Enrollment year
2022/2023
Academic discipline
BIO/09 (PHYSIOLOGY)
Department
DEPARTMENT OF BRAIN AND BEHAVIORAL SCIENCES
Course
PSYCHOLOGY, NEUROSCIENCE AND HUMAN SCIENCES
Curriculum
PERCORSO COMUNE
Period
2nd semester (12/02/2024 - 31/05/2024)
Lesson hours
36 lesson hours
Activity type
WRITTEN AND ORAL TEST
Prerequisites
A basic knowledge in “neurophysiology” is required
Learning outcomes
The course aims at offering knowledge in the field of computational neuroscience. Neural models able to describe, represent and interpret the reality. In particular, the focus will be on computational models correlated to behavioral features, within a neurobiological framework. There will be presented principles to build these neural models of brain structures, able to embed multi-scale information, from single neuron functional mechanism to microcircuits, till the generation of high-level functional behaviors. In view of applications, the models represent powerful tools to understand the complex operations underlying perception, actions and memory, in both physiological and pathological states. This multi-scale and multi-disciplinary approach is the key of challenging international projects, as Human Brain Project and EBRAINS.
To understand principles to build computational neural models, able to embed multi-scale information, from mechanisms of single neurons and synapses, to functional microcircuits with specific connectivity and plasticity, till the generation of high-level functional behaviors. Examples relative to specific brain structures. To acquire methods and tools to reconstruct, simulate and validate these models. To analyze the applications of such models in understanding the complex operations underlying perception, actions and memory, in both physiological and pathological states.
Course contents
- Multiscale neural data
- Neuronal Dynamics: Computational models of Single Neurons, at different simplification levels
- Synpases, connectome, plasticity
- Biological Modeling of Neural Networks
- Neural encoding and decoding, brain dynamics
- Neural Networks, learning algorithms
- Brain functions: computational neuroscience to model control systems, sensorimotor integrations and cognitive functions
Some examples will deal especially with the cerebellum circuit
Teaching methods
The course will be made up of lectures, integrated with seminars, hands-on laboratories with computational tools, and group discussions on scientific journal papers. Few specific seminars will be held by post-doc researchers from the lab: http://www-5.unipv.it/dangelo/
Reccomended or required readings
• Spitze, M. 2000. The Mind within the Net: Models of Learning, Thinking, and Acting Reprint Edition.
• Churchland, P.S. & Sejnowski T.J. 1994. The Computational Brain (Computational Neuroscience Series).
• Dayan, P. & Abbott, L.F. 2005. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems.
More details will be indicated during the course.
Assessment methods
The examination foresees written and oral parts
Further information
In the download area of the website “Psychology” section, the slides and materials used during the course will be made available.
Sustainable development goals - Agenda 2030