A Hidden Markov Model reveals magnetoencephalography spectral frequency-specific abnormalities of brain state power and phase-coupling in neuropathic pain View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-09-21

AUTHORS

Camille Fauchon, Junseok A. Kim, Rima El-Sayed, Natalie R. Osborne, Anton Rogachov, Joshua C. Cheng, Kasey S. Hemington, Rachael L. Bosma, Benjamin T. Dunkley, Jiwon Oh, Anuj Bhatia, Robert D. Inman, Karen Deborah Davis

ABSTRACT

Neuronal populations in the brain are engaged in a temporally coordinated manner at rest. Here we show that spontaneous transitions between large-scale resting-state networks are altered in chronic neuropathic pain. We applied an approach based on the Hidden Markov Model to magnetoencephalography data to describe how the brain moves from one activity state to another. This identified 12 fast transient (~80 ms) brain states including the sensorimotor, ascending nociceptive pathway, salience, visual, and default mode networks. Compared to healthy controls, we found that people with neuropathic pain exhibited abnormal alpha power in the right ascending nociceptive pathway state, but higher power and coherence in the sensorimotor network state in the beta band, and shorter time intervals between visits of the sensorimotor network, indicating more active time in this state. Conversely, the neuropathic pain group showed lower coherence and spent less time in the frontal attentional state. Therefore, this study reveals a temporal imbalance and dysregulation of spectral frequency-specific brain microstates in patients with neuropathic pain. These findings can potentially impact the development of a mechanism-based therapeutic approach by identifying brain targets to stimulate using neuromodulation to modify abnormal activity and to restore effective neuronal synchrony between brain states. More... »

PAGES

1000

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s42003-022-03967-9

DOI

http://dx.doi.org/10.1038/s42003-022-03967-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1151184627

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/36131088


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23 schema:description Neuronal populations in the brain are engaged in a temporally coordinated manner at rest. Here we show that spontaneous transitions between large-scale resting-state networks are altered in chronic neuropathic pain. We applied an approach based on the Hidden Markov Model to magnetoencephalography data to describe how the brain moves from one activity state to another. This identified 12 fast transient (~80 ms) brain states including the sensorimotor, ascending nociceptive pathway, salience, visual, and default mode networks. Compared to healthy controls, we found that people with neuropathic pain exhibited abnormal alpha power in the right ascending nociceptive pathway state, but higher power and coherence in the sensorimotor network state in the beta band, and shorter time intervals between visits of the sensorimotor network, indicating more active time in this state. Conversely, the neuropathic pain group showed lower coherence and spent less time in the frontal attentional state. Therefore, this study reveals a temporal imbalance and dysregulation of spectral frequency-specific brain microstates in patients with neuropathic pain. These findings can potentially impact the development of a mechanism-based therapeutic approach by identifying brain targets to stimulate using neuromodulation to modify abnormal activity and to restore effective neuronal synchrony between brain states.
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29 schema:keywords Hidden Markov Model
30 Markov model
31 abnormal activity
32 abnormalities
33 active time
34 activity
35 activity state
36 alpha power
37 approach
38 attentional state
39 band
40 beta band
41 brain
42 brain states
43 brain targets
44 chronic neuropathic pain
45 coherence
46 control
47 data
48 default mode network
49 development
50 dysregulation
51 findings
52 frequency-specific abnormalities
53 group
54 healthy controls
55 high power
56 imbalance
57 interval
58 large-scale resting-state networks
59 less time
60 low coherence
61 manner
62 mechanism-based therapeutic approaches
63 mode network
64 model
65 network
66 network state
67 neuromodulation
68 neuronal populations
69 neuronal synchrony
70 neuropathic pain
71 neuropathic pain group
72 nociceptive pathways
73 pain
74 pain group
75 pathway
76 pathway states
77 patients
78 people
79 population
80 power
81 rest
82 resting-state networks
83 salience
84 sensorimotor
85 sensorimotor network
86 short time interval
87 spontaneous transition
88 state
89 state power
90 study
91 synchrony
92 target
93 temporal imbalance
94 therapeutic approaches
95 time
96 time interval
97 transient brain states
98 transition
99 visits
100 schema:name A Hidden Markov Model reveals magnetoencephalography spectral frequency-specific abnormalities of brain state power and phase-coupling in neuropathic pain
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