Training and Research

PhD school courses/classes - 2024/2025

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

1. PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, instructions will be sent well in advance. No confirmation e-mail will be sent after signing up. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS

Credits: 2

Language: English

Teacher:  Luigina Mortari

DOTTORATO E MERCATO DEL LAVORO: WORKSHOP FORMATIVI PER DOTTORANDI E NEO-DOTTORI DI RICERCA

Credits: 4

Language: Italian
ARE YOU SURE YOU CAN DEFEAT A CHATBOT?

Credits: 1

Language: Italian
MEETING UKRAINE: THE IMPACT OF WAR AND FUTURE OPPORTUNITIES

Credits: 1

Language: Italian
OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE

Credits: 2

Language: English

Teacher:  Michele Scandola

Differential diagnosis of demyelinating diseases of the central nervous system

Credits: 2

Language: Italiano; English

Teacher:  Alberto Gajofatto

CSF DYNAMICS: ANATOMICAL AND FUNCTIONAL FEATURES

Credits: 0.5

Language: Italiano Eventualmente inglese

Teacher:  Alberto Feletti

Tecniche di immagine per l'analisi della composizione corporea

Credits: 1

Language: Inglese/English

Teacher:  Carlo Zancanaro

Tecniche di ricerca in neuroscienze: misurare e modulare l'attività neuronale

Credits: 2.3

Language: non prevista

Teacher:  Giuseppe Busetto

COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING

Credits: 4.5

Language: English

Teacher:  Matteo Bertucco

EMOTIONS, BELIEFS, AND SKILLS TO FACE CLIMATE CHANGE AND EMBRACE CLIMATE ACTION

Credits: 0.5

Language: English

Teacher:  Isolde Martina Busch

sleep related disoders: focus on REM and NREM parasomnia and SR movement disorders

Credits: 1.5

Language: italiano o inglese

Teacher:  Elena Antelmi

COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING  (2024/2025)

Teacher

Matteo Bertucco

Referent

Matteo Bertucco

Credits

4.5

Language

English

Class attendance

Free Choice

Location

VERONA

MoodleMoodle Seminars 0

Learning objectives

Motor learning has traditionally focused on how predictive or feedforward control is updated by past errors and has generally assumed that adaptation is driven by a single process, that variability is undesirable, and that learning, and control are shaped by a trade-off between speed and accuracy. The course will review recent research that examined how learning shapes both predictive and reactive control mechanisms and has shown that adaptation involves multiple, interacting processes, that the motor system tunes variability to the learning task, and that accuracy is not necessarily gained at the expense of speed. Course contents: - Skills acquisition in sensorimotor learning - Variability in sensorimotor learning - Reward in sensorimotor learning - Bayesian processing in sensorimotor learning.

Interested students must apply at the following link (application deadline is April 30, 2025):
https://forms.gle/MuPgafo3W6UbJpZc8

Prerequisites and basic notions

Bases of muscle neurophysiology and motor control

Program

Motor learning has traditionally focused on how predictive or feedforward control is updated by past errors and has generally assumed that adaptation is driven by a single process, that variability is undesirable, and that learning, and control are shaped by a trade-off between speed and accuracy. The course will review recent research that examined how learning shapes both predictive and reactive control mechanisms and has shown that adaptation involves multiple, interacting processes, that the motor system tunes variability to the learning task, and that accuracy is not necessarily gained at the expense of speed.
Course contents:
- Skills acquisition in sensorimotor learning
- Variability in sensorimotor learning
- Reward in sensorimotor learning
- Bayesian processing in sensorimotor learning

Bibliography

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Didactic methods

The teacher will use:
a) Lecture-style instruction
b) Group style activity through the discussion of scientific articles related to the topics covered during lectures.

Learning assessment procedures

The full attendance (100%) at the course will be required to obtain the CFU.
There will not be a final assessment for the course.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

The full attendance (100%) at the course will be required to obtain the CFU.
There will not be a final assessment for the course.

Criteria for the composition of the final grade

There will not be a final assessment for the course.

Scheduled Lessons

When Classroom Teacher topics
Friday 23 May 2025
10:00 - 12:30
Duration: 2:30 AM 		Palazzo ex ISEF - AULA SEMINARI (ex aula presidenza) [ - terra] Matteo Bertucco Lecture 1
Friday 23 May 2025
13:45 - 16:45
Duration: 3:30 AM 		Palazzo ex ISEF - AULA SEMINARI (ex aula presidenza) [ - terra] Matteo Bertucco Lecture 2
Friday 30 May 2025
08:30 - 16:50
Duration: 8:00 AM 		Palazzo ex ISEF - AULA D [ - 1] Matteo Bertucco Collaborative journal club sessions