Spike Rate Adaptation Model

Spike rate adaptation is a mechanism by which cells, not only save energy but, maintain better perception of the external world. In this video we can see two sensory neural cells (their receptive fields). In the model, a particle moves in a state space. The state space consists of 1 dimensional, one directional Markov process. The network output is the estimated position of the particle using Bayesian filtering theory.

Hypothesis:
Whenever a cell fires a spike (action potential), its activity decreases for a short period of time known as the refractory period. In this period the cell regains its ion balance and thus, the probability of firing decreases. This can be modeled by decreasing the magnitude of the tuning curves. Due to adaptation, the disturbances from adjacent cells decreases and thus, better perception of the external world (current state) can be accomplished.

This research is done under the supervision of Prof. Ron Meir at the Technion-Israeli Institute of technology.

To know a bit more about me and about what I do, please check my website:
www.technion.ac.il/~rz

Category:

Education

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• Spike Rate Adaptation
• Theoretical Neuroscience
• Technion
• Rani Zananiri
• refractory period
• action potential
• Ron Meir
• models
• brain
• intersting
• mathematical
• modeling the brain
• Neural Decoding