ReviewJournal of neurophysiology2017
Interfacing to the brain's motor decisions.
Review in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03665493 (Dopamine Effect on Inhibitory Control), which is not on this map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Dopamine Effect on Inhibitory Control
Who cites it
19 citing papers in PubMed.
- Factor Analysis of the Neurological Evaluation Scale (NES) and Corresponding Brain Function and Structures.International journal of methods in psychiatric research · 2026Article
- Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges.Frontiers in human neuroscience · 2025Review
- Intracortical brain-computer interfaces in primates: a review and outlook.Biomedical engineering letters · 2023Review
- Representation and decoding of bilateral arm motor imagery using unilateral cerebral LFP signals.Frontiers in human neuroscience · 2023Article
- Strong evidence for ideomotor theory: Unwilled manifestation of the conceptual attribute in movement control.Frontiers in psychology · 2023Article
- Executive Functions in Decision Making under Ambiguity and Risk in Healthy Adults: A Scoping Review Adopting the Hot and Cold Executive Functions Perspective.Brain sciences · 2022Article
- Active Brain-Computer Interfacing for Healthy Users.Frontiers in neuroscience · 2022Article
- A brief review of motor imagery and bimanual coordination.Frontiers in human neuroscience · 2022Review
- Article
- Robustness of sex-differences in functional connectivity over time in middle-aged marmosets.Scientific reports · 2020Article
- EEG Changes in Time and Time-Frequency Domain During Movement Preparation and Execution in Stroke Patients.Frontiers in neuroscience · 2020Article
- Explainable Artificial Intelligence for Neuroscience: Behavioral Neurostimulation.Frontiers in neuroscience · 2019Article
- Decoding Movement From Electrocorticographic Activity: A Review.Frontiers in neuroinformatics · 2019Review
- Commentary: Injecting Instructions into Premotor Cortex.Frontiers in cellular neuroscience · 2018Article
- Unilateral Stimulation of Subthalamic Nucleus Does Not Affect Inhibitory Control.Frontiers in neurology · 2018Article
- Increasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface.Frontiers in neuroscience · 2018Article
- The Weight of Emotions in Decision-Making: How Fearful and Happy Facial Stimuli Modulate Action Readiness of Goal-Directed Actions.Frontiers in psychology · 2018Article
- Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.Frontiers in psychology · 2017Review
- EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors.Frontiers in neuroscience · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject's motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.