{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T17:13:51Z","timestamp":1793294031944,"version":"4.5.0"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,8,26]],"date-time":"2021-08-26T00:00:00Z","timestamp":1629936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000334","name":"International Spinal Research Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000334","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:p>Central neuropathic pain (CNP) negatively impacts the quality of life in a large proportion of people with spinal cord injury (SCI). With no cure at present, it is crucial to improve our understanding of how CNP manifests, to develop diagnostic biomarkers for drug development, and to explore prognostic biomarkers for personalised therapy. Previous work has found early evidence of diagnostic and prognostic markers analysing Electroencephalogram (EEG) oscillatory features. In this paper, we explore whether non-linear non-oscillatory EEG features, specifically Higuchi Fractal Dimension (HFD), can be used as prognostic biomarkers to increase the repertoire of available analyses on the EEG of people with subacute SCI, where having both linear and non-linear features for classifying pain may ultimately lead to higher classification accuracy and an intrinsically transferable classifier. We focus on EEG recorded during imagined movement because of the known relation between the motor cortex over-activity and CNP. Analyses were performed on two existing datasets. The first dataset consists of EEG recordings from able-bodied participants (<jats:italic>N<\/jats:italic> = 10), participants with chronic SCI and chronic CNP (<jats:italic>N<\/jats:italic> = 10), and participants with chronic SCI and no CNP (<jats:italic>N<\/jats:italic> = 10). We tested for statistically significant differences in HFD across all pairs of groups using bootstrapping, and found significant differences between all pairs of groups at multiple electrode locations. The second dataset consists of EEG recordings from participants with subacute SCI and no CNP (<jats:italic>N<\/jats:italic> = 20). They were followed-up 6 months post recording to test for CNP, at which point (<jats:italic>N<\/jats:italic> = 10) participants had developed CNP and (<jats:italic>N<\/jats:italic> = 10) participants had not developed CNP. We tested for statistically significant differences in HFD between these two groups using bootstrapping and, encouragingly, also found significant differences at multiple electrode locations. Transferable machine learning classifiers achieved over 80% accuracy discriminating between groups of participants with chronic SCI based on only a single EEG channel as input. The most significant finding is that future and chronic CNP share common features and as a result, the same classifier can be used for both. This sheds new light on pain chronification by showing that frontal areas, involved in the affective aspects of pain and believed to be influenced by long-standing pain, are affected in a much earlier phase of pain development.<\/jats:p>","DOI":"10.3389\/fnins.2021.705652","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T12:27:02Z","timestamp":1630412822000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Markers of Central Neuropathic Pain in Higuchi Fractal Analysis of EEG Signals From People With Spinal Cord Injury"],"prefix":"10.3389","volume":"15","author":[{"given":"Keri","family":"Anderson","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristian","family":"Chirion","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Fraser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariel","family":"Purcell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Stein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksandra","family":"Vuckovic","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,8,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/s004220050394","article-title":"Use of the fractal dimension for the analysis of electroencephalographic time series","volume":"77","author":"Accardo","year":"1997","journal-title":"Biol. Cybernet"},{"key":"B2","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.cmpb.2005.06.011","article-title":"Non-linear analysis of EEG signals at various sleep stages","volume":"80","author":"Acharya","year":"2005","journal-title":"Comput. Methods Prog. Biomed"},{"key":"B3","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.ijpsycho.2012.05.001","article-title":"Fractality analysis of frontal brain in major depressive disorder","volume":"85","author":"Ahmadlou","year":"2012","journal-title":"Int. J. Psychophysiol"},{"key":"B4","unstructured":"Complexity analysis of spontaneous EEG495501\n            BhattacharyaJ.\n          Acta Neurobiol. Exp602000"},{"key":"B5","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1038\/sj.sc.3102077","article-title":"Electroencephalographic slowing and reduced reactivity in neuropathic pain following spinal cord injury","volume":"46","author":"Boord","year":"2008","journal-title":"Spinal Cord"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.1177\/0333102417733953","article-title":"Exploring resting-state EEG complexity before migraine attacks","volume":"38","author":"Cao","year":"2018","journal-title":"Cephalalgia"},{"key":"B7","unstructured":"DengK.\n          Omega: On-line memory-based general purpose system classifier (Phd thesis). Carnegie Mellon University, Pittsburgh, PA1998"},{"key":"B8","doi-asserted-by":"publisher","first-page":"4730","DOI":"10.1016\/j.eswa.2014.02.004","article-title":"Category-specific models for ranking effective paraphrases in community question answering","volume":"41","author":"Figueroa","year":"2014","journal-title":"Expert Syst. Appl"},{"key":"B9","doi-asserted-by":"publisher","first-page":"S71","DOI":"10.1016\/j.pain.2012.12.007","article-title":"Pain in patients with spinal cord injury","volume":"154","author":"Finnerup","year":"2013","journal-title":"Pain"},{"key":"B10","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.jpain.2013.09.008","article-title":"Phenotypes and predictors of pain following traumatic spinal cord injury: a prospective study","volume":"15","author":"Finnerup","year":"2014","journal-title":"J. Pain"},{"key":"B11","doi-asserted-by":"publisher","first-page":"2466","DOI":"10.1073\/pnas.012579499","article-title":"Fractal dynamics in physiology: alterations with disease and aging","volume":"99","author":"Goldberger","year":"2002","journal-title":"Proc. Natl. Acad. Sci. U.S.A"},{"key":"B12","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.pain.2009.12.001","article-title":"Brain circuitry underlying pain in response to imagined movement in people with spinal cord injury","volume":"148","author":"Gustin","year":"2010","journal-title":"Pain"},{"key":"B13","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1049\/ip-smt:20000862","article-title":"Prospects for routine detection of dementia using the fractal dimension of the human electroencephalogram","volume":"147","author":"Henderson","year":"2000","journal-title":"IEEE Proc. Sci. Meas. Technol"},{"key":"B14","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/0167-2789(88)90081-4","article-title":"Approach to an irregular time series on the basis of the fractal theory","volume":"31","author":"Higuchi","year":"1988","journal-title":"Phys. D Nonlinear Phenomena"},{"key":"B15","unstructured":"JarjeesM. S.\n          The causality between Electroencephalogram (EEG) and Central Neuropathic Pain (CNP), and the effectiveness of neuromodulation strategies on cortical excitability and CNP in patients with spinal cord injury (PhD thesis). University of Glasgow2017"},{"key":"B16","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1038\/sc.2012.84","article-title":"Brain EEG activity correlates of chronic pain in persons with spinal cord injury: clinical implications","volume":"51","author":"Jensen","year":"2013","journal-title":"Spinal Cord"},{"key":"B17","doi-asserted-by":"publisher","first-page":"2204","DOI":"10.1016\/j.pain.2011.06.017","article-title":"A new definition of neuropathic pain","volume":"152","author":"Jensen","year":"2011","journal-title":"Pain"},{"key":"B18","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1142\/S0218348X05002933","article-title":"Consecutive differences as a method of signal fractal analysis","volume":"13","author":"Kalauzi","year":"2005","journal-title":"Fractals"},{"key":"B19","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/0010-4825(88)90041-8","article-title":"Fractals and the analysis of waveforms","volume":"18","author":"Katz","year":"1988","journal-title":"Comput. Biol. Med"},{"key":"B20","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.cmpb.2016.05.014","article-title":"Application of Higuchi's fractal dimension from basic to clinical neurophysiology: a review","volume":"133","author":"Kesi\u0107","year":"2016","journal-title":"Comput. Methods Prog. Biomed"},{"key":"B21","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1088\/1741-2560\/2\/2\/002","article-title":"Fractal spectral analysis of pre-epileptic seizures in terms of criticality","volume":"2","author":"Li","year":"2005","journal-title":"J. Neural Eng"},{"key":"B22","doi-asserted-by":"publisher","first-page":"R1","DOI":"10.1088\/1741-2560\/4\/2\/R01","article-title":"A review of classification algorithms for EEG-based brain-computer interfaces","volume":"4","author":"Lotte","year":"2007","journal-title":"J. Neural Eng"},{"key":"B23","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1038\/sc.2013.34","article-title":"Burden of spinal cord injury-related neuropathic pain in the United States: retrospective chart review and cross-sectional survey","volume":"51","author":"Mann","year":"2013","journal-title":"Spinal Cord"},{"key":"B24","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/1475-925X-3-7","article-title":"Nonlinear analysis of EEG signals at different mental states","volume":"3","author":"Natarajan","year":"2004","journal-title":"Biomed. Eng"},{"key":"B25","doi-asserted-by":"crossref","DOI":"10.1109\/CBMS.1995.465426","article-title":"Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns,","volume-title":"Proceedings Eighth IEEE Symposium on Computer-Based Medical Systems","author":"Petrosian","year":"1995"},{"key":"B26","doi-asserted-by":"publisher","first-page":"217","DOI":"10.2170\/physiolsci.RP006307","article-title":"Fractal-based EEG data analysis of body parts movement imagery tasks","volume":"57","author":"Phothisonothai","year":"2007","journal-title":"J. Physiol. Sci"},{"key":"B27","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1093\/brain\/awh631","article-title":"Increased EEG power and slowed dominant frequency in patients with neurogenic pain","volume":"129","author":"Sarnthein","year":"2006","journal-title":"Brain J. Neurol"},{"key":"B28","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1162\/089976600300015565","article-title":"New support vector algorithms","volume":"12","author":"Sch\u00f6lkopf","year":"2000","journal-title":"Neural Comput"},{"key":"B29","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/S0304-3959(02)00452-9","article-title":"A longitudinal study of the prevalence and characteristics of pain in the first 5 years following spinal cord injury","volume":"103","author":"Siddall","year":"2003","journal-title":"Pain"},{"key":"B30","doi-asserted-by":"publisher","first-page":"e0149587","DOI":"10.1371\/journal.pone.0149587","article-title":"Electroencephalographic fractal dimension in healthy ageing and Alzheimer's disease","volume":"11","author":"Smits","year":"2016","journal-title":"PLoS ONE"},{"key":"B31","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.jtbi.2011.08.037","article-title":"Surrogate data modeling the relationship between high frequency amplitudes and Higuchi fractal dimension of EEG signals in anesthetized rats","volume":"289","author":"Spasic","year":"2011","journal-title":"J. Theoret. Biol"},{"key":"B32","doi-asserted-by":"publisher","first-page":"2266","DOI":"10.1016\/j.clinph.2005.06.011","article-title":"Nonlinear dynamical analysis of EEG and MEG: review of an emerging field","volume":"116","author":"Stam","year":"2005","journal-title":"Clin. Neurophysiol"},{"key":"B33","doi-asserted-by":"crossref","first-page":"2033","DOI":"10.1109\/IEMBS.2011.6090374","article-title":"Analysis of complexity based EEG features for the diagnosis of Alzheimer's disease,","volume-title":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Staudinger","year":"2011"},{"key":"B34","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1016\/j.neuroimage.2005.12.042","article-title":"Persistent EEG overactivation in the cortical pain matrix of neurogenic pain patients","volume":"31","author":"Stern","year":"2006","journal-title":"Neuroimage"},{"key":"B35","doi-asserted-by":"publisher","first-page":"1491","DOI":"10.3390\/s20051491","article-title":"Classification of pain event related potential for evaluation of pain perception induced by electrical stimulation","volume":"20","author":"Tripanpitak","year":"2020","journal-title":"Sensors"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1038\/s41467-018-02820-0","article-title":"Thalamocortical dysrhythmia detected by machine learning","volume":"9","author":"Vanneste","year":"2018","journal-title":"Nat. Commun"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1605","DOI":"10.1016\/j.clinph.2018.04.750","article-title":"Prediction of central neuropathic pain in spinal cord injury based on EEG classifier","volume":"129","author":"Vuckovic","year":"","journal-title":"Clin. Neurophysiol"},{"key":"B38","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1016\/j.jpain.2014.02.005","article-title":"Dynamic oscillatory signatures of central neuropathic pain in spinal cord injury","volume":"15","author":"Vuckovic","year":"2014","journal-title":"J. Pain"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1256.e1","DOI":"10.1016\/j.jpain.2018.04.011","article-title":"Electroencephalographic predictors of neuropathic pain in subacute spinal cord injury","volume":"19","author":"Vuckovic","year":"","journal-title":"J. Pain"},{"key":"B40","doi-asserted-by":"publisher","first-page":"2387","DOI":"10.1093\/brain\/awn169","article-title":"Residual spinothalamic tract pathways predict development of central pain after spinal cord injury","volume":"131","author":"Wasner","year":"2008","journal-title":"Brain"},{"key":"B41","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.pain.2008.10.007","article-title":"Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury","volume":"141","author":"Wrigley","year":"2009","journal-title":"Pain"},{"key":"B42","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1111\/j.1460-9568.2009.06801.x","article-title":"Neuropathic pain in spinal cord injury: significance of clinical and electrophysiological measures","volume":"30","author":"Wydenkeller","year":"2009","journal-title":"Eur. J. Neurosci"},{"key":"B43","doi-asserted-by":"publisher","first-page":"e100199","DOI":"10.1371\/journal.pone.0100199","article-title":"Fractal dimension of EEG activity senses neuronal impairment in acute stroke","volume":"9","author":"Zappasodi","year":"2014","journal-title":"PLoS ONE"},{"key":"B44","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1093\/brain\/awr270","article-title":"The nature and course of sensory changes following spinal cord injury: predictive properties and implications on the mechanism of central pain","volume":"135","author":"Zeilig","year":"2012","journal-title":"Brain"}],"container-title":["Frontiers in Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2021.705652\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T12:27:29Z","timestamp":1630412849000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2021.705652\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,26]]},"references-count":44,"alternative-id":["10.3389\/fnins.2021.705652"],"URL":"https:\/\/doi.org\/10.3389\/fnins.2021.705652","relation":{},"ISSN":["1662-453X"],"issn-type":[{"value":"1662-453X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,26]]},"article-number":"705652"}}