PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 16378515

Polychronization: computation with spikes.

Eugene M Izhikevich
View original source ↗Export metadata ↓

Abstract

We present a minimal spiking network that can polychronize, that is, exhibit reproducible time-locked but not synchronous firing patterns with millisecond precision, as in synfire braids. The network consists of cortical spiking neurons with axonal conduction delays and spike-timing-dependent plasticity (STDP); a ready-to-use MATLAB code is included. It exhibits sleeplike oscillations, gamma (40 Hz) rhythms, conversion of firing rates to spike timings, and other interesting regimes. Due to the interplay between the delays and STDP, the spiking neurons spontaneously self-organize into groups and generate patterns of stereotypical polychronous activity. To our surprise, the number of coexisting polychronous groups far exceeds the number of neurons in the network, resulting in an unprecedented memory capacity of the system. We speculate on the significance of polychrony to the theory of neuronal group selection (TNGS, neural Darwinism), cognitive neural computations, binding and gamma rhythm, mechanisms of attention, and consciousness as "attention to memories."

Explore related subjects

AttentionBrainMemoryModels, NeurologicalNeural Networks, ComputerNeuronal PlasticityNeuronsJournal ArticleResearch Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Eugene M Izhikevich. 2006. Polychronization: computation with spikes.. https://doi.org/10.1162/089976606775093882

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data.

The ultimate goal of brain connectivity studies is to propose, test, modify, and compare certain directional brain pathways. Path analysis or structural equation modeling (SEM) is an ideal statistical method for such studies. In this work, we propose a two-stage unified SEM plus GLM (General Linear Model) approach for the analysis of multisubject, multivariate functional magnetic resonance imaging (fMRI) time series data with subject-level covariates. In Stage 1, we analyze the fMRI multivariate time series for each subject individually via a unified SEM model by combining longitudinal pathways represented by a multivariate autoregressive (MAR) model, and contemporaneous pathways represented by a conventional SEM. In Stage 2, the resulting subject-level path coefficients are merged with subject-level covariates such as gender, age, IQ, etc., to examine the impact of these covariates on effective connectivity via a GLM. Our approach is exemplified via the analysis of an fMRI visual attention experiment. Furthermore, the significant path network from the unified SEM analysis is compared to that from a conventional SEM analysis without incorporating the longitudinal information as well as that from a Dynamic Causal Modeling (DCM) approach.

Attention↗
PubMed2007

Two spatially separated attention systems in the visual field: evidence from inhibition of return.

It has been demonstrated that the human visual field shows some functional inhomogeneities, in particular when the central and perifoveal regions are compared to the more peripheral regions. The present study examined this inhomogeneity by examining the effect of stimulus eccentricity on inhibition of return (IOR), a phenomenon that biases our attention towards novel locations against returning it back to previously attended locations. Eighteen subjects were examined in a visual detection task, in which a target appeared randomly following a nonpredictive spatial cue in the visual field. The eccentricities of the cues and targets were systematically manipulated from 5 degrees to 30 degrees with 5 degrees increments. Results showed that response times to targets that appeared at cued locations were significantly slower than those at uncued locations for all stimulus eccentricities, demonstrating the IOR effects. However, response times at cued locations increased significantly when stimulus eccentricity shifted from 15 degrees to 20 degrees, leading to a much stronger IOR effect at more peripheral regions compared to central and perifoveal regions, indicating a functional dissociation between these two regions of the visual field. Possible neural mechanisms underlying this dissociation are discussed, and two attention systems modulating the two functional regions of the visual field are put forward to best account the present finding implicating in particular midbrain mechanism.

Attention↗