Temporal stimulus properties that attract gaze to the periphery and repel gaze from fixation

Humans use saccadic eye movements to fixate different parts of their visual environment. While stimulus features that determine the location of the next fixation in static images have been extensively studied, temporal stimulus features that determine the timing of the gaze shifts received less attention. It is also unclear if stimulus features at the present gaze location can trigger gaze shifts to another location. To investigate these questions, we asked observers to switch their gaze between two blobs. In three different conditions, either the fixated blob, the peripheral blob, or both blobs were flickering. A time-frequency analysis of the flickering noise values, time locked to the gaze shifts, revealed significant phase locking in a time window 300 to 100 ms before the gaze shift at temporal frequencies below 20 Hz. The average phase angles at these time-frequency points indicated that observer´s gaze was repelled by decreasing contrast of the fixated blob and attracted by increasing contrast of the peripheral blob. These results show that temporal properties of both, fixated, and peripheral stimuli are capable of triggering gaze shifts

Dravet syndrome as epileptic encephalopathy: evidence from long-term course and neuropathology

Dravet syndrome is an epilepsy syndrome of infantile onset, frequently caused by SCN1A mutations or deletions. Its prevalence, long-term evolution in adults and neuropathology are not well known. We identified a series of 22 adult patients, including three adult post-mortem cases with Dravet syndrome. For all patients, we reviewed the clinical history, seizure types and frequency, antiepileptic drugs, cognitive, social and functional outcome and results of investigations. A systematic neuropathology study was performed, with post-mortem material from three adult cases with Dravet syndrome, in comparison with controls and a range of relevant paediatric tissue. Twenty-two adults with Dravet syndrome, 10 female, were included, median age 39 years (range 20–66). SCN1A structural variation was found in 60% of the adult Dravet patients tested, including one post-mortem case with DNA extracted from brain tissue. Novel mutations were described for 11 adult patients; one patient had three SCN1A mutations. Features of Dravet syndrome in adulthood include multiple seizure types despite polytherapy, and age-dependent evolution in seizure semiology and electroencephalographic pattern. Fever sensitivity persisted through adulthood in 11 cases. Neurological decline occurred in adulthood with cognitive and motor deterioration. Dysphagia may develop in or after the fourth decade of life, leading to significant morbidity, or death. The correct diagnosis at an older age made an impact at several levels. Treatment changes improved seizure control even after years of drug resistance in all three cases with sufficient follow-up after drug changes were instituted; better control led to significant improvement in cognitive performance and quality of life in adulthood in two cases. There was no histopathological hallmark feature of Dravet syndrome in this series. Strikingly, there was remarkable preservation of neurons and interneurons in the neocortex and hippocampi of Dravet adult post-mortem cases. Our study provides evidence that Dravet syndrome is at least in part an epileptic encephalopathy

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

Genetic modifiers affecting severity of epilepsy caused by mutation of sodium channel Scn2a

Mutations in the voltage-gated sodium channels SCN1A and SCN2A are responsible for several types of human epilepsy. Variable expressivity among family members is a common feature of these inherited epilepsies, suggesting that genetic modifiers may influence the clinical manifestation of epilepsy. The transgenic mouse model Scn2a Q54 has an epilepsy phenotype as a result of a mutation in Scn2a that slows channel inactivation. The mice display progressive epilepsy that begins with short-duration partial seizures that appear to originate in the hippocampus. The partial seizures become more frequent and of longer duration with age and often induce secondary generalized seizures. Clinical severity of the Scn2a Q54 phenotype is influenced by genetic background. Congenic C57BL/6J.Q54 mice exhibit decreased incidence of spontaneous seizures, delayed seizure onset, and longer survival in comparison with [C57BL/6J × SJL/J]F 1 .Q54 mice. This observation indicates that strain SJL/J carries dominant modifier alleles at one or more loci that determine the severity of the epilepsy phenotype. Genome-wide interval mapping in an N 2 backcross revealed two modifier loci on Chromosomes 11 and 19 that influence the clinical severity of of this sodium channel-induced epilepsy. Modifier genes affecting clinical severity in the Scn2a Q54 mouse model may contribute to the variable expressivity seen in epilepsy patients with sodium channel mutations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46986/1/335_2005_Article_49.pd

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets. BárbaraAvelar-Pereira 9 , EthanRoy2 , Valerie J.Sydnor3,4,5, JasonD.Yeatman1,2, The Fibr Community Science Consortium*, TheodoreD.Satterthwaite3,4,5,88 & Ariel Roke