Module: Computational Psychiatry

Module Specifications.

Current Academic Year 2024 - 2025

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Date posted: September 2024

Module Title	Computational Psychiatry
Module Code	PSY1102 (ITS) / PSY1102 (Banner)
Faculty	Science & Health	School	Psychology
Module Co-ordinator	-
Module Teachers	-
NFQ level	8	Credit Rating	5
Pre-requisite	Not Available
Co-requisite	Not Available
Compatibles	Not Available
Incompatibles	Not Available

Coursework Only

Description

The aim of this module is to present the student with key theoretical and empirical sources to support their understanding of how computational methods combine with a variety of data types to identify and understand neural differences, predict behaviour and effectively treat clinical disorders.

Learning Outcomes

1. Demonstrate an understanding of how differing computational methods combine with a variety of data types to identify and understand neural differences, predict behaviour and effectively treat clinical disorders
2. Demonstrate a critical appreciation of current cutting edge research in cognitive neuroscience and computational psychiatry
3. Demonstrate competency in theory-driven and data-driven approaches either separately or in combination to understand or predict behaviour
4. Demonstrate an understanding in how experimental design and environmental manipulation/control contribute to the field of computational neuroscience and psychiatry

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	24	Lecture Based on indicative content and learning outcomes
Seminars	11	Post Lecture Moderator and student-led tutorials
Tutorial	4	Companion Tutorials Moderator and student-led tutorials
Independent Study	86	Self directed learning including exam preparation
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Computational Psychiatry - Understanding, Predicting and Targeting Candidate Treatments
Developmental and Lifespan aspects; Candidate endophenotypes; Biomarkers. Theory driven versus data driven approaches to modelling behaviour.

Machine Learning: Computational Modelling

Typical and atypical decision-making

Theoretical Issues in Computational Psychiatry

Dimensions of functioning in human behaviour

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Assignment	Critical Review/Journal Critique: This assessment will assess students' ability to critically evaluate state-of-the-art approaches in the field (theory-driven or data-driven methods) for elucidating clinical disorders.	50%	n/a
In Class Test	MCQs and short form answers addressing LOs	50%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories: Resit category 1: A resit is available for both* components of the module. Resit category 2: No resit is available for a 100% continuous assessment module. Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 1

Indicative Reading List

Alan Anticevic, John D Murray eds: 2018, Computational Psychiatry: Mathematical Modeling of Mental Illness., Academic Press,
Anderson, Britt: 2014, Computational Neuroscience and Cognitive Modelling A Student's Introduction to Methods and Procedures, SAGE,
Busemeyer, J. R., & Diederich, A: 2010, Cognitive Modelling, SAGE,
Lee, M. D., & Wagenmakers, E. J.: 2014, Bayesian cognitive modeling: A practical course, Cambridge University Press.,
Peggy Series: 2020, Computational Psychiatry: A Primer., MIT Press,
Randall O’Reilly: 2020, Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain., MIT Press,

Other Resources

None