C9001 - Neural Cognition (LM)

Learning outcomes

This course will provide an accessible but highly challenging overview of the empirical evidence, theories and methods in cognitive neuroscience exploring how cognition is instantiated in neural activity. At the end of the course, students will be able to: I) Understand how cognitive, emotional, and social processes emerge from neural mechanisms, ranging from the cellular to the system level; II) Critically evaluate neuroscientific research, including its methods, findings, and limitations; III) Develop the ability to draw connections across cognitive neuroscience, psychology, computational modeling, and evolutionary theory; iv) Critically reflect on the societal and ethical implications of neural and cognitive research.

Course contents

The course is delivered during the second teaching period (2027) and is organized into four successive and integrated modules. Together, the modules offer a coherent overview of cognitive neuroscience, progressing from the neural mechanisms of learning, to the foundations of social cognition, the role of memory in imagining the past and future, and finally to contemporary theories that conceptualize the brain as a predictive system.

Module 1: The Learning Brain (Giuseppe di Pellegrino)

· Cognitive neuroscience: A brief introduction

· Neuron structure and function

· From neurons to networks: sensory, motor, and associative circuits

· Synaptic plasticity and Hebbian learning

· Supervised, unsupervised, and reinforcement learning

· Biological vs. machine learning paradigms

Module 2: The Social Brain (Alessio Avenanti)

· Neural systems underlying social interaction

· Theory of mind and empathy

· Mirror neuron system

· Neural bases of moral decision making

· Group dynamics: ingroup vs. outgroup processing

Module 3: The Time-Traveling Brain (Elisa Ciaramelli)

· Memory as mental time travel

· Episodic memory and future thinking

· The neural bases of episodic simulation

· The psychological function of episodic simulation

· The social communication of episodic memory

Module 4: The Predictive Brain (Vincenzo Romei)

· Perception as an active inference process

· The evolutionary advantage of prediction

· The brain as a prediction engine

· Neural correlates of perceptual decision making

· Adaptive vs. maladaptive predictions

Prerequisites

Students are expected to have high-school level knowledge of the anatomy and physiology of the nervous system.

It is recommended to view the videos on Neuroscience Core concepts, freely available at the Society for Neuroscience website: https://www.brainfacts.org/core-concepts

 

 

Readings/Bibliography

Scientific papers and other course materials will be made available through the course website. All assigned readings are mandatory and are required for the successful completion of the final examination.

Teaching methods

Teaching consists of lectures supplemented by multimedia materials, including PowerPoint presentations and videos. The course also includes interactive presentations and guided discussions of scientific papers and current research topics in cognitive neuroscience. As active participation is an integral part of the learning experience, attendance is strongly recommended.

Assessment methods

The final examination is designed to assess students' knowledge and understanding of the theoretical and methodological foundations of neural cognition.

The examination consists of four open-ended questions, one for each module. Each question is graded on a 30-point scale. The final grade (expressed out of 30) is calculated as the average of the four individual scores. The examination duration is 80 minutes.

The highest mark (30/30) is awarded to students who demonstrate a thorough knowledge of the course content and the ability to reason critically and flexibly about the topics covered, providing precise, comprehensive, and well-structured answers to all questions. A final mark of 30 cum laude is awarded only to students who receive a score of 30 on each of the four questions. Based on the correctness, completeness, and clarity of the answers, marks may range from 18/30 to 30/30.

During the examination, the use of any supporting materials, including textbooks, notes, and electronic devices (e.g., tablets, smartphones, smartwatches), is not permitted. The use of AI tools for assessment purposes is prohibited. Any use of such tools constitutes a violation of academic integrity.

Students must register for the examination through the AlmaEsami platform within the published deadlines. Students who are unable to register due to technical problems must promptly notify the Teaching Office (and, in any case, before the registration deadline) and send an email to Giuseppe di Pellegrino (g.dipellegrino@unibo.it). Admission to the examination under these circumstances is at the discretion of the course instructor.

Teaching tools

Teaching support materials include PowerPoint presentations, scientific papers and review articles, which are used in conjunction with lectures and collective discussions throughout the course.

Office hours

See the website of Giuseppe Di Pellegrino

See the website of Alessio Avenanti

See the website of Elisa Ciaramelli

See the website of Vincenzo Romei