Humboldt-Universität zu Berlin - Collaborative Research Center for Theoretical Biology

High-frequency (600 Hz) components in primate EEG: Analysis and modelling of sub-millisecond coherence of cortical stimulus-evoked 'population spike bursts'

The goal of project B4 is to understand how patterns of single-neuron activity are reflected in gross population activity which can be obtained noninvasively also in human subjects by highfrequency electroencephalography (hf-EEG). In a previous study we have shown that averaged 600 Hz EEG components are related to synchronous "population spike bursts" generated in the cortex. As spike bursts could constitute a neural code and/or influence network synchronisation and synaptic plasticity, the project focus in the second SFB funding phase has been the single-trial analysis of covariation between single-cell and hf-EEG activity: We found that single-cell burst responses to external stimulation recorded in somatosensory cortex of behaving macaque monkeys form distinct temporally-ordered burst patterns which are alternately elicited even when the same stimulus is presented. Critically, we showed that these burst patterns co-vary with high-frequency EEG signals, possibly reflecting correlated activity in an ensemble of responding neurons. This result challenges the common assumption that response variations are solely due to random phenomena occurring at the single cell level. To account for these findings we put forward a hypothesis that the bursts are arranged in both, temporal patterns (defined by the timing of the composing spikes) and spatial patterns (defined in relation to activity of other cells).

In the next SFB funding phase we propose to test the hypothesis and investigate its consequences. Specifically, we plan to study network interactions involved in the burst generation by combining experimental work, data analysis and modelling.

In the experimental part we will record simultaneously activity of multiple neurons together with epidural EEG and thalamic field activity in behaving macaque monkeys, continuing our collaboration with Prof. Stuart Baker (Newcastle, UK).

Three data analysis approaches will be pursued: spatio-temporal pattern searching, estimating spike-field coherence, and recovering state variables. With respect to spatio-temporal pattern searching we plan to apply standard estimates of inter-neural correlations (cross-correlation, joint post-stimulus time histograms, etc.) as well as data- and model-based classification methods (multi-dimensional scaling, unsupervised clustering, support vector machines, etc.) and computational algorithms for identification of functional and anatomical motifs. In order to estimate spike-field coherence we will extend existing methods relating point processes and real-valued signals (spike-triggered average, phase-locking indices, etc.) to the analysis of EEG fields and multi-neuronal spike trains. Finally, we will develop new techniques for recovering state variables and their dynamics based on various similarity measures (e.g., spike train metrics) combined with autocorrelation measures and model-based approaches (auto-regressive and hidden Markov models).

The experimental and data analysis approaches will be complemented by quantitative modelling of neural burst activity, extending from abstract statistical descriptions of single-unit firing and inter-neuronal correlations, to biologically-inspired multilayer neural networks and multiscale models of neural activity. These models, in turn, will help us to develop and test new data analysis approaches and, ultimately, to make experimentally-testable predictions.

The results of the project shall enable us to bridge the gap between microscopic (single-neuron) and macroscopic (EEG) activity. This may find practical applications in problems such as noninvasive recordings of population spike activity, monitoring variable brain states and extracranial determination of neuronal parameters such as neuronal time constants under physiological and pathological conditions.

description of the 1st period german version
description of the 2nd period