow and fast time-scales, with properties similar to those found in experiments. An apparent weakness
of our standard model is the tendency to produce anti-phase correlations for fast activity from the two areas. Increasing
the inter-areal delays in our model produces alternations of in-phase and anti-phase oscillations. The experimentally observed
in-phase correlations can most naturally be obtained by the involvement of both fast and slow inter-areal connections; e.g.,
by two axon populations corresponding to fast-conducting myelinated and slow-conducting unmyelinated axons.
Received: 22 August 2001 / Accepted in revised form: 8 April 2002 |
| |
Keywords: | |
本文献已被 PubMed SpringerLink 等数据库收录! |
|