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4 results for “multi-alternative”
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
<p>There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: 1) a positive distractor effect predicts high-value distractors improve decision-making; 2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalisation.</p>
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
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Data from: Multi-alternative decision making with non-stationary inputs
One of the most widely implemented models for multi-alternative decision-making is the multihypothesis sequential probability ratio test (MSPRT). It is asymptotically optimal, straightforward to implement, and has found application in modelling biological decision-making. However, the MSPRT is limited in application to discrete ('trial-based'), non-time-varying scenarios. By contrast, real world situations will be continuous and entail stimulus non-stationarity. In these circumstances, decision-making mechanisms (like the MSPRT) which work by accumulating evidence, must be able to discard outdated evidence which becomes progressively irrelevant. To address this issue, we introduce a new decision mechanism by augmenting the MSPRT with a rectangular integration window and a transparent decision boundary. This allows selection and de-selection of options as their evidence changes dynamically. Performance was enhanced by adapting the window size to problem difficulty. Further, we present an alternative windowing method which exponentially decays evidence and does not significantly degrade performance, while greatly reducing the memory resources necessary. The methods presented have proven successful at allowing for the MSPRT algorithm to function in a non-stationary environment.
Data from: Multi-alternative decision making with non-stationary inputs
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.