Fronto-central resting-state 15-29 Hz transient beta events change with therapeutic transcranial magnetic stimulation for posttraumatic stress disorder and major depressive disorder.

Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD) and shows promise for posttraumatic stress disorder (PTSD), yet effectiveness varies. Electroencephalography (EEG) can identify rTMS-associated brain changes. EEG oscillations are often examined using averaging approaches that mask finer time-scale dynamics. Recent advances show some brain oscillations emerge as transient increases in power, a phenomenon termed "Spectral Events," and that event characteristics correspond with cognitive functions. We applied Spectral Event analyses to identify potential EEG biomarkers of effective rTMS treatment. Resting 8-electrode EEG was collected from 23 patients with MDD and PTSD before and after 5 Hz rTMS targeting the left dorsolateral prefrontal cortex. Using an open-source toolbox ( https://github.com/jonescompneurolab/SpectralEvents ), we quantified event features and tested for treatment associated changes. Spectral Events in delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz) bands occurred in all patients. rTMS-induced improvement in comorbid MDD PTSD were associated with pre- to post-treatment changes in fronto-central electrode beta event features, including frontal beta event frequency spans and durations, and central beta event maxima power. Furthermore, frontal pre-treatment beta event duration correlated negatively with MDD symptom improvement. Beta events may provide new biomarkers of clinical response and advance the understanding of rTMS.

Fronto-central resting-state 15-29Hz transient beta events change with therapeutic transcranial magnetic stimulation for posttraumatic stress disorder and major depressive disorder.

Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD) and shows promise for posttraumatic stress disorder (PTSD), yet effectiveness varies. Electroencephalography (EEG) can identify rTMS-associated brain changes. EEG oscillations are often examined using averaging approaches that mask finer time-scale dynamics. Recent advances show some brain oscillations emerge as transient increases in power, a phenomenon termed "Spectral Events," and that event characteristics correspond with cognitive functions. We applied Spectral Event analyses to identify potential EEG biomarkers of effective rTMS treatment. Resting 8-electrode EEG was collected from 23 patients with MDD and PTSD before and after 5Hz rTMS targeting the left dorsolateral prefrontal cortex. Using an open-source toolbox ( https://github.com/jonescompneurolab/SpectralEvents ), we quantified event features and tested for treatment associated changes. Spectral Events in delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz) bands occurred in all patients. rTMS-induced improvement in comorbid MDD PTSD were associated with pre-to post-treatment changes in fronto-central electrode beta event features, including frontal beta event frequency spans and durations, and central beta event maxima power. Furthermore, frontal pre-treatment beta event duration correlated negatively with MDD symptom improvement. Beta events may provide new biomarkers of clinical response and advance the understanding of rTMS.

Thalamocortical Mechanisms Regulating the Relationship between Transient Beta Events and Human Tactile Perception.

Transient neocortical events with high spectral power in the 15-29 Hz beta band are among the most reliable predictors of sensory perception. Prestimulus beta event rates in primary somatosensory cortex correlate with sensory suppression, most effectively 100-300 ms before stimulus onset. However, the neural mechanisms underlying this perceptual association are unknown. We combined human magnetoencephalography (MEG) measurements with biophysical neural modeling to test potential cellular and circuit mechanisms that underlie observed correlations between prestimulus beta events and tactile detection. Extending prior studies, we found that simulated bursts from higher-order, nonlemniscal thalamus were sufficient to drive beta event generation and to recruit slow supragranular inhibition acting on a 300 ms timescale to suppress sensory information. Further analysis showed that the same beta-generating mechanism can lead to facilitated perception for a brief period when beta events occur simultaneously with tactile stimulation before inhibition is recruited. These findings were supported by close agreement between model-derived predictions and empirical MEG data. The postevent suppressive mechanism explains an array of studies that associate beta with decreased processing, whereas the during-event facilitatory mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.

Functional Connectivity in Infancy and Toddlerhood Predicts Long-Term Language and Preliteracy Outcomes.

Functional connectivity (FC) techniques can delineate brain organization as early as infancy, enabling the characterization of early brain characteristics associated with subsequent behavioral outcomes. Previous studies have identified specific functional networks in infant brains that underlie cognitive abilities and pathophysiology subsequently observed in toddlers and preschoolers. However, it is unknown whether and how functional networks emerging within the first 18 months of life contribute to the development of higher order, complex functions of language/literacy at school-age. This 5-year longitudinal imaging project starting in infancy, utilized resting-state functional magnetic resonance imaging and demonstrated prospective associations between FC in infants/toddlers and subsequent language and foundational literacy skills at 6.5 years old. These longitudinal associations were shown independently of key environmental influences and further present in a subsample of infant imaging data (≤12 months), suggesting early emerged functional networks specifically linked to high-order language and preliteracy skills. Moreover, emergent language skills in infancy and toddlerhood contributed to the prospective associations, implicating a role of early linguistic experiences in shaping the FC correlates of long-term oral language skills. The current results highlight the importance of functional organization established in infancy and toddlerhood as a neural scaffold underlying the learning process of complex cognitive functions.

Is Alpha Asymmetry a Byproduct or Cause of Spatial Attention? New Evidence Alpha Neurofeedback Controls Measures of Spatial Attention.

Cued spatial attention differentially modulates alpha power in attended relative to non-attended brain representations, termed the alpha asymmetry. Yet a causal role for alpha in attention is debated. In this issue of Neuron, Bagherzadeh et al., (2019) utilize neurofeedback to train alpha asymmetry and causally impact measures of spatial attention.

Relating anthropometric indicators to brain structure in 2-month-old Bangladeshi infants growing up in poverty: A pilot study.

Anthropometric indicators, including stunting, underweight, and wasting, have previously been associated with poor neurocognitive outcomes. This link may exist because malnutrition and infection, which are known to affect height and weight, also impact brain structure according to animal models. However, a relationship between anthropometric indicators and brain structural measures has not been tested yet, perhaps because stunting, underweight, and wasting are uncommon in higher-resource settings. Further, with diminished anthropometric growth prevalent in low-resource settings, where biological and psychosocial hazards are most severe, one might expect additional links between measures of poverty, anthropometry, and brain structure. To begin to examine these relationships, we conducted an MRI study in 2-3-month-old infants growing up in the extremely impoverished urban setting of Dhaka, Bangladesh. The sample size was relatively small because the challenges of investigating infant brain structure in a low-resource setting needed to be realized and resolved before introducing a larger cohort. Initially, fifty-four infants underwent T1 sequences using 3T MRI, and resulting structural images were segmented into gray and white matter maps, which were carefully evaluated for accurate tissue labeling by a pediatric neuroradiologist. Gray and white matter volumes from 29 infants (79 â€‹± â€‹10 days-of-age; F/M â€‹= â€‹12/17), whose segmentations were of relatively high quality, were submitted to semi-partial correlation analyses with stunting, underweight, and wasting, which were measured using height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) scores. Positive semi-partial correlations (after adjusting for chronological age and sex and correcting for multiple comparisons) were observed between white matter volume and HAZ and WAZ; however, WHZ was not correlated with any measure of brain volume. No associations were observed between income-to-needs or maternal education and brain volumetric measures, suggesting that measures of poverty were not associated with total brain tissue volume in this sample. Overall, these results provide the first link between diminished anthropometric growth and white matter volume in infancy. Challenges of conducting a developmental neuroimaging study in a low-resource country are also described.

Resting-State fMRI Networks in Children with Tuberous Sclerosis Complex.

BACKGROUND AND PURPOSE: There are no published studies examining resting state networks (RSNs) and their relationship with neurodevelopmental metrics in tuberous sclerosis complex (TSC). We aimed to identify major resting-state functional magnetic resonance imaging (rs-fMRI) networks in infants with TSC and correlate network analyses with neurodevelopmental assessments, autism diagnosis, and seizure history. METHODS: Rs-fMRI data from 34 infants with TSC, sedated with propofol during the scan, were analyzed to identify auditory, motor, and visual RSNs. We examined the correlations between auditory, motor, and visual RSNs at approximately 11.5 months, neurodevelopmental outcome at approximately 18.5 months, and diagnosis of autism spectrum disorders at approximately 36 months of age. RESULTS: RSNs were obtained in 76.5% (26/34) of infants. We observed significant negative correlations between auditory RSN and auditory comprehension test scores (p = .038; r = -.435), as well as significant positive correlations between motor RSN and gross motor skills test scores (p = .023; r = .564). Significant positive correlations between motor RSNs and gross motor skills (p = .012; r = .754) were observed in TSC infants without autism, but not in TSC infants with autism, which could suggest altered motor processing. There were no significant differences in RSNs according to seizure history. CONCLUSIONS: Negative correlation between auditory RSN, as well as positive correlation between motor RSN and developmental outcome measures might reflect different brain mechanisms and, when identified, may be helpful in predicting later function. A larger study of TSC patients with a healthy control group is needed before auditory and motor RSNs could be considered as neurodevelopmental outcome biomarkers.

The relationship between biological and psychosocial risk factors and resting-state functional connectivity in 2-month-old Bangladeshi infants: A feasibility and pilot study.

Childhood poverty has been associated with structural and functional alterations in the developing brain. However, poverty does not alter brain development directly, but acts through associated biological or psychosocial risk factors (e.g. malnutrition, family conflict). Yet few studies have investigated risk factors in the context of infant neurodevelopment, and none have done so in low-resource settings such as Bangladesh, where children are exposed to multiple, severe biological and psychosocial hazards. In this feasibility and pilot study, usable resting-state fMRI data were acquired in infants from extremely poor (n = 16) and (relatively) more affluent (n = 16) families in Dhaka, Bangladesh. Whole-brain intrinsic functional connectivity (iFC) was estimated using bilateral seeds in the amygdala, where iFC has shown susceptibility to early life stress, and in sensory areas, which have exhibited less susceptibility to early life hazards. Biological and psychosocial risk factors were examined for associations with iFC. Three resting-state networks were identified in within-group brain maps: medial temporal/striatal, visual, and auditory networks. Infants from extremely poor families compared with those from more affluent families exhibited greater (i.e. less negative) iFC in precuneus for amygdala seeds; however, no group differences in iFC were observed for sensory area seeds. Height-for-age, a proxy for malnutrition/infection, was not associated with amygdala/precuneus iFC, whereas prenatal family conflict was positively correlated. Findings suggest that it is feasible to conduct infant fMRI studies in low-resource settings. Challenges and practical steps for successful implementations are discussed.

A Prospective Study of the Impact of Transcranial Alternating Current Stimulation on EEG Correlates of Somatosensory Perception.

The (8-12 Hz) neocortical alpha rhythm is associated with shifts in attention across sensory systems, and is thought to represent a sensory gating mechanism for the inhibitory control of cortical processing. The present preliminary study sought to explore whether alpha frequency transcranial alternating current stimulation (tACS) could modulate endogenous alpha power in the somatosensory system, and whether the hypothesized modulation would causally impact perception of tactile stimuli at perceptual threshold. We combined electroencephalography (EEG) with simultaneous brief and intermittent tACS applied over primary somatosensory cortex at individuals' endogenous alpha frequency during a tactile detection task (n = 12 for EEG, n = 20 for behavior). EEG-measured pre-stimulus alpha power was higher on non-perceived than perceived trials, and analogous perceptual correlates emerged in early components of the tactile evoked response. Further, baseline normalized tactile detection performance was significantly lower during alpha than sham tACS, but the effect did not last into the post-tACS time period. Pre- to post-tACS changes in alpha power were linearly dependent upon baseline state, such that alpha power tended to increase when pre-tACS alpha power was low, and decrease when it was high. However, these observations were comparable in both groups, and not associated with evidence of tACS-induced alpha power modulation. Nevertheless, the tactile stimulus evoked response potential (ERP) revealed a potentially lasting impact of alpha tACS on circuit dynamics. The post-tACS ERP was marked by the emergence of a prominent peak ∼70 ms post-stimulus, which was not discernible post-sham, or in either pre-stimulation condition. Computational neural modeling designed to simulate macroscale EEG signals supported the hypothesis that the emergence of this peak could reflect synaptic plasticity mechanisms induced by tACS. The primary lesson learned in this study, which commanded a small sample size, was that while our experimental paradigm provided some evidence of an influence of tACS on behavior and circuit dynamics, it was not sufficient to induce observable causal effects of tACS on EEG-measured alpha oscillations. We discuss limitations and suggest improvements that may help further delineate a causal influence of tACS on cortical dynamics and perception in future studies.

Development of Tract-Specific White Matter Pathways During Early Reading Development in At-Risk Children and Typical Controls.

Developmental dyslexia is a neurodevelopmental disorder with a strong genetic basis. Previous studies observed white matter alterations in the left posterior brain regions in adults and school-age children with dyslexia. However, no study yet has examined the development of tract-specific white matter pathways from the pre-reading to the fluent reading stage in children at familial risk for dyslexia (FHD+) versus controls (FHD-). This study examined white matter integrity at pre-reading, beginning, and fluent reading stages cross-sectionally ( n = 78) and longitudinally (n = 45) using an automated fiber-tract quantification method. Our findings depict white matter alterations and atypical lateralization of the arcuate fasciculus at the pre-reading stage in FHD+ versus FHD- children. Moreover, we demonstrate faster white matter development in subsequent good versus poor readers and a positive association between white matter maturation and reading development using a longitudinal design. Additionally, the combination of white matter maturation, familial risk, and psychometric measures best predicted later reading abilities. Furthermore, within FHD+ children, subsequent good readers exhibited faster white matter development in the right superior longitudinal fasciculus compared with subsequent poor readers, suggesting a compensatory mechanism. Overall, our findings highlight the importance of white matter pathway maturation in the development of typical and atypical reading skills.

White Matter Alterations in Infants at Risk for Developmental Dyslexia.

Developmental dyslexia (DD) is a heritable condition characterized by persistent difficulties in learning to read. White matter alterations in left-lateralized language areas, particularly in the arcuate fasciculus (AF), have been observed in DD, and diffusion properties within the AF correlate with (pre-)reading skills as early as kindergarten. However, it is unclear how early these alterations can be observed. We investigated white matter structure in 14 infants with (FHD+; ages 6.6-17.6 months) and 18 without (FHD-; ages 5.1-17.6 months) familial risk for DD. Diffusion scans were acquired during natural sleep, and early language skills were assessed. Tractography for bilateral AF was reconstructed using manual and automated methods, allowing for independent validation of results. Fractional anisotropy (FA) was calculated at multiple nodes along the tracts for more precise localization of group differences. The analyses revealed significantly lower FA in the left AF for FHD+ compared with FHD- infants, particularly in the central portion of the tract. Moreover, expressive language positively correlated with FA across groups. Our results demonstrate that atypical brain development associated with DD is already present within the first 18 months of life, suggesting that the deficits associated with DD may result from altered structural connectivity in left-hemispheric regions.

A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range.

We present a detailed description of a set of FreeSurfer compatible segmentation guidelines tailored to infant MRI scans, and a unique data set of manually segmented acquisitions, with subjects nearly evenly distributed between 0 and 2 years of age. We believe that these segmentation guidelines and this dataset will have a wide range of potential uses in medicine and neuroscience.

Effects of sutures and fontanels on MEG and EEG source analysis in a realistic infant head model.

In infants, the fontanels and sutures as well as conductivity of the skull influence the volume currents accompanying primary currents generated by active neurons and thus the associated electroencephalography (EEG) and magnetoencephalography (MEG) signals. We used a finite element method (FEM) to construct a realistic model of the head of an infant based on MRI images. Using this model, we investigated the effects of the fontanels, sutures and skull conductivity on forward and inverse EEG and MEG source analysis. Simulation results show that MEG is better suited than EEG to study early brain development because it is much less sensitive than EEG to distortions of the volume current caused by the fontanels and sutures and to inaccurate estimates of skull conductivity. Best results will be achieved when MEG and EEG are used in combination.

Pediatric neuroimaging in early childhood and infancy: challenges and practical guidelines.

Structural and functional magnetic resonance imaging (fMRI) has been used increasingly to investigate typical and atypical brain development. However, in contrast to studies in school-aged children and adults, MRI research in young pediatric age groups is less common. Practical and technical challenges occur when imaging infants and children, which presents clinicians and research teams with a unique set of problems. These include procedural difficulties (e.g., participant anxiety or movement restrictions), technical obstacles (e.g., availability of child-appropriate equipment or pediatric MR head coils), and the challenge of choosing the most appropriate analysis methods for pediatric imaging data. Here, we summarize and review pediatric imaging and analysis tools and present neuroimaging protocols for young nonsedated children and infants, including guidelines and procedures that have been successfully implemented in research protocols across several research sites.

Assessment of the frequency-domain multi-distance method to evaluate the brain optical properties: Monte Carlo simulations from neonate to adult.

The near infrared spectroscopy (NIRS) frequency-domain multi-distance (FD-MD) method allows for the estimation of optical properties in biological tissue using the phase and intensity of radiofrequency modulated light at different source-detector separations. In this study, we evaluated the accuracy of this method to retrieve the absorption coefficient of the brain at different ages. Synthetic measurements were generated with Monte Carlo simulations in magnetic resonance imaging (MRI)-based heterogeneous head models for four ages: newborn, 6 and 12 month old infants, and adult. For each age, we determined the optimal set of source-detector separations and estimated the corresponding errors. Errors arise from different origins: methodological (FD-MD) and anatomical (curvature, head size and contamination by extra-cerebral tissues). We found that the brain optical absorption could be retrieved with an error between 8-24% in neonates and infants, while the error increased to 19-44% in adults over all source-detector distances. The dominant contribution to the error was found to be the head curvature in neonates and infants, and the extra-cerebral tissues in adults.