{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T04:23:36Z","timestamp":1775103816688,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T00:00:00Z","timestamp":1563235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81671038 , 31300939"],"award-info":[{"award-number":["81671038 , 31300939"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Public Weifare Projects of Zhejiang province","award":["2016C33G2041129"],"award-info":[{"award-number":["2016C33G2041129"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Complex nerve remodeling occurs in the injured brain area during functional rehabilitation after a brain injury; however, its mechanism has not been thoroughly elucidated. Neural remodeling can lead to changes in the electrophysiological activity, which can be detected in an electroencephalogram (EEG). In this paper, we used EEG band energy, approximate entropy (ApEn), sample entropy (SampEn), and Lempel\u2013Ziv complexity (LZC) features to characterize the intrinsic rehabilitation dynamics of the injured brain area, thus providing a means of detecting and exploring the mechanism of neurological remodeling during the recovery process after brain injury. The rats in the injury group (n = 12) and sham group (n = 12) were used to record the bilateral symmetrical EEG on days 1, 4, and 7 after a unilateral brain injury in awake model rats. The open field test (OFT) experiments were performed in the following three groups: an injury group, a sham group, and a control group (n = 10). An analysis of the EEG data using the energy, ApEn, SampEn, and LZC features demonstrated that the increase in SampEn was associated with the functional recovery. After the brain injury, the energy values of the delta1 bands on day 4; the delta2 bands on days 4 and 7; the theta, alpha, and beta bands and the values of ApEn, SampEn, and LZC of the cortical EEG signal on days 1, 4 and 7 were significantly lower in the injured brain area than in the non-injured area. During the process of recovery for the injured brain area, the values of the beta bands, ApEn, and SampEn of the injury group increased significantly, and gradually became equal to the value of the sham group. The improvement in the motor function of the model rats significantly correlated with the increase in SampEn. This study provides a method based on EEG nonlinear features for measuring neural remodeling in injured brain areas during brain function recovery. The results may aid in the study of neural remodeling mechanisms.<\/jats:p>","DOI":"10.3390\/e21070698","type":"journal-article","created":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T02:44:03Z","timestamp":1563331443000},"page":"698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Increased Sample Entropy in EEGs During the Functional Rehabilitation of an Injured Brain"],"prefix":"10.3390","volume":"21","author":[{"given":"Qiqi","family":"Cheng","sequence":"first","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Wenwei","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Kezhou","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8370-8308","authenticated-orcid":false,"given":"Weijie","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Li","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Ling","family":"Lei","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Tengfei","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Na","family":"Hou","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Yang","family":"Qu","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Yong","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Life Information Science &amp; Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S85","DOI":"10.1016\/j.wneu.2011.07.023","article-title":"Epidemiology and the Global Burden of Stroke","volume":"76","author":"Mukherjee","year":"2011","journal-title":"World Neurosurg."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.gene.2018.05.005","article-title":"Effect of infusion speed of 7.5% hypertonic saline on brain edema in patients with craniocerebral injury: An experimental study","volume":"665","author":"Jiang","year":"2018","journal-title":"Gene"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chang, W.H., Park, C.-H., Kim, D.Y., Shin, Y.-I., Ko, M.-H., Lee, A., Jang, S.Y., and Kim, Y.-H. (2016). Cerebrolysin combined with rehabilitation promotes motor recovery in patients with severe motor impairment after stroke. BMC Neurol., 16.","DOI":"10.1186\/s12883-016-0553-z"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1177\/0271678X18762636","article-title":"Longitudinal in\u00c2 vivo intrinsic optical imaging of cortical blood perfusion and tissue damage in focal photothrombosis stroke model","volume":"39","author":"Yang","year":"2018","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1172\/JCI200420001","article-title":"Neuronally expressed stem cell factor induces neural stem cell migration to areas of brain injury","volume":"113","author":"Sun","year":"2004","journal-title":"J. Clin. Investig."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"357","DOI":"10.4103\/1673-5374.153676","article-title":"Optimising repetitive transcranial magnetic stimulation for neural circuit repair following traumatic brain injury","volume":"10","author":"Rodger","year":"2015","journal-title":"Neural Regen. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1006\/nimg.1995.1023","article-title":"Analysis of fMRI Time-Series Revisited\u2014Again","volume":"2","author":"Worsley","year":"1995","journal-title":"NeuroImage"},{"key":"ref_8","first-page":"1369","article-title":"A combined PET\/CT scanner for clinical oncology","volume":"41","author":"Beyer","year":"2000","journal-title":"J. Nucl. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.cmpb.2013.08.014","article-title":"A model-based method for computation of correlation dimension, Lyapunov exponents and synchronization from depth-EEG signals","volume":"113","author":"Shayegh","year":"2014","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_10","first-page":"431","article-title":"Automated electroencephalographic analysis as a prognostic indicator in stroke","volume":"15","author":"Cohen","year":"1977","journal-title":"Med. Biol. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/0013-4694(76)90100-0","article-title":"Quantification of computer analyzed serial EEGs from stroke patients","volume":"41","author":"Cohen","year":"1976","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_12","first-page":"397","article-title":"Spectral EEG analysis following hemispheric stroke: Evidences of transhemispheric diaschisis","volume":"96","author":"Kamondi","year":"1997","journal-title":"Acta Neurol. Scand."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1097\/00004691-200107000-00002","article-title":"Localizing acute stroke-related EEG changes: Assessing the effects of spatial undersampling","volume":"18","author":"Luu","year":"2001","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1016\/j.clinph.2004.10.015","article-title":"Continuous energy variation during the seizure cycle: Towards an on-line accumulated energy","volume":"116","author":"Esteller","year":"2005","journal-title":"Clin. Neurophysiol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"046204","DOI":"10.1103\/PhysRevE.67.046204","article-title":"Indications of nonlinear structures in brain electrical activity","volume":"67","author":"Gautama","year":"2003","journal-title":"Phys. Rev. E"},{"key":"ref_16","first-page":"572","article-title":"Application of approximate entropy on dynamic characteristics of epileptic absence seizure","volume":"7","author":"Zhou","year":"2012","journal-title":"Neural Regen. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.medengphy.2005.07.004","article-title":"Analysis of EEG background activity in Alzheimer\u2019s disease patients with Lempel\u2013Ziv complexity and central tendency measure","volume":"28","author":"Hornero","year":"2006","journal-title":"Med. Eng. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Labate, D., Foresta, F.L., Mammone, N., and Morabito, F.C. (2015). Effects of Artifacts Rejection on EEG Complexity in Alzheimer\u2019s Disease, Springer International Publishing.","DOI":"10.1007\/978-3-319-18164-6_13"},{"key":"ref_19","unstructured":"Wu, H.J., Zheng, C.X., Zhang, J.W., and Zhang, H. (2003, January 20\u201322). In Nonlinear Entropy Analysis for Detecting Focal Cerebral Ischemia. Proceedings of the IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, Kyoto, Japan."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1016\/j.clinph.2008.01.104","article-title":"Abnormal EEG complexity in patients with schizophrenia and depression","volume":"119","author":"Li","year":"2008","journal-title":"Clin. Neurophysiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/1753-4631-3-6","article-title":"Comparative study of nonlinear properties of EEG signals of normal persons and epileptic patients","volume":"3","author":"Nurujjaman","year":"2009","journal-title":"Nonlinear Biomed. Phys."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"321","DOI":"10.4103\/1673-5374.200815","article-title":"Nonhuman primate models of focal cerebral ischemia","volume":"12","author":"Fan","year":"2017","journal-title":"Neural Regen Res."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Cl\u00e9ment, Y., Le Guisquet, A.-M., Venault, P., Chapouthier, G., and Belzung, C. (2009). Pharmacological Alterations of Anxious Behaviour in Mice Depending on Both Strain and the Behavioural Situation. PLoS ONE, 4.","DOI":"10.1371\/journal.pone.0007745"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis","volume":"134","author":"Delorme","year":"2004","journal-title":"J. Neurosci. Methods"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1073\/pnas.88.6.2297","article-title":"Approximate entropy as a measure of system complexity","volume":"88","author":"Pincus","year":"1991","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiol. Circ. Physiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1109\/TIT.1976.1055501","article-title":"On the Complexity of Finite Sequences","volume":"22","author":"Lempel","year":"1976","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1007\/s11760-012-0362-9","article-title":"Epileptic seizures detection in EEG using DWT-based ApEn and artificial neural network","volume":"8","author":"Kumar","year":"2014","journal-title":"Signal Image Video Process."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1016\/j.eswa.2007.12.065","article-title":"Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy","volume":"36","author":"Ocak","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1949","DOI":"10.1016\/S1388-2457(00)00435-1","article-title":"Power spectra and coherence in the EEG of a vegetative patient with severe asymmetric brain damage","volume":"111","author":"Davey","year":"2000","journal-title":"Clin. Neurophysiol."},{"key":"ref_31","unstructured":"Huang, L., Wang, Y., Liu, J., and Wang, J. (2004, January 1\u20135). Approximate entropy of EEG as a measure of cerebral ischemic injury. Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, CA, USA."},{"key":"ref_32","first-page":"48","article-title":"Determination of behavioral and cognitive dysfunction after moderate brain injury in rats","volume":"8","author":"Chen","year":"2004","journal-title":"Chin. Tissue Eng. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2087","DOI":"10.1360\/972012-1384","article-title":"Localization of brain injuries in vegetative and minimally conscious patients using symmetric electrode EEG analysis","volume":"58","author":"Li","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_34","first-page":"391","article-title":"Research progress in neuroplasticity and recovery of motor function after stroke","volume":"29","author":"Yuan","year":"2014","journal-title":"Chin. J. Rehabil. Med."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1161\/01.STR.0000250235.80253.e9","article-title":"Neurogenesis, angiogenesis, and MRI indices of functional recovery from stroke","volume":"38","author":"Michael","year":"2007","journal-title":"Stroke J. Cereb. Circ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1038\/sj.jcbfm.9600573","article-title":"Coupling of angiogenesis and neurogenesis in cultured endothelial cells and neural progenitor cells after stroke","volume":"28","author":"Teng","year":"2008","journal-title":"J. Cereb. Blood Flow Metab. Off. J. Int. Soc. Cereb. Blood Flow Metab."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/7\/698\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:06:07Z","timestamp":1760187967000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/7\/698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,16]]},"references-count":36,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["e21070698"],"URL":"https:\/\/doi.org\/10.3390\/e21070698","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,16]]}}}