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Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that may modulate cortical excitability, metabolite concentration, and human behaviour. The supplementary motor area (SMA) has been largely ignored as a potential target for tDCS neurorehabilitation but is an important region in motor compensation after brain injury with strong efferent connections to the primary motor cortex (M1). The objective of this work was to measure tissue metabolite changes in the human motor cortex immediately following tDCS. We hypothesized that bihemispheric tDCS would change levels of metabolites involved in neuromodulation including N-acetylaspartate (NAA), glutamate (Glu), and creatine (tCr). In this single-blind, randomized, cross-over study, fifteen healthy adults aged 21–60 participated in two 7T MRI sessions, to identify changes in metabolite concentrations by magnetic resonance spectroscopy. Immediately after 20 minutes of tDCS, there were no significant changes in metabolite levels or metabolite ratios comparing tDCS to sham. However there was a trend toward increased NAA/tCr concentration (p = 0.08) in M1 under the stimulating cathode. There was a strong, positive correlation between the change in the absolute concentration of NAA and the change in the absolute concentration of tCr (p<0.001) suggesting an effect of tDCS. Both NAA and creatine are important markers of neurometabolism. Our findings provide novel insight into the modulation of neural metabolites in the motor cortex immediately following application of bihemispheric tDCS. [ABSTRACT FROM AUTHOR]

Previous language production studies targeting the inferior frontal and superior temporal gyrus using anodal tDCS have provided mixed results. Part of this heterogeneity may be explained by limited target region focality of conventionally used electrode montages. We examined the focality of conventionally and alternative electrode montages. Electrical field distributions of anodal tDCS targeting IFG and pSTG were simulated in conventional setups (anodal electrode over left IFG/pSTG, reference electrode over right supraorbital region) and an alternative electrode montage in four different brains. Conventional montages showed maximum field strengths outside of the target regions. Results from alternative electrode montages showed that focality of tDCS could be improved by adjustments in electrode placement. Heterogeneity of findings of language production studies deploying conventional montages may in part be explained by diffuse electrical field distributions. Alternative montages may improve focality and provide more unequivocal results. [ABSTRACT FROM AUTHOR]

Objective: Deep brain stimulation (DBS) requires accurate localization of the anatomical target structure, and the precise placement of the DBS electrode within it. Ultra-high field 7 Tesla (T) MR images can be utilized to create patient-specific anatomical 3D models of the subthalamic nuclei (STN) to enhance pre-surgical DBS targeting as well as post-surgical visualization of the DBS lead position and orientation. We validated the accuracy of the 7T imaging-based patient-specific model of the STN and measured the variability of the location and dimensions across movement disorder patients. Methods: 72 patients who underwent DBS surgery were scanned preoperatively on 7T MRI. Segmentations and 3D volume rendering of the STN were generated for all patients. For 21 STN-DBS cases, microelectrode recording (MER) was used to validate the segmentation. For 12 cases, we computed the correlation between the overlap of the STN and volume of tissue activated (VTA) and the monopolar review for a further validation of the model’s accuracy and its clinical relevancy. Results: We successfully reconstructed and visualized the STN in all patients. Significant variability was found across individuals regarding the location of the STN center of mass as well as its volume, length, depth and width. Significant correlations were found between MER and the 7T imaging-based model of the STN (r = 0.86) and VTA-STN overlap and the monopolar review outcome (r = 0.61). Conclusion: The results suggest that an accurate visualization and localization of a patient-specific 3D model of the STN can be generated based on 7T MRI. The imaging-based 7T MRI STN model was validated using MER and patient’s clinical outcomes. The significant variability observed in the STN location and shape based on a large number of patients emphasizes the importance of an accurate direct visualization of the STN for DBS targeting. An accurate STN localization can facilitate postoperative stimulation parameters for optimized patient outcome. [ABSTRACT FROM AUTHOR]

A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license. [ABSTRACT FROM AUTHOR]

The number of selectable targets is one of the main factors that affect the performance of a brain-computer interface (BCI). Most existing code modulated visual evoked potential (c-VEP) based BCIs use a single pseudorandom binary sequence and its circularly shifting sequences to modulate different stimulus targets, making the number of selectable targets limited by the length of modulation codes. This paper proposes a novel paradigm for c-VEP BCIs, which divides the stimulus targets into four target groups and each group of targets are modulated by a unique pseudorandom binary code and its circularly shifting codes. Based on the paradigm, a four-group c-VEP BCI with a total of 64 stimulus targets was developed and eight subjects were recruited to participate in the BCI experiment. Based on the experimental data, the characteristics of the c-VEP BCI were explored by the analyses of auto- and cross-correlation, frequency spectrum, signal to noise ratio and correlation coefficient. On the basis, single-trial data with the length of one stimulus cycle were classified and the attended target was recognized. The averaged classification accuracy across subjects was 88.36% and the corresponding information transfer rate was as high as 184.6 bit/min. These results suggested that the c-VEP BCI paradigm is both feasible and effective, and provides a new solution for BCI study to substantially increase the number of available targets. [ABSTRACT FROM AUTHOR]

Functional connectivity (FC) characterizes brain activity from a multivariate set of N brain signals by means of an NxN matrix A, whose elements estimate the dependence within each possible pair of signals. Such matrix can be used as a feature vector for (un)supervised subject classification. Yet if N is large, A is highly dimensional. Little is known on the effect that different strategies to reduce its dimensionality may have on its classification ability. Here, we apply different machine learning algorithms to classify 33 children (age [6-14 years]) into two groups (healthy controls and Attention Deficit Hyperactivity Disorder patients) using EEG FC patterns obtained from two phase synchronisation indices. We found that the classification is highly successful (around 95%) if the whole matrix A is taken into account, and the relevant features are selected using machine learning methods. However, if FC algorithms are applied instead to transform A into a lower dimensionality matrix, the classification rate drops to less than 80%. We conclude that, for the purpose of pattern classification, the relevant features should be selected among the elements of A by using appropriate machine learning algorithms. [ABSTRACT FROM AUTHOR]

Magnitudes or quantities of the different dimensions that define a stimulus (e.g., space, speed or numerosity) influence the perceived duration of that stimulus, a phenomenon known as (temporal) interference effects. This complicates studying the neurobiological foundation of the perception of time, as any signatures of temporal processing are tainted by interfering dimensions. In earlier work, in which judgements on either time or numerosity were made while EEG was recorded, we used Maximum Likelihood Estimation (MLE) to estimate, for each participant separately, the influence of temporal and numerical information on making duration or numerosity judgements. We found large individual differences in the estimated magnitudes, but ML-estimates allowed us to partial out interference effects. However, for such analyses, it is essential that estimates are meaningful and stable. Therefore, in the current study, we examined the reliability of the MLE procedure by comparing the interference magnitudes estimated in two sessions, spread a week apart. In addition to the standard paradigm, we also presented task variants in which the interfering dimension was manipulated, to assess which aspects of the numerosity dimension exert the largest influence on temporal processing. The results indicate that individual interference magnitudes are stable, both between sessions and over tasks. Further, the ML-estimates of the time-numerosity judgement tasks were predictive of performance in a standard temporal judgement task. Thus, how much temporal information participants use in time estimations tasks seems to be a stable trait that can be captured with the MLE procedure. ML-estimates are, however, not predictive of performance in other interference-tasks, here operationalized by a numerical Stroop task. Taken together, the MLE procedure is a reliable tool to quantify individual differences in magnitude interference effects and can therefore reliably inform the analysis of neuroimaging data when contrasts are needed between the accumulation of a temporal and an interfering dimension. [ABSTRACT FROM AUTHOR]

Emojis are ideograms that are becoming ubiquitous in digital communication. However, no research has yet investigated how humans process semantic and pragmatic content of emojis in real time. We investigated neural responses to irony-producing emojis, the question being whether emoji-generated irony is processed similarly to word-generated irony. Previous ERP studies have routinely found P600 effects to verbal irony. Our research sought to identify whether the same neural responses could also be elicited by emoji-induced irony. In three experiments, participants read sentences that ended in either a congruent, incongruent, or ironic (wink) emoji. Results across all three experiments demonstrated clear P600 effects, the amplitudes of which were correlated with participants’ tendency to treat the emoji as a marker of irony, as indicated by behavioral comprehension question responses. These ironic wink emojis also elicited a strong P200 effect, also found in studies of verbal irony processing. Moreover, unexpected emojis (both mismatch and ironic emoji) also elicited late frontal positivities, which have been implicated processing unpredicted words in context. These results are the first to identify how linguistically-relevant ideograms are processed in real-time at the neural level, and specifically draw parallels between the processing of word- and emoji-induced irony. [ABSTRACT FROM AUTHOR]

This paper addresses the overlearning problem in the independent component analysis (ICA) used for the removal of muscular artifacts from electroencephalographic (EEG) records. We note that for short EEG records with high number of channels the ICA fails to separate artifact-free EEG and muscular artifacts, which has been previously attributed to the phenomenon called overlearning. We address this problem by projecting an EEG record into several subspaces with a lower dimension, and perform the ICA on each subspace separately. Due to a reduced dimension of the subspaces, the overlearning is suppressed, and muscular artifacts are better separated. Once the muscular artifacts are removed, the signals in the individual subspaces are combined to provide an artifact free EEG record. We show that for short signals and high number of EEG channels our approach outperforms the currently available ICA based algorithms for muscular artifact removal. The proposed technique can efficiently suppress ICA overlearning for short signal segments of high density EEG signals. [ABSTRACT FROM AUTHOR]

A key component of working memory is the ability to remember multiple items simultaneously. To understand how the human brain maintains multiple items in memory, we examined direct brain recordings of neural oscillations from neurosurgical patients as they performed a working memory task. We analyzed the data to identify the neural representations of individual memory items by identifying recording sites with broadband gamma activity that varied according to the identity of the letter a subject viewed. Next, we tested a previously proposed model of working memory, which had hypothesized that the neural representations of individual memory items sequentially occurred at different phases of the theta/alpha cycle. Consistent with this model, the phase of the theta/alpha oscillation when stimulus-related gamma activity occurred during maintenance reflected the order of list presentation. These results suggest that working memory is organized by a cortical phase code coordinated by coupled theta/alpha and gamma oscillations and, more broadly, provide support for the serial representation of items in working memory. [ABSTRACT FROM AUTHOR]

We investigate how susceptible human drivers are to auditory signals in three situations: when stationary, when driving, or when being driven by an autonomous vehicle. Previous research has shown that human susceptibility is reduced when driving compared to when being stationary. However, it is not known how susceptible humans are under autonomous driving conditions. At the same time, good susceptibility is crucial under autonomous driving conditions, as such systems might use auditory signals to communicate a transition of control from the automated vehicle to the human driver. We measured susceptibility using a three-stimulus auditory oddball paradigm while participants experienced three driving conditions: stationary, autonomous, or driving. We studied susceptibility through the frontal P3 (fP3) Electroencephalography Event-Related Potential response (EEG ERP response). Results show that the fP3 component is reduced in autonomous compared to stationary conditions, but not as strongly as when participants drove themselves. In addition, the fP3 component is further reduced when the oddball task does not require a response (i.e., in a passive condition, versus active). The implication is that, even in a relatively simple autonomous driving scenario, people’s susceptibility of auditory signals is not as high as would be beneficial for responding to auditory stimuli. [ABSTRACT FROM AUTHOR]

Neurofeedback (NF) is a form of behavioral therapy used to treat e.g. attention-deficit/hyperactivity disorder (ADHD). Briefly, subjects are fed-back a putatively dysfunctional parameter of their brain activity in real time and must learn to control it in a suggested direction. NF protocols for ADHD have been used in practice for decades, though no clear standards on NF design have been implemented. Furthermore, studies often present only data from the general outcome of the NF treatment and do not look at how exactly the NF paradigm affects brain functionality, or what exactly the NF is training. The current study is two-fold: firstly, we look at how the functional connectivity (FC) patterns within key networks associated with ADHD differ between rests, feedback trials, success and failure in a complete functional near-infrared spectroscopy-based NF experiment on adults with ADHD. Secondly, due to methodological concerns discovered during the analysis of our data, we address important considerations in the design of NF that are often ignored in protocols being used widely in therapy and research today. In particular, we examine the common average reference and its impact on network activity as well as the importance of balancing the randomization in a design. Finally, we discuss how these methodological considerations may have influenced our FC results. [ABSTRACT FROM AUTHOR]

Background and purpose: Spared fibers after spinal cord injury (SCI) tend to consist predominantly of subcortical circuits that are not under volitional (cortical) control. We aim to improve function after SCI by using targeted physical exercises designed to simultaneously stimulate cortical and spared subcortical neural circuits. Methods: Participants with chronic motor-incomplete SCI enrolled in a single-center, prospective interventional crossover study. Participants underwent 48 sessions each of weight-supported robotic-assisted treadmill training and a novel combination of balance and fine hand exercises, in randomized order, with a 6-week washout period. Change post-intervention was measured for lower extremity motor score, soleus H-reflex facilitation; seated balance function; ambulation; spasticity; and pain. Results: Only 9 of 21 enrolled participants completed both interventions. Thirteen participants completed at least one intervention. Although there were no statistically significant differences, multimodal training tended to increase short-interval H-reflex facilitation, whereas treadmill training tended to improve dynamic seated balance. Discussion: The low number of participants who completed both phases of the crossover intervention limited the power of this study to detect significant effects. Other potential explanations for the lack of significant differences with multimodal training could include insufficient engagement of lower extremity motor cortex using skilled upper extremity exercises; and lack of skill transfer from upright postural stability during multimodal training to seated dynamic balance during testing. To our knowledge, this is the first published study to report seated posturography outcomes after rehabilitation interventions in individuals with SCI. Conclusion: In participants with chronic incomplete SCI, a novel mix of multimodal exercises incorporating balance exercises with skilled upper extremity exercises showed no benefit compared to an active control program of body weight-supported treadmill training. To improve participant retention in long-term rehabilitation studies, subsequent trials would benefit from a parallel group rather than crossover study design. [ABSTRACT FROM AUTHOR]

Mindfulness based stress reduction (MBSR) training has been proposed to improve attentional skills by modulating thalamo-cortical loops that affect the sensitivity of relevant cortical areas like the somatosensory cortex. This modulation may be reflected in the electroencephalographic (EEG) alpha rhythm, and could affect the processing of subsequently applied intracutaneous electrical stimuli. Participants took part in an MBSR training and participated in two EEG sessions. EEG was measured in variants of an endogenous orienting paradigm in which attention had to be directed to the left or right forearm. After the orienting interval, the electrical stimulus was applied, equally likely on the attended or the unattended forearm. One group of participants took part in the EEG session before and after the training, while the other group took part after the training, and another time, eight weeks later. The influence of the MBSR training and spatial attention were examined with behavioral measures, lateralized alpha power within the orienting interval, and with event-related potentials (ERPs) evoked by the electrical stimuli. Self-reported mindfulness was clearly affected by the training, but no influence was found on other behavioral measures. Alpha power was clearly lateralized due to spatial attention and several ERP components (N130, N180, P340) were modulated by spatial attention but no support was found for an influence of the MBSR training. Finally, analyses revealed that individual differences in training time modulated some of the observed effects, but no support was found for an influence on attentional orienting. [ABSTRACT FROM AUTHOR]

Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep “sleep-wake” phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%–78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported. [ABSTRACT FROM AUTHOR]

Although misfolding of normal prion protein (PrPC) into abnormal conformers (PrPSc) is critical for prion disease pathogenesis our current understanding of the underlying molecular pathophysiology is rudimentary. Exploiting an electrophysiology paradigm, herein we report that at least modestly proteinase K (PK)-resistant PrPSc (PrPres) species are acutely synaptotoxic. Brief exposure to ex vivo PrPSc from two mouse-adapted prion strains (M1000 and MU02) prepared as crude brain homogenates (cM1000 and cMU02) and cell lysates from chronically M1000-infected RK13 cells (MoRK13-Inf) caused significant impairment of hippocampal CA1 region long-term potentiation (LTP), with the LTP disruption approximating that reported during the evolution of murine prion disease. Proof of PrPSc (especially PrPres) species as the synaptotoxic agent was demonstrated by: significant rescue of LTP following selective immuno-depletion of total PrP from cM1000 (dM1000); modestly PK-treated cM1000 (PK+M1000) retaining full synaptotoxicity; and restoration of the LTP impairment when employing reconstituted, PK-eluted, immuno-precipitated M1000 preparations (PK+IP-M1000). Additional detailed electrophysiological analyses exemplified by impairment of post-tetanic potentiation (PTP) suggest possible heightened pre-synaptic vulnerability to the acute synaptotoxicity. This dysfunction correlated with cumulative insufficiency of replenishment of the readily releasable pool (RRP) of vesicles during repeated high-frequency stimulation utilised for induction of LTP. Broadly comparable results with LTP and PTP impairment were obtained utilizing hippocampal slices from PrPC knockout (PrPo/o) mice, with cM1000 serial dilution assessments revealing similar sensitivity of PrPo/o and wild type (WT) slices. Size fractionation chromatography demonstrated that synaptotoxic PrP correlated with PK-resistant species >100kDa, consistent with multimeric PrPSc, with levels of these species >6 ng/ml appearing sufficient to induce synaptic dysfunction. Biochemical analyses of hippocampal slices manifesting acute synaptotoxicity demonstrated reduced levels of multiple key synaptic proteins, albeit with noteworthy differences in PrPo/o slices, while such changes were absent in hippocampi demonstrating rescued LTP through treatment with dM1000. Our findings offer important new mechanistic insights into the synaptic impairment underlying prion disease, enhancing prospects for development of targeted effective therapies. [ABSTRACT FROM AUTHOR]

Background and objective: To determine rates of adverse events (AEs) related to deep brain stimulation (DBS) surgery or implanted devices from a large series from a single institution. Sound comparisons with the literature require the definition of unambiguous categories, since there is no consensus on the reporting of such AEs. Patients and methods: 123 consecutive patients (median age 63 yrs; female 45.5%) treated with DBS in the subthalamic nucleus (78 patients), ventrolateral thalamus (24), internal pallidum (20), and centre médian-parafascicular nucleus (1) were analyzed retrospectively. Both mean and median follow-up time was 4.7 years (578 patient-years). AEs were assessed according to three unambiguous categories: (i) hemorrhages including other intracranial complications because these might lead to neurological deficits or death, (ii) infections and similar AEs necessitating the explantation of hardware components as this results in the interruption of DBS therapy, and (iii) lead revisions for various reasons since this involves an additional intracranial procedure. For a systematic review of the literature AE rates were calculated based on primary data presented in 103 publications. Heterogeneity between studies was assessed with the I2 statistic and analyzed further by a random effects meta-regression. Publication bias was analyzed with funnel plots. Results: Surgery- or hardware-related AEs (23) affected 18 of 123 patients (14.6%) and resolved without permanent sequelae in all instances. In 2 patients (1.6%), small hemorrhages in the striatum were associated with transient neurological deficits. In 4 patients (3.3%; 0.7% per patient-year) impulse generators were removed due to infection. In 2 patients electrodes were revised (1.6%; 0.3% per patient-year). There was no lead migration or surgical revision because of lead misplacement. Age was not statistically significant different (p>0.05) between patients affected by AEs or not. AE rates did not decline over time and similar incidences were found among all patients (423) implanted with DBS systems at our institution until December 2016. A systematic literature review revealed that exact AE rates could not be determined from many studies, which could not be attributed to study designs. Average rates for intracranial complications were 3.8% among studies (per-study analysis) and 3.4% for pooled analysis of patients from different studies (per-patient analysis). Annual hardware removal rates were 3.6 and 2.4% for per-study and per-patient analysis, respectively, and lead revision rates were 4.1 and 2.6%, respectively. There was significant heterogeneity between studies (I2 ranged between 77% and 91% for the three categories; p< 0.0001). For hardware removal heterogeneity (I2 = 87.4%) was reduced by taking study size (p< 0.0001) and publication year (p< 0.01) into account, although a significant degree of heterogeneity remained (I2 = 80.0%; p< 0.0001). Based on comparisons with health care-related databases there appears to be publication bias with lower rates for hardware-related AEs in published patient cohorts. Conclusions: The proposed categories are suited for an unequivocal assessment of AEs even in a retrospective manner and useful for benchmarking. AE rates in the present cohorts from our institution compare favorable with the literature. [ABSTRACT FROM AUTHOR]

Photophobia is a common condition in which bright light causes an unpleasant feeling due to increased sensitivity to light. In addition to discomfort, photophobia may be accompanied by visual dysfunction. The present study was conducted in order to examine whether visual evoked cortical responses contribute to the assessment of visual dysfunction due to bright light. Visual evoked magnetic fields (VEFs) following the presentation of a uniform bright light of 200–3700 cd/m2 in the lower visual field were recorded in 10 healthy volunteers and the effects of five color lenses: yellow, blue, gray, green, and colorless, were examined. VEFs were subjected to a multi-dipole analysis that resulted in the separation of several source activities, including the retina, V1, V2, V6, and fusiform gyrus. Source activity in the retina corresponding to the ERG b-wave exhibited a reduced amplitude and elongated peak latency with the yellow lens. Its latency strongly correlated with transmittance at 450 nm. On the other hand, cortical activities in V1 and the fusiform gyrus were stronger with the yellow lens than with the other color and colorless lenses. Only blue-light blocking showed significant effects. The result showing that the yellow lens enhanced V1 and fusiform activities indicated that processing in these areas was improved when subjects used this lens. The combination of delayed retinal activity and increased visual cortex activity may be an objective indicator of the effects of a color lens on visual function. [ABSTRACT FROM AUTHOR]

When we observe a dynamic emotional facial expression, we usually automatically anticipate how that expression will develop. Our objective was to study a neurocognitive biomarker of this anticipatory process for facial pain expressions, operationalized as a mismatch effect. For this purpose, we studied the behavioral and neuroelectric (Event-Related Potential, ERP) correlates, of a match or mismatch, between the intensity of an expression of pain anticipated by the participant, and the intensity of a static test expression of pain displayed with the use of a representational momentum paradigm. Here, the paradigm consisted in displaying a dynamic facial pain expression which suddenly disappeared, and participants had to memorize the final intensity of the dynamic expression. We compared ERPs in response to congruent (intensity the same as the one memorized) and incongruent (intensity different from the one memorized) static expression intensities displayed after the dynamic expression. This paradigm allowed us to determine the amplitude and direction of this intensity anticipation by measuring the observer’s memory bias. Results behaviorally showed that the anticipation was backward (negative memory bias) for high intensity expressions of pain (participants expected a return to a neutral state) and more forward (memory bias less negative, or even positive) for less intense expressions (participants expected increased intensity). Detecting mismatch (incongruent intensity) led to faster responses than detecting match (congruent intensity). The neuroelectric correlates of this mismatch effect in response to the testing of expression intensity ranged from P100 to LPP (Late Positive Potential). Path analysis and source localization suggested that the medial frontal gyrus was instrumental in mediating the mismatch effect through top-down influence on both the occipital and temporal regions. Moreover, having the facility to detect incongruent expressions, by anticipating emotional state, could be useful for prosocial behavior and the detection of trustworthiness. [ABSTRACT FROM AUTHOR]

We used event-related potentials to investigate morphosyntactic development in 78 adult English-speaking learners of Spanish as a second language (L2) across the proficiency spectrum. We examined how development is modulated by the similarity between the native language (L1) and the L2, by comparing number (a feature present in English) and gender agreement (novel feature). We also investigated how development is impacted by structural distance, manipulating the distance between the agreeing elements by probing both within-phrase ( muy “fruit-FEM-SG very juicy-FEM-SG”) and across-phrase agreement ( es “strawberry-FEM-SG is tart-FEM-SG”). Regression analyses revealed that the learners’ overall proficiency, as measured by a standardized test, predicted their accuracy with the target properties in the grammaticality judgment task (GJT), but did not predict P600 magnitude to the violations. However, a relationship emerged between immersion in Spanish-speaking countries and P600 magnitude for gender. Our results also revealed a correlation between accuracy in the GJT and P600 magnitude, suggesting that behavioral sensitivity to the target property predicts neurophysiological sensitivity. Subsequent group analyses revealed that the highest-proficiency learners showed equally robust P600 effects for number and gender. This group also elicited more positive waveforms for within- than across-phrase agreement overall, similar to the native controls. The lowest-proficiency learners showed a P600 for number overall, but no effects for gender. Unlike the highest-proficiency learners, they also showed no sensitivity to structural distance, suggesting that sensitivity to such linguistic factors develops over time. Overall, these results suggest an important role for proficiency in morphosyntactic development, although differences emerged between behavioral and electrophysiological measures. While L2 proficiency predicted behavioral sensitivity to agreement, development with respect to the neurocognitive mechanisms recruited in processing only emerged when comparing the two extremes of the proficiency spectrum. Importantly, while both L1-L2 similarity and hierarchical structure impact development, they do not constrain it. [ABSTRACT FROM AUTHOR]

Background: Most humans have the ability to activate the auricular muscles. Although (intentional) control suggests an involvement of higher cortical centers underlying posterior auricular muscle (PAM) activation, the cortical representation of the auricular muscles is still unknown. Methods: With the purpose of identifying a possible cortical representation area we performed automated robotic and image-guided transcranial magnetic stimulation (TMS) mapping (n = 8) and functional magnetic resonance imaging (fMRI) (n = 13). For topographical comparison, a similar experimental protocol was applied for the first dorsal interosseus muscle (FDI) of the hand. Results: The calculated centers of gravity (COGs) of both muscles were located on the precentral gyrus with the PAM COGs located more laterally compared to the FDI. The distance between the mean PAM and mean FDI COG was 26.3 mm. The TMS mapping results were confirmed by fMRI, which showed a dominance of cortical activation within the precentral gyrus during the corresponding motor tasks. The correspondence of TMS and fMRI results was high. Conclusion: The involvement of the primary motor cortex in PAM activation might point to an evolved function of the auricular muscles in humans and/or the ability of intentional (and selective) muscle activation. [ABSTRACT FROM AUTHOR]

One of the founding experiments in the field of Neuro-Information-Systems (NeuroIS), which aims at exploring the neural correlates of the technology acceptance model, suggests that perceived ease of use (PEoU) is associated with activity in the dorsolateral prefrontal cortex (DLPFC) while perceived usefulness is associated with activity in the insula, caudate nucleus and anterior cingulate cortex. To further assess the link between DLPFC and PEoU, transcranial direct current stimulation (tDCS) was applied over bilateral DLPFC (F3 and F4) immediately before an online shopping task. Forty-two participants were divided in three stimulation groups: left anodal/right cathodal, left cathodal/right anodal and sham. No change in PEoU was observed post stimulation but participants in the left anodal/right cathodal stimulation group took longer to make a purchase compared to sham stimulation and had different visual fixation patterns over the buy buttons. This is, to our knowledge, the first use of non-invasive brain stimulation in the field of NeuroIS. Although the involvement of DLPFC in PEoU could not be confirmed, the present study suggests that non-invasive brain stimulation may be a useful research tool in NeuroIS. [ABSTRACT FROM AUTHOR]

One important organizational property of morphology is competition. Different means of expression are in conflict with each other for encoding the same grammatical function. In the current study, we examined the nature of this control mechanism by testing the formation of comparative adjectives in English during language production. Event-related brain potentials (ERPs) were recorded during cued silent production, the first study of this kind for comparative adjective formation. We specifically examined the ERP correlates of producing synthetic relative to analytic comparatives, e.g. angrier vs. more angry. A frontal, bilaterally distributed, enhanced negative-going waveform for analytic comparatives (vis-a-vis synthetic ones) emerged approximately 300ms after the (silent) production cue. We argue that this ERP effect reflects a control mechanism that constrains grammatically-based computational processes (viz. more comparative formation). We also address the possibility that this particular ERP effect may belong to a family of previously observed negativities reflecting cognitive control monitoring, rather than morphological encoding processes per se. [ABSTRACT FROM AUTHOR]

Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level accuracy using a feedforward architecture, providing neuroscientists with the opportunity to assess one successful series of representational transformations that enable categorization in silico. The goal of the current study is to assess the extent to which sequential scene category representations built by a CNN map onto those built in the human brain as assessed by high-density, time-resolved event-related potentials (ERPs). We found correspondence both over time and across the scalp: earlier (0–200 ms) ERP activity was best explained by early CNN layers at all electrodes. Although later activity at most electrode sites corresponded to earlier CNN layers, activity in right occipito-temporal electrodes was best explained by the later, fully-connected layers of the CNN around 225 ms post-stimulus, along with similar patterns in frontal electrodes. Taken together, these results suggest that the emergence of scene category representations develop through a dynamic interplay between early activity over occipital electrodes as well as later activity over temporal and frontal electrodes. [ABSTRACT FROM AUTHOR]

Behavioral and neurophysiological findings in vision suggest that perceptual grouping is not a unitary process and that different grouping principles have different processing requirements and neural correlates. The present study aims to examine whether the same occurs in the haptic modality using two grouping principles widely studied in vision, spatial proximity and texture similarity. We analyzed behavioral responses (accuracy and response times) and conducted an independent component analysis of brain oscillations in alpha and beta bands for haptic stimuli grouped by spatial proximity and texture similarity, using a speeded orientation detection task performed on a novel haptic device (MonHap). Behavioral results showed faster response times for patterns grouped by spatial proximity relative to texture similarity. Independent component clustering analysis revealed the activation of a bilateral network of sensorimotor and parietal areas while performing the task. We conclude that, as occurs in visual perception, grouping the elements of the haptic scene by means of their spatial proximity is faster than forming the same objects by means of texture similarity. In addition, haptic grouping seems to involve the activation of a network of widely distributed bilateral sensorimotor and parietal areas as reflected by the consistent event-related desynchronization found in alpha and beta bands. [ABSTRACT FROM AUTHOR]

Generally, prognostication of coma outcome currently combines behavioral, reflex, and possibly neuroimaging tests that are interpreted by an attending physician. Electroencephalography, particularly, event-related brain potentials (ERP) have received attention due to evidence demonstrating the positive predictive value of certain ERP including the mismatch negativity (MMN) and the P3a, for coma emergence. We describe a set of ERP paradigms designed to require and reflect increasing levels of cognitive processing with the added objective of determining the influence of each paradigm’s context strength on its ability to elicit ERPs. These paradigms were then used without explicit instructions to participants to attend to the stimuli to determine which paradigms possessed sufficient context “strength” to elicit ERPs in the absence of active participation on the part of the subject; a circumstance often encountered in brain injury patients. These paradigms were then validated on two groups of adults–younger and older, and the difference due to active participation was validated on another group of younger adults. Results show that paradigms with stronger stimulus context features performed better than those with weaker contexts, and that older adults generally had significantly attenuated and delayed responses compared to younger adults. Based on these findings, it is recommended the use of the auditory oddball paradigm that includes novel stimuli to elicit the mismatch negativity and P300, and semantic violation sentences to elicit the N400. These findings also reinforce the procedure of instructing participants about the requirements of a protocol–regardless of the patient’s diagnosis or apparent state–in order to help those who are able to attend to show the most robust responses possible. [ABSTRACT FROM AUTHOR]

The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brain’s global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brain’s response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research. [ABSTRACT FROM AUTHOR]

Previous studies, which examined whether symbolic and non-symbolic quantity representations are processed by two independent systems or by one common system, reached contradicting findings, possibly due to methodological differences. Indeed, some researchers advocate the two systems approach, based on the presence of notation-specific switch cost in conditions where adults have to compare pairs of symbolic and non-symbolic quantities, in combination with the absence of such a cost in conditions containing quantities of the same notation. However, other researchers used matching instructions, and reported a facilitation in the mixed notation conditions, suggesting that the two systems are automatically integrated. In the current study, we conducted three experiments, in which we examined the existence of two separate quantity systems, but we used various experimental manipulations (e.g., task instructions, presentation order) to unravel the previous inconsistent findings. In Experiment 1, we investigated the role of task instructions by presenting participants with pure and mixed notation trials with both comparison and matching tasks. In Experiment 2, we tested the role of blocked and randomized presentation order for the pure and mixed trials. Our data showed that cost for switching between the symbolic and non-symbolic quantities is present, but is prone to a certain methodological drawback: when the differences between the processing times for two sequentially presented stimuli of different notations are not taken into account, this masks the cost for switching between the two systems. To overcome this problem, in Experiment 3 we used an audio-visual paradigm. Overall, our results provide further evidence for the existence of distinct quantity representations, independently of task instructions or presentation order. Additionally, considering this methodological pitfall we argue that the audio-visual paradigm is better suited when investigating the integration between symbolic and non- symbolic quantities. [ABSTRACT FROM AUTHOR]

Preferential processing of self-related information is a well-documented phenomenon on both the behavioral and neural levels. However, the impact of self-esteem on this self-preference has not been studied in a systematic way. Here, the electrophysiological correlates of explicit self-reflection were investigated in individuals with low (LSE) and high self-esteem (HSE). Participants evaluated trait adjectives in reference to the self or to an “other” person (close-other, famous) while EEG was recorded. The analysis of event-related potentials focused on the late positive component (LPC), which exhibits a fronto-central distribution and latency over 500 ms. In both LSE and HSE groups, the amplitudes of LPC were enhanced in the self condition when compared to control conditions (both close-other and famous). Crucially, LPC amplitudes in the HSE group were significantly higher than in the LSE group. Moreover, the self-preference effect, defined as the difference between amplitudes of LPC associated with the evaluation of words in relation to oneself vs. other people, was significantly higher in the HSE group than in the LSE group. Overall, our findings indicate that people with high self-esteem tend to engage in self-referential processing to a higher extent. [ABSTRACT FROM AUTHOR]

Anatomical atlases have been developed to improve the targeting of basal ganglia in deep brain stimulation. However, the sole anatomy cannot predict the functional outcome of this surgery. Deep brain stimulation is often a compromise between several functional outcomes: motor, fluency and neuropsychological outcomes in particular. In this study, we have developed anatomo-clinical atlases for the targeting of subthalamic and medial globus pallidus deep brain stimulation. The activated electrode coordinates of 42 patients implanted in the subthalamic nucleus and 29 patients in the medial globus pallidus were studied. The atlas was built using the representation of the volume of tissue theoretically activated by the stimulation. The UPDRS score was used to represent the motor outcome. The Stroop test was represented as well as semantic and phonemic fluencies. For the subthalamic nucleus, best motor outcomes were obtained when the supero-lateral part of the nucleus was stimulated whereas the semantic fluency was impaired in this same region. For the medial globus pallidus, best outcomes were obtained when the postero ventral part of the nucleus was stimulated whereas the phonemic fluency was impaired in this same region. There was no significant neuropsychological impairment. We have proposed new anatomo-clinical atlases to visualize the motor and neuropsychological consequences at 6 months of subthalamic nucleus and pallidal stimulation in patients with Parkinson's disease. [ABSTRACT FROM AUTHOR]

Virtual reality has been increasingly used in research on balance rehabilitation because it provides robust and novel sensory experiences in controlled environments. We studied 19 healthy young subjects performing a balance beam walking task in two virtual reality conditions and with unaltered view (15 minutes each) to determine if virtual reality high heights exposure induced stress. We recorded number of steps off the beam, heart rate, electrodermal activity, response time to an auditory cue, and high-density electroencephalography (EEG). We hypothesized that virtual high heights exposure would increase measures of physiological stress compared to unaltered viewing at low heights. We found that the virtual high height condition increased heart rate variability and heart rate frequency power relative to virtual low heights. Virtual reality use resulted in increased number of step-offs, heart rate, electrodermal activity, and response time compared to the unaltered viewing at low heights condition. Our results indicated that virtual reality decreased dynamic balance performance and increased physical and cognitive loading compared to unaltered viewing at low heights. In virtual reality, we found significant decreases in source-localized EEG peak amplitude relative to unaltered viewing in the anterior cingulate, which is considered important in sensing loss of balance. Our findings indicate that virtual reality provides realistic experiences that can induce physiological stress in humans during dynamic balance tasks, but virtual reality use impairs physical and cognitive performance during balance. [ABSTRACT FROM AUTHOR]

Probabilistic formalism of quantum mechanics is used to quantitatively link the global scale mass potential with the underlying electrical activity of excitable cells. Previous approaches implemented methods of classical physics to reconstruct the mass potential in terms of explicit physical models of participating cells and the volume conductor. However, the multiplicity of cellular processes with extremely intricate mixtures of deterministic and random factors prevents the creation of consistent biophysical parameter sets. To avoid the uncertainty inherent in physical attributes of cell ensembles, we undertake here a radical departure from deterministic equations of classical physics, instead applying the probabilistic reasoning of quantum mechanics. Crucial steps include: (1) the relocation of the elementary bioelectric sources from a cellular to a molecular level; (2) the creation of microscale particle models in terms of a non-homogenous birth-and-death process. To link the microscale processes with macroscale potentials, time-frequency analysis was applied for estimation of the empirical characteristic functions for component waveforms of electroencephalogram (EEG), eye-blink electromyogram (EMG), and electrocardiogram (ECG). We describe universal models for the amplitude spectra and phase functions of functional components of mass potentials. The corresponding time domain relationships disclose the dynamics of mass potential components as limit distribution functions produced by specific microscale transients. The probabilistic laws governing the microscale machinery, founded on an empirical basis, are presented. Computer simulations of particle populations with time dependent transition probabilities reveal that hidden deterministic chaos underlies development of the components of mass potentials. We label this kind of behaviour “transient deterministic chaos”. [ABSTRACT FROM AUTHOR]

We employ a time-dependent Hurst analysis to identify EEG signals that differentiate between healthy controls and combat-related PTSD subjects. The Hurst exponents, calculated using a rescaled range analysis, demonstrate a significant differential response between healthy and PTSD samples which may lead to diagnostic applications. To overcome the non-stationarity of EEG data, we apply an appropriate window length wherein the EEG data displays stationary behavior. We then use the Hurst exponents for each channel as hypothesis test statistics to identify differences between PTSD cases and controls. Our study included a cohort of 12 subjects with half healthy controls. The Hurst exponent of the PTSD subjects is found to be significantly smaller than the healthy controls in channel F3. Our results indicate that F3 may be a useful channel for diagnostic applications of Hurst exponents in distinguishing PTSD and healthy subjects. [ABSTRACT FROM AUTHOR]

This paper addresses a chaos kernel function for the relevance vector machine (RVM) in EEG signal classification, which is an important component of Brain-Computer Interface (BCI). The novel kernel function has evolved from a chaotic system, which is inspired by the fact that human brain signals depict some chaotic characteristics and behaviors. By introducing the chaotic dynamics to the kernel function, the RVM will be enabled for higher classification capacity. The proposed method is validated within the framework of one versus one common spatial pattern (OVO-CSP) classifier to classify motor imagination (MI) of four movements in a public accessible dataset. To illustrate the performance of the proposed kernel function, Gaussian and Polynomial kernel functions are considered for comparison. Experimental results show that the proposed kernel function achieved higher accuracy than Gaussian and Polynomial kernel functions, which shows that the chaotic behavior consideration is helpful in the EEG signal classification. [ABSTRACT FROM AUTHOR]

Recently, several new materials for mattresses have been introduced. Although some of these, such as low rebound (pressure-absorbing/memory foam) and high rebound mattresses have fairly different characteristics, effects of these mattresses on sleep have never been scientifically evaluated. In the current study, we have evaluated effects of a high rebound mattress topper [HR] on sleep and its associated physiology, and the effects were compared to those of a low rebound mattress toppers (LR) in healthy young (n = 10) and old (n = 20) adult males with a randomized, single-blind, cross over design. We found that sleeping with HR compared to LR induced a larger decline in core body temperature (CBT) in the initial phase of nocturnal sleep both in young (minimum CBT: 36.05 vs 36.35°C) and old (minimum CBT: 36.47 vs. 36.55°C) subjects, and declines in the CBT were associated with increases in deep sleep/delta power (+27.8% in young and +24.7% in old subjects between 11:00–01:00). We also found significantly smaller muscle activities during roll over motions with HR (-53.0 to -66.1%, depending on the muscle) during a separate daytime testing. These results suggest that sleeping with HR in comparison to with LR, may facilitate restorative sleep at the initial phase of sleep. [ABSTRACT FROM AUTHOR]

Sensory suppression is a mechanism that attenuates selective information. As for long-latency suppression in auditory and somatosensory systems, paired-pulse suppression, observed as 2 identical stimuli spaced by approximately 500 ms, is widely known, though its mechanism remains to be elucidated. In the present study, we investigated the relationship between auditory and somatosensory long-latency suppression of change-related cortical responses using magnetoencephalography. Somatosensory change-related responses were evoked by an abrupt increase in stimulus strength in a train of current-constant square wave pulses at 100 Hz to the left median nerve at the wrist. Furthermore, auditory change-related responses were elicited by an increase in sound pressure by 15 dB in a continuous sound composed of a train of 25-ms pure tones. Binaural stimulation was used in Experiment 1, while monaural stimulation was used in Experiment 2. For both somatosensory and auditory stimuli, the conditioning and test stimuli were identical, and inserted at 2400 and 3000 ms, respectively. The results showed clear suppression of the test response in the bilateral parisylvian region, but not in the postcentral gyrus of the contralateral hemisphere in the somatosensory system. Similarly, the test response in the bilateral supratemporal plane (N100m) was suppressed in the auditory system. Furthermore, there was a significant correlation between suppression of right N100m and right parisylvian activity, suggesting that similar mechanisms are involved in both. Finally, a high test-retest reliability for suppression was seen with both modalities. Suppression revealed in the present study is considered to reflect sensory inhibition ability in individual subjects. [ABSTRACT FROM AUTHOR]

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning. [ABSTRACT FROM AUTHOR]

The strength model of self-control is one of the most influential and well-established models of self-regulation in social psychology. However, recent attempts to replicate the ego depletion effect have sometimes failed. The goal of this study is to investigate self-reported replication rates and the frequency of a set of questionable research practices (QRP) in ego depletion research. A literature search resulted in 1721 researchers who had previously published on ego depletion. They were invited to participate in an anonymous online survey. The respondents (n = 277), on average, had published over three papers on ego depletion, and had completed more than two additional, unpublished studies. Respondents indicated that in more than 40% of their studies, results were similar in magnitude to those reported in the existing literature, and more than 60% reported conducting a priori power analyses. 39.2% of respondents were aware of other researchers who engaged in the surveyed QRP’s, while 37.7% affirmed to have employed said QRP’s. These results underline the importance of reducing QRP’s to reliably test the validity of the ego depletion effect. [ABSTRACT FROM AUTHOR]

Hypotension or low blood pressure (BP) is a common problem in preterm neonates and has been associated with adverse short and long-term neurological outcomes. Deciding when and whether to treat hypotension relies on an understanding of the relationship between BP and brain functioning. This study aims to investigate the interaction (coupling) between BP and continuous multichannel unedited EEG recordings in preterm infants less than 32 weeks of gestational age. The EEG was represented by spectral power in four frequency sub-bands: 0.3–3 Hz, 3–8 Hz, 8–15 Hz and 15–30 Hz. BP was represented as mean arterial pressure (MAP). The level of coupling between the two physiological systems was estimated using linear and nonlinear methods such as correlation, coherence and mutual information. Causality of interaction was measured using transfer entropy. The illness severity was represented by the clinical risk index for babies (CRIB II score) and contrasted to the computed level of interaction. It is shown here that correlation and coherence, which are linear measures of the coupling between EEG and MAP, do not correlate with CRIB values, whereas adjusted mutual information, a nonlinear measure, is associated with CRIB scores (r = -0.57, p = 0.003). Mutual information is independent of the absolute values of MAP and EEG powers and quantifies the level of coupling between the short-term dynamics in both signals. The analysis indicated that the dominant causality is from changes in EEG producing changes in MAP. Transfer entropy (EEG to MAP) is associated with the CRIB score (0.3–3 Hz: r = 0.428, p = 0.033, 3–8 Hz: r = 0.44, p = 0.028, 8–15 Hz: r = 0.416, p = 0.038) and indicates that a higher level of directed coupling from brain activity to blood pressure is associated with increased illness in preterm infants. This is the first study to present the nonlinear measure of interaction between brain activity and blood pressure and to demonstrate its relation to the initial illness severity in the preterm infant. The obtained results allow us to hypothesise that the normal wellbeing of a preterm neonate can be characterised by a nonlinear coupling between brain activity and MAP, whereas the presence of weak coupling with distinctive directionality of information flow is associated with an increased mortality rate in preterms. [ABSTRACT FROM AUTHOR]

Sedation induces changes in electroencephalography (EEG) dynamics. However, the distinct EEG dynamic characteristics at comparable sedation levels have not been well studied, resulting in potential interpretation errors in EEG monitoring during sedation. We aimed to analyze the EEG dynamics of dexmedetomidine and propofol at comparable sedation levels and to explore EEG changes with increased sedation levels for each agent. We measured the Bispectral Index (BIS) and 20-channel EEG under dexmedetomidine and propofol sedation from wakefulness, moderate sedation, and deep sedation to recovery in healthy volunteers (n = 10) in a randomized, 2-day, crossover study. Observer’s Assessment of Alertness and Sedation (OAA/S) score was used to assess sedation levels. Despite similar changes in increased delta oscillations, multiple differences in the EEG spatiotemporal dynamics were observed between these two agents. During moderate sedation, both dexmedetomidine and propofol induced increased spindle power; however, dexmedetomidine decreased the global alpha/beta/gamma power, whereas propofol decreased the alpha power in the occipital area and increased the global spindle/beta/gamma power. During deep sedation, dexmedetomidine was associated with increased fronto-central spindle power and decreased global alpha/beta/gamma power, but propofol was associated with increased theta/alpha/spindle/beta power, which was maximized in the frontal area. The transition of topographic alpha/spindle/beta power distribution from moderate sedation to deep sedation completely differed between these two agents. Our study demonstrated that there was a distinct hierarchy of EEG changes with increased sedation depths by propofol and dexmedetomidine. Differences in EEG dynamics at the same sedation level might account for differences in the BIS value and reflect the different sedation mechanisms. EEG-based clinical sedation monitoring should consider the effect of drug types on EEG dynamics. [ABSTRACT FROM AUTHOR]

This study investigates quality prediction methods for synthesized speech using EEG. Training a predictive model using EEG is challenging due to a small number of training trials, a low signal-to-noise ratio, and a high correlation among independent variables. When a predictive model is trained with a machine learning algorithm, the features extracted from multi-channel EEG signals are usually organized as a vector and their structures are ignored even though they are highly structured signals. This study predicts the subjective rating scores of synthesized speeches, including their overall impression, valence, and arousal, by creating tensor structured features instead of vectorized ones to exploit the structure of the features. We extracted various features to construct a tensor feature that maintained their structure. Vectorized and tensorial features were used to predict the rating scales, and the experimental result showed that prediction with tensorial features achieved the better predictive performance. Among the features, the alpha and beta bands are particularly more effective for predictions than other features, which agrees with previous neurophysiological studies. [ABSTRACT FROM AUTHOR]

Cracking the cytoarchitectural organization, activity patterns, and neurotransmitter nature of genetically-distinct cell types in the lateral hypothalamus (LH) is fundamental to develop a mechanistic understanding of how activity dynamics within this brain region are generated and operate together through synaptic connections to regulate circuit function. However, the precise mechanisms through which LH circuits orchestrate such dynamics have remained elusive due to the heterogeneity of the intermingled and functionally distinct cell types in this brain region. Here we reveal that a cell type in the mouse LH identified by the expression of the calcium-binding protein parvalbumin (PVALB; LHPV) is fast-spiking, releases the excitatory neurotransmitter glutamate, and sends long range projections throughout the brain. Thus, our findings challenge long-standing concepts that define neurons with a fast-spiking phenotype as exclusively GABAergic. Furthermore, we provide for the first time a detailed characterization of the electrophysiological properties of these neurons. Our work identifies LHPV neurons as a novel functional component within the LH glutamatergic circuitry. [ABSTRACT FROM AUTHOR]

Human brain function depends on directed interactions between multiple areas that evolve in the subsecond range. Time-varying multivariate autoregressive (tvMVAR) modeling has been proposed as a way to help quantify directed functional connectivity strengths with high temporal resolution. While several tvMVAR approaches are currently available, there is a lack of unbiased systematic comparative analyses of their performance and of their sensitivity to parameter choices. Here, we critically compare four recursive tvMVAR algorithms and assess their performance while systematically varying adaptation coefficients, model order, and signal sampling rate. We also compared two ways of exploiting repeated observations: single-trial modeling followed by averaging, and multi-trial modeling where one tvMVAR model is fitted across all trials. Results from numerical simulations and from benchmark EEG recordings showed that: i) across a broad range of model orders all algorithms correctly reproduced patterns of interactions; ii) signal downsampling degraded connectivity estimation accuracy for most algorithms, although in some cases downsampling was shown to reduce variability in the estimates by lowering the number of parameters in the model; iii) single-trial modeling followed by averaging showed optimal performance with larger adaptation coefficients than previously suggested, and showed slower adaptation speeds than multi-trial modeling. Overall, our findings identify strengths and weaknesses of existing tvMVAR approaches and provide practical recommendations for their application to modeling dynamic directed interactions from electrophysiological signals. [ABSTRACT FROM AUTHOR]

As a crucial living environment, the Internet shapes cognition. The Internet provides massive information that can be accessed quickly via hyperlinks, but the information is typically fragmentary and concrete rather than integrative. According to construal level theory, the processing of this concrete and fragmentary information, should reduce attentional scope. Two experiments were conducted to test this hypothesis. In Experiment 1, three groups of participants were asked to shop online, read magazines or have a rest respectively, and a divided attention Navon-letter task was employed to measure the attentional scope before and after the assigned activity. It was found that the difference between reaction times in response to local vs. global targets was decreased only after Internet use, while there was no decrease in either the reading or resting group. In Experiment 2, the same procedure was used, and EEG/ERP methods were used to record both behavioral response and neural activity. Results showed that before the assigned activity, there was no significant difference in N2 amplitude in response to local vs. global targets in any of the three groups; during the activity, the lower-alpha activity induced by Internet use was significantly lower than that induced by reading or resting; after the activity, correspondingly, a more negative N2 wave was induced by the global than local targets only in the Internet group, while there were no significant differences in the other groups. Consistent with construal level theory, the results suggest that when surfing the Internet, attentional scope is reduced, and this effect might continue after Internet activity. [ABSTRACT FROM AUTHOR]

Source analyses on event related potentials (ERPs) derived from the electroencephalogram (EEG) were performed to examine the respective roles of cortical areas preceding exogenously triggered saccades, combined convergences, and combined divergences. All eye movements were triggered by the offset of a central fixation light emitting diode (LED) and the onset of a lateral LED at various depths in an otherwise fully darkened room. Our analyses revealed that three source pairs, two located in the frontal lobe–the frontal eye fields (FEF) and an anterior frontal area–, and one located within the occipital cortex, can account for 99.2% of the observed ERPs. Overall, the comparison between source activities revealed the largest activity in the occipital cortex, while no difference in activity between FEF and the anterior frontal area was obtained. For all sources, increased activity was observed for combined vergences, especially combined convergences, relative to saccades. Behavioral results revealed that onset latencies were longest for combined convergences, intermediate for combined divergences, and the shortest for saccades. Together, these findings fit within a perspective in which both occipital and frontal areas play an important role in retinal disparity detection. In the case of saccades and combined divergences stimulus-locked activity was larger than response-locked activity, while no difference between stimulus- and response-locked activity was observed for combined convergences. These findings seem to imply that the electrophysiological activity preceding exogenous eye movements consists of a sensory-related part that is under cortical control, while subcortical structures may be held responsible for final execution. [ABSTRACT FROM AUTHOR]

The BDNF Val66Met polymorphism is associated with impaired short-term plasticity in the motor cortex, short-term motor learning, and intermanual transfer of a procedural motor skill. Here, we investigated the impact of the Val66Met polymorphism on the modulation of cortical excitability and interhemispheric inhibition through sensorimotor practice of simple dynamic skills with the right and left first dorsal interosseous (FDI) muscles. To that end, we compared motor evoked potentials (MEP) amplitudes and short-interval intracortical inhibition (SICI) in the bilateral representations of the FDI muscle in the primary motor cortex (M1), and interhemispheric inhibition (IHI) from the left to right M1, before and after right and left FDI muscle training in an alternated sequence. Val66Met participants did not differ from their Val66Val counterparts on motor performance at baseline and following motor training, or on measures of MEP amplitude and IHI. However, while the Val66Val group displayed significant SICI reduction in the bilateral M1 in response to motor training, SICI remained unchanged in the Val66Met group. Further, Val66Val group’s SICI decrease in the left M1, which was also observed following unimanual training with the right hand in the Control Right group, was correlated with motor improvement with the left hand. The potential interaction between left and right M1 activity during bimanual training and the implications of altered activity-dependent cortical excitability on short-term motor learning in Val66Met carriers are discussed. [ABSTRACT FROM AUTHOR]

Mental fatigue is one of the main reasons for the decline of response inhibition. This study aimed to explore the impairing influence of mental fatigue on a driver’s response inhibition. The effects of mental fatigue on response inhibition were assessed by comparing brain activity and behavioral indices when performing a Go/NoGo task before and after a 90-min fatigue manipulation task. Participants in the driving group performed a simulated driving task, while individuals in the control group spent the same time watching movies. We found that participants in the driving group reported higher levels of mental fatigue and had a higher percentage of eye closure and larger lateral deviations from their lane positions, which indicated there was effective manipulation of mental fatigue through a prolonged simulated driving task. After manipulation of mental fatigue, we observed increased reaction time and miss rates, delayed NoGo-N2 latency and Go-P3 latency, and decreased NoGo-P3 amplitude, which indicated that mental fatigue may slow down the speed of the inhibition process, delay the evaluation of visual stimuli and reduce the availability of attentional resources. These findings revealed the underlying neurological mechanisms of how mental fatigue impaired response inhibition. [ABSTRACT FROM AUTHOR]

Sleep science is entering a new era, thanks to new data-driven analysis approaches that, combined with mouse gene–editing technologies, show a promise in functional genomics and translational research. However, the investigation of sleep is time consuming and not suitable for large-scale phenotypic datasets, mainly due to the need for subjective manual annotations of electrophysiological states. Moreover, the heterogeneous nature of sleep, with all its physiological aspects, is not fully accounted for by the current system of sleep stage classification. In this study, we present a new data-driven analysis approach offering a plethora of novel features for the characterization of sleep. This novel approach allowed for identifying several substages of sleep that were hidden to standard analysis. For each of these substages, we report an independent set of homeostatic responses following sleep deprivation. By using our new substages classification, we have identified novel differences among various genetic backgrounds. Moreover, in a specific experiment with the Zfhx3 mouse line, a recent circadian mutant expressing both shortening of the circadian period and abnormal sleep architecture, we identified specific sleep states that account for genotypic differences at specific times of the day. These results add a further level of interaction between circadian clock and sleep homeostasis and indicate that dissecting sleep in multiple states is physiologically relevant and can lead to the discovery of new links between sleep phenotypes and genetic determinants. Therefore, our approach has the potential to significantly enhance the understanding of sleep physiology through the study of single mutations. Moreover, this study paves the way to systematic high-throughput analyses of sleep. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is modeled to explore the mechanisms of this effective, but poorly understood, treatment for motor symptoms of drug-refractory Parkinson’s disease and dystonia. First, a neural field model of the corticothalamic-basal ganglia (CTBG) system is developed that reproduces key clinical features of Parkinson’s disease, including its characteristic 4–8 Hz and 13–30 Hz electrophysiological signatures. Deep brain stimulation of the STN is then modeled and shown to suppress the pathological 13–30 Hz (beta) activity for physiologically realistic and optimized stimulus parameters. This supports the idea that suppression of abnormally coherent activity in the CTBG system is a major factor in DBS therapy for Parkinson’s disease, by permitting normal dynamics to resume. At high stimulus intensities, nonlinear effects in the target population mediate wave-wave interactions between resonant beta activity and the stimulus pulse train, leading to complex spectral structure that shows remarkable similarity to that seen in steady-state evoked potential experiments. [ABSTRACT FROM AUTHOR]

Our ability to parse our acoustic environment relies on the brain’s capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain’s sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance). In this work, we investigate the brain’s sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects’ behavior indicates an important role of perceptual constraints in listeners’ ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG) responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain’s ability to process stochastic sound sequences. [ABSTRACT FROM AUTHOR]