Elias Ebrahimzadeh, Farahnaz Fayaz, Lila Rajabion, Masoud Seraji, Fatemeh Aflaki, Ahmad Hammoud, Zahra Taghizadeh, Mostafa Asgarinejad, Hamid Soltanian-Zadeh
{"title":"Machine learning approaches and non-linear processing of extracted components in frontal region to predict rTMS treatment response in major depressive disorder.","authors":"Elias Ebrahimzadeh, Farahnaz Fayaz, Lila Rajabion, Masoud Seraji, Fatemeh Aflaki, Ahmad Hammoud, Zahra Taghizadeh, Mostafa Asgarinejad, Hamid Soltanian-Zadeh","doi":"10.3389/fnsys.2023.919977","DOIUrl":"https://doi.org/10.3389/fnsys.2023.919977","url":null,"abstract":"<p><p>Predicting the therapeutic result of repetitive transcranial magnetic stimulation (rTMS) treatment could save time and costs as ineffective treatment can be avoided. To this end, we presented a machine-learning-based strategy for classifying patients with major depression disorder (MDD) into responders (R) and nonresponders (NR) to rTMS treatment. Resting state EEG data were recorded using 32 electrodes from 88 MDD patients before treatment. Then, patients underwent 7 weeks of rTMS, and 46 of them responded to treatment. By applying Independent Component Analysis (ICA) on EEG, we identified the relevant brain sources as possible indicators of neural activity in the dorsolateral prefrontal cortex (DLPFC). This was served through estimating the generators of activity in the sensor domain. Subsequently, we added physiological information and placed certain terms and conditions to offer a far more realistic estimation than the classic EEG. Ultimately, those components mapped in accordance with the region of the DLPFC in the sensor domain were chosen. Features extracted from the relevant ICs time series included permutation entropy (PE), fractal dimension (FD), Lempel-Ziv Complexity (LZC), power spectral density, correlation dimension (CD), features based on bispectrum, frontal and prefrontal cordance, and a combination of them. The most relevant features were selected by a Genetic Algorithm (GA). For classifying two groups of R and NR, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were applied to predict rTMS treatment response. To evaluate the performance of classifiers, a 10-fold cross-validation method was employed. A statistical test was used to assess the capability of features in differentiating R and NR for further research. EEG characteristics that can predict rTMS treatment response were discovered. The strongest discriminative indicators were EEG beta power, the sum of bispectrum diagonal elements in delta and beta bands, and CD. The Combined feature vector classified R and NR with a high performance of 94.31% accuracy, 92.85% specificity, 95.65% sensitivity, and 92.85% precision using SVM. This result indicates that our proposed method with power and nonlinear and bispectral features from relevant ICs time-series can predict the treatment outcome of rTMS for MDD patients only by one session pretreatment EEG recording. The obtained results show that the proposed method outperforms previous methods.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"919977"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034109/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9560078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nucleus incertus provides eye velocity and position signals to the vestibulo-ocular cerebellum: a new perspective of the brainstem-cerebellum-hippocampus network.","authors":"Guy Cheron, Laurence Ris, Ana Maria Cebolla","doi":"10.3389/fnsys.2023.1180627","DOIUrl":"https://doi.org/10.3389/fnsys.2023.1180627","url":null,"abstract":"<p><p>The network formed by the brainstem, cerebellum, and hippocampus occupies a central position to achieve navigation. Multiple physiological functions are implicated in this complex behavior. Among these, control of the eye-head and body movements is crucial. The gaze-holding system realized by the brainstem oculomotor neural integrator (ONI) situated in the nucleus prepositus hypoglossi and fine-tuned by the contribution of different regions of the cerebellum assumes the stability of the image on the fovea. This function helps in the recognition of environmental targets and defining appropriate navigational pathways further elaborated by the entorhinal cortex and hippocampus. In this context, an enigmatic brainstem area situated in front of the ONI, the nucleus incertus (NIC), is implicated in the dynamics of brainstem-hippocampus theta oscillation and contains a group of neurons projecting to the cerebellum. These neurons are characterized by burst tonic behavior similar to the burst tonic neurons in the ONI that convey eye velocity-position signals to the cerebellar flocculus. Faced with these forgotten cerebellar projections of the NIC, the present perspective discusses the possibility that, in addition to the already described pathways linking the cerebellum and the hippocampus via the medial septum, these NIC signals related to the vestibulo-ocular reflex and gaze holding could participate in the hippocampal control of navigation.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"1180627"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9617620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keith G Jones, Carter Lybbert, Matthew J Euler, Jason Huang, Seth Lunt, Sindhu V Richards, Jacob E Jessop, Adam Larson, David H Odell, Kai Kuck, Scott C Tadler, Brian J Mickey
{"title":"Diversity of electroencephalographic patterns during propofol-induced burst suppression.","authors":"Keith G Jones, Carter Lybbert, Matthew J Euler, Jason Huang, Seth Lunt, Sindhu V Richards, Jacob E Jessop, Adam Larson, David H Odell, Kai Kuck, Scott C Tadler, Brian J Mickey","doi":"10.3389/fnsys.2023.1172856","DOIUrl":"https://doi.org/10.3389/fnsys.2023.1172856","url":null,"abstract":"<p><p>Burst suppression is a brain state consisting of high-amplitude electrical activity alternating with periods of quieter suppression that can be brought about by disease or by certain anesthetics. Although burst suppression has been studied for decades, few studies have investigated the diverse manifestations of this state within and between human subjects. As part of a clinical trial examining the antidepressant effects of propofol, we gathered burst suppression electroencephalographic (EEG) data from 114 propofol infusions across 21 human subjects with treatment-resistant depression. This data was examined with the objective of describing and quantifying electrical signal diversity. We observed three types of EEG burst activity: canonical broadband bursts (as frequently described in the literature), spindles (narrow-band oscillations reminiscent of sleep spindles), and a new feature that we call low-frequency bursts (LFBs), which are brief deflections of mainly sub-3-Hz power. These three features were distinct in both the time and frequency domains and their occurrence differed significantly across subjects, with some subjects showing many LFBs or spindles and others showing very few. Spectral-power makeup of each feature was also significantly different across subjects. In a subset of nine participants with high-density EEG recordings, we noted that each feature had a unique spatial pattern of amplitude and polarity when measured across the scalp. Finally, we observed that the Bispectral Index Monitor, a commonly used clinical EEG monitor, does not account for the diversity of EEG features when processing the burst suppression state. Overall, this study describes and quantifies variation in the burst suppression EEG state across subjects and repeated infusions of propofol. These findings have implications for the understanding of brain activity under anesthesia and for individualized dosing of anesthetic drugs.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"1172856"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10309040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9746062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Arousal system stimulation and anesthetic state alter visuoparietal connectivity.","authors":"Axel Hutt, Anthony G Hudetz","doi":"10.3389/fnsys.2023.1157488","DOIUrl":"https://doi.org/10.3389/fnsys.2023.1157488","url":null,"abstract":"<p><p>Cortical information processing is under the precise control of the ascending arousal system (AAS). Anesthesia suppresses cortical arousal that can be mitigated by exogenous stimulation of the AAS. The question remains to what extent cortical information processing is regained by AAS stimulation. We investigate the effect of electrical stimulation of the nucleus Pontis Oralis (PnO), a distinct source of ascending AAS projections, on cortical functional connectivity (FC) and information storage at mild, moderate, and deep anesthesia. Local field potentials (LFPs) recorded previously in the secondary visual cortex (V2) and the adjacent parietal association cortex (PtA) in chronically instrumented unrestrained rats. We hypothesized that PnO stimulation would induce electrocortical arousal accompanied by enhanced FC and active information storage (AIS) implying improved information processing. In fact, stimulation reduced FC in slow oscillations (0.3-2.5 Hz) at low anesthetic level and increased FC at high anesthetic level. These effects were augmented following stimulation suggesting stimulus-induced plasticity. The observed opposite stimulation-anesthetic impact was less clear in the γ-band activity (30-70 Hz). In addition, FC in slow oscillations was more sensitive to stimulation and anesthetic level than FC in γ-band activity which exhibited a rather constant spatial FC structure that was symmetric between specific, topographically related sites in V2 and PtA. Invariant networks were defined as a set of strongly connected electrode channels, which were invariant to experimental conditions. In invariant networks, stimulation decreased AIS and increasing anesthetic level increased AIS. Conversely, in non-invariant (complement) networks, stimulation did not affect AIS at low anesthetic level but increased it at high anesthetic level. The results suggest that arousal stimulation alters cortical FC and information storage as a function of anesthetic level with a prolonged effect beyond the duration of stimulation. The findings help better understand how the arousal system may influence information processing in cortical networks at different levels of anesthesia.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"1157488"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9410437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Erratum: Electrophysiological markers of fairness and selfishness revealed by a combination of dictator and ultimatum games.","authors":"","doi":"10.3389/fnsys.2023.1186493","DOIUrl":"https://doi.org/10.3389/fnsys.2023.1186493","url":null,"abstract":"[This corrects the article DOI: 10.3389/fnsys.2022.765720.].","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"1186493"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9289470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Imaging the cerebellum in post-traumatic stress and anxiety disorders: a mini-review.","authors":"Patricia Gil-Paterna, Tomas Furmark","doi":"10.3389/fnsys.2023.1197350","DOIUrl":"https://doi.org/10.3389/fnsys.2023.1197350","url":null,"abstract":"<p><p>Post-traumatic stress disorder (PTSD) and anxiety disorders are among the most prevalent psychiatric conditions worldwide sharing many clinical manifestations and, most likely, neural mechanisms as suggested by neuroimaging research. While the so-called fear circuitry and traditional limbic structures of the brain, particularly the amygdala, have been extensively studied in sufferers of these disorders, the cerebellum has been relatively underexplored. The aim of this paper was to present a mini-review of functional (task-activity or resting-state connectivity) and structural (gray matter volume) results on the cerebellum as reported in magnetic resonance imaging studies of patients with PTSD or anxiety disorders (49 selected studies in 1,494 patients). While mixed results were noted overall, e.g., regarding the direction of effects and anatomical localization, cerebellar structures like the vermis seem to be highly involved. Still, the neurofunctional and structural alterations reported for the cerebellum in excessive anxiety and trauma are complex, and in need of further evaluation.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"17 ","pages":"1197350"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10123404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}