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Record W3015161228 · doi:10.5287/ora-r52yj5qwa

The interaction of COMT genotype, tolcapone and acute stress, on brain activity and working memory performance

2019· dissertation· en· W3015161228 on OpenAlexaboutno aff
Marieke Martens

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2019
Typedissertation
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyWorking memoryNeuroscienceCognitive psychologyCognition

Abstract

fetched live from OpenAlex

An inverted-U-shaped relationship exists between dopamine and prefrontal cortex (PFC) dependent cognitive function, whereby either too little or too much dopamine signalling impairs cognitive performance. Genetic, pharmacological, pathological, and environmental factors can affect a person’s position on the curve. In this thesis I explored three of such factors and their potential interactions. Interestingly, an inverted-U relationship also exists between acute stress and PFC-dependent cognitive performance, with moderate stress levels facilitating, and high levels impairing cognitive function. The enzyme catechol-O-methyltransferase (COMT) metabolises dopamine in the PFC. The human COMT gene contains a functional polymorphism (Val158Met) that influences enzyme activity: the ancestral COMT-Val allele has ~40% greater activity than the COMT-Met allele. COMT activity can also be altered pharmacologically by inhibitors, like tolcapone. Previous research showed that COMT Val158Met affects the functional connectivity of the PFC at rest and linked the COMT-Met allele with better PFC-dependent performance. Moreover, COMT genotype and tolcapone interact, with the drug having opposite effects on cognition in COMT-Met and COMT-Val homozygotes. The goal of this DPhil project is to extend these findings. In particular, there is evidence that stress also impacts dopamine signalling, and some indication that it interacts with COMT. However, it is unknown whether this interaction is modulated by COMT inhibition by tolcapone. First, two stressors were explored, - a novel VR stressor and the Montreal Imaging Stress Task (MIST). Both induced a physiological and psychological stress response, however with a different magnitude and duration. The MIST induced a stronger and longer lasting physiological response, whilst the VR lift seemed to induce higher subjective ratings of stress and anxiety. The main study of this thesis was a randomised, double-blind, placebo-controlled, between-subjects study of the effects of COMT genotype and tolcapone and their interaction, on behaviour and patterns of brain activity using MRI. I demonstrate that COMT and tolcapone influence cerebral blood flow, resting state functional connectivity, stress sensitivity and working memory related brain activation and performance. However, the majority of my findings are not compatible with a ‘simple’ inverted-U model, whereby stress acts only to increase central dopamine levels and thereby enhance (baseline) performance in COMT-Val homozygotes, and impair it in COMT-Met homozygotes. In future it would be of interest to further study these inverted-Us by investigating how different forms of PFC dependent cognitive functions are affected by different kinds of stressors. However, these relationships are complicated by the fact that some of the cognitive effects of stress are likely mediated by non-dopaminergic mechanisms, the context dependency of the different inverted-U relationships, the stress response not being a unitary concept, and the need for multidisciplinary approaches and falsifiable hypotheses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.280
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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