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Closed-Loop Stimulus Optimization to Increase Communication Efficiency in Brain-Computer Interfaces

Award Number: R21DC018347
ORGANIZATION: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Abstract Assistive devices such as augmentative and alternative communication (AAC) systems are used by people with communication and motor disabilities, such as amyotrophic lateral sclerosis (ALS, commonly known as Lou Gehrig’s disease), to communicate and interact with their environment. There are various commercially available AAC devices that are controlled by access methods such as touch, switch, head tracking and eye gaze; however, these access methods become difficult or impossible to use when sustained muscle control is more challenging or voluntary motor control is lost. There are brain-computer interface (BCI) communication systems, such as the P300 speller, that use sensory stimulation to elicit and then detect sensory neural responses in electroencephalography (EEG) data, and these communication aids do not require any motor control on the part of the affected individual. However, the accuracies and spelling speeds of stimulus-driven BCIs are suboptimal due to the inherent limitations associated with relying on sensory stimulation, which generates highly variable neural responses, as well as the necessity of processing inherently noisy EEG data to extract the relevant neural information that is needed to control the BCI. Current BCI communication rates can potentially be improved with closed-loop optimisation techniques that exploit information from the user’s responses to previous stimuli to optimally tune the BCI system’s parameters to achieve the desired goal of maximising system performance under conditions of uncertainty. A closed-loop strategy can be used to select stimuli that are maximally informative of the user’s intent given the neural responses that are being measured, and I hypothesise that this data-adaptive approach to stimulus selection will minimise BCI decision errors and achieve better device control. Conventional BCIs use open-loop stimulus control methods as the stimulus presentation schedule is typically set in advance or occurs randomly, and there has been limited development of closed-loop stimulus paradigms in BCIs. The goal of the research that I propose is to investigate the feasibility of a novel closed-loop stimulus selection algorithm that will optimise the BCI stimulus presentation schedule in real-time based on the measured EEG data and the BCI system’s belief about the user’s intent, with proof-of-concept demonstrated in the P300 BCI speller. Specific Aim 1 will initially develop and test the novel algorithm in a non-disabled cohort to leverage the time efficiency and practicality of non-disabled participant studies to evaluate the real-time feasibility and potential utility of the closed-loop stimulus selection algorithm. Specific Aim 2 will test the closed-loop stimulus selection algorithm in individuals with ALS to assess the performance of the algorithm in a clinically relevant cohort. The successful development and testing of the proposed closed-loop stimulus selection algorithm in a challenging system such as the P300 BCI speller has the potential to instigate a paradigm shift towards closed-loop methods for BCI control and other applications where optimising system parameters in real-time to improve overall system performance could be of benefit.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2023 ( Subtotal = $0 )
2023	2022	DUKE UNIVERSITY	2200 W MAIN ST	DURHAM	NC	27705	DURHAM	USA	Research Related to Deafness and Communication Disorders	000	3	1/9/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2022 ( Subtotal = $155,839 )
2022	2022	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	000	3	12/21/2021	NON-COMPETING CONTINUATION	$140,255
2022	2022	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	001	3	4/21/2022	NON-COMPETING CONTINUATION	$15,584
														Subtotal = $155,839

Issue Date FY: 2021 ( Subtotal = $413,521 )
2021	2021	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	002	2	8/19/2021	SUPPLEMENT FOR EXPANSION	$266,638
2021	2021	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	000	2	12/22/2020	NON-COMPETING CONTINUATION	$132,194
2021	2021	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	001	2	1/8/2021	NON-COMPETING CONTINUATION	$14,689
														Subtotal = $413,521

Issue Date FY: 2020 ( Subtotal = $147,065 )
2020	2020	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Research Related to Deafness and Communication Disorders	000	1	12/18/2019	NEW	$147,065
														Subtotal = $147,065

Grand Total All Awards = $716,425

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Closed-Loop Stimulus Optimization to Increase Communication Efficiency in Brain-Computer Interfaces

Award Number: R21DC018347

ORGANIZATION: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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