Cardiac arrhythmia and epilepsy genetic variants in sudden unexpected death in epilepsy.

Introduction: Sudden Unexpected Death in Epilepsy (SUDEP) is the leading epilepsy-related cause of death, affecting approximately 1 per 1,000 individuals with epilepsy per year. Genetic variants that affect autonomic function, such as genes associated with cardiac arrhythmias, may predispose people with epilepsy to greater risk of both sudden cardiac death and SUDEP. Advances in next generation sequencing allow for the exploration of gene variants as potential biomarkers. Methods: Genetic testing for the presence of cardiac arrhythmia and epilepsy gene variants was performed via genetic panels in 39 cases of SUDEP identified via autopsy by the Ontario Forensic Pathology Service. Variants were summarized by in-silico evidence for pathogenicity from 4 algorithms (SIFT, PolyPhen-2, PROVEAN, Mutation Taster) and allele frequencies in the general population (GnomAD). A maximum credible population allele frequency of 0.00004 was calculated based on epilepsy prevalence and SUDEP incidence to assess whether a variant was compatible with a pathogenic interpretation. Results: Median age at the time of death was 33.3 years (range: 2, 60). Fifty-nine percent (n=23) were male. Gene panels detected 62 unique variants in 45 genes: 19 on the arrhythmia panel and 26 on the epilepsy panel. At least one variant was identified in 28 (72%) of decedents. Missense mutations comprised 57 (92%) of the observed variants. At least three in silico models predicted 12 (46%) cardiac arrhythmia panel missense variants and 20 (65%) epilepsy panel missense variants were pathogenic. Population allele frequencies were <0.00004 for 11 (42%) of the cardiac variants and 10 (32%) of the epilepsy variants. Together, these metrics identified 13 SUDEP variants of interest. Discussion: Nearly three-quarters of decedents in this SUDEP cohort carried variants in comprehensive epilepsy or cardiac arrhythmia gene panels, with more than a third having variants in both panels. The proportion of decedents with cardiac variants aligns with recent studies of the disproportionate cardiac burden the epilepsy community faces compared to the general population and suggests a possible cardiac contribution to epilepsy mortality. These results identified 13 priority targets for future functional studies of these genes potential role in sudden death and demonstrates the necessity for further exploration of potential genetic contributions to SUDEP.

Prevalence of epileptiform electroencephalographic abnormalities in people without a history of seizures: A systematic review and meta-analysis.

Abnormal patterns identified on electroencephalogram (EEG) are one of the primary diagnostic tests for epilepsy. However, epidemiological studies have established that both benign and epileptiform abnormalities (EAs) occur on the EEG of nonepileptic, seizure-free people as well. The reported rates of EAs in nonepileptic, seizure-free populations vary, and the true prevalence is unknown. The primary objective of this systematic review and meta-analysis was to estimate the overall prevalence of EAs in the EEG of people without a history of seizures. Secondary aims were to characterize (1) the cortical localization of focal abnormalities, (2) the proportion of findings that occurred during standard EEG stimulation protocols, and (3) the persistence and implications of abnormalities at follow-up. A comprehensive electronic search of six bibliographic databases was completed: Embase, MEDLINE, PsycInfo, Cumulative Index of Nursing and Allied Health Literature, Cochrane Central Register for Controlled Trials, and Web of Science. No search date restrictions were applied. Overall effect size was calculated using a generalized linear mixed-effects model. Fifty-three studies, totaling 73 990 individuals, met our inclusion criteria. The overall point prevalence of EAs was 1.74% (95% confidence interval [CI] = 1.13-2.67). Due to the risk of bias in the literature, especially from participant selection, we believe this to be an overestimate of the true prevalence. Prevalence of EAs was greater in children (2.45%, 95% CI = 1.41-4.21) and the elderly (5.96%, 95% CI = 1.39-22.13) compared with adults (.93%, 95% CI = .48-1.80). Reports of developing epilepsy after an EA-positive EEG were rare. The likelihood of subsequent positive findings on follow-up EEG may be as high as 50%. Our study has limitations in that males were overrepresented in the study samples, there is substantial heterogeneity among studies, and many studies provided insufficient detail about their exclusion criteria. Nonetheless, our estimates provide benchmark data for future studies examining EAs in clinical populations, particularly behavioral and psychiatric populations.

Predictors of harsh parenting practices and inter-partner conflict during the COVID-19 pandemic in Ontario, Canada: a cross-sectional analysis from the Ontario Parent Survey.

OBJECTIVES: Guided by the bioecological model, the purpose of this study was to examine the associations of (1) individual level factors (sociodemographic, health behaviour and mental health), (2) family (micro) level COVID-19 experiences (difficulty with household management, managing child mood and behaviour, and pandemic-related positive experiences) and (3) community (macro) level factors (residential instability, ethnic concentration, material deprivation and dependency, an indicator of age and labour force) with harsh parenting practices and inter-partner conflict during the early lockdown of the COVID-19 pandemic in Ontario, Canada. DESIGN: A cross-sectional analysis of data from the Ontario Parent Survey. SETTING: A convenience sample of 7451 caregivers living in Ontario, Canada, at the time of baseline data collection (May-June 2020). PARTICIPANTS: Caregivers aged 18 years and older with children 17 years or younger. OUTCOME MEASURES: Parenting practices over the past 2 months was assessed using a published modification of the Parenting Scale. The frequency of inter-partner conflict over the past month was assessed using the Marital Conflict scale. RESULTS: Individual (sociodemographic factors, alcohol use, and higher depressive and anxiety symptoms) and family (difficulties with managing the household and child mood and behaviour) level factors were positively associated with inter-partner conflict and harsh parenting practices. Having fewer positive experiences (eg, performing activities with children), and economic adversity at the family level were positively associated with inter-partner conflict but inversely associated with harsh parenting. At the community level, residential instability was negatively associated with harsh parenting practices. CONCLUSIONS: Individual and family level factors were associated with harsh parenting and inter-partner conflict. The associations of fewer positive experiences and economic hardship with harsh parenting practices may be more complex than initially thought. Efforts that raise awareness and address caregiver mental health concerns are needed as part of the pandemic response to promote positive inter-partner and parent-child interactions.

Feedforward and feedback interactions between visual cortical areas use different population activity patterns.

Brain function relies on the coordination of activity across multiple, recurrently connected brain areas. For instance, sensory information encoded in early sensory areas is relayed to, and further processed by, higher cortical areas and then fed back. However, the way in which feedforward and feedback signaling interact with one another is incompletely understood. Here we investigate this question by leveraging simultaneous neuronal population recordings in early and midlevel visual areas (V1-V2 and V1-V4). Using a dimensionality reduction approach, we find that population interactions are feedforward-dominated shortly after stimulus onset and feedback-dominated during spontaneous activity. The population activity patterns most correlated across areas were distinct during feedforward- and feedback-dominated periods. These results suggest that feedforward and feedback signaling rely on separate "channels", which allows feedback signals to not directly affect activity that is fed forward.

Modelling the neural code in large populations of correlated neurons.

Neurons respond selectively to stimuli, and thereby define a code that associates stimuli with population response patterns. Certain correlations within population responses (noise correlations) significantly impact the information content of the code, especially in large populations. Understanding the neural code thus necessitates response models that quantify the coding properties of modelled populations, while fitting large-scale neural recordings and capturing noise correlations. In this paper, we propose a class of response model based on mixture models and exponential families. We show how to fit our models with expectation-maximization, and that they capture diverse variability and covariability in recordings of macaque primary visual cortex. We also show how they facilitate accurate Bayesian decoding, provide a closed-form expression for the Fisher information, and are compatible with theories of probabilistic population coding. Our framework could allow researchers to quantitatively validate the predictions of neural coding theories against both large-scale neural recordings and cognitive performance.

Neuronal variability reflects probabilistic inference tuned to natural image statistics.

Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike count variance and mean, and the modulation of V1 activity and variability by spatial context in images. Our results show that the properties of a basic aspect of cortical responses-their variability-can be explained by a probabilistic representation tuned to naturalistic inputs.

An Open Resource for Non-human Primate Optogenetics.

Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on animal models more closely related to humans, such as non-human primates (NHPs), has been mixed. To make evidence-based decisions in primate optogenetics, the scientific community would benefit from a centralized database listing all attempts, successful and unsuccessful, of using optogenetics in the primate brain. We contacted members of the community to ask for their contributions to an open science initiative. As of this writing, 45 laboratories around the world contributed more than 1,000 injection experiments, including precise details regarding their methods and outcomes. Of those entries, more than half had not been published. The resource is free for everyone to consult and contribute to on the Open Science Framework website. Here we review some of the insights from this initial release of the database and discuss methodological considerations to improve the success of optogenetic experiments in NHPs.

Temporal Contingencies Determine Whether Adaptation Strengthens or Weakens Normalization.

A fundamental and nearly ubiquitous feature of sensory encoding is that neuronal responses are strongly influenced by recent experience, or adaptation. Theoretical and computational studies have proposed that many adaptation effects may result in part from changes in the strength of normalization signals. Normalization is a "canonical" computation in which a neuron's response is modulated (normalized) by the pooled activity of other neurons. Here, we test whether adaptation can alter the strength of cross-orientation suppression, or masking, a paradigmatic form of normalization evident in primary visual cortex (V1). We made extracellular recordings of V1 neurons in anesthetized male macaques and measured responses to plaid stimuli composed of two overlapping, orthogonal gratings before and after prolonged exposure to two distinct adapters. The first adapter was a plaid consisting of orthogonal gratings and led to stronger masking. The second adapter presented the same orthogonal gratings in an interleaved manner and led to weaker masking. The strength of adaptation's effects on masking depended on the orientation of the test stimuli relative to the orientation of the adapters, but was independent of neuronal orientation preference. Changes in masking could not be explained by altered neuronal responsivity. Our results suggest that normalization signals can be strengthened or weakened by adaptation depending on the temporal contingencies of the adapting stimuli. Our findings reveal an interplay between two widespread computations in cortical circuits, adaptation and normalization, that enables flexible adjustments to the structure of the environment, including the temporal relationships among sensory stimuli.SIGNIFICANCE STATEMENT Two fundamental features of sensory responses are that they are influenced by adaptation and that they are modulated by the activity of other nearby neurons via normalization. Our findings reveal a strong interaction between these two aspects of cortical computation. Specifically, we show that cross-orientation masking, a form of normalization, can be strengthened or weakened by adaptation depending on the temporal contingencies between sensory inputs. Our findings support theoretical proposals that some adaptation effects may involve altered normalization and offer a network-based explanation for how cortex adjusts to current sensory demands.