Biology subjects

Gilmour, W.

Publications and source records attributed to Gilmour, W..

3 recordsLinked to original sources

bioRxiv2025

Focused ultrasound neuromodulation of mediodorsal thalamus disrupts decision flexibility during reward learning

When learning to find the most beneficial course of action, the prefrontal cortex guides decisions by comparing estimates of the relative value of the options available. Basic neuroscience studies in animals support the view that the thalamus can regulate this activity within and across the prefrontal cortex. We studied a group of patients (n=37) undergoing unilateral MR guided focused ultrasound for essential tremor, performing the restless bandit, a reward reinforcement learning task, immediately before and after thalamotomy. Thalamotomy significantly impaired the proportion of switch choices during the task without affecting overall performance. This effect was observed when the task was delivered to co-incide with maximal vasogenic thalamic oedema but not in a control group tested on the same day of their treatment. A reinforcement learning model fitted to the patients choices replicated the effect of thalamotomy when the model increased exploitation of the bandits learnt value estimate. This shift in the explore-exploit trade-off, manifesting as reduced choice flexibility, co-varied with the pattern of post-operative oedema extension into mediodorsal nucleus. These findings confirm a causal role of the thalamus and specifically the mediodorsal nucleus, in regulating the extent to which value estimates are used to guide decisions and learning from reward.

neuroscience↗

bioRxiv2025

A Study of Calibration as a Measurement of Trustworthiness of Large Language Models in Biomedical Research

ObjectivesTo assess the calibration of 9 large language models (LLMs) within biomedical natural language processing (BioNLP) tasks, furthering understanding of trustworthiness and reliability in real-world settings. Materials and MethodsFor each LLM, we collected responses and corresponding confidence scores for all 13 datasets (grouped into 6 tasks) of the Biomedical Language Understanding & Reasoning Benchmark (BLURB). Confidence scores were assigned using 3 strategies: Verbal, Self-consistency, Hybrid. For evaluation, we introduced Flex-ECE (Flexible Expected Calibration Error): a novel adaptation of ECE that accounts for partial correctness in model responses, allowing for a more realistic assessment of calibration in language-based settings. Two post-hoc calibration techniques--isotonic regression and histogram binning--were evaluated. ResultsAcross tasks, mean calibration ranged from 23.9% (Population-Intervention-Comparison-Outcome extraction) to 46.6% (Relation Extraction). Across LLMs, Medicine-Llama3-8B had the best mean overall calibration (29.8%); Flan-T5-XXL had the highest ranking on 5/13 datasets. Across strategies, self-consistency (mean: 27.3%) had better calibration than Verbal (mean: 42.0%) and Hybrid (mean: 44.2%). Post-hoc methods substantially improved calibration, with best mean calibrated Flex-ECEs ranging from 0.1% to 4.1%. DiscussionThe poor out-of-the-box calibration of LLMs poses a risk to trustworthy deployment of such models in real-world BioNLP applications. Calibration can be improved post-hoc and is a recommended practice. Non-binary metrics for LLM evaluation such as Flex-ECE provide a more realistic assessment of trustworthiness of LLMs, and indeed any model that can be partially right/wrong. ConclusionThis study shows that out-of-the-box calibration of LLMs is very poor, but traditional post-hoc calibration techniques are useful to calibrate LLMs.

bioinformatics↗

bioRxiv2023

Impaired value-based decision-making in Parkinson's Disease Apathy

Apathy is a common and disabling complication of Parkinsons disease characterised by reduced goal-directed behaviour. Several studies have reported dysfunction within pre-frontal cortical regions and projections from brainstem nuclei whose neuromodulators include dopamine, serotonin and noradrenaline. Work in animal and human neuroscience have confirmed contributions of these neuromodulators on aspects of motivated decision making. Specifically, non-dopaminergic neuromodulators, influence decisions to explore alternative courses of action or persist in an existing strategy to achieve a rewarding goal. Building upon this work, we hypothesised that Apathy in Parkinsons disease should be associated with a failure to adequately monitor and make adaptive choices when the rewarding outcome of decisions are uncertain. Using a 4-armed restless bandit reinforcement learning task, we studied decision making in 75 volunteers; 53 patients with Parkinsons disease, with and without clinical apathy, and 22 age matched healthy controls. Patients with Apathy exhibited impaired ability to choose the highest value bandit. Task performance predicted an individual patients apathy severity measured using the Lille Apathy Rating scale (R = -0.46, p<0.001). Computational modelling of the patients choices confirmed the apathy group made decisions that that were indifferent to the learnt value of the options, consistent with previous reports of reward insensitivity. Further analysis demonstrated a shift away from exploiting the highest value option and a reduction in perseveration which also correlated with apathy scores (R = -0.5, p<0.001). We went on to acquire fMRI in 59 volunteers; a group of 19 patients with and 20 without apathy and 20 age matched controls performing the restless bandit task. Analysis of the fMRI signal at the point of reward feedback confirmed diminished signal within ventromedial prefrontal cortex in Parkinsons disease, which was more marked in Apathy, but not predictive of their individual Apathy severity. Using a model-based categorisation of choice type, decisions to explore lower value bandits in the apathy group activated pre-frontal cortex to a similar degree to the age-matched controls. In contrast, Parkinsons patients without apathy demonstrated significantly increased activation across a distributed thalamo-cortical network. Enhanced activity in the thalamus predicted individual apathy severity across both patient groups and exhibited functional connectivity with dorsal anterior cingulate cortex and anterior insula. Given that task performance in patients without apathy was no different to the age-matched controls, we interpret the recruitment of this network as a possible compensatory mechanism, which compensates against symptomatic manifestation of apathy in Parkinsons disease.

neuroscience↗