Biology subjects

Garner, K. G.

Publications and source records attributed to Garner, K. G..

4 recordsLinked to original sources

bioRxiv2026

Towards the definition and measurement of routines and the cognitive processes that underpin their maintenance

The benefits of routines for daily functioning are widely acknowledged, yet, despite their apparent importance, methods for quantifying routine maintenance and the causes of their disruption remain lacking. Here, we propose a novel means of defining and quantifying routines (transition entropy). Using the transition entropy, we show that routines can be robustly elicited on tasks that require searching through a grid of squares for a hidden target. Over two experiments (N=100 each), we show that use of routines---as quantified by transition entropy---is robustly perturbed by frequent switches between search grids, as locations specific to the currently irrelevant grid become competitive for selection. Using a normative model that tracks task dynamics, we show that disruption to routines can be attributed to reduced sensitivity to the odds of success for completing a task. This suggests that routine maintenance may be disrupted by over-sensitivity to a lack of reward early in routine performance, or increased expectations regarding the utility of pursuing other tasks.

neuroscience↗

bioRxiv2023

Stimulating prefrontal cortex facilitates training transfer by increasing representational overlap

Difficulties in multitasking may be the price humans pay for our ability to generalise learning to new tasks. Mitigating these costs through training has been associated with reduced overlap of constituent task representations within a task-related brain network. Transcranial direct current stimulation (tDCS), which can modulate neural activity, has shown promise in generalising training gains. Whether tDCS influences the changes in task-associated representations to produce such training generalisation remains unexplored. Here, we paired prefrontal cortex tDCS with multitasking training, and collected functional magnetic resonance imaging data pre- and post- training. We found that 1mA tDCS enhanced visual search performance, and using machine learning to assess the overlap of brain activity related to the training, show that these generalised gains were predicted by changes in classification accuracy for patterns of frontal, parietal, and cerebellar activity in participants who received left prefrontal cortex stimulation. Thus, prefrontal cortex tDCS interacts with training related changes in task representations, potentially driving the generalisation of learning.

neuroscience↗

bioRxiv2022

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

neuroscience↗

bioRxiv2017

Distinct selection mechanisms for when predictions and rewards guide visual selective attention

How does the brain combine information predictive of the value of a visually guided task (incentive value) with information predictive of where task relevant stimuli may occur (spatial certainty)? Human behavioural evidence indicates that these two predictions may be combined additively to bias visual selection (additive hypothesis), whereas neuroeconomic studies posit that they may be multiplicatively combined (expected value hypothesis). We sought to adjudicate between these two alternatives. Participants viewed two coloured placeholders that specified the potential value of correctly identifying an imminent letter target if it appeared in that placeholder. Then, prior to the targets presentation, an endogenous spatial cue was presented indicating the targets more likely location. Spatial cues were parametrically manipulated with regards to the information gained (in bits). Across two experiments, performance was better for targets appearing in high versus low value placeholders and better when targets appeared in validly cued locations. Interestingly, as shown with a Bayesian model selection approach, these effects did not interact, clearly supporting the additive hypothesis. Even when conditions were adjusted to increase the optimality of a multiplicative operation, support for it remained. These findings refute recent theories that expected value computations are the singular mechanism driving the deployment of endogenous spatial attention. Instead, incentive value and spatial certainty seem to act independently to influence visual selection.

neuroscience↗