Dataset Information

Anytime collaborative brain-computer interfaces for enhancing perceptual group decision-making.

ABSTRACT: In this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

SUBMITTER: Bhattacharyya S

PROVIDER: S-EPMC8379268 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Anytime collaborative brain-computer interfaces for enhancing perceptual group decision-making.

Bhattacharyya Saugat S Valeriani Davide D Cinel Caterina C Citi Luca L Poli Riccardo R

Scientific reports 20210820 1

In this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves ...[more]

PMID: 34417494

Similar Datasets

Project description:The ability to make decisions based on external information, prior knowledge, and evidence is a crucial aspect of cognition and may determine the success and survival of an organism. Despite extensive work on decision-making mechanisms/models, understanding the effects of alertness on neural and cognitive processes remain limited. Here we use EEG and behavioral modeling to characterize cognitive and neural dynamics of perceptual decision-making in awake/low alertness periods in humans (14 male, 18 female) and characterize the compensatory mechanisms as alertness decreases. Well-rested human participants, changing between full-wakefulness and low alertness, performed an auditory tone-localization task, and its behavioral dynamics were quantified with psychophysics, signal detection theory, and drift-diffusion modeling, revealing slower reaction times, inattention to the left side of space, and a lower rate of evidence accumulation in periods of low alertness. Unconstrained multivariate pattern analysis (decoding) showed a ∼280 ms delayed onset driven by low alertness of the neural signatures differentiating between left and right decision, with a spatial reconfiguration from centroparietal to lateral frontal regions 150-360 ms. To understand the neural compensatory mechanisms with decreasing alertness, we connected the evidence-accumulation behavioral parameter to the neural activity, showing in the early periods (125-325 ms) a shift in the associated patterns from right parietal regions in awake, to right frontoparietal during low alertness. This change in the neurobehavioral dynamics for central accumulation-related cognitive processes defines a clear reconfiguration of the brain networks' regions and dynamics needed for the implementation of decision-making, revealing mechanisms of resilience of cognition when challenged by decreased alertness.SIGNIFICANCE STATEMENT Most living organisms make multiple daily decisions, and these require a degree of evidence from both the environment and the internal milieu. Such decisions are usually studied under sequential sampling models and involve making a behavioral choice based on sensory encoding, central accumulation, and motor implementation processes. Since there is little research on how decreasing alertness affects such cognitive processes, this study has looked at the cognitive and neural dynamics of perceptual decision-making in people while fully awake and in drowsy periods. Using computational modeling of behavior and neural dynamics on human participants performing an auditory tone-localization task, we reveal how low alertness modulates evidence accumulation-related processes and its corresponding compensatory neural signatures.

Dataset Information

Anytime collaborative brain-computer interfaces for enhancing perceptual group decision-making.

Publications

Anytime collaborative brain-computer interfaces for enhancing perceptual group decision-making.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets