{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,12]],"date-time":"2026-11-12T08:18:51Z","timestamp":1794471531007,"version":"4.9.1"},"reference-count":58,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:00:00Z","timestamp":1779235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In Parkinson disease (PD), enhanced beta frequency band activity in cortico-basal ganglia networks has been proposed as a possible biomarker for adaptive deep brain stimulation (DBS). Previous studies demonstrated enhanced beta frequency peaks both in the acute Haloperidol (HALO) and the chronic 6-hydroxydopamine (6-OHDA) rat models of parkinsonism. Beta peaks decreased after apomorphine (APO) injection or with DBS of the subthalamic nucleus (STN).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We investigate changes in motor cortical oscillatory activity using fractal dimension (FD) in the HALO and the 6-OHDA rat models of PD. Additionally, we test a support vector machine (SVM) model to predict neuronal dynamics in the 6-OHDA PD model which has been used earlier in an acute rat model of PD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In the HALO model, electrocorticogram (ECoG) was recorded from the motor cortex (MCtx) (1) during basal activity, (2) after injection of HALO (0.5 mg\/kg), and (3) after subsequent APO injection (1 mg\/kg). For the chronic 6-OHDA model, MCtx-ECoG recordings were obtained (1) during basal activity, and (2) during STN DBS. Higuchi's FD algorithm and SVM-based classification were utilized for analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Average FD values in the MCtx were higher in both PD models compared to controls (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.001). APO injection (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.001) and STN DBS (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt; 0.05) reduced average FD values in both models. The SVM model achieved 80% classification accuracy and an AUC of 0.86 in the 6-OHDA rat model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The non-linear analysis of FD reveals changes in cortical oscillatory patterns in rodent models of PD. SVM-based predictions demonstrate potential for classifying altered neural activity, which may offer future strategies for adaptive DBS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1816020","type":"journal-article","created":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T04:43:39Z","timestamp":1779252219000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Complexity of fractal dimension patterns and machine learning-based classification of altered motor cortical oscillatory activity in rodent models of Parkinson disease"],"prefix":"10.3389","volume":"17","author":[{"given":"Mesbah","family":"Alam","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Hannover Medical School","place":["Hannover, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arif","family":"Abdulbaki","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, 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