Course Catalogue

Hormones and Behaviour VETSCI3012

  • Academic Session: 2026-27
  • School: School of Biodiversity One Health Vet Med
  • Credits: 30
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

This course examines the effects of hormones on behaviour in animals. Therefore, the class will consider how genes and hormones influence the development and activation of behavioural/cognitive abilities; with a focus on sex differences. The meaning of 'gender', as applied in the course, will be discussed and defined. Topics will include the effects of hormones on sexual differentiation, reproductive behaviour, parental behaviour, physiological stability and biological rhythms, regulation of body weight, learning and memory. The general approach of this class is integrating studies from rodents to birds, and primates to humans, to formulate a comprehensive picture of the current research field. A major goal of the class is to evaluate past and current literature culminating with prospective experiments for future investigations as well as highlight the ethical use and short comings of generative AI for this purpose. Each class is divided into two sections. The first consists of a lecture based on the selected weekly topics. The lecture will provide the necessary background information while emphasizing the current research directions and questions. The lecture will be followed by student oral presentations. The student presentations are based on an assigned article that reveals recent insight into the topic covered that week.

Timetable

Weekly lectures and tutorials (oral presentations), practical sessions for data analysis.

Requirements of Entry

Students must have attained the minimum requirements for entry into level 3 of the Veterinary Biosciences [Hons]/MSci Programme as specified in the Veterinary Biosciences [Hons]/MSci Programme Supplementary Regulations.

Excluded Courses

None

Co-requisites

None

Assessment

End of course assessment (30%): Written exam (30%) - may consist of multiple choice questions, short answer questions and/or data interpretation questions.

 

Report 1 (10%) - Critically evaluate an essay written by artificial intelligence (e.g., Chatgpt).

 

Set exercise (20%) - A science communication project that communicates a scientific publication to the general public. The output could be in the form of a newspaper article, (v)Blog (or similar online media), or video clip.

 

Oral presentation (20%) - An oral presentation on one scientific publication.

 

Report 2 (20%) - A report on a study that examines differences in brain and behaviour. Report consists of data collection and evaluation.

Main Assessment In: April/May

Course Aims

■ To provide an overview of the bidirectional relation of hormone and behavioural interactions

■ To outline how sex differences are established at multiple levels of biological organisation

■ To outline how the brain is a mosaic, composed of sex differences along a spectrum

■ To give an overview of the ways hormones change the probability and intensity of behaviour

■ To provide insights into how behaviour can change hormone action

■ To overview the endogenous rhythms in hormone-behaviour relations

■ To develop the ability to retrieve, critically appraise and discuss i) appropriate peer reviewed research literature and ii) output from generative AI models

Intended Learning Outcomes of Course

By the end of this course students will be able to:

Knowledge:

1. Describe how sex differences are created and establish variation in gender

2. Explain how hormones change behaviour and how behaviour feedback regulates hormones

3. Explain how the brain controls behaviour and is modified by hormone signalling pathways

4. Critically evaluate scientific publications in relation to neuroscience and endocrinology

5. Describe how social behaviour is modified by hormones and experience

 

Skills:

6. Demonstrate analytical skills and interpretation of data

7. Critically examine outputs of generative AI

8. Demonstrate an ability to communicate science to a lay audience

Minimum Requirement for Award of Credits

No exceptions