Cognitive Genetics and Cognitive Therapy Group
Our work in cognitive genetics has focused on characterising the effects of genetic variants linked to risk for psychosis on brain structure and function. Aspects of brain structure, such as brain volume and white matter integrity, and brain functions, such as cortical activations that occur during information processing are likely to mediate the effects of genetic variants on illness. In what’s often described as an intermediate or 'endophenotype' approach, studying these brain based ‘phenotypes’ may help bring us closer to the mechanism of gene activity so as to understand the broader illness phenotype. To do this our work draws on neuropsychological, electrophysiological, and neuro-imaging techniques for investigating the role of gene function at the level of individual brain systems.
Our research is focussed on the key question: how do genes increase risk for psychosis? To address this question we are studying the effects of recently identified psychosis risk genes on brain structure and brain function. Identifying and charactiersing how neural systems are affected by risk genes can tell us much about the neurobiology of the psychosis, a key requirement for the development of new treatments. Two recent developments in this work include focusing on risk genes effects on aspects of social cognition, and communication or ‘connectivity’ between brain regions.
1. Social cognitive neuroscience
Disability in schizophrenia (SZ) results from, and is predicted by, deficits in social cognition that are not targeted by current treatments. Targeting these deficits is challenging because the underlying neural mechanisms are poorly understood. The purpose of our research into this area is twofold: (1) to delineate patterns of abnormal activations within cortical and sub-cortical regions during performance of social cognition tasks; (2) to comprehensively evaluate the impact on social cognition of common and rare genetic variation contributing to the genetic architecture of schizophrenia and related phenotypes. Investigating the biology of social cognition in SZ patients rather than simply in healthy participants is relatively novel for our field. Moreover, analysis of imaging data on patients and controls collected here, together with our existing behavioural social cognition data and genome data, uniquely positions us to establish the effects of risk variants on social cognition at the level of behaviour, cortical activation, and neuroanatomy.
2. Neural Connectivity
Neural connectivity has recently been proposed as an intermediate phenotype for schizophrenia. In the CogGene lab, we are examining the effects of specific schizophrenia risk variants on:
1. Structural connectivity: the white matter tracts connecting different parts of the brain
2. Functional connectivity: the correlation of activity between different parts of the brain
3. Effective connectivity: the effect of one group of neurons on another
To carry out this research, we are using diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), with analysis techniques including DTI tractography, psychophysiological interactions (PPI) and dynamic causal modelling (DCM). Characterising the effects of these variants on neural networks has the potential to further elucidate the mechanisms by which they increase risk, which may guide future treatment strategies.
Diffusion tensor imaging of white matter tracts in the brain
Research Volunteers needed
For details on how to participate in our research please click 'Volunteers Needed'.
1. Neuropsychological Assessment
Measures of neuropsychological ability, including general cognitive ability (IQ), memory, and attention have been extensively used to investigate variance in cognition in both health controls and patients. This provides a relatively simple and cost-effective strategy for measuring the effects of individual genes on cognition in large numbers of individuals.
2. Electrophysiological Tests
The use of high density EEG to study variance in sensory information processing, both at early and late processing stages involves a non-invasive measurement of electrical impulses picked up by scalp electrodes. This approach allows mili-second accuracy in recording brain responses to visual and auditory stimuli.
3. Neuroimaging Approaches
This involves the use of MRI for a wide range of purposes, including measurement of grey and white matter density, white matter integrity (DTI), and functional MRI (fMRI). Collectively, these approaches provide millimetre accuracy in investigating the influence of individual genes on brain structure and function.
| Book Chapters |
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| Journal Articles |
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| Book Reviews |
| Donohoe G. Book Review: ‘Genes brain and Development. The neurocognition of genetics disorders. In Neuropsychological rehabilitation, 2010. 20(5) 798-799. |
| Non-Peer reviewed |
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| Conference Proceedings |
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Rose, E.J., Hargreaves, A., Morris, D.W., Fahey, C., Gill, M., Corvin, Rose, E.J., Greene, C., Morris, D.W., Fahey, C., Robertson, I., Garavan, Rose, E.J., Mothersill, O., Greene, C., Kelly, S., Morris, D.W., Fahey, O'Donoghue, T; Morris, Dw; Fahey, C; Da Costa, A; Foxe, Jj; Hoerold, D; Gill, M; Corvin, A; Donohoe, G. The Nos1 Variants Rs6490121 Previously Associated With Both Schizophrenia And Poorer Cognitive Performance Also Influences Early Visual Processing In Healthy Participants Irish conference of Medical Genetics, Belfast, 2011.
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Details on current vacancies are available on the trinity college vacancies website at: www.tcd.ie/vacancies
The work of the CogGene lab is generously sponsored by Science foundation Ireland, the Higher Education Authority (Ireland), the Wellcome trust, and NARSAD.
Brain images constructed using MRIcroGL (http://www.mccauslandcenter.sc.edu/mricrogl/).
Gary Donohoe, Associate Professor in Clinical Neuropsychology, Group Leader
Derek Morris, Assistant Professor of Molecular Psychiatry
Ken OReilly, Lecturer in Clinical Psychology
Craig Chigwedere, Lecturer in CBT
Emma Jane Rose, Research Fellow
Deepa Pal, Research Fellow
April Hargreaves, PhD Student
Sinéad Kelly, PhD Student
Omar Mothersill, PhD Student
Rachel Dillon, PhD Student
Ana McLaughlin, PhD Student