Cortical signatures of auditory object binding in children with autism spectrum disorder are anomalous in concordance with behavior and diagnosis.

Organizing sensory information into coherent perceptual objects is fundamental to everyday perception and communication. In the visual domain, indirect evidence from cortical responses suggests that children with autism spectrum disorder (ASD) have anomalous figure-ground segregation. While auditory processing abnormalities are common in ASD, especially in environments with multiple sound sources, to date, the question of scene segregation in ASD has not been directly investigated in audition. Using magnetoencephalography, we measured cortical responses to unattended (passively experienced) auditory stimuli while parametrically manipulating the degree of temporal coherence that facilitates auditory figure-ground segregation. Results from 21 children with ASD (aged 7-17 years) and 26 age- and IQ-matched typically developing children provide evidence that children with ASD show anomalous growth of cortical neural responses with increasing temporal coherence of the auditory figure. The documented neurophysiological abnormalities did not depend on age, and were reflected both in the response evoked by changes in temporal coherence of the auditory scene and in the associated induced gamma rhythms. Furthermore, the individual neural measures were predictive of diagnosis (83% accuracy) and also correlated with behavioral measures of ASD severity and auditory processing abnormalities. These findings offer new insight into the neural mechanisms underlying auditory perceptual deficits and sensory overload in ASD, and suggest that temporal-coherence-based auditory scene analysis and suprathreshold processing of coherent auditory objects may be atypical in ASD.

Biallelic MED27 variants lead to variable ponto-cerebello-lental degeneration with movement disorders.

MED27 is a subunit of the Mediator multiprotein complex, which is involved in transcriptional regulation. Biallelic MED27 variants have recently been suggested to be responsible for an autosomal recessive neurodevelopmental disorder with spasticity, cataracts and cerebellar hypoplasia. We further delineate the clinical phenotype of MED27-related disease by characterizing the clinical and radiological features of 57 affected individuals from 30 unrelated families with biallelic MED27 variants. Using exome sequencing and extensive international genetic data sharing, 39 unpublished affected individuals from 18 independent families with biallelic missense variants in MED27 have been identified (29 females, mean age at last follow-up 17 ± 12.4 years, range 0.1-45). Follow-up and hitherto unreported clinical features were obtained from the published 12 families. Brain MRI scans from 34 cases were reviewed. MED27-related disease manifests as a broad phenotypic continuum ranging from developmental and epileptic-dyskinetic encephalopathy to variable neurodevelopmental disorder with movement abnormalities. It is characterized by mild to profound global developmental delay/intellectual disability (100%), bilateral cataracts (89%), infantile hypotonia (74%), microcephaly (62%), gait ataxia (63%), dystonia (61%), variably combined with epilepsy (50%), limb spasticity (51%), facial dysmorphism (38%) and death before reaching adulthood (16%). Brain MRI revealed cerebellar atrophy (100%), white matter volume loss (76.4%), pontine hypoplasia (47.2%) and basal ganglia atrophy with signal alterations (44.4%). Previously unreported 39 affected individuals had seven homozygous pathogenic missense MED27 variants, five of which were recurrent. An emerging genotype-phenotype correlation was observed. This study provides a comprehensive clinical-radiological description of MED27-related disease, establishes genotype-phenotype and clinical-radiological correlations and suggests a differential diagnosis with syndromes of cerebello-lental neurodegeneration and other subtypes of 'neuro-MEDopathies'.

Predictive coding across the left fronto-temporal hierarchy during language comprehension.

We used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy ("error" activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model). Between 600 and 1,000 ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that produced top-down error), whereas highly implausible inputs activated left inferior frontal cortex, posterior fusiform (unsuppressed orthographic prediction error/reprocessing), and medial temporal cortex (possibly supporting new learning). Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.

Role of articulatory motor networks in perceptual categorization of speech signals: a 7T fMRI study.

Speech and language processing involve complex interactions between cortical areas necessary for articulatory movements and auditory perception and a range of areas through which these are connected and interact. Despite their fundamental importance, the precise mechanisms underlying these processes are not fully elucidated. We measured BOLD signals from normal hearing participants using high-field 7 Tesla fMRI with 1-mm isotropic voxel resolution. The subjects performed 2 speech perception tasks (discrimination and classification) and a speech production task during the scan. By employing univariate and multivariate pattern analyses, we identified the neural signatures associated with speech production and perception. The left precentral, premotor, and inferior frontal cortex regions showed significant activations that correlated with phoneme category variability during perceptual discrimination tasks. In addition, the perceived sound categories could be decoded from signals in a region of interest defined based on activation related to production task. The results support the hypothesis that articulatory motor networks in the left hemisphere, typically associated with speech production, may also play a critical role in the perceptual categorization of syllables. The study provides valuable insights into the intricate neural mechanisms that underlie speech processing.

The caring competencies of nursing students: Comparing the four and two-year Bachelor of Nursing Programme.

The study was conducted to determine and compare the caring behaviours of nursing students in four-year BS Nursing (Bachelor of Science in nursing) and two-year Post- RN BSN (Registered nurse to Bachelor of Science in Nursing) programmes. A cross-sectional analytical study was conducted in the nursing institutes of KP from July to September 2022. The sample size was 383 calculated by using the Rao soft sample size calculator. through Caring Behaviour Inventory (CBI-24) having six point Likert scale. Descriptive and inferential statistics were calculated through SPSS 20.0. There were more males, i.e. 60.6%, as compared to female students (39.4%). The overall mean score of caring competencies of Post-RN BS Nursing (Registered nurse to Bachelor of Science in Nursing) was 27.17±2.17 which is higher than 23.19±4.1 for BSN students (Bachelor of Science in nursing). Caring behaviours of overall participants are correlated with gender (p=0.001), age (p=0.001), and semester (p=0.001). The caring competency of Post-RN BS nursing students' are higher than the BS Nursing programme students. That could be due to the clinical exposure of Post-Rn students after completing a three-year Diploma in General Nursing.

Sex-related patterns in the electroencephalogram and their relevance in machine learning classifiers.

Deep learning is increasingly being proposed for detecting neurological and psychiatric diseases from electroencephalogram (EEG) data but the method is prone to inadvertently incorporate biases from training data and exploit illegitimate patterns. The recent demonstration that deep learning can detect the sex from EEG implies potential sex-related biases in deep learning-based disease detectors for the many diseases with unequal prevalence between males and females. In this work, we present the male- and female-typical patterns used by a convolutional neural network that detects the sex from clinical EEG (81% accuracy in a separate test set with 142 patients). We considered neural sources, anatomical differences, and non-neural artifacts as sources of differences in the EEG curves. Using EEGs from 1140 patients, we found electrocardiac artifacts to be leaking into the supposedly brain activity-based classifiers. Nevertheless, the sex remained detectable after rejecting heart-related and other artifacts. In the cleaned data, EEG topographies were critical to detect the sex, but waveforms and frequencies were not. None of the traditional frequency bands was particularly important for sex detection. We were able to determine the sex even from EEGs with shuffled time points and therewith completely destroyed waveforms. Researchers should consider neural and non-neural sources as potential origins of sex differences in their data, they should maintain best practices of artifact rejection, even when datasets are large, and they should test their classifiers for sex biases.

Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder.

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.

Exome sequencing in a Romanian Bardet-Biedl syndrome cohort revealed an overabundance of causal BBS12 variants.

Bardet-Biedl syndrome (BBS), is an emblematic ciliopathy hallmarked by pleiotropy, phenotype variability, and extensive genetic heterogeneity. BBS is a rare (~1/140,000 to ~1/160,000 in Europe) autosomal recessive pediatric disorder characterized by retinal degeneration, truncal obesity, polydactyly, cognitive impairment, renal dysfunction, and hypogonadism. Twenty-eight genes involved in ciliary structure or function have been implicated in BBS, and explain the molecular basis for ~75%-80% of individuals. To investigate the mutational spectrum of BBS in Romania, we ascertained a cohort of 24 individuals in 23 families. Following informed consent, we performed proband exome sequencing (ES). We detected 17 different putative disease-causing single nucleotide variants or small insertion-deletions and two pathogenic exon disruptive copy number variants in known BBS genes in 17 pedigrees. The most frequently impacted genes were BBS12 (35%), followed by BBS4, BBS7, and BBS10 (9% each) and BBS1, BBS2, and BBS5 (4% each). Homozygous BBS12 p.Arg355* variants were present in seven pedigrees of both Eastern European and Romani origin. Our data show that although the diagnostic rate of BBS in Romania is likely consistent with other worldwide cohorts (74%), we observed a unique distribution of causal BBS genes, including overrepresentation of BBS12 due to a recurrent nonsense variant, that has implications for regional diagnostics.

NGS-driven molecular diagnosis of heterogeneous hereditary neurological disorders reveals novel and known variants in disease-causing genes.

Hereditary neurological disorders (HNDs) are a clinically and genetically heterogeneous group of disorders. These disorders arise from the impaired function of the central or peripheral nervous system due to aberrant electrical impulses. More than 600 various neurological disorders, exhibiting a wide spectrum of overlapping clinical presentations depending on the organ(s) involved, have been documented. Owing to this clinical heterogeneity, diagnosing these disorders has been a challenge for both clinicians and geneticists and a large number of patients are either misdiagnosed or remain entirely undiagnosed. Contribution of genetics to neurological disorders has been recognized since long; however, the complete picture of the underlying molecular bases are under-explored. The aim of this study was to accurately diagnose 11 unrelated Pakistani families with various HNDs deploying NGS as a first step approach. Using exome sequencing and gene panel sequencing, we successfully identified disease-causing genomic variants these families. We report four novel variants, one each in, ECEL1, NALCN, TBR1 and PIGP in four of the pedigrees. In the rest of the seven families, we found five previously reported pathogenic variants in POGZ, FA2H, PLA2G6 and CYP27A1. Of these, three families segregate a homozygous 18 bp in-frame deletion of FA2H, indicating a likely founder mutation segregating in Pakistani population. Genotyping for this mutation can help low-cost population wide screening in the corresponding regions of the country. Our findings not only expand the existing repertoire of mutational spectrum underlying neurological disorders but will also help in genetic testing of individuals with HNDs in other populations.

How expectations of pain elicited by consciously and unconsciously perceived cues unfold over time.

Expectation can shape the perception of pain within a fraction of time, but little is known about how perceived expectation unfolds over time and modulates pain perception. Here, we combine magnetoencephalography (MEG) and machine learning approaches to track the neural dynamics of expectations of pain in healthy participants with both sexes. We found that the expectation of pain, as conditioned by facial cues, can be decoded from MEG as early as 150 ms and up to 1100 ms after cue onset, but decoding expectation elicited by unconsciously perceived cues requires more time and decays faster compared to consciously perceived ones. Also, results from temporal generalization suggest that neural dynamics of decoding cue-based expectation were predominately sustained during cue presentation but transient after cue presentation. Finally, although decoding expectation elicited by consciously perceived cues were based on a series of time-restricted brain regions during cue presentation, decoding relied on the medial prefrontal cortex and anterior cingulate cortex after cue presentation for both consciously and unconsciously perceived cues. These findings reveal the conscious and unconscious processing of expectation during pain anticipation and may shed light on enhancing clinical care by demonstrating the impact of expectation cues.

A recessive variant in TFAM causes mtDNA depletion associated with primary ovarian insufficiency, seizures, intellectual disability and hearing loss.

Mitochondrial disorders are collectively common, genetically heterogeneous disorders in both pediatric and adult populations. They are caused by molecular defects in oxidative phosphorylation, failure of essential bioenergetic supply to mitochondria, and apoptosis. Here, we present three affected individuals from a consanguineous family of Pakistani origin with variable seizures and intellectual disability. Both females display primary ovarian insufficiency (POI), while the male shows abnormal sex hormone levels. We performed whole exome sequencing and identified a recessive missense variant c.694C > T, p.Arg232Cys in TFAM that segregates with disease. TFAM (mitochondrial transcription factor A) is a component of the mitochondrial replisome machinery that maintains mtDNA transcription and replication. In primary dermal fibroblasts, we show depletion of mtDNA and significantly altered mitochondrial function and morphology. Moreover, we observed reduced nucleoid numbers with significant changes in nucleoid size or shape in fibroblasts from an affected individual compared to controls. We also investigated the effect of tfam impairment in zebrafish; homozygous tfam mutants carrying an in-frame c.141_149 deletion recapitulate the mtDNA depletion and ovarian dysgenesis phenotypes observed in affected humans. Together, our genetic and functional data confirm that TFAM plays a pivotal role in gonad development and expands the repertoire of mitochondrial disease phenotypes.

Biallelic variants in PCDHGC4 cause a novel neurodevelopmental syndrome with progressive microcephaly, seizures, and joint anomalies.

PURPOSE: We aimed to define a novel autosomal recessive neurodevelopmental disorder, characterize its clinical features, and identify the underlying genetic cause for this condition. METHODS: We performed a detailed clinical characterization of 19 individuals from nine unrelated, consanguineous families with a neurodevelopmental disorder. We used genome/exome sequencing approaches, linkage and cosegregation analyses to identify disease-causing variants, and we performed three-dimensional molecular in silico analysis to predict causality of variants where applicable. RESULTS: In all affected individuals who presented with a neurodevelopmental syndrome with progressive microcephaly, seizures, and intellectual disability we identified biallelic disease-causing variants in Protocadherin-gamma-C4 (PCDHGC4). Five variants were predicted to induce premature protein truncation leading to a loss of PCDHGC4 function. The three detected missense variants were located in extracellular cadherin (EC) domains EC5 and EC6 of PCDHGC4, and in silico analysis of the affected residues showed that two of these substitutions were predicted to influence the Ca2+-binding affinity, which is essential for multimerization of the protein, whereas the third missense variant directly influenced the cis-dimerization interface of PCDHGC4. CONCLUSION: We show that biallelic variants in PCDHGC4 are causing a novel autosomal recessive neurodevelopmental disorder and link PCDHGC4 as a member of the clustered PCDH family to a Mendelian disorder in humans.

Epileptic Activity Intrinsically Generated in the Human Cerebellum.

Neoplastic or dysplastic neuronal tissue in the brain stem and cerebellum can become epileptogenic in pediatric patients. However, it is unknown whether such tissue may transform intrinsic properties of the human cerebellum, making it capable of generating epileptic population activity. We noninvasively detected epileptiform signals unaveraged in a pediatric patient with epilepsy due to a tumor in the middle cerebellar peduncle. Analysis of generators of the signals revealed that the cerebellum ipsilateral and contralateral to the tumor was the dominant interictal spike generator and could initiate ictal activity, suggesting that human cerebellum may become capable of intrinsically generating epileptic activity. ANN NEUROL 2020;88:418-422.

Knowledge, Attitude, and Barriers Toward ADRs Reporting Among Health-Care Professionals at Tertiary Care Health Settings in Peshawar, Pakistan: A Web Based Study.

Background: Underreporting of adverse drug reactions (ADRs) is considered a major determinant of poor ADR signal detection in Pakistan. Considering this, the study was proposed to evaluate healthcare professionals' (HCPs) knowledge attitude toward and the barriers that discourse ADRs reporting. Methods: A cross-sectional survey was distributed among HCPs in 3 major tertiary care facilities of Peshawar. A self-administered, 31 items questionnaire was circulated online to collect the required information. Relative index ranking was used to identify the top barriers to the ADR reporting process. Results: HCPs (n = 322) were requested, and over one-third (n = 122) responded. Of the total, 97 (79.5%) were males, and by designation, 59(48.4%) were resident medical officers. About 45% of the HCPs did not identify the appropriate pharmacovigilance (PV) definition. More than half of the HCPs (52.2%) distinguished the appropriate PV purpose. Nearly 80% HCPs did not know the acceptable reporting time frame, while 22.1% HCPs knew that regulatory body for ADRs does not exist in Pakistan. The majority (95.08%) of the HCPs either strongly agreed or agreed that reporting an ADRs is a professional obligation and all the HCPs were of the opinion that PV should be taught in detail to HCPs. Exploring the barriers, it was identified that the key barriers to ADRs reporting were "unavailability of professional environment to discuss ADRs," Relative Importance Index (RII) = 0.813, "lack of incentives for reporting" (RII = 0.774), "lack of knowledge regarding reporting" (RII = 0.693), and "insufficient knowledge of pharmacotherapy in detecting ADRs" (RII = 0.662). In addition to these, "complicated reporting forms" (RII = 0.616), "lack of motivation for reporting ADRs" (RII = 0.610), and "absence of professional confidence" were seen as major hindrances in effective reporting of ADRs (RII = 0.598). Conclusion: Concerning PV and ADR reporting poor knowledge was noted. However, the majority of the HCPs showed an explicit attitude regarding ADRs reporting. The majority of the HCPs disclosed unavailability of professional environment to discuss about ADRs, lack of incentives, and how to report the main factors hindering the ADRs reporting. It is emphasized that health authorities carve out a niche for a well purposeful PV center and pledge educational activities and trainings for increasing understanding and approaches regarding reporting of ADR.

Detectability of cerebellar activity with magnetoencephalography and electroencephalography.

Electrophysiological signals from the cerebellum have traditionally been viewed as inaccessible to magnetoencephalography (MEG) and electroencephalography (EEG). Here, we challenge this position by investigating the ability of MEG and EEG to detect cerebellar activity using a model that employs a high-resolution tessellation of the cerebellar cortex. The tessellation was constructed from repetitive high-field (9.4T) structural magnetic resonance imaging (MRI) of an ex vivo human cerebellum. A boundary-element forward model was then used to simulate the M/EEG signals resulting from neural activity in the cerebellar cortex. Despite significant signal cancelation due to the highly convoluted cerebellar cortex, we found that the cerebellar signal was on average only 30-60% weaker than the cortical signal. We also made detailed M/EEG sensitivity maps and found that MEG and EEG have highly complementary sensitivity distributions over the cerebellar cortex. Based on previous fMRI studies combined with our M/EEG sensitivity maps, we discuss experimental paradigms that are likely to offer high M/EEG sensitivity to cerebellar activity. Taken together, these results show that cerebellar activity should be clearly detectable by current M/EEG systems with an appropriate experimental setup.

Distinct Regional Oscillatory Connectivity Patterns During Auditory Target and Novelty Processing.

Auditory attention allows us to focus on relevant target sounds in the acoustic environment while maintaining the capability to orient to unpredictable (novel) sound changes. An open question is whether orienting to expected vs. unexpected auditory events are governed by anatomically distinct attention pathways, respectively, or by differing communication patterns within a common system. To address this question, we applied a recently developed PeSCAR analysis method to evaluate spectrotemporal functional connectivity patterns across subregions of broader cortical regions of interest (ROIs) to analyze magnetoencephalography data obtained during a cued auditory attention task. Subjects were instructed to detect a predictable harmonic target sound embedded among standard tones in one ear and to ignore the standard tones and occasional unpredictable novel sounds presented in the opposite ear. Phase coherence of estimated source activity was calculated between subregions of superior temporal, frontal, inferior parietal, and superior parietal cortex ROIs. Functional connectivity was stronger in response to target than novel stimuli between left superior temporal and left parietal ROIs and between left frontal and right parietal ROIs, with the largest effects observed in the beta band (15-35 Hz). In contrast, functional connectivity was stronger in response to novel than target stimuli in inter-hemispheric connections between left and right frontal ROIs, observed in early time windows in the alpha band (8-12 Hz). Our findings suggest that auditory processing of expected target vs. unexpected novel sounds involves different spatially, temporally, and spectrally distributed oscillatory connectivity patterns across temporal, parietal, and frontal areas.

A computational paradigm for real-time MEG neurofeedback for dynamic allocation of spatial attention.

BACKGROUND: Neurofeedback aids volitional control of one's own brain activity using non-invasive recordings of brain activity. The applications of neurofeedback include improvement of cognitive performance and treatment of various psychiatric and neurological disorders. During real-time magnetoencephalography (rt-MEG), sensor-level or source-localized brain activity is measured and transformed into a visual feedback cue to the subject. Recent real-time fMRI (rt-fMRI) neurofeedback studies have used pattern recognition techniques to decode and train a brain state to link brain activities and cognitive behaviors. Here, we utilize the real-time decoding technique similar to ones employed in rt-fMRI to analyze time-varying rt-MEG signals. RESULTS: We developed a novel rt-MEG method, state-based neurofeedback (sb-NFB), to decode a time-varying brain state, a state signal, from which timings are extracted for neurofeedback training. The approach is entirely data-driven: it uses sensor-level oscillatory activity to find relevant features that best separate the targeted brain states. In a psychophysical task of spatial attention switching, we trained five young, healthy subjects using the sb-NFB method to decrease the time necessary for switch spatial attention from one visual hemifield to the other (referred to as switch time). Training resulted in a decrease in switch time with training. We saw that the activity targeted by the training involved proportional changes in alpha and beta-band oscillations, in sensors at the occipital and parietal regions. We also found that the state signal that encodes whether subjects attend to the left or right visual field effectively switches consistently with the task. CONCLUSION: We demonstrated the use of the sb-NFB method when the subject learns to increase the speed of shifting covert spatial attention from one visual field to the other. The sb-NFB method can target timing features that would otherwise also include extraneous features such as visual detection and motor response in a simple reaction time task.

Maturational Changes in Human Dorsal and Ventral Visual Networks.

Developmental neuroimaging studies report the emergence of increasingly diverse cognitive functions as closely entangled with a rise-fall modulation of cortical thickness (CTh), structural cortical and white-matter connectivity, and a time-course for the experience-dependent selective elimination of the overproduced synapses. We examine which of two visual processing networks, the dorsal (DVN; prefrontal, parietal nodes) or ventral (VVN; frontal-temporal, fusiform nodes) matures first, thus leading the neuro-cognitive developmental trajectory. Three age-dependent measures are reported: (i) the CTh at network nodes; (ii) the matrix of intra-network structural connectivity (edges); and (iii) the proficiency in network-related neuropsychological tests. Typically developing children (age ~6 years), adolescents (~11 years), and adults (~21 years) were tested using multiple-acquisition structural T1-weighted magnetic resonance imaging (MRI) and neuropsychology. MRI images reconstructed into a gray/white/pial matter boundary model were used for CTh evaluation. No significant group differences in CTh and in the matrix of edges were found for DVN (except for the left prefrontal), but a significantly thicker cortex in children for VVN with reduced prefrontal ventral-fusiform connectivity and with an abundance of connections in adolescents. The higher performance in children on tests related to DVN corroborates the age-dependent MRI structural connectivity findings. The current findings are consistent with an earlier maturational course of DVN.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG.

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

A neural mechanism of direct and observational conditioning for placebo and nocebo responses.

Classical theories suggest placebo analgesia and nocebo hyperalgesia are based on expectation and conditioned experience. Whereas the neural mechanism of how expectation modulates placebo and nocebo effects during pain anticipation have been extensively studied, little is known about how experience may change brain networks to produce placebo and nocebo responses. We investigated the neural pathways of direct and observational conditioning for conscious and nonconscious conditioned placebo/nocebo effects using magnetoencephalography and a face visual cue conditioning model. We found that both direct and observational conditioning produced conscious conditioned placebo and nocebo effects and a nonconscious conditioned nocebo effect. Alpha band brain connectivity changes before and after conditioning could predict the magnitude of conditioned placebo and nocebo effects. Particularly, the connectivity between the rostral anterior cingulate cortex and middle temporal gyrus was an important indicator for the manipulation of placebo and nocebo effects. Our study suggests that conditioning can mediate our pain experience by encoding experience and modulating brain networks.