Enhancing Attention in Elderly Using a Brain-Computer-Interface
ConditionMild Cognitive Impairment (MCI)
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-90
SponsorUniversity of Texas at Austin
About this trial
Cognitive reserve refers to the brain's ability to maintain cognitive performance despite age-related changes or neuropathology. Enhancing cognitive reserve is thought to delay cognitive decline and improve functional outcomes in aging and neurodegenerative conditions. Attention and memory-related neural processes are considered key contributors to cognitive reserve, yet it remains unclear whether these neural markers can be deliberately strengthened through targeted training and non-invasive interventions.
The goal of this clinical study is to investigate whether mindfulness-based meditation and non-invasive brain stimulation can enhance neural markers of attention and memory that serve as proxies for cognitive reserve in cognitively healthy adults and older adults diagnosed with mild cognitive impairment (MCI). Investigators hypothesize that strengthening these neural markers will lead to measurable improvements in cognitive reserve-related functions in both healthy aging and MCI populations.
This study further hypothesizes that neural markers of attention can be selectively enhanced using an electroencephalography (EEG)-based brain-computer interface (BCI) combined with non-invasive interventions such as mindfulness-based relaxation or neuromodulation. During the study, participants will perform a computerized memory task while their EEG signals are recorded in real time. A BCI will analyze these signals to decode the presence or absence of the P300 event-related potential, a well-established neural marker of attentional control and cognitive resource allocation. Real-time feedback and intervention will be used to modulate these neural processes with the goal of promoting adaptive changes in attention-related brain activity.
By integrating EEG-based decoding, behavioral training, and non-invasive interventions, this study aims to determine whether targeted modulation of attention-related neural activity can support cognitive reserve in aging and mild cognitive impairment.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Good general health.
Normal or corrected vision.
no history of neurological/psychiatric disease
ability to read and understand English
Disqualifiers
Neurological or psychiatric diseases that could be contraindicated for tACS (e.g., personal history of epilepsy/seizure brain damage, history of fainting, bipolar disorder, schizophrenia, current substance use disorder, etc.).
Medications that elevate seizure threshold (e.g., stimulant medication, high dose bupropion).
Factors hindering EEG acquisition and tACS delivery (e.g., skin infection, wounds, dermatitis, inability to access the scalp of the participant).
Neurological or psychiatric diseases that could be contraindicated for tACS (e.g., personal history of epilepsy/seizure brain damage, pacemakers, history of fainting, bipolar disorder, schizophrenia, current substance use disorder, etc.).
Trial design
Design model
Parallel
Treatments tested in this trial
transcranial electrical stimulation
DevicetACS is delivered as a pre-task neuromodulatory intervention intended to prime neural activity before cognitive assessment. Electroencephalography (EEG) signals will be recorded from subjects as they perform nback tasks. The neural correlates of attention 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 nback training with this intervention.
Mindfulness Meditation
BehavioralA relaxation protocol based on mindfulness meditation will be carried out. This consists of closing the eyes and focusing on breathing and relaxing for a period of 5 minutes. Electroencephalography (EEG) signals will be recorded from subjects as they perform nback tasks. The neural correlates of attention 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 nback training with this intervention
Treatment groups
100 Participants
are divided into 4 treatment groupsGroup A: Behavior-based Attention control with MeditationActive comparator 1 intervention
Group B: Behavior-based Attention control with Open-Loop tACSActive comparator 1 intervention
Group C: EEG-based Attention Control and MeditationExperimental treatment 1 intervention
Group D: EEG-Based Attention Control and Open-Loop tACSExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
Change in neural correlates of attention across different intervention sessions
This outcome measures whether neural correlates of attentional markers (e.g. amplitude, peak-to-peak, band power and connectivity measures of neural correlates) change across sessions as a result of intervention.
Time frame
From enrollment to the end of the study after 3 days (young adults) or 8 days (older adults)Secondary outcomes
1
Change in correct answer rate of memory task across intervention sessions
The correct answer rate per nback run reflects the improvements in attentional and memory skills across the two conditions. It measures the percentage of each trial memorized correctly. The score is 0-50, and the higher the value, the better the outcome.
Time frame
From enrollment to the end of the study after 3 days (young adults) or 8 days (older adults)Sponsors and contacts
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Source ClinicalTrials.gov