Non-invasive BCI for Cognitive Enhancement

NCT ID: NCT05311878

Last Updated: 2025-04-24

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 32 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-01-01
• Study Completion Date: 2023-11-01

Brief Summary

People's perceptual skills can significantly affect their abilities to make optimal decisions, judgments, and actions in real-world dynamic environments. Perceptual learning refers to training and experiences to induce improvements in the ability to make sense of what people see, hear, feel, taste or smell based on ambiguous sensory information. In this study, investigators hypothesise that there exist neural signatures that robustly encode the conscious visual perception of rotations of a cursor and the magnitudes of these rotations in a novel, rotation-based perceptual learning task. Investigators also hypothesise that online, instantaneous EEG-based feedback on subjects' visual perceptions of rotations with an EEG-based Brain Computer Interface (BCI) can foster perceptual learning much more effectively than behaviour perceptual training, especially in very small rotation magnitudes that represent extremely difficult perceptual tasks.

Conditions

Healthy Subjects; Neuropsychiatric Disorders

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

EEG based perceptual training

Subjects complete a perceptual learning task in which EEG-based visual feedback is provided

Group Type: EXPERIMENTAL

EEG-based perceptual training

Intervention Type: DEVICE

Electroencephalography (EEG) signals will be recorded from subjects as they perform rotation-based perceptual tasks. The neural correlates of conscious perception of rotations will be processed and decoded in real-time using machine learning algorithms to provide feedback. Subjects are instructed to assume a mental state/find a strategy to maximise the accuracy of feedback. In total, each subject will complete 5 sessions of perceptual training with this intervention.

Behavior based perceptual training

Subjects complete a perceptual learning task in which ground truth visual feedback is provided

Group Type: ACTIVE_COMPARATOR

Behavior based perceptual training

Intervention Type: DEVICE

Subjects complete the rotation-based perceptual tasks, and ground truth visual feedback is provided indicating whether subjects have spotted the rotations correctly. Subjects are instructed to spot as many rotation as possible to maximise the accuracy of feedback. In total, each subject will complete 5 sessions of perceptual training with this intervention.

Interventions

EEG-based perceptual training

Electroencephalography (EEG) signals will be recorded from subjects as they perform rotation-based perceptual tasks. The neural correlates of conscious perception of rotations will be processed and decoded in real-time using machine learning algorithms to provide feedback. Subjects are instructed to assume a mental state/find a strategy to maximise the accuracy of feedback. In total, each subject will complete 5 sessions of perceptual training with this intervention.

Intervention Type: DEVICE

Behavior based perceptual training

Subjects complete the rotation-based perceptual tasks, and ground truth visual feedback is provided indicating whether subjects have spotted the rotations correctly. Subjects are instructed to spot as many rotation as possible to maximise the accuracy of feedback. In total, each subject will complete 5 sessions of perceptual training with this intervention.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

Able-bodied volunteers:

• good general health
• normal or corrected vision
• no history of neurological/psychiatric disease
• ability to read and understand English
• ability to understand information and ability to give a free and informed consent

Subjects with neuropsychiatric diseases

• Subjects with neuropsychiatric diseases such as bipolar disorder and schizophrenia.
• normal or corrected vision
• ability to read and understand English
• ability to understand information and ability to give a free and informed consent

Exclusion Criteria

• short attentional spans or cognitive deficits that prevent to remain concentrated during the experimental sessions
• concomitant serious illnesses (e.g., metabolic disorders, cardiac arrest)
• factors hindering proper EEG acquisition (e.g., scalp wound, uncontrolled muscle activity)

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Texas at Austin

OTHER

Sponsor Role: lead

Responsible Party

Jose del R. Millan

Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Jose del R. Millan, PhD

Role: PRINCIPAL_INVESTIGATOR

The University of Texas at Austin

Locations

Engineering Education and Research Center

Austin, Texas, United States

Countries

United States

Other Identifiers

2020030073_p2

Identifier Type: -

Identifier Source: org_study_id