Sex differences in neuronal systems function and behaviour: beyond a single diagnosis in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is associated with functional brain alterations that underlie the expression of behaviour. Males are diagnosed up to four times more than females, and sex differences have been identified in memory, cognitive flexibility, verbal fluency, and social communication. Unfortunately, there exists a lack of information on the sex-dependent mechanisms of ASD, as well as biological markers to distinguish sex-specific symptoms in ASD. This can often result in a standardized diagnosis for individuals across the spectrum, despite significant differences in the various ASD subtypes. Alterations in neuronal connectivity and oscillatory activity, such as is observed in ASD, are highly coupled to behavioural states. Yet, despite the well-identified sexual dimorphisms that exist in ASD, these functional patterns have rarely been analyzed in the context of sex differences or symptomology. This review summarizes alterations in neuronal oscillatory function in ASD, discusses the age, region, symptom and sex-specific differences that are currently observed across the spectrum, and potential targets for regulating neuronal oscillatory activity in ASD. The need to identify sex-specific biomarkers, in order to facilitate specific diagnostic criteria and allow for more targeted therapeutic approaches for ASD will also be discussed.

Selective enhancement of low-gamma activity by tACS improves phonemic processing and reading accuracy in dyslexia

The phonological deficit in dyslexia is associated with altered low-gamma oscillatory function in left auditory cortex, but a causal relationship between oscillatory function and phonemic processing has never been established. After confirming a deficit at 30 Hz with electroencephalography (EEG), we applied 20 minutes of transcranial alternating current stimulation (tACS) to transiently restore this activity in adults with dyslexia. The intervention significantly improved phonological processing and reading accuracy as measured immediately after tACS. The effect was selective to 30 Hz stimulation, and proportional to dyslexia severity. Importantly, we observed that the focal intervention on the left auditory cortex also decreased 30 Hz activity in the right superior temporal cortex, resulting in reinstating a left dominance for the oscillatory response, as present in controls. These findings formally establish a causal role of neural oscillations in phonological processing, and offer solid neurophysiological grounds for a potential correction of low-gamma anomalies, and for alleviating of the phonological deficit in dyslexia.

GSK-3β disrupts neural oscillatory function to inhibit learning and memory in rats

Background. Alterations in glycogen synthase kinase-3β (GSK-3β) activity have been implicated in disorders of cognitive impairment including Alzheimer’s disease and schizophrenia. Another characteristic of cognitive impairment is the dysregulation of neural oscillatory activity, macroscopic electrical rhythms in brain critical to systems communication. A direct functional relationship between GSK-3β and neural oscillations has not been elucidated.Methods. In the present study, the impact of increasing GSK-3β activity in prefrontal cortex (PFC) or hippocampus (HIP) on the regulation of neural oscillations in rats was investigated using an adeno-associated viral vector containing a persistently active mutant of GSK-3β (S9A), and changes in learning and memory and tau phosphorylation assessed.Results. Increasing GSK-3β activity in either region had similar effects on oscillatory spectral power, enhancing theta and/or gamma oscillatory power recorded from one or both regions. Increasing PFC GSK-3β activity additionally suppressed high gamma PFC-HIP coherence. These oscillatory changes were accompanied by deficits in recognition memory, spatial learning and/or reversal learning. Increased pathogenic tau phosphorylation was also evident in regions where GSK-3β activity was elevated. Conclusions. These findings indicate that increased GSK-3β activity in PFC or HIP dysregulates neural oscillatory function in, and between, these regions. This suggests that GSK-3β may not only play an early role in cognitive decline in Alzheimer’s disease but may also play a more central role in disorders of cognitive dysfunction through the regulation of neurophysiological network function.

Distinguishing two Different Mental States with Application of Non-Linear Parameters

Electroencephalograph (EEG) is useful modality nowadays which is utilized to capture cognitive activities in the form of a signal representing the potential for a given period. Brain Computer Interface (BCI) systems are one of the practical application of EEG signal. Response to mental task is a well-known type of BCI systems which augments the life of disabled persons to communicate their core needs to machines that can able to distinguish among mental states corresponding to thought responses to the EEG. The success of classification of these mental tasks depends on the pertinent set formation of features (analysis, extraction and selection) of the EEG signals for the classification process. In the recent past, a filter based heuristic technique, Empirical Mode Decomposition (EMD), is employed to analyse EEG signal. EMD is a mathematical technique which is suitable to analyze a non-stationary and non-linear signal such as EEG. In this work, three stage feature set formation from EEG signal for building classification model is suggested to distinguish different mental states. In the first stage, the signal is broken into a number of oscillatory functions through EMD algorithm. The second stage involves compact representation in terms of four different features obtained from the each oscillatory function. It has also observed that not all features are relevant therefore there is need to select most relevant features from the pool of the formed features which is carried out in the third stage. Two well-known multi-variate feature selection algorithms are investigated in combination with EMD algorithm for forming the feature vectors for further classification. Classification is carried out with help of learning the Support Vector Machine (SVM) classification model. Experimental result on a publicly available dataset shows the superior performance of the proposed approach

Efficient Computation of Highly Oscillatory Integrals by Using QTT Tensor Approximation

We propose a new method for the efficient approximation of a class of highly oscillatory weighted integrals where the oscillatory function depends on the frequency parameter ${\omega \ge 0}$, typically varying in a large interval. Our approach is based, for a fixed but arbitrary oscillator, on the pre-computation and low-parametric approximation of certain ω-dependent prototype functions whose evaluation leads in a straightforward way to recover the target integral. The difficulty that arises is that these prototype functions consist of oscillatory integrals which makes them difficult to evaluate. Furthermore, they have to be approximated typically in large intervals. Here we use the quantized-tensor train (QTT) approximation method for functional M-vectors of logarithmic complexity in M in combination with a cross-approximation scheme for TT tensors. This allows the accurate approximation and efficient storage of these functions in the wide range of grid and frequency parameters. Numerical examples illustrate the efficiency of the QTT-based numerical integration scheme on various examples in one and several spatial dimensions.

Disruption of gene expression rhythms in mice lacking secretory vesicle proteins IA-2 and IA-2β

Insulinoma-associated protein (IA)-2 and IA-2β are transmembrane proteins involved in neurotransmitter secretion. Mice with targeted disruption of both IA-2 and IA-2β (double-knockout, or DKO mice) have numerous endocrine and physiological disruptions, including disruption of circadian and diurnal rhythms. In the present study, we have assessed the impact of disruption of IA-2 and IA-2β on molecular rhythms in the brain and peripheral oscillators. We used in situ hybridization to assess molecular rhythms in the hypothalamic suprachiasmatic nuclei (SCN) of wild-type (WT) and DKO mice. The results indicate significant disruption of molecular rhythmicity in the SCN, which serves as the central pacemaker regulating circadian behavior. We also used quantitative PCR to assess gene expression rhythms in peripheral tissues of DKO, single-knockout, and WT mice. The results indicate significant attenuation of gene expression rhythms in several peripheral tissues of DKO mice but not in either single knockout. To distinguish whether this reduction in rhythmicity reflects defective oscillatory function in peripheral tissues or lack of entrainment of peripheral tissues, animals were injected with dexamethasone daily for 15 days, and then molecular rhythms were assessed throughout the day after discontinuation of injections. Dexamethasone injections improved gene expression rhythms in liver and heart of DKO mice. These results are consistent with the hypothesis that peripheral tissues of DKO mice have a functioning circadian clockwork, but rhythmicity is greatly reduced in the absence of robust, rhythmic physiological signals originating from the SCN. Thus, IA-2 and IA-2β play an important role in the regulation of circadian rhythms, likely through their participation in neurochemical communication among SCN neurons.

Oscillation criteria for first order forced dynamic equations

We obtain some new oscillation criteria for solutions to certain first order forced dynamic equations on a time scale T of the form x?(t) + r(t)??(x? (t)) + p(t)?? (x? (t)) + q(t)??(x?(t)) = f(t); with ??(u) :=?u?n-1, ?>0. > 0. Here r(t); p (t) ; q(t) and f (t) are rdcontinuous functions on T and the forcing term f(t) is not required to be the derivative of an oscillatory function. Our results in the special cases when T = R and T = N involve and improve some previous oscillation results for first-order differential and difference equations. An example illustrating the importance of our results is also included.