Neuropsychology Kent
Tina Popielarczyk
Studying Psychology at postgraduate level gives you the opportunity to delve into the methodological and theoretical issues that are considered important in the study of cognitive/neuropsychology. Examine the relationship between brain and mind through the learning about vision, learning and emotion.
Examine how cognitive psychological, neuropsychological, neurobiological and computer science approaches can be combined to understand how the human mind/brain solves a variety of complex problems, such as recognising objects, remembering previous experiences, reading, speaking and reasoning.
Build on existing knowledge, abilities and skills by developing both in basic and advanced contemporary statistical and methodological issues in psychology. While studying the relationship between brain and mind, through the understanding of vision, learning, memory, language and memory. Preparing you for doctoral study, an academic career or a job in the NHS as a psychologist/assistant.
Conducting both basic and applied research in several areas, Psychology at Kent is highly regarded as a leading European centre for postgraduate research. Our long-established international reputation in social psychology is complemented by our strengths in cognitive, developmental and forensic psychology. We attract excellent visiting scholars and postgraduate students from both within the UK and overseas.
Some of our PhD students are self-funded, and others are funded by grants or awards either from the School, UK or their countries of origin. Some are also paid to undertake part-time teaching within the School. We have a strong track record of attracting ESRC research studentship funding, which involves partnerships with external organisations such as Age UK and the Equality and Human Rights Commission and collaborative studentships with partners such as People United.
Therefore, your existing degree transcript should note that you have taken and passed a minimum of one term each in statistics and social science research methods courses (or two terms of a joint statistics and research methods course). A British Psychological Society-accredited degree will likely meet this requirement. Applicants with other degrees may be asked to provide additional evidence of training in statistics.
Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.
The modules below are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.
This module provides a postgraduate-level orientation to essential contemporary statistical and methodological issues. Students will learn techniques typically used for research in psychology and other disciplines that use sampling statistics. The methodological issues considered include qualitative research methodologies; experimental, quasi-experimental, and correlational research designs in the laboratory and field; and issues surrounding the replicability and reporting of research. The statistical techniques taught include univariate and multivariate descriptive and inferential statistics; ANOVA as a form of general linear model; correlation and linear multiple regression; and nonparametric tests such as chi-square.
This module provides a postgraduate-level orientation to advanced statistical issues in predictive models with a one-variable outcome. Students will learn techniques typically used for research in psychology and other disciplines that use sampling statistics, which ultimately depend on a common basis of linear modelling that follows a complex evolution into multiple specific applications. These may include: moderation with interactions involving ordinal variables; mediation models using regression; connections between linear models and traditional ANOVA approaches; factorial ANOVA, ANCOVA, repeated and mixed ANOVA; and multilevel modelling. The teaching assumes recent experience with basic statistical concepts, software, and tests which will be provided by a prerequisite module.
The course provides a coherent base for understanding the methodological and theoretical issues that are currently considered important in the study of cognitive psychology and neuropsychology. Students will be shown how to critically appraise the philosophical and theoretical underpinnings of the various disciplines that comprise cognitive psychology and neuropsychology, and to evaluate how these disciplines may successfully be combined to further scientific understanding of the core problems in cognitive psychology and neuropsychology today. A selection of material from areas such as vision, learning, memory, language, reasoning, emotion will be referred to in order to examine the relationship between brain and mind, the modularity of brain and mind, and the notion of different levels/frameworks of description and explanation.
This module provides students with an understanding of academic research and an ability to identify and utilise appropriate strategies and techniques for the purpose of individual investigation, research and practice within a subject specific area of their course route. The module guides students through appropriate research and/or data collection to ensure that they have the source material required to write their dissertation. This module will prepare students to undertake the dissertation module in Stage 2 of their course, including matching students with supervisors and ensuring that their proposal is satisfactory to reach the required level of independent thought in their dissertation project.
This module provides a postgraduate-level foundational course in Psychometrics, also known as 'test theory' or 'theory of psychological tests and measurements'. It is intended primarily for students of psychology and any other field of social science where test are constructed or used, but also for students with a mathematics/statistics background interested in psychometric testing. The module introduces students to the main quantitative concepts, methods, and computational techniques needed for the informed use, development, evaluation, and application of tests in the behavioural/social sciences, including educational tests. The course begins with describing fundamental properties and levels of measurement, and some models and methods for 'scaling' an attribute. Fundamental concepts of Classical Test Theory such as 'true score' and 'error of measurement' are considered, and key techniques needed for evaluating reliability and validity of test scores are studied. Factor analysis is studied in depth as a fundamental technique to evaluate the number and structure of attributes the test measures. Factor analytic methods are extended to binary and ordinal test items, and Item Response Theory methods are introduced including Rasch scaling. With these foundations, psychometric applications from various fields of behavioural studies are considered, and it is demonstrated how the choice of scaling method can have implications for substantive conclusions.
This module provides a postgraduate-level foundational course in multivariate modelling, with a particular focus on applications in psychology, public health and education. It is intended primarily for students of psychology and any other field of social science where relationships between multiple observations on humans and other subjects are of interest, but also for students with a mathematics/statistics background interested in such applications. With foundations taught in the pre-requisite module, PSYC8013 Psychometrics, 'measurement by modelling' is formally introduced using a Structural Equation Modelling (SEM) framework. Within this framework, specific techniques such as path analysis, confirmatory factor analysis, basic longitudinal analysis and multiple-group analysis are taught. Data analysis applications from various fields of psychological studies are considered, and it is demonstrated how to model/test statistically complex phenomena such as spurious and indirect effects, growth and change, measurement invariance, and others.
This module will provide you with a wide-ranging, detailed and critical overview of neuropsychological theories of ageing. It will draw on evidence from healthy and pathological ageing, incorporating cognitive and neuroscientific research. The curriculum will focus on theories of cognitive ageing, presenting evidence sourced using a range of cognitive psychological and neuropsychological methods. It will include detailed neuropsychological profiles of pathological ageing conditions such as Alzheimer's Disease, Frontotemporal Dementia and Parkinson's Disease, allowing you to compare and contrast how specific neural changes attributable to disease processes result in different cognitive deficits. We will also discuss clinical considerations when working with older adults, demonstrating how research informs clinical practice. Finally, the module will introduce the notion of "successful ageing" and you will critically evaluate the evidence for lifestyle factors such as diet, sleep, exercise, and mental stimulation.
The central theme of this module will be to explore how cognition functions in the real world, that is, to investigate the application of cognitive models to the broader context of human behaviour. Possible topics for study include: the role of cognition in development, emotion, memory and action; applications to eyewitness testimony, intentional forgetting and embodied cognition. Practical applications and relevance to a general understanding of behaviour will be emphasised throughout.
This module will provide students with theoretical instruction and practical experience in some key advanced research methods appropriate for scientific research in cognitive (neuro)psychology. The study of cognitive processes and the temporal nature of brain activity will feature highly in this module.
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