Adult Inception of Ketogenic Diet Therapy Increases Sleep during the Dark Cycle in C57BL/6J Wild Type and Fragile X Mice.

Sleep problems are a significant phenotype in children with fragile X syndrome. Our prior work assessed sleep-wake cycles in Fmr1KO male mice and wild type (WT) littermate controls in response to ketogenic diet therapy where mice were treated from weaning (postnatal day 18) through study completion (5-6 months of age). A potentially confounding issue with commencing treatment during an active period of growth is the significant reduction in weight gain in response to the ketogenic diet. The aim here was to employ sleep electroencephalography (EEG) to assess sleep-wake cycles in mice in response to the Fmr1 genotype and a ketogenic diet, with treatment starting at postnatal day 95. EEG results were compared with prior sleep outcomes to determine if the later intervention was efficacious, as well as with published rest-activity patterns to determine if actigraphy is a viable surrogate for sleep EEG. The data replicated findings that Fmr1KO mice exhibit sleep-wake patterns similar to wild type littermates during the dark cycle when maintained on a control purified-ingredient diet but revealed a genotype-specific difference during hours 4-6 of the light cycle of the increased wake (decreased sleep and NREM) state in Fmr1KO mice. Treatment with a high-fat, low-carbohydrate ketogenic diet increased the percentage of NREM sleep in both wild type and Fmr1KO mice during the dark cycle. Differences in sleep microstructure (length of wake bouts) supported the altered sleep states in response to ketogenic diet. Commencing ketogenic diet treatment in adulthood resulted in a 15% (WT) and 8.6% (Fmr1KO) decrease in body weight after 28 days of treatment, but not the severe reduction in body weight associated with starting treatment at weaning. We conclude that the lack of evidence for improved sleep during the light cycle (mouse sleep time) in Fmr1KO mice in response to ketogenic diet therapy in two studies suggests that ketogenic diet may not be beneficial in treating sleep problems associated with fragile X and that actigraphy is not a reliable surrogate for sleep EEG in mice.

Seizure Assessment and Forecasting With Efficient Rapid-EEG: A Retrospective Multicenter Comparative Effectiveness Study.

BACKGROUND AND OBJECTIVES: Approximately 30% of critically ill patients have seizures, and more than half of these seizures do not have an overt clinical correlate. EEG is needed to avoid missing seizures and prevent overtreatment with antiseizure medications. Conventional-EEG (cEEG) resources are logistically constrained and unable to meet their growing demand for seizure detection even in highly developed centers. Brief EEG screening with the validated 2HELPS2B algorithm was proposed as a method to triage cEEG resources, but it is hampered by cEEG requirements, primarily EEG technologists. Seizure risk-stratification using reduced time-to-application rapid response-EEG (rrEEG) systems (∼5 minutes) could be a solution. We assessed the noninferiority of the 2HELPS2B score on a 1-hour rrEEG compared to cEEG. METHODS: A multicenter retrospective EEG diagnostic accuracy study was conducted from October 1, 2021, to July 31, 2022. Chart and EEG review performed with consecutive sampling at 4 tertiary care centers, included records of patients ≥18 years old, from January 1, 2018, to June 20, 2022. Monte Carlo simulation power analysis yielded n = 500 rrEEG; for secondary outcomes n = 500 cEEG and propensity-score covariate matching was planned. Primary outcome, noninferiority of rrEEG for seizure risk prediction, was assessed per area under the receiver operator characteristic curve (AUC). Noninferiority margin (0.05) was based on the 2HELPS2B validation study. RESULTS: A total of 240 rrEEG with follow-on cEEG were obtained. Median age was 64 (interquartile range 22); 42% were female. 2HELPS2B on a 1-hour rrEEG met noninferiority to cEEG (AUC 0.85, 95% CI 0.78-0.90, p = 0.001). Secondary endpoints of comparison with a matched contemporaneous cEEG showed no significant difference in AUC (0.89, 95% CI 0.83-0.94, p = 0.31); in false negative rate for the 2HELPS2B = 0 group (p = 1.0) rrEEG (0.021, 95% CI 0-0.062), cEEG (0.016, 95% CI 0-0.048); nor in survival analyses. DISCUSSION: 2HELPS2B on 1-hour rrEEG is noninferior to cEEG for seizure prediction. Patients with low-risk (2HELPS2B = 0) may be able to forgo prolonged cEEG, allowing for increased monitoring of at-risk patients. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.

Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice.

Nearly half of children with fragile X syndrome experience sleep problems including trouble falling asleep and frequent nighttime awakenings. The goals here were to assess sleep-wake cycles in mice in response to Fmr1 genotype and a dietary intervention that reduces hyperactivity. Electroencephalography (EEG) results were compared with published rest-activity patterns to determine if actigraphy is a viable surrogate for sleep EEG. Specifically, sleep-wake patterns in adult wild type and Fmr1KO littermate mice were recorded after EEG electrode implantation and the recordings manually scored for vigilance states. The data indicated that Fmr1KO mice exhibited sleep-wake patterns similar to wild type littermates when maintained on a control purified ingredient diet. Treatment with a high-fat, low-carbohydrate ketogenic diet increased the percentage of non-rapid eye movement (NREM) sleep in both wild type and Fmr1KO mice during the dark cycle, which corresponded to decreased activity levels. Treatment with a ketogenic diet flattened diurnal sleep periodicity in both wild type and Fmr1KO mice. Differences in several sleep microstructure outcomes (number and length of sleep and wake bouts) supported the altered sleep states in response to a ketogenic diet and were correlated with altered rest-activity cycles. While actigraphy may be a less expensive, reduced labor surrogate for sleep EEG during the dark cycle, daytime resting in mice did not correlate with EEG sleep states.

Multi-shell connectome DWI-based graph theory measures for the prediction of temporal lobe epilepsy and cognition.

Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE. SVM was able to predict group membership (mean accuracy = 0.70, area under the curve (AUC) = 0.747, Brier score (BS) = 0.264) using 10-fold cross-validation. In addition, k-means clustering identified 2 TLE clusters: 1 similar to controls, and 1 dissimilar. Clusters were significantly different in their distribution of cognitive phenotypes, with the Dissimilar cluster containing the majority of TLE with cognitive impairment (χ2 = 6.641, P = 0.036). In addition, cluster membership showed significant correlations between GT measures and clinical variables. Given that SVM classification seemed driven by the Dissimilar cluster, SVM analysis was repeated to classify Dissimilar versus Similar + Controls with a mean accuracy of 0.91 (AUC = 0.957, BS = 0.189). Altogether, the pattern of results shows that GT measures based on connectome DWI could be significant factors in the search for clinical and neurobehavioral biomarkers in TLE.

Late dominance of the right hemisphere during narrative comprehension.

PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.

Dual orexin antagonist normalized sleep homeostatic drive, enhanced GABAergic inhibition, and suppressed seizures after traumatic brain injury.

STUDY OBJECTIVES: Traumatic brain injury (TBI) can result in posttraumatic epilepsy (PTE) and sleep disturbances. We hypothesized that treatment with sleep aids after TBI can ameliorate PTE. METHODS: CD-1 mice underwent controlled cortical impact (CCI), sham injury, or no craniotomy. Sham and CCI groups underwent a monthlong daily treatment with sleep aids including a dual orexin antagonist (DORA-22) or THIP (gaboxadol) or a respective vehicle starting on the day of CCI. We performed continuous EEG (electroencephalography) recordings at week 1 and months 1, 2, and 3 for ~1 week each time. Seizure analysis occurred at all-time points and sleep analysis occurred in week 1 and month-1/2 in all groups. Subsets of CCI and sham groups were subjected to voltageclamp experiments in hippocampal slices to evaluate GABAergic synaptic inhibition. RESULTS: DORA-22 treatment suppressed seizures in month 1-3 recordings. TBI reduced the amplitude and frequency of miniature inhibitory synaptic currents (mIPSCs) in dentate granule cells and these changes were rescued by DORA-22 treatment. Sleep analysis showed that DORA-22 increased nonrapid eye movement (NREM) sleep during lights-off whereas THIP increased REM sleep during lights-on in week 1. Both treatments displayed subtle changes in time spent in NREM or REM at month-1/2 as well. TBI not only increased normalized EEG delta power (NΔ) at week-1 and month-1 but also resulted in the loss of the homeostatic diurnal oscillation of NΔ, which was restored by DORA-22 but not THIP treatment. CONCLUSIONS: Dual orexin antagonists may have a therapeutic potential in suppressing PTE potentially by enhancing GABAergic inhibition and impacting sleep homeostatic drive.

Network phenotypes and their clinical significance in temporal lobe epilepsy using machine learning applications to morphological and functional graph theory metrics.

Machine learning analyses were performed on graph theory (GT) metrics extracted from brain functional and morphological data from temporal lobe epilepsy (TLE) patients in order to identify intrinsic network phenotypes and characterize their clinical significance. Participants were 97 TLE and 36 healthy controls from the Epilepsy Connectome Project. Each imaging modality (i.e., Resting-state functional Magnetic Resonance Imaging (RS-fMRI), and structural MRI) rendered 2 clusters: one comparable to controls and one deviating from controls. Participants were minimally overlapping across the identified clusters, suggesting that an abnormal functional GT phenotype did not necessarily mean an abnormal morphological GT phenotype for the same subject. Morphological clusters were associated with a significant difference in the estimated lifetime number of generalized tonic-clonic seizures and functional cluster membership was associated with age. Furthermore, controls exhibited significant correlations between functional GT metrics and cognition, while for TLE participants morphological GT metrics were linked to cognition, suggesting a dissociation between higher cognitive abilities and GT-derived network measures. Overall, these findings demonstrate the existence of clinically meaningful minimally overlapping phenotypes of morphological and functional GT networks. Functional network properties may underlie variance in cognition in healthy brains, but in the pathological state of epilepsy the cognitive limits might be primarily related to structural cerebral network properties.

Cognitive status in a 62-year-old male with lifelong temporal lobe epilepsy and multiple comorbidities.

This is a case report of a 62-year-old male with lifelong temporal lobe epilepsy presented with an interesting matrix of clinical, cognitive, psychiatric, neuroinaging and psychosocial features. This was one of the cases presented for review and discussion at the ILAE Neuropsychology Training Course as part of a case series discussion and is highlighted to illustrate the potential for neuropsychological resilience in a patient with epilepsy.

Deficits in Behavioral and Neuronal Pattern Separation in Temporal Lobe Epilepsy.

In temporal lobe epilepsy, the ability of the dentate gyrus to limit excitatory cortical input to the hippocampus breaks down, leading to seizures. The dentate gyrus is also thought to help discriminate between similar memories by performing pattern separation, but whether epilepsy leads to a breakdown in this neural computation, and thus to mnemonic discrimination impairments, remains unknown. Here we show that temporal lobe epilepsy is characterized by behavioral deficits in mnemonic discrimination tasks, in both humans (females and males) and mice (C57Bl6 males, systemic low-dose kainate model). Using a recently developed assay in brain slices of the same epileptic mice, we reveal a decreased ability of the dentate gyrus to perform certain forms of pattern separation. This is because of a subset of granule cells with abnormal bursting that can develop independently of early EEG abnormalities. Overall, our results linking physiology, computation, and cognition in the same mice advance our understanding of episodic memory mechanisms and their dysfunction in epilepsy.SIGNIFICANCE STATEMENT People with temporal lobe epilepsy (TLE) often have learning and memory impairments, sometimes occurring earlier than the first seizure, but those symptoms and their biological underpinnings are poorly understood. We focused on the dentate gyrus, a brain region that is critical to avoid confusion between similar memories and is anatomically disorganized in TLE. We show that both humans and mice with TLE experience confusion between similar situations. This impairment coincides with a failure of the dentate gyrus to disambiguate similar input signals because of pathologic bursting in a subset of neurons. Our work bridges seizure-oriented and memory-oriented views of the dentate gyrus function, suggests a mechanism for cognitive symptoms in TLE, and supports a long-standing hypothesis of episodic memory theories.

Sleep Deprivation Exacerbates Seizures and Diminishes GABAergic Tonic Inhibition.

Patients with epilepsy report that sleep deprivation is a common trigger for breakthrough seizures. The basic mechanism of this phenomenon is unknown. In the Kv1.1-/- mouse model of epilepsy, daily sleep deprivation indeed exacerbated seizures though these effects were lost after the third day. Sleep deprivation also accelerated mortality in ~ 52% of Kv1.1-/- mice, not observed in controls. Voltage-clamp experiments on the day after recovery from sleep deprivation showed reductions in GABAergic tonic inhibition in dentate granule cells in epileptic Kv1.1-/- mice. Our results suggest that sleep deprivation is detrimental to seizures and survival, possibly due to reductions in GABAergic tonic inhibition. ANN NEUROL 2021;90:840-844.

Network topology of the cognitive phenotypes of temporal lobe epilepsy.

PURPOSE: The neuropsychological complications of temporal lobe epilepsy are characterized by a spectrum of reproducible cognitive phenotypes that vary in the presence, type and degree of impairment. The nature of the disruptions to the neuropsychological networks that underlie these phenotypes remain to be characterized and represent the subject of this investigation. METHODS: Participants included 30 healthy controls and 104 patients with temporal lobe epilepsy who fell into three cognitive phenotypes (intact, focal impairment, generalized impairment). Eighteen neuropsychological measures representing multiple cognitive domains (language, memory, executive function, visuoperception, motor speed) were examined by graph theory techniques within the control and each epilepsy cognitive phenotype group to characterize their global and local network properties. RESULTS: Across the control and epilepsy cognitive phenotype groups (intact to focal to generalized impairment), there was: 1) an orderly breakdown in the positive manifold reflected by a stepwise reduction of positive associations among the neuropsychological tests, 2) stepwise abnormal increases in global measures including the normalized clustering coefficient and modularity index, 3) stepwise abnormal decreases in normalized global efficiency, 4) a community structure demonstrating well organized modules within the control group while each epilepsy group showed deviations from controls, and 5) lower strength, compared to controls, across 8 nodes in the focal and generalized impairment groups compared to only 3 nodes in the no-impairment epilepsy group, pointing to the superior integration of local connections in controls. DISCUSSION: The cognitive phenotypes of temporal lobe epilepsy are characterized by orderly abnormalities in their underlying neuropsychological networks. These findings inform the network perturbations that underlie the taxonomy of cognitive abnormality in temporal lobe epilepsy and provide a model for examination of similar issues in other focal and generalized epilepsies.

Proceedings of the Sleep and Epilepsy Workshop: Section 3 Mortality: Sleep, Night, and SUDEP.

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in patients with refractory epilepsy. Likely pathophysiological mechanisms include seizure-induced cardiac and respiratory dysregulation. A frequently identified feature in SUDEP cases is that they occur at night. This raises the question of a role for sleep state in regulating of SUDEP. An association with sleep has been identified in a number of studies with patients and in animal models. The focus of this section of the Sleep and Epilepsy Workshop was on identifying and understanding the role for sleep and time of day in the pathophysiology of SUDEP.

Proceedings of the Sleep and Epilepsy Workshop: Section 1 Decreasing Seizures-Improving Sleep and Seizures, Themes for Future Research.

Epileptic seizures, sleep, and circadian timing share bilateral interactions, but concerted work to characterize these interactions and to leverage them to the advantage of patients with epilepsy remains in beginning stages. To further the field, a multidisciplinary group of sleep physicians, epileptologists, circadian timing experts, and others met to outline the state of the art, gaps of knowledge, and suggest ways forward in clinical, translational, and basic research. A multidisciplinary panel of experts discussed these interactions, centered on whether improvements in sleep or circadian rhythms improve decrease seizure frequency. In addition, education about sleep was lacking in among patients, their families, and physicians, and that focus on education was an extremely important "low hanging fruit" to harvest. Improvements in monitoring technology, experimental designs sensitive to the rigor required to dissect sleep versus circadian influences, and clinical trials in seizure reduction with sleep improvements were appropriate.

Sleep-wake characteristics in a mouse model of severe traumatic brain injury: Relation to posttraumatic epilepsy.

Study objectives: Traumatic brain injury (TBI) results in sequelae that include posttraumatic epilepsy (PTE) and sleep-wake disturbances. Here, we sought to determine whether sleep characteristics could predict development of PTE in a model of severe TBI. Methods: Following controlled cortical impact (CCI) or sham injury (craniotomy only), CD-1 mice were implanted with epidural electroencephalography (EEG) and nuchal electromyography (EMG) electrodes. Acute (1st week) and chronic (months 1, 2, or 3) 1-week-long video-EEG recordings were performed after the injury to examine epileptiform activity. High-amplitude interictal events were extracted from EEG using an automated method. After scoring sleep-wake patterns, sleep spindles and EEG delta power were derived from nonrapid eye movement (NREM) sleep epochs. Brain CTs (computerized tomography) were performed in sham and CCI cohorts to quantify the brain lesions. We then employed a no craniotomy (NC) control to perform 1-week-long EEG recordings at week 1 and month 1 after surgery. Results: Posttraumatic seizures were seen in the CCI group only, whereas interictal epileptiform activity was seen in CCI or sham. Sleep-wake disruptions consisted of shorter wake or NREM bout lengths and shorter duration or lower power for spindles in CCI and sham. NREM EEG delta power increased in CCI and sham groups compared with NC though the CCI group with posttraumatic seizures had lower power at a chronic time point compared with those without. Follow-up brain CTs showed a small lesion in the sham injury group suggesting a milder form of TBI that may account for their interictal activity and sleep changes. Significance: In our TBI model, tracking changes in NREM delta power distinguishes between CCI acutely and animals that will eventually develop PTE, but further work is necessary to identify sleep biomarkers of PTE. Employing NC controls together with sham controls should be considered in future TBI studies.

Untangling a Web: Basic Mechanisms of the Complex Interactions Between Sleep, Circadian Rhythms, and Epilepsy.

Seizures have sleep-wake and circadian patterns in various epilepsies and, in turn, disrupt sleep and circadian rhythms. The resultant sleep deprivation (SD) is an exacerbating factor for seizures that sets up a vicious cycle that can potentially lead to disease progression and even to epilepsy-related mortality. A variety of cellular or network electrophysiological changes and changes in expression of clock-controlled genes or other transcription factors underlie sleep-wake and circadian distribution of seizures, as well as the disruptions seen in both. A broad understanding of these mechanisms may help in designing better treatments to prevent SD-induced seizure exacerbation, disrupt the vicious cycle of disease progression, and reduce epilepsy-related mortality.

Local Sleep Slow-Wave Activity Colocalizes With the Ictal Symptomatogenic Zone in a Patient With Reflex Epilepsy: A High-Density EEG Study.

Background: Slow-wave activity (SWA) during non-rapid eye movement (NREM) sleep reflects synaptic potentiation during preceding wakefulness. Epileptic activity may induce increases in state-dependent SWA in human brains, therefore, localization of SWA may prove useful in the presurgical workup of epileptic patients. We analyzed high-density electroencephalography (HDEEG) data across vigilance states from a reflex epilepsy patient with a clearly localizable ictal symptomatogenic zone to provide a proof-of-concept for the testability of this hypothesis. Methods: Overnight HDEEG recordings were obtained in the patient during REM sleep, NREM sleep, wakefulness, and during a right facial motor seizure then compared to 10 controls. After preprocessing, SWA (i.e., delta power; 1-4 Hz) was calculated at each channel. Scalp level and source reconstruction analyses were computed. We assessed for statistical differences in maximum SWA between the patient and controls within REM sleep, NREM sleep, wakefulness, and seizure. Then, we completed an identical statistical comparison after first subtracting intrasubject REM sleep SWA from that of NREM sleep, wakefulness, and seizure SWA. Results: The topographical analysis revealed greater left hemispheric SWA in the patient vs. controls in all vigilance states except REM sleep (which showed a right hemispheric maximum). Source space analysis revealed increased SWA in the left inferior frontal cortex during NREM sleep and wakefulness. Ictal data displayed poor source-space localization. Comparing each state to REM sleep enhanced localization accuracy; the most clearly localizing results were observed when subtracting REM sleep from wakefulness. Conclusion: State-dependent SWA during NREM sleep and wakefulness may help to identify aspects of the potential epileptogenic zone. Future work in larger cohorts may assess the clinical value of sleep SWA to help presurgical planning.

Network, clinical and sociodemographic features of cognitive phenotypes in temporal lobe epilepsy.

This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

Neuroticism in temporal lobe epilepsy is associated with altered limbic-frontal lobe resting-state functional connectivity.

Neuroticism, a core personality trait characterized by a tendency towards experiencing negative affect, has been reported to be higher in people with temporal lobe epilepsy (TLE) compared with healthy individuals. Neuroticism is a known predictor of depression and anxiety, which also occur more frequently in people with TLE. The purpose of this study was to identify abnormalities in whole-brain resting-state functional connectivity in relation to neuroticism in people with TLE and to determine the degree of unique versus shared patterns of abnormal connectivity in relation to elevated symptoms of depression and anxiety. Ninety-three individuals with TLE (55 females) and 40 healthy controls (18 females) from the Epilepsy Connectome Project (ECP) completed measures of neuroticism, depression, and anxiety, which were all significantly higher in people with TLE compared with controls. Resting-state functional connectivity was compared between controls and groups with TLE with high and low neuroticism using analysis of variance (ANOVA) and t-test. In secondary analyses, the same analytics were performed using measures of depression and anxiety and the unique variance in resting-state connectivity associated with neuroticism independent of symptoms of depression and anxiety identified. Increased neuroticism was significantly associated with hyposynchrony between the right hippocampus and Brodmann area (BA) 9 (region of prefrontal cortex (PFC)) (p < 0.005), representing a unique relationship independent of symptoms of depression and anxiety. Hyposynchrony of connection between the right hippocampus and BA47 (anterior frontal operculum) was associated with high neuroticism and with higher depression and anxiety scores (p < 0.05), making it a shared abnormal connection for the three measures. In conclusion, increased neuroticism exhibits both unique and shared patterns of abnormal functional connectivity with depression and anxiety symptoms between regions of the mesial temporal and frontal lobe.

Sleep and diurnal rest-activity rhythm disturbances in a mouse model of Alzheimer's disease.

STUDY OBJECTIVES: Accumulating evidence suggests a strong association between sleep, amyloid-beta (Aß) deposition, and Alzheimer's disease (AD). We sought to determine if (1) deficits in rest-activity rhythms and sleep are significant phenotypes in J20 AD mice, (2) metabotropic glutamate receptor 5 inhibitors (mGluR5) could rescue deficits in rest-activity rhythms and sleep, and (3) Aß levels are responsive to treatment with mGluR5 inhibitors. METHODS: Diurnal rest-activity levels were measured by actigraphy and sleep-wake patterns by electroencephalography, while animals were chronically treated with mGluR5 inhibitors. Behavioral tests were performed, and Aß levels measured in brain lysates. RESULTS: J20 mice exhibited a 4.5-h delay in the acrophase of activity levels compared to wild-type littermates and spent less time in rapid eye movement (REM) sleep during the second half of the light period. J20 mice also exhibited decreased non-rapid eye movement (NREM) delta power but increased NREM sigma power. The mGluR5 inhibitor CTEP rescued the REM sleep deficit and improved NREM delta and sigma power but did not correct rest-activity rhythms. No statistically significant differences were observed in Aß levels, rotarod performance, or the passive avoidance task following chronic mGluR5 inhibitor treatment. CONCLUSIONS: J20 mice have disruptions in rest-activity rhythms and reduced homeostatic sleep pressure (reduced NREM delta power). NREM delta power was increased following treatment with a mGluR5 inhibitor. Drug bioavailability was poor. Further work is necessary to determine if mGluR5 is a viable target for treating sleep phenotypes in AD.

Brain aging in temporal lobe epilepsy: Chronological, structural, and functional.

The association of epilepsy with structural brain changes and cognitive abnormalities in midlife has raised concern regarding the possibility of future accelerated brain and cognitive aging and increased risk of later life neurocognitive disorders. To address this issue we examined age-related processes in both structural and functional neuroimaging among individuals with temporal lobe epilepsy (TLE, N = 104) who were participants in the Epilepsy Connectome Project (ECP). Support vector regression (SVR) models were trained from 151 healthy controls and used to predict TLE patients' brain ages. It was found that TLE patients on average have both older structural (+6.6 years) and functional (+8.3 years) brain ages compared to healthy controls. Accelerated functional brain age (functional - chronological age) was mildly correlated (corrected P = 0.07) with complex partial seizure frequency and the number of anti-epileptic drug intake. Functional brain age was a significant correlate of declining cognition (fluid abilities) and partially mediated chronological age-fluid cognition relationships. Chronological age was the only positive predictor of crystallized cognition. Accelerated aging is evident not only in the structural brains of patients with TLE, but also in their functional brains. Understanding the causes of accelerated brain aging in TLE will be clinically important in order to potentially prevent or mitigate their cognitive deficits.