Theoretical Neuroscience Podcast

We know a lot about of how neurons in the primary visual cortex (V1) of mammals respond to visual stimuli.

But how does the vast information contained in the spiking of millions of neurons in V1 give rise to our visual percepts?

The guest's theory is that V1 acts as a "saliency detector" directing the gaze to the most important object in the visual scene. Then V1 in collaboration with higher visual areas determines what this object is in an iterative feedforward-feedback loop.

A key goal of computational neuroscience is to build mathematical models linking single-neuron activity to systems-level activity.

The guest has taken some bold steps in this direction by developing and exploring a multi-area model for the macaque visual cortex, and later also a model for the human cortex, using millions of simplified spiking neuron models.

We discuss the many design choices, the challenge of running the models, and what has been learned so far.

It is widely thought that spikes (action potentials) are the main carrier of information in the brain.

But what is the neural code, that is, what aspects of the spike trains carry the information? The detailed temporal structure or maybe only the average firing rate? And is there information in the correlation between spike trains in populations of similar neurons?

The guest has thought about these and other coding questions throughout his career.

Starting from the pioneering work of Hodgkin, Huxley and Rall in the 1950s and 60s, we have a well-founded biophysics-based mathematical understanding of how neurons integrate signals from other neurons and generate action potentials.

Today's guest wrote the classic book "Biophysics of Computation" on the subject in 1998.

We discuss its contents, what has changed in the last 25 years, and also touch on his other main research interest: consciousness research.

The book "Models of the Mind" published in 2021 gives an excellent popular account of the history and questions of interest in theoretical neuroscience.

I could think of no other person more suitable to invite for the inaugural episode of the podcast than its author Grace Lindsay.

In the podcast we discuss highlights from the book as well as recent developments and the future of our field.