Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex
Course duration: 6 h
What equations may describe the most powerful processes taking place in a piece of brain cortex? Of course, the equations are based on single neuron equations. Thus, we start with a discussion of integrate-and-fire and Hodgkin-Huxley-like models. How many control signals does a neuron have? What is its input-output function? Is it precise, the Hodgkin-Huxley formalism, if compare with experiments? Can we control a real neuron by a computer? Can we change a cell's activity with a computer, for example, artificially add ionic channels? To answer the questions, we will consider single neuron properties and an experimental dynamic-clamp technique of intracellular registrations. The technique can be considered as, probably, the most primitive example of brain-computer interface systems.
Then, in the second part, we remember that a neuron is an element of a network. What equations do describe the connectivity and synaptic plasticity? Can a neuron be a measuring tool to study the network? The methods of synaptic conductance estimations will be discussed in this part.
The third part will be devoted to the consideration of a statistical ensemble of neurons and its different models, starting from the detailed ones, belonging to the probability density approach, and reducing to the simplest, firing-rate type models.
In the foгrth part, a model of a piece of the visual cortex will be described and compared with experiments, in particular, intracellular registrations and optical imaging data. Some elementary mechanisms of information processing by the cortex will be discussed.
Tutor
Dr. Anton Chizhov
Country: Russia
Place of employment: Senior Researcher, Ioffe Physical Technical Institute of the Russian Academy of Sciences, Saint Petersburg
Spheres of researches: biophysical models of separate neurons; development of records for experimental intracellular measurements held in a dynamic condition of neuron connection with computer (Dynamic-Clamp); statistical theory of neuron population models; biophysically-detailed model of cortical neural tissue, a model of visual cortex.
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