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Dr Rick Adams
Centre for Medical Image Computing
Dept of Computer Science
1st floor, 90 High Holborn
London
-- UK --
WC1V 6LJ
Dr Rick Adams profile picture
Appointment
  • Research Fellow
  • Mental Health Neuroscience
  • Division of Psychiatry
  • Faculty of Brain Sciences
Biography

I did a Medicine and Neuroscience BSc at Cambridge University and Clinical Medicine at UCL. 

I worked as a medical and psychiatric doctor from 2004-10, obtaining my MRCP and MRCPsych. 

From 2009-10 I did an MSc in the Philosophy of Mental Disorder at KCL. 

From 2010-14, I did my PhD at the Wellcome Centre for Human Neuroimaging at UCL, supervised by Prof Karl Friston. 

From 2014-18, I was an NIHR Clinical Lecturer in Psychiatry at UCL (Division of Psychiatry and Institute of Cognitive Neuroscience), in Prof Jon Roiser's group. 

In 2016 I took up a Bogue Fellowship to study at Yale University in Dr Alan Anticevic's group. I've also enjoyed fruitful collaborations with Prof Oliver Howes (KCL, Imperial), Prof Neil Burgess (UCL) and Prof Mark Edwards (St. George's). 

From 2018-22 I was an MRC Skills Development Fellow in Prof Janaina Mourao-Miranda's group in the Dept of Computer Science and Max Planck UCL Centre for Computational Psychiatry and Ageing Research. 

I am currently a Future Leaders Fellow in the Institute of Cognitive Neuroscience (Division of Psychiatry) and Centre for Medical Image Computing (Dept of Computer Science).


From 2016-21 I was a member of the Gatsby/Wellcome Neuroscience Project, whose goal is to update the neuroscience content of the training curriculum for psychiatrists in the UK.  


Since 2014 I have co-organised (with Dr Xiaosi Gu – now at Mount Sinai, NYC) the UCL Computational Psychiatry Course: the first such course in the world. It provides a 2 day introduction to the computational modelling of behaviour in psychiatric research, and the slides and audio of past lectures are online here: 

http://www.cpcourse.org


Research Summary

I use Computational Psychiatry to understand schizophrenia and the psychosis spectrum. Computational models can link biological, social and psychological accounts of mental function and dysfunction in a mathematically rigorous way (Adams et al., 2016, JNNP).


There may be two major biological pathologies in schizophrenia: 

i) dysfunction of NMDA receptors, which may be compensated by interneuron downregulation, causing disinhibition and loss of 'SNR' in higher hierarchical areas such as prefrontal cortex and hippocampus.

ii) increased synthesis and release of dopamine in the striatum.


I use models of brain function to understand how these changes might contribute to schizophrenia and psychosis. Examples include:


i) Modelling perception, action & cognition: 

The brain may perform (or approximate) Bayesian inference on the causes of its sensory data (e.g. by updating top-down predictions with bottom-up prediction errors). Imprecise prior beliefs could cause various phenomena in schizophrenia (Adams et al., 2013, Front Psychiatry). Altered circuit properties could also affect belief stability and 'noise' in decision-making (e.g. in the ‘beads’ task; Adams et al., 2018, J Neurosci), and delusions could arise due to habitual and affective influences on a noisy cognitive system (Adams et al, 2021, Schiz Res). 


ii) Modelling imaging data:

Dynamic causal modelling (DCM) uses biophysical models of imaging data to estimate e.g. E/I in different brain areas. We found increased E/I in prefrontal cortex in schizophrenia (Ranlund, Adams, et al., 2016, Hum Brain Mapp) and decreased coupling between hippocampus and mPFC (Adams et al., 2020, Brain).


iii) Mapping behavioural models on to the brain:

Are our models of behaviour instantiated in the brain? We have tested whether behavioural model parameters correlate with E/I parameters from M/EEG data (Adams et al., 2016, Neuroimage) or dopamine 2/3 receptor availability from PET data (Adams et al., 2020, Cereb Cortex). 


iv) Discovering new psychosis phenotypes:

I have collaborated with Dr Alan Anticevic (Yale) in using DCM on large functional imaging datasets to try to understand excitatory and/or inhibitory neuron pathology in schizophrenia (Adams et al., 2022, Biol Psych), presented here: www.quentinhuys.com/tcpw/events/rick-adams/ 

My next project (2022-) aims to use both DCM and machine learning methods (applied to M/EEG data) to infer excitatory and inhibitory neuron pathology in individuals with schizophrenia and thus better target glutamatergic treatments early on in the disorder.


Google Scholar: https://bit.ly/33gpNdv

Semantic Scholar: https://bit.ly/2U1Q3nU

Teaching Summary

As of 2020, I have supervised 5 PhD projects, 10 Masters projects, 2 BSc projects and 3 visiting scholar projects at UCL. 5 of the BSc/Masters projects were awarded distinctions. If you are interested in undertaking a Computational Psychiatry PhD at UCL, most PhD students come from the schemes below. PSYCHIATRY NEEDS APPLICANTS FROM DIVERSE BACKGROUNDS – DON'T HESITATE TO EMAIL ME IF YOU'D LIKE ADVICE!


UCL-Birkbeck MRC Doctoral Training Programme: 

www.ucl.ac.uk/mrc-dtp/research-themes


UCL-Wellcome Mental Health PhD: 

www.ucl.ac.uk/mental-health/study/ucl-wellcome-4-year-phd-mental-health-science


UCL Institute of Mental Health PhD programme:

www.ucl.ac.uk/mental-health/phd-studentship-opportunities 


UCL-NIMH Joint Doctoral Training Program in Neuroscience:

www.nimh.nih.gov/labs-at-nimh/scientific-director/office-of-fellowship-and-training/nimh-ucl-graduate-neuroscience-program/index.shtml


Max Planck-UCL Computational Psychiatry PhD programme:

https://www.mps-ucl-centre.mpg.de/news/press-information/new-doctoral-programme-of-the-max-planck-ucl-centre-for-computational-psychiatry-and-ageing-research


Leverhulme Doctoral Training Programme for the Ecological Study of the Brain:

ecologicalbrain.org


London Interdisciplinary Doctoral Programme (LIDo, BBSRC)

lido-dtp.ac.uk 


Gatsby UCL PhD Programme:

http://www.gatsby.ucl.ac.uk/teaching/phd/index.html


UCL CoMPLEX PhD programme:

www.ucl.ac.uk/complex


If you are interested in learning more about Computational Psychiatry, I highly recommend the following resources:

cmod4mh.com

www.translationalneuromodeling.org/cpcourse

mitpress.mit.edu/books/computational-psychiatry

www.sciencedirect.com/book/9780128098257/computational-psychiatry

Appointments
01-MAY-2022 – 01-MAY-2026 Future Leaders Fellow ICN & CMIC University College London, United Kingdom
31-JUL-2018 – 31-JUL-2021 MRC Skills Development Fellow CMIC, Dept of Computer Science UCL, United Kingdom
01-APR-2018 – 31-JUL-2021 Affiliate Member Wellcome Centre for Human Neuroimaging Institute of Neurology, UCL, United Kingdom
01-APR-2018 – 31-JUL-2018 UCLH BRC Postgraduate Research Fellow Division of Psychiatry UCL, United Kingdom
01-MAR-2014 – 01-MAR-2018 NIHR Clinical Lecturer in Psychiatry Institute of Cognitive Neuroscience & Division of Psychiatry University College London, United Kingdom
13-SEP-2010 – 28-FEB-2014 Clinical Research Associate Wellcome Trust Centre for Neuroimaging Institute of Neurology, United Kingdom
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