LEARNING OUTCOMES

Neuro-electronic interface modeling, transducers and measurement techniques for electrophysiology: in-vivo and in-vitro. Specific analysis techniques for neuronal electrophysiological signals. Problem of coding and transmission of information in neural systems.

AIMS AND LEARNING OUTCOMES

Modeling of the neuro-electronic interface: capability to model wet-wardware interface (circuital models)

Techniques for electrophysiology and applications: ability to develop and use an experimental set-up from micro-to-macro (Micro Electrode Arrays; EEG)

Analysis techniques for neuronal signals: understanding algorithms for signal analysis; ability to implement algorithm for point-process and (introduction) time series.

Code of information and information transmission: ability to focus on the main issue about neural code and information transmission (connectivity and dynamics)

PREREQUISITES

Fundamental of chemistry, biophysics, mathematics, electronics and computer science provided during the first three years of the Laurea in Biomedical Engineering.

TEACHING METHODS

Combination of traditional lectures (40 hours) and classroom discussion of the scientific paper presentations selected by each student (10-15 hours).  Lab activities - optional (8 hours)

SYLLABUS/CONTENT

Modeling of the neuro-electronic interface: theoretical models of the solid-liquid interface; polarizable and not polarizable interface; Microtransducers and electrophysiological techniques; Micro Electrode, Silicon Transistors, Organic Transistors.
Techniques for electrophysiology and applications: in-vitro and in-vivo electrophysiology, intra-cellular and extracellular measurements, patch clamp; single cell recordings, network electrophysiology.
Analysis techniques for neuronal signals: spike and burst detection algorithms; statistical analysis and multiple spike train analysis (ISI, J-ISI, C-ISI, IBI); cross-correlation analysis; functional connectivity
Code of information and information transmission: neuronal input-output response; information theory applied to neuronal signals; entropy and mutual information; neuronal avalanches and self-organized criticalities.

RECOMMENDED READING/BIBLIOGRAPHY

• Bioelectronics: MOSFETs, biosensors, neurons, M. Grattarola e G. Massobrio, McGraw -Hill, (1998)
• Principle of applied Biomedical instrumentation, Geddes and Baker, Wiley Interscience ed., 1989.
• Electrodes and the measurements of bioelectric events, Ed. by L.A. Geddes, Wiley Interscience Pub., 1972.
• SPIKES: exploring the neural code, Riecke, Warland, de Reuyter van Steveninck, Bialek, MIT press, 1997.
• Bayesian Brain: probabilistic approaches to neural coding, Ed. By K. Doya, S. Ishii, A. Pouget, R.P.N. Rao,, MIT Press 2007
• Toward Replacement Parts For The Brain: Implantable Biomimetic Electronics As Neural Prostheses, T. Berger, D. Glanzman eds, MIT press 2005