87996 - Physics in Neuroscience and Medicine

Course Unit Page

  • Teacher Claudia Testa

  • Learning modules Claudia Testa (Modulo 1)
    Leonardo Brizi (Modulo 2)

  • Credits 6

  • SSD FIS/07

  • Teaching Mode Traditional lectures (Modulo 1)
    Traditional lectures (Modulo 2)

  • Language English

  • Campus of Bologna

  • Degree Programme Second cycle degree programme (LM) in Physics (cod. 9245)

  • Course Timetable from Feb 28, 2023 to May 02, 2023

    Course Timetable from May 05, 2023 to May 30, 2023

Academic Year 2022/2023

Learning outcomes

At the end of the course the student will have the knowledge of important physical principles and experimental procedures applied to medical diagnosis and scientific research in medicine. Particular attention will be devoted to nuclear magnetic resonance (NMR) relaxometry, diffusometry, spectroscopy and imaging and their combination, along with more traditional techniques (CT, PET, EEG, MEG, NIRS). The student will also learn about advanced diagnostic techniques for neuroscience, based on morphological and functional images, which are the instruments for brain function and connectivity research. He/she will be able to use software for planning pulse sequences and simulate the results of NMR experiments and for data inversion in one and two dimensions (T1, T2, self-diffusion coefficient). Moreover magnetic resonance neuroimaging data will be analyzed in a practical tutorial, simulating a post processing session.

Course contents

Physical basis of Nuclear Magnetic Resonance (NMR). Time Domain NMR (TD-NMR) - Relaxometry and Diffusometry: characterization of relaxation times (T1 and T2) and self-diffusion coefficient (D). Bloembergen, Purcell, Pound theory (BPP Theory). Magnetic Resonance for fluids in Porous Media: surface effects, relaxation times in porous materials and in biological tissues. Inversion from data time domain to relaxation times - UPEN algorithm and UpenWin software. Basis of two-dimensional NMR: relaxation-relaxation, relaxation-exchange and diffusion-relaxation. Single-sided NMR: basic concepts of MR in the constant field gradient of a portable NMR device (MOUSE PM10), profiles and examples of in-situ application.

NMR Spectroscopy- Chemical shift and J-coupling. NMR imaging (MRI) - k-space and k-space mapping. Time diagrams for NMR and MRI experiments. Multi-dimensional experiments. NMR for fluids under confinement. Ex-situ experiments by means of portable NMR devices. Relaxation times in biological tissues. Apparent diffusion coefficients and diffusion tensor. In vivo Magnetic Resonance Spectroscopy- Post processing - relative and absolute quantification. Single voxel (SV) and Chemical shift Imaging. Heteronuclear spectroscopy. Diffusion weighted/Diffusion Tensor imaging. Tractography, whole brain tractography. Structural connectivity. Functional MRI - Block design - Resting state fMRI. Functional connectivity by fMRI and fNIRS. Multi-modal imaging - combination of MRI, CT, PET, MEG, EEG. Practical tutorials on inversion from data time domain to relaxation times by means of UPEN algorithm and UpenWin software in one and two dimensions. Practical tutorials simulating post processing sessions. Examples of applications in medicine, neuroscience and in the field of fluids in porous media.


The Human Central Nervous System, Nieuwenhuys, Rudolf, Voogd, Jan, Huijzen, Christiaan van. 2008. Springer

Callaghan, Principles of MRMicroscopy

In Vivo NMR Spectroscopy: Principles and Techniques, 2nd Edition Robin A. de Graaf

Diffusion MRI- Hedi Johansen-Berg-Timothy E.J. Berg Elsevier

Functional Magnetic Resonance Imaging. An Introduction to Methods Edited by Peter Jezzard, Paul M Matthews, and Stephen M Smith

MRI: The Basics- 2017, Ray H Hashemi, CJ Lisanti, WG Bradley. Wolters Kluwer

Scientific papers suggested during lessons.

Teaching methods

Frontal lessons. Supplementary exercises are proposed during the lessons to be solved in groups and discussed during class. Part of the course (module 2) consists in practical exercises. NMR data will be acquired and processed using dedicated softwares.

Assessment methods

The final exam will be an oral exam to test the students' acquired knowledge. The exam will begin with a discussion about the reports made by the students on topics faced during the frontal lessons. The compilation of reports will require the comprehension and the use of algorihms and software dedicated to data analyses. After this discussion, the exam will continue on at least two other topics concerning the rest of the program. The total duration of the exam will be about 45 minutes. The knowledge of these topics and the assessment of the use of a pertinent scientific speech will be considered as an excellent score.

Teaching tools

Pc, video projector, softwares and laboratory instruments.

Office hours

See the website of Claudia Testa

See the website of Leonardo Brizi