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Computational neuroscience II
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Computational neuroscience II
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Academic year 2023/2024
- Course ID
- NEU0278B
- Teacher
- Tommaso Brischetto Costa (Lecturer)
- Year
- 2nd year
- Teaching period
- First semester
- Type
- Related or integrative
- Credits/Recognition
- 2
- Course disciplinary sector (SSD)
- M-PSI/01 - general psychology
- Delivery
- Formal authority
- Language
- English
- Attendance
- Optional
- Type of examination
- Oral
- Type of learning unit
- modulo
- Modular course
- Computational neuroscience (NEU0278)
- Prerequisites
- introductory course in mathematical analysis
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Sommario del corso
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Course objectives
The purpose of the second module will be to present the basic requirements of the models used in the study of the principles and mechanisms that guide the development, organized, process and mental skills of the central nervous system. In particular we will address the different levels of description of the nervous system's possibilities: micro-scale, meso-scale and macro-scale.
- physiology of the neuron
- levels of description of the nervous system
- analysis of the neural signal
- information theory
- from neuron to systems: functional, structural and anatomical connectivity
- general systems theory
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Results of learning outcomes
The student will be able to deal with the different issues concerning theoretical neuroscience in an appropriate way and will be able to face and carry out research in this field- Oggetto:
Program
The aim of the course is to introduce the fundamental concepts of the models used in the study of the principles and mechanisms that guide the development, organization, information processing and mental skills of the central nervous system. In particular we will deal with the different levels of possible description of the nervous system: micro-scale, meso-scale and macro-scale. At the micro-scale level we will describe the neuron, its characteristics and the characteristics and properties of the synaptic response model and how all this can be described by an elegant equation introduced by Hodgkin and Huxley. Furthermore, simplified neuron models such as Integrate and Fire (IF) will be developed and the noise model that can be incorporated into the deterministic model to model the neural response will be developed. Finally, models describing the collective behavior of neuronal groups will be introduced. At the meso-scale level models of simple networks will be developed that describe the cortical organization of the nervous system and the problems of coding and decoding the signal. At the macro-scale level, using the models described in the micro and meso scale levels, the relationships between structure and functions of the brain will be investigated and how to build explanatory models of the various cognitive functions and pathologies of the nervous system and how to compare them with experimental data. . In addition, the dynamic description of macro-scale brain activity will be addressed.- Oggetto:
Course delivery
in presence
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Learning assessment methods
oral
Suggested readings and bibliography
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Notes and articles provided during the course- Oggetto:
