Time-invariant person-specific frequency templates in human brain activity.

The various human brain tasks are performed at different locations and time scales. Yet, we discovered the existence of time-invariant (above an essential time scale) partitioning of the brain activity into personal state-specific frequency bands. For that, we perform temporal and ensemble averaging of best wavelet packet bases from multielectrode electroencephalogram recordings.

Adult, sex-specific behavior characterized by elevated neuronal functional complexity.

Adult, sex-specific behaviors are good models for context-specific behavioral patterns. Here, we focus on a unique example: locust oviposition. The neural network's rhythmic output can be activated at all life stages, including embryonic, in both females and males.

Self-regulated complexity in cultured neuronal networks.

New quantified observables of complexity are identified and utilized to study sequences (time series) recorded during the spontaneous activity of different size cultured networks. The sequence is mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The sequence regularity is associated with the domain homogeneity and its complexity with its local and global variations.

Hidden neuronal correlations in cultured networks.

Utilization of a clustering algorithm on neuronal spatiotemporal correlation matrices recorded during a spontaneous activity of in vitro networks revealed the existence of hidden correlations: the sequence of synchronized bursting events (SBEs) is composed of statistically distinguishable subgroups each with its own distinct pattern of interneuron spatiotemporal correlations. These findings hint that each of the SBE subgroups can serve as a template for coding, storage, and retrieval of a specific information.

A method for spike sorting and detection based on wavelet packets and Shannon's mutual information.

Studying the dynamics of neural activity via electrical recording, relies on the ability to detect and sort neural spikes recorded from a number of neurons by the same electrode. We suggest the wavelet packets decomposition (WPD) as a tool to analyze neural spikes and extract their main features. The unique quality of the wavelet packets-adaptive coverage of both time and frequency domains using a set of localized packets, facilitate the task.

Long term behavior of lithographically prepared in vitro neuronal networks.

We measured the long term spontaneous electrical activity of neuronal networks with different sizes, grown on lithographically prepared substrates and recorded with multi-electrode-array technology. The time sequences of synchronized bursting events were used to characterize network dynamics. All networks exhibit scale-invariant Lévy distributions and long-range correlations.