Experimental Neurobiology

Course manual 2025/2026

Course content

During this course, students will get hands-on experience with various commonly used research methods in the field of neuroscience and learn to critically evaluate the (dis)advantages of each of these techniques for answering specific research questions.

Topics that will be addressed are:

• neuronal activity and neuronal communication;
• (comparative) brain anatomy;
• animal behaviour test;
• molecular techniques;
• immunohistochemistry;
• electrophysiology;
• microscopy;

Students will learn more about these topics by means of seminars given by specialists in the field, practical work (in the lab as well as behind the computer), lab tours, written assignments and presentations.

Study materials

Literature

• Recent review, book chapters  and research articles are the base of lectures and practicals. These are announced on Canvas.

Syllabus

• The course syllabus, including instruction to perform the activities included in this course, is made available on Canvas

Practical training material

• All the materials necessary to perform the practical activities included in this course are provided by the course organization.

Software

• The software required to perform the practical "Neurons in action" is provided by the course organization.

Objectives

• Explain where neuronal activity originates and how neurons communicate
• Recognize the major (sub)anatomical structures in the (mammalian) brain and explain their main function(s)
• Execute basic experiments using different tasks commonly used in behavioural and translational neuroscience
• Critically evaluate a variety of research paradigms, ranging from molecular biology to behavioural tasks
• Critically evaluate published research
• Understand ethical aspects and best practices for research in behavioural and translational neuroscience
• Understand the difference between conceptualisation and operationalisation of variables used in behavioural neuroscience
• Create a valid, innovative research proposal related to topics addressed in the course
• Assess the appropriate use of large language models for research and learning in neurobiology

Teaching methods

• Lecture
• Seminar
• Computer lab session/practical training
• Self-study
• Working independently on e.g. a project or thesis
• Supervision/feedback meeting

Introductory lectures, (computer) practicum, lab practicals and site visits (Netherlands Institute for Neuroscience)

Learning activities

Attendance

Assessment

Inspection of assessed work

Contact your supervisor to make an appointment for inspection.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Additional information

Use of GenAI

Within the Research Master Brain and Cognitive Sciences, you are allowed to use Generative AI (GenAI) to support your learning process. For example, you can use large language models (LLMs) to help your self-study by generating flashcards, or generating explanations of concepts. GenAI should be a support tool to help you reach the course's learning objectives, not a system you delegate activities to that are meant to promote your learning. The course examiner has final say on which use cases are permissible or not within their course.

You may not use GenAI to create any content you submit for assessment, regardless of whether it's graded numerically or on a pass/fail basis. The only exception is if an assignment description explicitly allows GenAI use. In such cases, permissible use is delineated by the course instructor.

Never share personal information, research data, or course materials with a GenAI system, except for UvA AI Chat. This UvA-hosted system was built with GDPR compliance and data security in mind. If in doubt about sharing information, don't share. You can always check with your course coordinator whether any intended use case is responsible.

Teachers are never allowed to use GenAI to grade your work. They may, however, use it to formulate their feedback.

Course-specific pilot

This particular course is part of a pilot experiment in which the deliberate use (or non-use) of GenAI by students is self-reported and discussed during plenary sessions with the whole cohort. Each week, you will fill in a brief form to reflect on any GenAI use. This information will be used to inform both course development within MBCS and, together with other pilots, overall GenAI policy at UvA.

Course-specific rules on GenAI use

Within this specific course, permissible GenAI use is limited to:

• Use of UvA AI Chat (http://aichat.uva.nl)
• Supporting your self-study (e.g. by summarising articles, testing your understanding or generating explanations). Be mindful that information provided by any large language model, including UvA AI Chat, may be erroneous. Always question output and, if in doubt, bring your questions to class.
• Get feedback on written assignments before submission. Please note that you remain accountable for any work that you submit, so make sure you understand and support any feedback that you use. Allowing GenAI use for feedback presupposes that you first went through steps like ideation, analysis or structuring arguments without technological assistance. By first doing the deep thinking yourself, your learning becomes better.
• Writing your research proposal. See Canvas for more specific instructions: you are asked to maintain an AI Journal which you will submit at the end of the course. This AI Journal is different from the GenAI diary mentioned above.

Last year's student feedback

In order to provide students some insight how we use the feedback of student feedback to enhance the quality of education, we decided to include the table below in all course guides.

Contact information

Coordinator

• Carlos Fitzsimons