EEG activation differences in the pre-motor cortex and supplementary motor area between normal individuals with high and low traits of autism

The human mirror neuron system (hMNS) is believed to provide a basic mechanism for social cognition. Event-related desynchronization (ERD) in alpha (8–12 Hz) and low beta band (12–20 Hz) over sensori-motor cortex has been suggested to index mirror neurons' activity. We tested whether autistic traits revealed by high and low scores on the Autistic Quotient (AQ) in the normal population are linked to variations in the electroencephalogram (EEG) over motor, pre-motor cortex and supplementary motor area (SMA) during action observation. Results revealed that in the low AQ group, the pre-motor cortex and SMA were more active during hand action than static hand observation whereas in the high AQ group the same areas were active both during static and hand action observation. In fact participants with high traits of autism showed greater low beta ERD while observing the static hand than those with low traits and this low beta ERD was not significantly different when they watched hand actions. Over primary motor cortex, the classical alpha and low beta ERD during hand actions relative to static hand observation was found across all participants. These findings suggest that the observation–execution matching system works differently according to the degree of autism traits in the normal population and that this is differentiated in terms of the EEG according to scalp site and bandwidth.

Reduced cortico-motor facilitation in a normal sample with high traits of autism

Recent research in social neuroscience proposes a link between mirror neuron system (MNS) and social cognition. The MNS has been proposed to be the neural mechanism underlying action recognition and intention understanding and more broadly social cognition. Pre-motor MNS has been suggested to modulate the motor cortex during action observation. This modulation results in an enhanced cortico-motor excitability reflected in increased motor evoked potentials (MEPs) at the muscle of interest during action observation. Anomalous MNS activity has been reported in the autistic population whose social skills are notably impaired. It is still an open question whether traits of autism in the normal population are linked to the MNS functioning. We measured TMS-induced MEPs in normal individuals with high and low traits of autism as measured by the autistic quotient (AQ), while observing videos of hand or mouth actions, static images of a hand or mouth or a blank screen. No differences were observed between the two while they observed a blank screen. However participants with low traits of autism showed significantly greater MEP amplitudes during observation of hand/mouth actions relative to static hand/mouth stimuli. In contrast, participants with high traits of autism did not show such a MEP amplitude difference between observation of actions and static stimuli. These results are discussed with reference to MNS functioning.

NeMo: a platform for neural modelling of spiking neurons using GPUs

Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to the number and interconnectedness of neurons in the brain. Furthermore, where such simulations are used in an embodied setting, the simulation must be real-time in order to be useful. In this paper we present NeMo, a platform for such simulations which achieves high performance through the use of highly parallel commodity hardware in the form of graphics processing units (GPUs). NeMo makes use of the Izhikevich neuron model which provides a range of realistic spiking dynamics while being computationally efficient. Our GPU kernel can deliver up to 400 million spikes per second. This corresponds to a real-time simulation of around 40 000 neurons under biologically plausible conditions with 1000 synapses per neuron and a mean firing rate of 10 Hz.

To eat or not to eat? Kinematics and muscle activity of reach-to-grasp movements are influenced by the action goal, but observers do not detect these differences

Recent evidence suggests that the mirror neuron system responds to the goals of actions, even when the end of the movement is hidden from view. To investigate whether this predictive ability might be based on the detection of early differences between actions with different outcomes, we used electromyography (EMG) and motion tracking to assess whether two actions with different goals (grasp to eat and grasp to place) differed from each other in their initial reaching phases. In a second experiment, we then tested whether observers could detect early differences and predict the outcome of these movements, based on seeing only part of the actions. Experiment 1 revealed early kinematic differences between the two movements, with grasp-to-eat movements characterised by an earlier peak acceleration, and different grasp position, compared to grasp-to-place movements. There were also significant differences in forearm muscle activity in the reaching phase of the two actions. The behavioural data arising from Experiments 2a and 2b indicated that observers are not able to predict whether an object is going to be brought to the mouth or placed until after the grasp has been completed. This suggests that the early kinematic differences are either not visible to observers, or that they are not used to predict the end-goals of actions. These data are discussed in the context of the mirror neuron system

More questions for mirror neurons

The mirror neuron system is widely held to provide direct access to the motor goals of others. This paper critically investigates this idea, focusing on the so-called ‘intentional worry’. I explore two answers to the intentional worry: first that the worry is premised on too limited an understanding of mirror neuron behaviour (Sections 2 and 3), second that the appeal made to mirror neurons can be refined in such a way as to avoid the worry (Section 4). I argue that the first response requires an account of the mechanism by which small-scale gestures are supposedly mapped to larger chains of actions but that none of the extant accounts of this mechanism are plausible. Section 4 then briefly examines refinements of the mirror neuron-mindreading hypothesis which avoid the intentional worry. I conclude that these refinements may well be plausible but that they undermine many of the claims standardly made for mirror neurons.

Beta event-related desynchronization as an index of individual differences in processing human facial expression: further investigations of autistic traits in typically developing adults

The human mirror neuron system (hMNS) has been associated with various forms of social cognition and affective processing including vicarious experience. It has also been proposed that a faulty hMNS may underlie some of the deficits seen in the autism spectrum disorders (ASDs). In the present study we set out to investigate whether emotional facial expressions could modulate a putative EEG index of hMNS activation (mu suppression) and if so, would this differ according to the individual level of autistic traits [high versus low Autism Spectrum Quotient (AQ) score]. Participants were presented with 3 s films of actors opening and closing their hands (classic hMNS mu-suppression protocol) while simultaneously wearing happy, angry, or neutral expressions. Mu-suppression was measured in the alpha and low beta bands. The low AQ group displayed greater low beta event-related desynchronization (ERD) to both angry and neutral expressions. The high AQ group displayed greater low beta ERD to angry than to happy expressions. There was also significantly more low beta ERD to happy faces for the low than for the high AQ group. In conclusion, an interesting interaction between AQ group and emotional expression revealed that hMNS activation can be modulated by emotional facial expressions and that this is differentiated according to individual differences in the level of autistic traits. The EEG index of hMNS activation (mu suppression) seems to be a sensitive measure of the variability in facial processing in typically developing individuals with high and low self-reported traits of autism.

Human frontal lobes are not relatively large

One of the most pervasive assumptions about human brain evolution is that it involved relative enlargement of the frontal lobes. We show that this assumption is without foundation. Analysis of five independent data sets using correctly scaled measures and phylogenetic methods reveals that the size of human frontal lobes, and of specific frontal regions, is as expected relative to the size of other brain structures. Recent claims for relative enlargement of human frontal white matter volume, and for relative enlargement shared by all great apes, seem to be mistaken. Furthermore, using a recently developed method for detecting shifts in evolutionary rates, we find that the rate of change in relative frontal cortex volume along the phylogenetic branch leading to humans was unremarkable and that other branches showed significantly faster rates of change. Although absolute and proportional frontal region size increased rapidly in humans, this change was tightly correlated with corresponding size increases in other areas andwhole brain size, and with decreases in frontal neuron densities. The search for the neural basis of human cognitive uniqueness should therefore focus less on the frontal lobes in isolation and more on distributed neural networks.

A dynamic causal model of the coupling between pulse stimulation and neural activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

Patterning and detailed study of human hNT astrocytes on parylene-C/silicon dioxide substrates to the single cell level

It is estimated that the adult human brain contains 100 billion neurons with 5–10 times as many astrocytes. Although it has been generally considered that the astrocyte is a simple supportive cell to the neuron, recent research has revealed new functionality of the astrocyte in the form of information transfer to neurons of the brain. In our previous work we developed a protocol to pattern the hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO2 substrates. In this work, we report how we have managed to pattern hNT astrocytes, on parylene-C/SiO2 substrates to single cell resolution. This article disseminates the nanofabrication and cell culturing steps necessary for the patterning of such cells. In addition, it reports the necessary strip lengths and strip width dimensions of parylene-C that encourage high degrees of cellular coverage and single cell isolation for this cell type. The significance in patterning the hNT astrocyte on silicon chip is that it will help enable single cell and network studies into the undiscovered functionality of this interesting cell, thus, contributing to closer pathological studies of the human brain.

Effects of parylene-C photooxidation on serum-assisted glial and neuronal patterning

The increasing use of patterned neural networks in multielectrode arrays and similar devices drives the constant development and evaluation of new biomaterials. Recently, we presented a promising technique to guide neurons and glia reliably and effectively. Parylene-C, a common hydrophobic polymer, was photolithographically patterned on silicon oxide (SiO2) and subsequently activated via immersion in serum. In this article, we explore the effects of ultraviolet (UV)-induced oxidation on parylene's ability to pattern neurons and glia. We exposed parylene-C stripe patterns to increasing levels of UV radiation and found a dose-dependent reduction in the total mass of patterned cells, as well as a gradual loss of glial and neuronal conformity to the patterns. In contrast, nonirradiated patterns had superior patterning results and increased presence of cells. The reduced cell adhesion and patterning after the formation of aldehyde and carboxyl groups on UV-radiated parylene-C supports our hypothesis that cell adhesion and growth on parylene is facilitated by hydrophobic adsorption of serum proteins. We conclude that unlike other cell patterning schemes, our technique does not rely on photooxidation of the polymer. Nonetheless, the precise control of oxygenated groups on parylene could pave the way for the differential binding of proteins and other molecules on the surface, aiding in the adhesion of alternative cell types. © 2010 Wiley Periodicals, Inc. J Biomed Mater Res, 2010

Controlled adhesion and growth of long term glial and neuronal cultures on Parylene-C

This paper explores the long term development of networks of glia and neurons on patterns of Parylene-C on a SiO2 substrate. We harvested glia and neurons from the Sprague-Dawley (P1–P7) rat hippocampus and utilized an established cell patterning technique in order to investigate cellular migration, over the course of 3 weeks. This work demonstrates that uncontrolled glial mitosis gradually disrupts cellular patterns that are established early during culture. This effect is not attributed to a loss of protein from the Parylene-C surface, as nitrogen levels on the substrate remain stable over 3 weeks. The inclusion of the anti-mitotic cytarabine (Ara-C) in the culture medium moderates glial division and thus, adequately preserves initial glial and neuronal conformity to underlying patterns. Neuronal apoptosis, often associated with the use of Ara-C, is mitigated by the addition of brain derived neurotrophic factor (BDNF). We believe that with the right combination of glial inhibitors and neuronal promoters, the Parylene-C based cell patterning method can generate structured, active neural networks that can be sustained and investigated over extended periods of time. To our knowledge this is the first report on the concurrent application of Ara-C and BDNF on patterned cell cultures.

First human hNT astrocytes patterned to single cell resolution on parylene-C/Silicon dioxide substrates

In our previous work we developed a successful protocol to pattern the human hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO2 substrates. This communication, reports how we have successfully managed to pattern the supportive cell to the neuron, the hNT astrocyte, on such substrates. Here we disseminate the nanofabrication, cell differentiation and cell culturing protocols necessary to successfully pattern the first human hNT astrocytes to single cell resolution on parylene-C/SiO2 substrates. This is performed for varying parylene strip widths providing excellent contrast to the SiO2 substrate and elegant single cell isolation at 10μm strip widths. The breakthrough in patterning human cells on a silicon chip has widespread implications and is valuable as a platform technology as it enables a detailed study of the human brain at the cellular and network level.

Repressor element 1 silencing transcription factor couples loss of pluripotency with neural induction and neural differentiation

Neural differentiation of embryonic stem cells (ESCs) requires coordinated repression of the pluripotency regulatory program and reciprocal activation of the neurogenic regulatory program. Upon neural induction, ESCs rapidly repress expression of pluripotency genes followed by staged activation of neural progenitor and differentiated neuronal and glial genes. The transcriptional factors that underlie maintenance of pluripotency are partially characterized whereas those underlying neural induction are much less explored, and the factors that coordinate these two developmental programs are completely unknown. One transcription factor, REST (repressor element 1 silencing transcription factor), has been linked with terminal differentiation of neural progenitors and more recently, and controversially, with control of pluripotency. Here, we show that in the absence of REST, coordination of pluripotency and neural induction is lost and there is a resultant delay in repression of pluripotency genes and a precocious activation of both neural progenitor and differentiated neuronal and glial genes. Furthermore, we show that REST is not required for production of radial glia-like progenitors but is required for their subsequent maintenance and differentiation into neurons, oligodendrocytes, and astrocytes. We propose that REST acts as a regulatory hub that coordinates timely repression of pluripotency with neural induction and neural differentiation.

Neural stem cells and cell replacement therapy: making the right cells

The past few years have seen major advances in the field of NSC (neural stem cell) research with increasing emphasis towards its application in cell-replacement therapy for neurological disorders. However, the clinical application of NSCs will remain largely unfeasible until a comprehensive understanding of the cellular and molecular mechanisms of NSC fate specification is achieved. With this understanding will come an increased possibility to exploit the potential of stem cells in order to manufacture transplantable NSCs able to provide a safe and effective therapy for previously untreatable neurological disorders. Since the pathology of each of these disorders is determined by the loss or damage of a specific neural cell population, it may be necessary to generate a range of NSCs able to replace specific neurons or glia rather than generating a generic NSC population. Currently, a diverse range of strategies is being investigated with this goal in mind. In this review, we focus on the relationship between NSC specification and differentiation and discuss how this information may be used to direct NSCs towards a particular fate.

Towards optimizing the selection of neurons in affordable neural networks

This paper considers variations of a neuron pool selection method known as Affordable Neural Network (AfNN). A saliency measure, based on the second derivative of the objective function is proposed to assess the ability of a trained AfNN to provide neuronal redundancy. The discrepancies between the various affordability variants are explained by correlating unique sub group selections with relevant saliency variations. Overall this study shows that the method in which neurons are selected from a pool is more relevant to how salient individual neurons are, than how often a particular neuron is used during training. The findings herein are relevant to not only providing an analogy to brain function but, also, in optimizing the way a neural network using the affordability method is trained.