Massachusetts Institute of Technology
A model for cerebral cortical neuron group electric activity and its implications for cerebral function
Abstract
dc:description.abstractThe electroencephalogram, or EEG, is a recording of the field potential generated by the electric activity of neuronal populations of the brain. Its utility has long been recognized as a monitor which reflects the vigilance states of the brain, such as arousal, drowsiness, and sleep stages. Moreover, it is used to detect pathological conditions such as seizures, to calibrate drug action during anesthesia, and to understand cognitive task signatures in healthy and abnormal subjects. Being an aggregate measure of neural activity, understanding the neural origins of EEG oscillations has been limited. With the advent of recording techniques, however, and as an influx of experimental evidence on cellular and network properties of the neocortex has become available, a closer look into the neuronal mechanisms for EEG generation is warranted. Accordingly, we introduce an effective neuronal skeleton circuit at a neuronal group level which could reproduce basic EEG-observable slow (< 15 Hz) oscillatory phenomenon. The circuit incorporates basic laminar organization principles of the cortex. Interaction between neuronal groups is defined on three scales, namely the columnar (0.3mm), columnar assembly (1-2mm) and areal (> 3mm). The effective circuit makes use of the dynamic properties of the layer 5 network to explain intra-cortically generated augmenting responses, restful alpha, slow wave (< 1Hz) oscillations, and disinhibition-induced seizures. Based on recent cellular evidence, we propose a hierarchical binding mechanism in tufted layer 5 cells which acts as a controlled gate between local cortical activity and inputs arriving from distant cortical areas. This gate is manifested by the switch in output firing patterns in tufted
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2002
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Karameh, Fadi Nabih
- Advisor dc:contributor.advisor
-
- Munther A. Dahleh and Steve G. Massaquoi.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- en_US
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/27110
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/27110