| Unit name | Foundations of Neuroscience |
|---|---|
| Unit code | MEDIM7001 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Academic Year (weeks 1 - 52) |
| Unit director | Dr. Whitcomb |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | Bristol Medical School |
| Faculty | Faculty of Health Sciences |
In this Unit, students are introduced to several fundamental subjects in neuroscience, including Neuroanatomy; Neurophysiology and neurotransmission; Sleep; Perception and cognition; Neuroplasticity; Stem cells; Brain imaging; and Animal models in neuroscience.
In addition to these core subjects, students will also receive training in practical and transferable skills, including Research design and statistical analysis; Finding research information by using the library and internet; Reading, interpreting and presenting research results; and scientific writing.
The Aims and objectives of this Unit are to:
(i) Introduce students to the field of neuroscience by exploring a broad range of foundational subjects, thereby preparing students with varied backgrounds for subsequent course units;
(ii) Help students develop their fundamental knowledge of brain structure and function and the major areas of research within the neurosciences;
(iii) Introduce students to the basics of statistical analysis to prepare them for data management and interpretation during the research project unit;
(iv) Help students develop skills in experimental design, including the application of appropriate statistical analyses.
(v) Help students develop expertise in reading, interpreting and presenting research results and scientific writing.
At the end of this unit the student will be able to:
(i) Discuss the principal ideas that underly the fundamental areas within the field of neuroscience.
(ii) Describe and explain some of the statistical analysis approaches that are most frequently used within neuroscience, and apply that knowledge within the context of research design.
The student will also have gained experience in:
(a) Essay writing
(b) Presenting a research paper in a Journal Club.
This Unit has a blended approach to teaching, and is therefore taught through a mixture of in-person taught sessions, structured online learning sessions, and self-directed learning. The sessions in this Unit include lectures, tutorial(s), workshop(s), practical, student presentation and self-directed study.
The Unit is assessed through a summative 2,000-word essay (100%). A formative stage consisting of individual feedback on a 500-word draft essay is included in the writing process.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MEDIM7001).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
