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The study will investigate the use of Electroencephalography (EEG) in understanding mild cognitive impairment (MCI). EEG is commonly used in everyday clinical practice for the assessment of a wide range of neurological disorders. It records the brains spontaneous electrical signals and offers a non-invasive means of visually evaluating brain signals. By analysing these signals, we aim to uncover invaluable insights into cognitive impairments and the ageing brains cognitive processes.
The Electroencephalogram (EEG) is widely used in clinical practice to assess various neurological disorders. It records the brains spontaneous electrical activity, providing a non-invasive way to visually examine brain signals. By analysing these signals, we aim to gain valuable insights into cognitive impairments and the cognitive processes of the ageing brain. The P300 is an event-related potential (ERP) that serves as a crucial EEG-based biomarker, whose amplitude and latency are key points of research in cognitive impairments. Typically elicited by a visual speller, the P300 could be used for the communication through brain-computer interface (BCI). A P300-based BCI enables communication by detecting the P300 response to specific target letters, allowing users to select letters they wish to spell through interactive interface. In this study, we will recruit 15 elderly participants with mild cognitive impairment (MCI) symptoms and 15 controls without MCI. We will customise the P300-BCI by adjusting the inter-stimulus interval (ISI) and the matrix size which is the probability of the target presenting. This will help us investigate how these parameter settings influence the P300 components and the accuracy of the P300-BCI in both groups. Additionally, this study could help explore the potential of the P300-BCI to mitigate MCI symptoms and provide evidence for its further development.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Elderly with Mild Cognitive Impairments |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MoCA Test | Diagnostic Test | MoCA (Montreal Cognitive Assessment or The MoCA Test) was validated as a highly sensitive tool for early detection of mild cognitive impairment (MCI) in hundreds of peer-reviewed studies since 2000. MoCA has been widely adopted in clinical settings and used in academic and non-academic research around the world. The sensitivity of MoCA for detecting MCI is 90%, compared to 18% for the MMSE. Prospective participants meeting the eligibility criteria, as determined by the Montreal Cognitive Assessment (MoCA) test, will be invited to the Brain- Computer Interface (BCI) laboratory at the Kroto Research Centre on the University of Sheffield north campus to participate in the study. |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of the Brain-Computer Interface (BCI) model across different settings which is being tested | This outcome measure will assess the accuracy of the P300-based Brain-Computer Interface (BCI) system across different settings being tested. Using state-of-the-art BCI classification models, the accuracy of P300-BCI system classification will be determined through offline analysis of EEG data collected during the experiment. | Through study completion, an average of 9 months. |
| Measure | Description | Time Frame |
|---|---|---|
| The scores of the Montreal Cognitive Assessment (MoCA) | Montreal Cognitive Assessment (MoCA) was validated as a highly sensitive tool for early detection of mild cognitive impairment (MCI) in hundreds of peer-reviewed studies since 2000. It has been widely adopted in clinical settings and used in academic and non-academic research around the world. The results of MoCA are interpreted based on a score range, with higher scores indicating less cognitive impairment: 26-30: Normal cognition 18-25: Mild cognitive impairment 10-17: Moderate cognitive impairment Under 10: Severe cognitive impairment |
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Inclusion Criteria:
Exclusion Criteria:
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Participants will be from the Sheffield Memory Clinic run by Dr Blackburn. This sees approximately 400 new patients per year of whom 15-20% have MCI, it is a research active clinic, and we have a database of people interested in taking part in research. Suitable participants will be identified in the clinic by a member of their clinical staff or contacted from their database.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Mahnaz Arvaneh | Contact | +44 1142225649 | m.arvaneh@sheffield.ac.uk | |
| Jin Ni | Contact | +44 7787100398 | jni14@sheffield.ac.uk |
| Name | Affiliation | Role |
|---|---|---|
| Mahnaz Arvaneh | University of Sheffield | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The University of Sheffield | Sheffield | South Yorkshire | S3 7ES | United Kingdom |
We plan to share anonymized data from the study, including raw EEG data and relevant metadata. The data will be available starting six months after publication and will remain accessible for a period of five years. Researchers who wish to access the data will be required to submit a formal request, and access will be granted upon approval by our data access committee.
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| ID | Term |
|---|---|
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D003072 | Cognition Disorders |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
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| Random Dot Motion (RDM) task | Device | Random Dot Motion task (RDM) has been widely used in research on spatial attention, and decision-making ability, etc., and its results (accuracy and reaction time) can be used as indicators to detect spatial attention. During the assessment, participants were required to monitor a series of dots in constant random motion on the screen. The dots sometimes moved coherently together to the left or right, and participants were required to press the left mouse button when they perceived them moving to the left and the right mouse button when they observed them moving to the right. We are going to use the motion coherence level of 50%. The higher the coherence level, the greater the number of dots moving together, and the combination of the moving direction and coherence level of the dots appear randomly during the task. |
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| P300-BCI task without feedback | Device | Two different speller matrix sizes: 3×3 and 5×5, two inter-stimulus intervals (ISIs): 117ms (i.e., commonly used ISI for healthy adults) and 175ms (i.e., 50% longer than the widely used ISI) and two spelling words (QUICK and JUMP) are designed in this experiment to explore the calibration accuracy of these eight parameter combinations in the young and old groups and obtain the best parameter combination. The matrix contains letters and digits, and the target letters will be displayed below the matrix letter by letter. When the speller runs, the rows and columns in the matrix will flash 15 times each randomly. Each flash will last for 55ms, and the subsequent ISI will last for different times according to different parameter designs. Participants only need to focus on the target letter and silently count the number it flashes, as flashing target letters can generate P300 if well attended. |
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| Through study completion, an average of 9 months. |
| Reaction times of the Random Dot Motion (RDM) test | In the Random Dot Motion (RDM) test, the reaction times of the mild cognitive impairment (MCI) patients are slower and more variable. | Through study completion, an average of 9 months. |
| Error rates of the Random Dot Motion (RDM) test | In the Random Dot Motion (RDM) test, the error rates of the mild cognitive impairment (MCI) patients are higher, particularly in challenging conditions (e.g., low coherence level). | Through study completion, an average of 9 months. |
| Characteristics of the P300 amplitude across different settings | P300 amplitude refers to the magnitude of the positive deflection in the EEG signal occurring approximately 300 milliseconds after the presentation of a target stimulus. The P300 amplitude is typically measured in microvolts (µV). Data will be averaged across trials for each participant. | Through study completion, an average of 9 months. |
| Characteristics of the P300 latency across different settings | P300 latency represents the time interval between the onset of a target stimulus and the peak of the P300 wave in the EEG signal, which is a measure of the speed of cognitive processing. The P300 latency will be measured in milliseconds (ms) and will be calculated by averaging across task trials for each participant. | Through study completion, an average of 9 months. |
| Answers to the two questionnaires, using a 10-point rating scale | Through study completion, an average of 9 months. |