Designing a Spatial Navigation Intervention Protocol Informed by Region-specific Brain Activation for Mild Cognitive Impairment
SNav
2 other identifiers
interventional
30
1 country
1
Brief Summary
The goal of this one-arm clinical trial is to determine whether participants with mild cognitive impairment (MCI) can successfully navigate a virtual reality (VR) maze. The VR maze is designed as a training tool aimed at improving participants' spatial navigation abilities. Main Aims:
- 1.To determine whether at least 70% of older adults enrolled in the study can complete twenty-four 50-minute training sessions over a 4-month period.
- 2.To assess whether combining virtual reality with EEG recordings can be used to measure brain activation and changes in brain activation associated with spatial navigation learning.
- 3.Walk in an open, unobstructed space while wearing VR goggles.
- 4.Explore up to fifty different virtual mazes in sequence and attempt to find their way through each one.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Aug 2026
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
November 4, 2025
CompletedFirst Posted
Study publicly available on registry
November 6, 2025
CompletedStudy Start
First participant enrolled
August 1, 2026
ExpectedPrimary Completion
Last participant's last visit for primary outcome
December 23, 2027
Study Completion
Last participant's last visit for all outcomes
December 23, 2027
May 22, 2026
May 1, 2026
1.4 years
November 4, 2025
May 21, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Change in Immediate Maze Time (IMT)
Change in immediate maze time will be assessed as a Behavioral marker of change and determined using the floor maze test (FMT), which combines navigation with walking. Participants will be positioned at the entry point of the FMT and instructed to find their way to the exit point of the FMT. A fixed 15-second planning period will be given to plan the route. The time elapsed from the end of the planning period to successful exit (i.e., IMT), in seconds, will be recorded. Paired t-tests will be used to compare the Floor Maze Test time between baseline and post intervention.
Change from baseline to post-intervention at 4 months
Secondary Outcomes (2)
Change in time required to travel the VR-SN maze
Change from baseline to post-intervention at 4 months
Change in mobile Brain Body Imaging (MoBI) markers
Change from baseline to post-intervention at 2 months (~ midpoint) and at 4 months
Study Arms (1)
Full-immersive virtual-reality (VR) maze
EXPERIMENTALVirtual reality maze session 1: Individualized, face-to-face introductory session to describe and answer questions about the protocol. Virtual reality EEG session 2 (baseline): Each session lasts 50 minutes. Initial maze complexity will be set at the lowest level (i.e., one turn to reach target). A maze will be repeated until performed without errors after which a new maze is introduced. The up-down transformed rule will be used to adjust complexity based on a participant's performance. Specifically, a three-up/one-down rule, meaning that for three consecutive error-free mazes the complexity of the maze will be adjusted by introducing an additional turn-to-target and for any error the number of turns to reach the target will be reduced by one. Virtual reality maze sessions 3-23 (no EEG): Participants take part in six sessions within 10 days over a 4-month period. Virtual reality-SN EEG sessions 12 \& 24: Participants are trained on the virtual reality maze while EEG is recorded.
Interventions
A full-immersive virtual-reality environment where participants train ability to navigate and find their way through a maze in virtual reality has been developed. The virtual-reality environment is well-suited to maintain learner motivation throughout the intervention by providing appropriate challenges (i.e., maze complexity can be adjusted to the learner's progress), positive feedback (i.e., reaching the maze goal), and novelty (i.e., new mazes for each session). 50 different VR mazes, varying in difficulty from 1 to 4 intersections, have been built.
Eligibility Criteria
You may qualify if:
- Age 65 and older with amnestic mild cognitive impairment (aMCI);
- Can speak English;
- Agrees to MoBI recording;
- Normal or corrected-to-normal vision/audition;
- Able to walk unassisted for 10 minutes;
- Plan to be in the area for next year
You may not qualify if:
- Dementia (Memory Impairment/AD8 screen);
- Medical conditions that affect participation such as vertigo and neck pain;
- Hospitalization in the past six months or plans for surgery affecting participation in the next four months;
- Mobility limitations solely due to musculoskeletal limitation or pain;
- Terminal illness with life expectancy less than 12 months;
- Presence of clinical disorders that overtly alter attention like delirium;
- Active psychoses or psychiatric symptoms;
- Living in nursing home;
- Participation in intervention trial;
- Standard contraindications to EEG including seizure medication, epilepsy, stroke, traumatic brain injury;
- Pregnant women
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Albert Einstein College of Medicine
The Bronx, New York, 10461, United States
Related Publications (49)
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PMID: 33129261BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Pierfilippo De Sanctis, PhD
Albert Einstein College of Medicine
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
November 4, 2025
First Posted
November 6, 2025
Study Start (Estimated)
August 1, 2026
Primary Completion (Estimated)
December 23, 2027
Study Completion (Estimated)
December 23, 2027
Last Updated
May 22, 2026
Record last verified: 2026-05
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
- Time Frame
- The research community will have access to data when the award ends. As required by NDA, studies will also be created that contain the data used for every publication. Those studies will be shared when the pre-print is available. NDA studies have digital object identifiers (DOI) to aid in findability. This DOI will be included in relevant publications. NDA will make decisions about how long to preserve the data, but that data archive has not deleted any deposited data up to now. Data will be share before the end of the project or at the time of publication whatever comes first. Data will be stored for at least three years.
- Access Criteria
- Data will be findable for the research community through the NDA Collection that will be established when this application is funded. For all publications, an NDA study will be created. Each of those studies is assigned a digital object identifier (DOI). This data DOI will be referenced in the publication to allow the research community easy access to the exact data used in the publication.
Demographic, cognitive, clinical, and 32-channel EEG electrophysiological data will be acquired. Virtual reality is presented through SteamVR's HTC Vive technology, specialized for full-immersive 3D experiences using motion tracking to move and interaction within the virtual environment. All data will be de-identified prior to receipt by the repository, but the information needed to generate a global unique identifier for the NIMH Data Archive (NDA) will be collected. Scientific data is expected to reach 10 terabytes. The clinical, cognitive and EEG data will be analyzed with custom matlab code written using MATLAB® environment and EEGLAB package for EEG data. While MATLAB is commercial software, most universities have site licenses available. All code will be shared on the GitHub lab website. The code can be found by searching for "labname" on GitHub. The main readme.md file for the project will also include instructions.