Exploring neurofeedback learning using a neurofeedback treatment for central neuropathic pain after a spinal cord injury
Exploring neurofeedback learning using a neurofeedback treatment for central neuropathic pain after a spinal cord injury
Early evidence suggests that individuals can learn voluntary modulation of their own brain activity, called neurofeedback, to relieve central neuropathic pain (CNP) after a spinal cord injury (SCI). CNP after SCI is a life-changing illness that is difficult to treat. Neurofeedback that uses electrical brain activity (electroencephalogram; EEG) is a non-invasive and non-pharmaceutical treatment, which minimises side-effects. Thus, a neurofeedback system was developed in previous work targeting EEG activity associated with CNP after SCI in order to relieve pain. However, it was unclear how individuals become successful at neurofeedback and current literature on neurofeedback learning is sparse and inconsistent. The aim of this thesis was to explore mental behaviour during neurofeedback training to understand neurofeedback learning. This was done by examining mental strategies used by participants during neurofeedback training, questionnaires of general learning factors, and autonomic responses during neurofeedback training. Twenty-five able-bodied individuals (13 female, mean age = 30.96) and ten individuals with CNP after SCI (3 female, mean age = 51.70) completed neurofeedback training on four separate visits, where interviews were conducted after each visit. Standardised questionnaires examined the influence of general learning factors (self-efficacy, locus of control, motivation, and difficulty) on neurofeedback success. Autonomic responses (heart rate, respiration, and galvanic skin response) were examined in relation to neurofeedback success. A framework model and thematic analysis were used to examine qualitative interview data. Descriptive statistics and correlations were used to examine quantitative data. No mental behaviour differences were found between able-bodied individuals and individuals with CNP after SCI. Perceived performance of the neurofeedback task seemed to influence participants’ approach to achieving the neurofeedback task. Negative affect was somewhat associated with being unsuccessful at neurofeedback. Only self-efficacy had a moderate correlation with neurofeedback success (r =< 0.587, p =< 0.020). No autonomic responses were significantly correlated with neurofeedback success. The mental behaviour of 70% of participants were directly inspired by the user interface design. Interviews revealed five types of success goals created by participants to assess their neurofeedback performance; not all goals aligned with the researchers’ success goal despite reminders of the task instructions. Furthermore, no participant could focus on more than one piece of information from the user interface at once. A third of participants reported that the interface design interfered with their neurofeedback performance. This thesis displays the complexity of behaviour involved in neurofeedback learning that future research should acknowledge, and particularly emphasises the importance of a user interface design that facilitates neurofeedback learning.
University of Southampton
Anil, Krithika
2b2690a5-37f4-4b3e-9b4c-df721d12a2f3
June 2020
Anil, Krithika
2b2690a5-37f4-4b3e-9b4c-df721d12a2f3
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Anil, Krithika
(2020)
Exploring neurofeedback learning using a neurofeedback treatment for central neuropathic pain after a spinal cord injury.
University of Southampton, Doctoral Thesis, 228pp.
Record type:
Thesis
(Doctoral)
Abstract
Early evidence suggests that individuals can learn voluntary modulation of their own brain activity, called neurofeedback, to relieve central neuropathic pain (CNP) after a spinal cord injury (SCI). CNP after SCI is a life-changing illness that is difficult to treat. Neurofeedback that uses electrical brain activity (electroencephalogram; EEG) is a non-invasive and non-pharmaceutical treatment, which minimises side-effects. Thus, a neurofeedback system was developed in previous work targeting EEG activity associated with CNP after SCI in order to relieve pain. However, it was unclear how individuals become successful at neurofeedback and current literature on neurofeedback learning is sparse and inconsistent. The aim of this thesis was to explore mental behaviour during neurofeedback training to understand neurofeedback learning. This was done by examining mental strategies used by participants during neurofeedback training, questionnaires of general learning factors, and autonomic responses during neurofeedback training. Twenty-five able-bodied individuals (13 female, mean age = 30.96) and ten individuals with CNP after SCI (3 female, mean age = 51.70) completed neurofeedback training on four separate visits, where interviews were conducted after each visit. Standardised questionnaires examined the influence of general learning factors (self-efficacy, locus of control, motivation, and difficulty) on neurofeedback success. Autonomic responses (heart rate, respiration, and galvanic skin response) were examined in relation to neurofeedback success. A framework model and thematic analysis were used to examine qualitative interview data. Descriptive statistics and correlations were used to examine quantitative data. No mental behaviour differences were found between able-bodied individuals and individuals with CNP after SCI. Perceived performance of the neurofeedback task seemed to influence participants’ approach to achieving the neurofeedback task. Negative affect was somewhat associated with being unsuccessful at neurofeedback. Only self-efficacy had a moderate correlation with neurofeedback success (r =< 0.587, p =< 0.020). No autonomic responses were significantly correlated with neurofeedback success. The mental behaviour of 70% of participants were directly inspired by the user interface design. Interviews revealed five types of success goals created by participants to assess their neurofeedback performance; not all goals aligned with the researchers’ success goal despite reminders of the task instructions. Furthermore, no participant could focus on more than one piece of information from the user interface at once. A third of participants reported that the interface design interfered with their neurofeedback performance. This thesis displays the complexity of behaviour involved in neurofeedback learning that future research should acknowledge, and particularly emphasises the importance of a user interface design that facilitates neurofeedback learning.
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Published date: June 2020
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Local EPrints ID: 447115
URI: http://eprints.soton.ac.uk/id/eprint/447115
PURE UUID: f5f30320-1cfc-4e96-8cca-fdb12090eae2
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Date deposited: 03 Mar 2021 17:32
Last modified: 17 Mar 2024 02:56
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Krithika Anil
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