In silico : controlling the late phase of long term facilitation in the aplysia californica - a spatio-temporal stochastic simulation.

Learning and Memory is a complex physiological process. It has therefore taken the work of many researchers to elucidate the molecular mechanism of memory. A few prominent researchers have spent the last decades of their careers, successfully pinpointing, with broad-like brushes, the mechanism towar...

Full description

Saved in:
Bibliographic Details
Main Author: Cheng, Anthony Youzhi.
Other Authors: School of Chemical and Biomedical Engineering
Format: Final Year Project
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/45748
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:Learning and Memory is a complex physiological process. It has therefore taken the work of many researchers to elucidate the molecular mechanism of memory. A few prominent researchers have spent the last decades of their careers, successfully pinpointing, with broad-like brushes, the mechanism towards acquiring memory. Short–term and long-term memory are a mysterious feature in human psychology. Researchers like Eric R. Kandel, have shown that the facilitation of short term to long term memory requires protein synthesis (or the activation of the transcription and translation mechanism). It is postulated that this conversion to long term memory requires a switch-like mechanism. One such mathematical model that explains how the dynamics of autoregulation is achieved in the interlocked positive and negative feedback loop. Another component is the switch-like mechanism found by modeling a signaling repressor molecule. This paper will present to you how the PKA, Ca2+ and MAPK signaling systems may control the transcription and translational machinery in the postsynaptic neuron. In addition, we simulate the network with a spatio-temporal simulator, Smoldyn, to draw attention to some of the likely parameters that can cause fast transition states.