OVERVIEW

The aim of the course is to introduce the state-of.the art in the field of neural-interfaces. Hardware interfaces (neuro-electronic systems); techniques for measuring the electrophysiological activity of excitable cells and tissues; analysis techniques for neuronal signal analysis (from micro-to-macro; from patch-clamp to EEG). Introduction to functional connectivity (connectome) and interplay between connectivity and dynamics (dynome). Introduction to code of information in neuronal systems and brain-machine-interface (BMI).

AIMS AND CONTENT

LEARNING OUTCOMES

• Fundamentals for designing microtransducer for neural interfaces.
• Operative abilities in the use of lab instruments for electrophysiological recordings.
• Design and implementation of software tools for neuronal signal analysis.
• Analysis of experimental neuronal data.

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 

TEACHERS AND EXAM BOARD

Exam Board

SERGIO MARTINOIA (President)

PAOLO MASSOBRIO

ROBERTO RAITERI

LESSONS

Class schedule

NEUROENGINEERING AND NEUROTECHNOLOGIES

EXAMS

EXAM DESCRIPTION

Public presentation of a selected Journal Paper on arguments related to the course. Presentation by two students are encouraged. Written exam oreinted to the solution of specific problem-exercise and theoretical questions.

ASSESSMENT METHODS

The exam is constituted by the study and presentation of a scientific paper and by an additional written and oral examination.

Exam schedule

FURTHER INFORMATION

Office: Via All’Opera Pia 11 A
Lab: Neuroengineering and Neurotechnologies, Via All’Opera Pia 13 (level -1)