PYMDCN: Gathering Data in Cognition and Neuroscience

Module code: PYMDCN

Module provider: Psychology; School of Psych and Clin Lang Sci

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 1

Module convenor: Mr Nicholas Hedger, email: n.hedger@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: Yes

Last updated: 23 May 2024

Overview

Module aims and purpose

The purpose of this module is to provide students with working knowledge of research in the field of cognitive neuroscience, and practical experience of gathering and analysing fMRI and EEG data. The module interweaves lectures and hands-on experience about data gathering, processing and analysis, with a focus on robust, open and reproducible methods (including scripting of analyses on shared cloud computing infrastructures). Students will familiarise themselves with each step of typical processing pipelines, learn how to script and automate analyses, and be introduced to the best practices in reproducible neuroimaging. Students enrolling on this module should be confident and competent with Undergraduate level statistics and possess general computing skills (for more information see Outline Content).

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Demonstrate a deep understanding of the two most common methods cognitive neuroscience, fMRI and EEG, including the theoretical and practical aspects related to the recording and analysis of brain signals, and current issues and debates related to reproducibility;
2. Explain the steps involved in the pipeline that permits the recording of brain signals in fMRI and EEG, and carry out EEG recording using scientific-grade equipment;
3. Select, explain and apply appropriate analytical pipelines to the analysis of fMRI and EEG signal in a robust and reproducible way.

Module content

The module covers the main mechanisms of brain functioning and current debates involved in the analysis of fMRI and EEG data at both theoretical and practical levels. Topics covered include neuroanatomy, cognitive neuroscience, the physics of MRI and EEG, what each technique actually measures, pre-processing, modelling and analysis of fMRI and EEG data. PYMDCN is designed to provide students with working knowledge of the recording and the statistical analysis of fMRI and EEG data, for students who are likely to need the transferrable skills of analysing such complex datasets in the future (not necessarily neuroimaging data).

We strongly advise you to only select this module if you are confident and competent with Undergraduate level statistics, and possess general computing skills: specifically, the module reviews the steps required to process and analyse data, the theory and application of inferential statistics (i.e. GLM, t-tests) and the scripting (coding) of reproducible analytical pipelines. If you are unsure, please carefully review the module description and/or contact the Module Convenor for guidance.

Structure

Teaching and learning methods

The module is divided into two parts, one covering EEG and the other fMRI. Theoretical content about the brain and the statistical analysis of neuroimaging data is delivered by a lecture, followed by practical workshops using equipment in the Centre for Integrative Neuroscience & Neurodynamics to record data and the University cloud computing infrastructure to analyse data. Example data sets and the final coursework relate to healthy brain functioning.

Study hours

At least 80 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Throughout the module, students will have the opportunity to partake in individual and group tasks, which will be reviewed and discussed orally during the sessions, such as creating a cheatsheet about the analyses, creating a poster describing typical pipelines of analysis or formative quiz style of exercises.

Reassessment

Additional costs