Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference.

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

Optimal Surgical Extent for Memory and Seizure Outcome in Temporal Lobe Epilepsy.

OBJECTIVE: Postoperative memory decline is an important consequence of anterior temporal lobe resection (ATLR) for temporal lobe epilepsy (TLE), and the extent of resection may be a modifiable factor. This study aimed to define optimal resection margins for cognitive outcome while maintaining a high rate of postoperative seizure freedom. METHODS: This cohort study evaluated the resection extent on postoperative structural MRI using automated voxel-based methods and manual measurements in 142 consecutive patients with unilateral drug refractory TLE (74 left, 68 right TLE) who underwent standard ATLR. RESULTS: Voxel-wise analyses revealed that postsurgical verbal memory decline correlated with resections of the posterior hippocampus and inferior temporal gyrus, whereas larger resections of the fusiform gyrus were associated with worsening of visual memory in left TLE. Limiting the posterior extent of left hippocampal resection to 55% reduced the odds of significant postoperative verbal memory decline by a factor of 8.1 (95% CI 1.5-44.4, p = 0.02). Seizure freedom was not related to posterior resection extent, but to the piriform cortex removal after left ATLR. In right TLE, variability of the posterior extent of resection was not associated with verbal and visual memory decline or seizures after surgery. INTERPRETATION: The extent of surgical resection is an independent and modifiable risk factor for cognitive decline and seizures after left ATLR. Adapting the posterior extent of left ATLR might optimize postoperative outcome, with reduced risk of memory impairment while maintaining comparable seizure-freedom rates. The current, more lenient, approach might be appropriate for right ATLR. ANN NEUROL 2022;91:131-144.

Contribution of the µ-opioid receptor system to affective disorders in temporal lobe epilepsy: A bidirectional relationship?

OBJECTIVE: Affective disorders are frequent comorbidities of temporal lobe epilepsy (TLE). The endogenous opioid system has been implicated in both epilepsy and affective disorders, and may play a significant role in their bidirectional relationship. In this cross-sectional study, we investigated the association between µ-opioid receptor binding and affective disorders in patients with TLE. METHODS: Nine patients with TLE and depression/anxiety underwent 11 C-carfentanil positron emission tomography (CFN PET) and neuropsychiatric assessment, including the Hospital Anxiety and Depression Scale and the Positive and Negative Affect Schedule. The normalized CFN PET scans were compared with those of 26 age-matched healthy controls. Correlation analyses with affective symptoms were performed by region of interest-based analysis focusing on the limbic circuit and orbitofrontal cortex. RESULTS: We observed widely reduced CFN binding potential (BP) in bilateral frontal lobes and striata in patients with TLE compared to healthy controls. In the TLE group, more severe anxiety and negative affect were associated with decreased CFN BP in the posterior cingulate gyrus. SIGNIFICANCE: In patients with TLE, interictally reduced binding in the opioid system was associated with higher levels of anxiety and negative affect. We speculate that seizure-related agonist-driven desensitization and downregulation of opioid receptors could be a potential underlying pathomechanism.

Neuropsychiatric aspects of long COVID: A comprehensive review.

Although some patients have persistent symptoms or develop new symptoms following coronavirus disease 2019 (COVID-19) infection, neuropsychiatric aspects of long COVID are not well known. This review summarizes and provides an update on the neuropsychiatric dimensions of long COVID. Its neuropsychiatric manifestations commonly include fatigue, cognitive impairment, sleep disorders, depression, anxiety, and post-traumatic stress disorder. There are no specific tests for long COVID, but some characteristic findings such as hypometabolism on positron emission tomography have been reported. The possible mechanisms of long COVID include inflammation, ischemic effects, direct viral invasion, and social and environmental changes. Some patient characteristics and the severity and complications of acute COVID-19 infection may be associated with an increased risk of neuropsychiatric symptoms. Long COVID may resolve spontaneously or persist, depending on the type of neuropsychiatric symptoms. Although established treatments are lacking, various psychological and pharmacological treatments have been attempted. Vaccination against COVID-19 infection plays a key role in the prevention of long coronavirus disease. With differences among the SARS-CoV-2 variants, including the omicron variant, the aspects of long COVID are likely to change in the future. Further studies clarifying the aspects of long COVID to develop effective treatments are warranted.

Neuroimaging-based brain-age prediction in diverse forms of epilepsy: a signature of psychosis and beyond.

Epilepsy is a diverse brain disorder, and the pathophysiology of its various forms and comorbidities is largely unknown. A recent machine learning method enables us to estimate an individual's "brain-age" from MRI; this brain-age prediction is expected as a novel individual biomarker of neuropsychiatric disorders. The aims of this study were to estimate the brain-age for various categories of epilepsy and to evaluate clinical discrimination by brain-age for (1) the effect of psychosis on temporal lobe epilepsy (TLE), (2) psychogenic nonepileptic seizures (PNESs) from MRI-negative epilepsies, and (3) progressive myoclonic epilepsy (PME) from juvenile myoclonic epilepsy (JME). In total, 1196 T1-weighted MRI scans from healthy controls (HCs) were used to build a brain-age prediction model with support vector regression. Using the model, we calculated the brain-predicted age difference (brain-PAD: predicted age-chronological age) of the HCs and 318 patients with epilepsy. We compared the brain-PAD values based on the research questions. As a result, all categories of patients except for extra-temporal lobe focal epilepsy showed a significant increase in brain-PAD. TLE with hippocampal sclerosis presented a significantly higher brain-PAD than several other categories. The mean brain-PAD in TLE with inter-ictal psychosis was 10.9 years, which was significantly higher than TLE without psychosis (5.3 years). PNES showed a comparable mean brain-PAD (10.6 years) to that of epilepsy patients. PME had a higher brain-PAD than JME (22.0 vs. 9.3 years). In conclusion, neuroimaging-based brain-age prediction can provide novel insight into or clinical usefulness for the diverse symptoms of epilepsy.

Barriers to telemedicine among physicians in epilepsy care during the COVID-19 pandemic: A national-level cross-sectional survey in Japan.

OBJECTIVE: This study aimed to investigate the factors affecting the unwillingness of physicians involved in epilepsy care to continue telemedicine during the coronavirus disease 2019 (COVID-19) pandemic in Japan. METHOD: This was a national-level cross-sectional survey initiated by Japan Young Epilepsy Section (YES-Japan) which is a national chapter of The Young Epilepsy Section of the International League Against Epilepsy (ILAE-YES). We asked physicians who conducted telemedicine in patients with epilepsy (PWE) during the COVID-19 pandemic at four clinics and 21 hospitals specializing in epilepsy care in Japan from March 1 to April 30, 2021. The following data were collected: (1) participant profile, (2) characteristics of PWE treated by telemedicine, and (3) contents and environmental factors of telemedicine. Statistically significant variables (p < 0.05) in the univariate analysis were analyzed in a multivariate binary logistic regression model to detect the independently associated factors with the unwillingness to continue telemedicine. RESULT: Among the 115 respondents (response rate: 64%), 89 were included in the final analysis. Of them, 60 (67.4%) were willing to continue telemedicine, and 29 (32.6%) were unwilling. In the univariate binary logistic regression analysis, age (Odds ratio [OR] = 1.84, 95% confidence interval [CI] 1.10-3.09, p = 0.02), psychiatrist (OR = 5.88, 95% CI 2.15-16.08, p = 0.001), hospital (OR = 0.10, 95% CI 0.01-0.94, p = 0.04), the number of COVID-19 risk factors in the participant (OR = 2.88, 95% CI 1.46-5.69, p = 0.002), the number of COVID-19 risk factors in the cohabitants (OR = 2.52, 95% CI 1.05-6.01, p = 0.04), COVID-19 epidemic area (OR = 4.37, 95% CI 1.18-16.20, p = 0.03), consultation time during telemedicine (OR = 2.51, 95% CI 1.32-4.76, p = 0.005), workload due to telemedicine (OR = 4.17, 95% CI 2.11-8.24, p < 0.001) were statistically significant. In the multivariate binary logistic regression analysis, workload due to telemedicine (OR = 4.93, 95% CI 1.96-12.35) was independently associated with the unwillingness to continue telemedicine. CONCLUSION: This national-level cross-sectional survey found that workload due to telemedicine among physicians involved in epilepsy care was independently associated with the unwillingness to continue telemedicine.

Risk factors for psychological distress in electroencephalography technicians during the COVID-19 pandemic: A national-level cross-sectional survey in Japan.

OBJECTIVE: To identify the risk factors for psychological distress in electroencephalography (EEG) technicians during the coronavirus disease 2019 (COVID-19) pandemic. METHOD: In this national-level cross-sectional survey initiated by Japan Young Epilepsy Section (YES-Japan), which is a national chapter of The Young Epilepsy Section of the International League Against Epilepsy (ILAE-YES), a questionnaire was administered to 173 technicians engaged in EEG at four clinics specializing in epilepsy care and 20 hospitals accredited as (quasi-) epilepsy centers or epilepsy training facilities in Japan from March 1 to April 30, 2021. We collected data on participants' profiles, information about work, and psychological distress outcome measurements, such as the K-6 and Tokyo Metropolitan Distress Scale for Pandemic (TMDP). Linear regression analysis was used to identify the risk factors for psychological distress. Factors that were significantly associated with psychological distress in the univariate analysis were subjected to multivariate analysis. RESULTS: Among the 142 respondents (response rate: 82%), 128 were included in the final analysis. As many as 35.2% of EEG technicians have been under psychological distress. In multivariate linear regression analysis for K-6, female sex, examination for patients (suspected) with COVID-19, and change in salary or bonus were independent associated factors for psychological distress. Contrastingly, in multivariate linear regression analysis for TMDP, female sex, presence of cohabitants who had to be separated from the respondent due to this pandemic, and change in salary or bonus were independent associated factors for psychological distress. CONCLUSION: We successfully identified the risk factors associated with psychological distress in EEG technicians during the COVID-19 pandemic. Our results may help in understanding the psychological stress in EEG technicians during the COVID-19 pandemic and improving the work environment, which is necessary to maintain the mental health of EEG technicians.

Automated Volumetry of Medial Temporal Lobe Subregions in Mild Cognitive Impairment and Alzheimer Disease.

PURPOSE: Hippocampal subfield volumetry should be more useful than whole hippocampal (WH) volumetry for diagnosing Alzheimer disease (AD). This study sought to confirm this. METHODS: We investigated cognitively normal (CN) participants and patients with mild cognitive impairment (MCI) or AD using high-resolution T2-weighted and 3-dimensional T1-weighted magnetic resonance imaging. Using medial temporal subregion volumetry, we investigated discriminative power for MCI and AD versus CN. PATIENTS: We recruited 30 CN participants, 30 amnestic MCI patients, and 49 AD patients between April 2015 and October 2016. RESULTS: For AD, discriminative power of the combined volumes of the subiculum, entorhinal cortex, and cornu ammonis 1 was highest [area under the curve (AUC)=0.915; 85.7% sensitivity, 86.7% specificity, 86.1% accuracy], and was significantly higher than that of the WH volume (AUC=0.887; 90.0% sensitivity, 75.5% specificity, 84.5% accuracy) (P=0.019). For MCI, discriminative power of the subiculum volume was highest (AUC=0.747; 80.0% sensitivity, 73.3% specificity, 76.7% accuracy), but was only slightly higher than that of the WH volume (AUC=0.730; 56.7% sensitivity, 90.0% specificity, 73.3% accuracy). CONCLUSIONS: Using the combined volumes of the subiculum, entorhinal cortex, and cornu ammonis 1 may enable greater diagnostic accuracy compared with the WH volume or any single subfield in AD patients.

Brain morphological and microstructural features in cryptogenic late-onset temporal lobe epilepsy: a structural and diffusion MRI study.

PURPOSE: Although epilepsy in the elderly has attracted attention recently, there are few systematic studies of neuroimaging in such patients. In this study, we used structural MRI and diffusion tensor imaging (DTI) to investigate the morphological and microstructural features of the brain in late-onset temporal lobe epilepsy (TLE). METHODS: We recruited patients with TLE and an age of onset > 50 years (late-TLE group) and age- and sex-matched healthy volunteers (control group). 3-Tesla MRI scans, including 3D T1-weighted images and 15-direction DTI, showed normal findings on visual assessment in both groups. We used Statistical Parametric Mapping 12 (SPM12) for gray and white matter structural normalization and comparison and used Tract-Based Spatial Statistics (TBSS) for fractional anisotropy and mean diffusivity comparisons of DTI. In both methods, p < 0.05 (family-wise error) was considered statistically significant. RESULTS: In total, 30 patients with late-onset TLE (mean ± SD age, 66.8 ± 8.4; mean ± SD age of onset, 63.0 ± 7.6 years) and 40 healthy controls (mean ± SD age, 66.6 ± 8.5 years) were enrolled. The late-onset TLE group showed significant gray matter volume increases in the bilateral amygdala and anterior hippocampus and significantly reduced mean diffusivity in the left temporofrontal lobe, internal capsule, and brainstem. No significant changes were evident in white matter volume or fractional anisotropy. CONCLUSIONS: Our findings may reflect some characteristics or mechanisms of cryptogenic TLE in the elderly, such as inflammatory processes.

Marked accumulation of oligodendroglia-like cells in temporal lobe epilepsy with amygdala enlargement and hippocampal sclerosis.

Although an increasing number of cases of temporal lobe epilepsy (TLE) with ipsilateral amygdala enlargement (AE) have been reported, there are few pathological reports, and no clear consensus has been established. Oligodendroglia or oligodendroglia-like cells (OLCs) have recently attracted attention in epilepsy studies. Here, we report the clinical and pathological findings of a 40-year-old male TLE patient with AE and hippocampal sclerosis, in whom histopathological study demonstrated remarkable clustering of OLCs around the uncus. The patient began to have refractory seizures at the age of 14, and preoperative MRI revealed left amygdala enlargement and left hippocampal atrophy. Other examinations were consistent with left mesial temporal epileptogenicity. He underwent surgical resection and achieved seizure freedom. Histopathological study of the amygdala showed swollen neurons with relatively large bodies and thick neurites, accompanied by vacuolar degeneration in the background. Additionally, there were marked clusters of OLCs with round nuclei and densely stained chromatin around the uncus. The OLCs were Olig2-positive. In the hippocampus, severe cell loss in CA1 and granule cell dispersion in the dentate gyrus were found. These findings may provide some insights for further pathological investigations of TLE with non-neoplastic AE.

Computed-tomography-guided anatomic standardization for quantitative assessment of dopamine transporter SPECT.

PURPOSE: For the quantitative assessment of dopamine transporter (DAT) using [123I]FP-CIT single-photon emission computed tomography (SPECT) (DaTscan), anatomic standardization is preferable for achieving objective and user-independent quantification of striatal binding using a volume-of-interest (VOI) template. However, low accumulation of DAT in Parkinson's disease (PD) would lead to a deformation error when using a DaTscan-specific template without any structural information. To avoid this deformation error, we applied computed tomography (CT) data obtained using SPECT/CT equipment to anatomic standardization. METHODS: We retrospectively analyzed DaTscan images of 130 patients with parkinsonian syndromes (PS), including 80 PD and 50 non-PD patients. First we segmented gray matter from CT images using statistical parametric mapping 12 (SPM12). These gray-matter images were then anatomically standardized using the diffeomorphic anatomical registration using exponentiated Lie algebra (DARTEL) algorithm. Next, DaTscan images were warped with the same parameters used in the CT anatomic standardization. The target striatal VOIs for decreased DAT in PD were generated from the SPM12 group comparison of 20 DaTscan images from each group. We applied these VOIs to DaTscan images of the remaining patients in both groups and calculated the specific binding ratios (SBRs) using nonspecific counts in a reference area. In terms of the differential diagnosis of PD and non-PD groups using SBR, we compared the present method with two other methods, DaTQUANT and DaTView, which have already been released as software programs for the quantitative assessment of DaTscan images. RESULTS: The SPM12 group comparison showed a significant DAT decrease in PD patients in the bilateral whole striatum. Of the three methods assessed, the present CT-guided method showed the greatest power for discriminating PD and non-PD groups, as it completely separated the two groups. CONCLUSION: CT-guided anatomic standardization using the DARTEL algorithm is promising for the quantitative assessment of DaTscan images.

Intraventricular temperature measured by diffusion-weighted imaging compared with brain parenchymal temperature measured by MRS in vivo.

We examined and compared the temperatures of the intraventricular cerebrospinal fluid (Tv ) and the brain parenchyma (Tp ) using MRI, with reference to the tympanic membrane temperature (Tt ) in healthy subjects. We estimated Tv and Tp values from data gathered simultaneously by MR diffusion-weighted imaging (DWI) and MRS, respectively, in 35 healthy volunteers (17 males, 18 females; age 25-78 years). We also obtained Tt values just before each MR examination to evaluate the relationships among the three temperatures. There were significant positive correlations between Tv and Tp (R = 0.611, p < 0.001). The correlation was also significant after correction for Tt (R = 0.642, p < 0.001). There was no significant correlation between Tv and Tt or between Tp and Tt in the men or the women. Negative correlations were found between Tv and age and between Tp and age in the males but not females. DWI thermometry seems to reflect the intracranial environment as accurately as MRS thermometry. An age-dependent decline in temperature was evident in our male subjects by both DWI and MRS thermometry, probably due to the decrease in cerebral metabolism with age. Copyright © 2016 John Wiley & Sons, Ltd.

Impaired cerebral blood flow networks in temporal lobe epilepsy with hippocampal sclerosis: A graph theoretical approach.

Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE.

Chronic periodic lateralised epileptic discharges and anti-N-methyl-D-aspartate receptor antibodies.

Periodic lateralised epileptiform discharges (PLEDs) are uncommon transient electroencephalographic findings accompanied by acute brain lesions. A small proportion of PLEDs persist for more than three months and are called "chronic" PLEDs, the pathophysiology of which is still debated. Herein, we report a man with right hemispheric PLEDs which lasted for more than 14 months and mild left hemispatial neglect after he experienced status epilepticus. Although MRI was normal, positron emission tomography revealed right temporo-parieto-occipital hypometabolism, which coincided with the source area of PLEDs estimated by magnetoencephalography. In addition, levels of anti-N-methyl-D-aspartate (NMDA) receptor antibodies and granzyme B were found to be high in the cerebrospinal fluid. Following two courses of steroid pulse therapy, the patient's left spatial neglect improved and the PLEDs were partially resolved. These findings suggest that the chronic PLEDs present in this case were an interictal phenomenon and that their pathophysiology involved autoimmune processes.

Glymphatic System Activity and Brain Morphology in Patients With Psychogenic Non-epileptic Seizures.

BACKGROUND: To clarify the neural correlates underlying psychogenic non-epileptic seizures (PNES), we compared glymphatic system activity between patients with PNES and healthy participants using diffusion tensor imaging (DTI)-analysis along the perivascular space (ALPS) method. METHODS: The DTI scans were acquired from 16 patients with PNES and 25 healthy participants. We computed the DTI-ALPS index as an index of glymphatic system function and estimated the disease-related changes in the DTI-ALPS index and brain structures in PNES patients. RESULTS: There were no significant differences in the DTI-ALPS index between patients with PNES and healthy participants. On the other hand, patients with PNES had decreased fractional anisotropy values in the bilateral posterior cingula, a higher mean diffusivity value around the left insula, and a lower gray matter volume in the bilateral amygdalae compared with healthy participants. CONCLUSIONS: Patients with PNES exhibited an impairment of white matter integrity and a reduction of gray matter volume, but no glymphatic-system changes. These findings will play a significant role in our comprehension of this complex illness.

Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging.

Background: Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics. Objective: The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics. Methods: Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics. Results: Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology. Conclusions: This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.

Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance.

BACKGROUND AND HYPOTHESIS: Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. STUDY DESIGN: In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis. STUDY RESULTS: SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009). CONCLUSIONS: The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.

[Epilepsy in the Elderly Population: Clinical Practice and Recent Updates].

Optimal medical care and welfare is an urgent issue among the elderly population in a rapidly aging society. Epilepsy is a common chronic neurological disorder that affects all ages with peaks observed in children and in elderly individuals. Considering rapid population aging, the prevalence of epilepsy in the elderly population is expected to increase in the future. Clinicians should be aware of the clinical features of epilepsy in elderly patients because these differ from those observed in young patients from several perspectives. In this article, we review the clinical practice and recent updates in epilepsy in the elderly population. Epilepsy in elderly patients requires careful attention to subtle seizure symptoms and electroencephalography findings, and this disorder is associated with a wide range of differential diagnosis. Treatment is primarily pharmacological, and seizures may often be well controlled. Etiologies include dementia and cerebrovascular disease; however, a few patients may present with epilepsy secondary to an unknown cause. Psychosocial issues such as driver's license and stigma are also important.

White Matter Structural Connectivity and Its Impact on Psychogenic Non-Epileptic Seizures: An Evidence-Based Review.

Psychiatric non-epileptic seizure (PNES), also known as a form of functional neurological disorders (FND), is a common but still underrecognized disorder presenting seizure-like symptoms and no electrophysiological abnormality. Despite the significant burden of this disorder, the neurobiological mechanisms are not clearly understood, which hinders the development of better diagnosis and treatment. In the recent neuroimaging research on PNES, brain network analysis has become a relevant topic beyond conventional methodologies. The human brain is a highly intricate system of interconnected regions that collaborate to facilitate a wide range of cognitive and behavioral functions. White matter tracts, which are comprised of bundles of axonal fibers, are the primary means by which information is transmitted between different brain regions. As such, comprehending the organization and structure of the brain's white matter network is critical for gaining insight into its functional architecture. This review article aims to provide an overview of the brain mechanisms underlying PNES, with a special focus on analyzing brain networks.