SYSTEMS NEUROSCIENCE I - PERCEPTION
Introduction. Naturalism in the philosophy of science/philosophy of mind (S. Tsinorema)
Causality in scientific explanation-Mental causation (S. Tsinorema)
Introduction to the philosophy of language (S. Tsinorema)
Introduction to philosophy of mind - Substance dualism (K. Frankish)
Behaviourism - Identity theory (K. Frankish)
Functionalism - The representational theory of Mind (K. Frankish)
Eliminativism - The problem of Consciousness (K. Frankish)
Property dualism - Physicalist theories of consciousness (K. Frankish)
Introduction to the philosophy of science (K. Frankish)
Introduction to the phenomenological philosophy of mind (F. Vassiliou)
Philosophy of perception. Introduction: Direct vs indirect realism. The argument from hallucination (M. Venieri)
Direct realism: Disjunctivism, enactive perception, representationalism (M. Venieri)
Indirect realism: Sense data theory, adverbialism. Virtual reality: Philosophical aspects (M. Venieri)
Introduction to computational neuroscience and Matlab Primer 1: Vectors and Matrices, Variance and Covariance, Plotting, Randomness, M-files and functions (E. Hourdakis)
Matlab primer 2: Basic mathematical methods: Ordinary differential equations, PCA, convolution, correlation, built-in libraries and toolboxes (E. Hourdakis)
The single neuron model - computational capacity and relative problems, transfer function (E. Hourdakis)
Attractor networks and neural oscillators (E. Hourdakis)
Supervised learning, gradient descent, local extrema (E. Hourdakis)
Other learning methods. Association learning, Hebb's rule, reinforcement learning (E. Hourdakis)
Problem formulation, data collection and analysis, phase-plane analysis and mutual information, signal-to-noise ratio (E. Hourdakis)
Abstract neuron models FitzHugh–Nagumo model, IF, Izhikevich (I. Chitzanidi)
Neural coding. Local/rate coding, population codes, tuning curves, poisson neurons (E. Hourdakis)
Biophysical neuron models .Cable theory, HH equations, compartmental models (P. Poirazi and associates)
The Neuron simulator (P. Poirazi and associates)
Synaptic plasticity, adaptation and learning (P. Poirazi and associates)