Course - Neural Networks - NEVR3004
NEVR3004 - Neural Networks
About
Examination arrangement
Examination arrangement: School exam
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 4 hours | D |
Course content
Neural data analysis and network models of brain functions are the primary focus of this course. We will review current computational models and how these models continue to develop together with experiments to further our understanding of the brain. The lectures will include the following topics:
- Principles of single neuron models: from point neurons to Hudgkin-Huxley
- Network models of memory: Hopfield Network, Attractor Networks of Spiking neurons, Balanced Networks
- Models of grid cells: Continuous attractor models and single neuron models
- Neural Coding: Information theory, role of correlated activity
The course involves writing an essay based on one of the topics covered in the course, or a topic agreed with the course coordinator. The essay must be written in the style of an academic article, reviewing the chosen topic, its historical development in relation to experiments, and also discussing at least one result (from published literature) related to the topic but not covered in the course.
The essays are due at the end of the course. The essay will be evaluated as pass/fail. The grade for the course will be determined from a written exam.
Learning outcome
After successfully passing the course, the student will be able to:
- understand the role of quantitative approaches to neural data analysis and neural modelling.
- think critically about theories and outstanding issues in the field of theoretical neurosciences.
- approach relevant methods and theories that are useful for his/her field of research.
- understand the relationship between major theoretical concepts in neuroscience and experimental data.
- grasp the historical steps taken for the development of major themes in theoretical.
Learning methods and activities
The course is taught in the second half of the spring semester. The language of teaching and evaluation is English. This course has restricted admission. Students admitted to the MSc in Neuroscience are guaranteed a seat. Other students must apply for a seat by the given deadlines.
The course will consist of a set of lectures and a teacher assistant will be available during the semester at times to be determined together with the students.
In addition to the final exam an essay on one aspect of the course (of the students choosing) must be submitted.
This course has restricted admission. Students admitted to the MSc in Neuroscience are guaranteed a seat. Other students must apply for a seat by the given deadlines.
Compulsory assignments
- Essay
Further on evaluation
Obligatory assignment: Essay.
Approved essay is a requirement for the students to take the final written exam. Approved obligatory assignment essay is valid for two academic years
Specific conditions
Limited admission to classes. For more information: https://i.ntnu.no/wiki/-/wiki/English/Admission+to+courses+with+restricted+admission
Compulsory activities from previous semester may be approved by the department.
Recommended previous knowledge
NEVR2010 (Introduction to neuroscience) or equivalent background. Familiarity with preliminary concepts in mathematics (see e.g. appendices A1 and A2 of the book Neural Networks and Brain Function by Rolls and Treves) or the book Cerebral Cortex by Edmund Rolls
Required previous knowledge
Limited admission to classes.
Compulsory activities from previous semester may be approved by the department
Course materials
To be announced.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| NEVR3030 | 7.5 |
No
Version: 1
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: SPRING 2023
Extraordinary deadline for course registration: 2022-12-01
Language of instruction: English
Location: Trondheim
- Computer and Information Science
- Neuroscience
- Biology
- Philosophy
- Physics
- Informatics
- Chemistry
- Medicine
- Psychology
Department with academic responsibility
Kavli Institute for Systems Neuroscience
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn UTS School exam 100/100 D 2022-12-10 15:00 INSPERA
-
Room Building Number of candidates - Spring ORD School exam 100/100 D INSPERA
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"