Abstract

The subject of the talk belongs to the area of computational neuroscience, a new and rapidly evolving field of neuroscience whose aim is to apply various computational tools to the study of the brain. Understanding how the brain operates is one of the major challenges tackled by scientists. Many theories have been suggested regarding how patterns of basic electrical signals become sensations of taste, sight and sound.

Neurons transmit information around the neural circuit as electrical pulses. But how does the brain translate this information, enabling us to perceive and understand the world? One theory posits that different types of information are represented by patterned sequences of electrical charges across an array of neurons. According to this theory each perceived object generates a distinct pattern within the system of nerve cells for the brain to interpret. Each time the same object is viewed, the neural circuit will create an identical pattern in a precise and controlled manner.

In the talk I intend to discuss some experiments conducted to examine this theory. Specifically, we studied how electrical potential fluctuations of individual cortical neurons can precisely repeat during spontaneous activity, seconds to minutes apart. These repeats, also called cortical motifs, were suggested to reflect a replay of sequential neuronal firing patterns. However, a statistical analysis of three different types of stochastic surrogate data that preserve dynamical characteristics of the recorded data, revealed no evidence for the existence of deterministically generated cortical motifs. Rather, we suggest that the observed patterns occurred purely by chance.

All the necessary biological background will be provided in the first part of the talk.

The talk is based on the paper: Stochastic emergence of repeating cortical motifs in spontaneous membrane potential fluctuations in vivo, Mokeichev, A. and Okun, M. and Barak, O. and Katz, Y. and Ben-Shahar, O. and Lampl, I., Neuron 2007