Catalogo dei Corsi di studio

Students will be provided a solid background on the main techniques used to image the human brain in vivo, and of their application in the cognitive neuroscientific field; a critical view of the validity and the limits of knowledge on the human mind derived by the application of such methods; a set of practical abilities in planning and analyzing cognitive neuroimaging experiments; and a series of conceptual tools to personally and critically evaluate results obtained by research in the field of cognitive neuroimaging.

Knowledge and understanding: Students will understand the historical and conceptual foundations of cognitive neuroscience; will be able to fully appreciate the potentials and the limits of recording brain signals as a tool for understanding the functional architecture of the human mind; will know the basic technical characteristics of the main neuroimaging techniques; will master the main experimental paradigms employed in functional neuroimaging experiments; will understand the statistical foundations of data analysis as applied to neuroimaging data.

Applying knowledge and understanding: Students will become competent in planning and implementing cognitive tasks to be associated with neuroimaging techniques and research protocols for studying neurophysiological mechanisms underlying cognitive functions in clinical and pre-clinical fields and in the interpretation of imaging results, in designing full experiments, including the data analysis strategy, while avoiding common pitfalls and methodological problems.

Making judgements: Students will be able to read and fully understand papers in the cognitive neuroimaging literature and to critically evaluate their methods and conclusions, identifying their potential impact and conceptual and methodological issues.

Communication skills: Students will become competent in writing short project proposals and in presenting their proposals orally in a limited amount of time with the help of slides.

Learning skills: Students will develop instrumental and research skills useful for acquiring further knowledge.

Programma

The course provides an overview of the application of brain imaging methods to study human cognitive and sensorimotor processes and to identify neural architectures underlying normal and abnormal cognitive functioning. The main foundational and methodological issues, listed below, will be introduced and critically discussed during lectures, together with the presentation of typical findings and applications, with particular emphasis on the field of visual cognition:

1) Introduction: history of cognitive neuroscience and of neuroimaging techniques; basic conceptual foundations of cognitive neuroimaging.

2) Technological and physiological foundations of neuroimaging: cerebral metabolism, blood flow and oxygenation; positron emission tomography; (functional) magnetic resonance imaging; electro- and magneto-encephalography.

3) Experimental design in functional neuroimaging: cognitive subtraction; categorical, parametric, and factorial designs; block and event-related designs.

4) Data analysis in functional neuroimaging: preprocessing; general linear model; statistical inference; voxel- and ROI-based approaches; data-driven approaches.

5) Conceptual issues in neuroimaging: functional specialization vs. integration; relationship with computational models of mind functioning.

6) Structural neuroimaging: morphometry, structural connectivity, lesion-symptom mapping.

7) Advanced methods: adaptation and priming, pattern analysis, decoding, machine learning.

8) Connectomics: resting-state networks, psychophysiological interactions, dynamic causal modelling.

The laboratory consists in guided practical experience in visualizing, manipulating, and analyzing brain images, using MATLAB and widely used tools such as SPM, FieldTrip, and MRIcro, and will include: analysis of sample PET data; complete preprocessing and analyzing of a true single-subject fMRI dataset; complete preprocessing and analyzing of a true single-subject EEG dataset; analysis of lesional, morphometric and functional connectivity data; writing simple MATLAB scripts to automate processing steps.

Testi adottati

Teaching material is available on the course site on the Sapienza e-learning platform, and consists of slides, online resources, and scientific papers which either are publicly accessible or can be downloaded via the Sapienza digital library.

Prerequisiti

Students should be familiar with the gross neuroanatomy of the cerebral cortex (lobes, gyri, sulci, sensory and motor systems), and with basic neurophysiological concepts (neurons, synapses, circuits). Students should be also familiar with basic parametric statistics (t-test, ANOVA, regression).

Modalità di valutazione

The final evaluation will be based on three main scores:

1) an evaluation of the personal contribution of the student during the course (project presentations, discussion of others' projects, participation to laboratory activities): up to 10/30;

2) an evaluation of the final products presented by the student (final written project, artifacts produced during laboratory sessions): up to 10/30;

3) final exam: up to 10/30.

The final exam will take place in written form and will test the ability to apply learned concepts and methodologies to real research situations. It may consist of any combination of the following: 1) building a working experimental paradigm on the basis of an experimental hypothesis presented by the instructor; 2) designing a data analysis strategy based on an experiment presented by the instructor; 3) identifying potential theoretical and methodological issues in a neuroimaging experiment presented by the instructor.