A database of age-appropriate average MRI templates

Association between caregiver and infant visual neurocognition

Previous work has shown that caregiver attention shapes visual cognition in infants through dyadic interactions. Is this association measurable when visual cognition is objectively measured in caregivers and infants using comparable experimental paradigms? In the current study, we presented infants (N = 86) and caregivers (N = 78) with age-specific variants of the same preferential looking visual cognition task to investigate whether caregiver visual cognition was associated with their infants' visual cognition. In each trial of the task, two side-by-side flashing displays of coloured shapes were presented. On the 'unchanging' side, the colours of the shapes remained the same. On the 'changing' side, the colour of one shape changed after each flash. Load was varied by changing the number of shapes across trials (low, medium, and high loads). We extracted looking dynamics using video recordings and brain function using functional near-infrared spectroscopy as both infants and caregivers engaged with the task. Change preference (CP) score, which represented the amount of time spent looking at the changing side divided by the total looking duration, showed a load-dependent modulation for both infants and caregivers. Both groups showed the highest CP scores at the low load. Further, higher caregiver CP scores was associated with higher infant CP scores at the low load. Both infants and caregivers engaged canonical regions of the fronto-parietal network involved in visual cognition. Critically, higher caregiver CP scores were associated with greater activation in the left superior parietal lobule in younger infants, a region involved in allocating visuo-spatial attention and working memory maintenance. Further, there was spatial overlap between performance-dependent regions in the right parietal cortex in caregivers and younger infants. Our findings provide first evidence of a heritability-related visual neurocognitive association between caregivers and their children in the first year of life.

The maturation of infant and toddler visual cortex neural activity and associations with fine motor performance

Our understanding of how visual cortex neural processes mature during infancy and toddlerhood is limited. Using magnetoencephalography (MEG), the present study investigated the development of visual evoked responses (VERs) in both cross-sectional and longitudinal samples of infants and toddlers 2 months to 3 years. Brain space analyses focused on N1m and P1m latency, as well as the N1m-to-P1m amplitude. Associations between VER measures and developmental quotient (DQ) scores in the cognitive/visual and fine motor domains were also examined. Results showed a nonlinear decrease in N1m and P1m latency as a function of age, characterized by rapid changes followed by slower progression, with the N1m latency plateauing at 6-7 months and the P1m latency plateauing at 8-9 months. The N1m-to-P1m amplitude also exhibited a non-linear decrease, with strong responses observed in younger infants (∼2-3 months) and then a gradual decline. Associations between N1m and P1m latency and fine motor DQ scores were observed, suggesting that infants with faster visual processing may be better equipped to perform fine motor tasks. The present findings advance our understanding of the maturation of the infant visual system and highlight the relationship between the maturation of visual system and fine motor skills.

Highlights

The infant N1m and P1m latency shows a nonlinear decrease.N1m latency decreases precede P1m latency decreases.N1m-to-P1m amplitude shows a nonlinear decrease, with stronger responses in younger than older infants.N1m and P1m latency are associated with fine motor DQ.

The Neural Bases of Language Processing During Social and Non-Social Contexts: A fNIRS Study of Autistic and Neurotypical Preschool-Aged Children

Background

Little is known about how the brains of autistic children process language during real-world "social contexts," despite the fact that challenges with language, communication, and social interaction are core features of Autism Spectrum Disorder (ASD).

Methods

We investigated the neural bases of language processing during social and non-social contexts in a sample of N=20 autistic and N=20 neurotypical (NT) preschool-aged children, 3 to 6 years old. Functional near-infrared spectroscopy (fNIRS) was used to measure children's brain response to "live language" spoken by a live experimenter during an in-person social context (i.e., book reading), and "recorded language" played via an audio recording during a non-social context (i.e., screen time). We examined within-group and between-group differences in the strength and localization of brain response to live language and recorded language, as well as correlations between children's brain response and language skills measured by the Preschool Language Scales.

Results

In the NT group, brain response to live language was greater than brain response to recorded language in the right temporal parietal junction (TPJ). In the ASD group, the strength of brain response did not differ between conditions. The ASD group showed greater brain response to recorded language than the NT group in the right inferior and middle frontal gyrus (IMFG). Across groups, children's language skills were negatively associated with brain response to recorded language in the right IMFG, suggesting that processing recorded language required more cognitive effort for children with lower language skills. Children's language skills were also positively associated with the difference in brain response between conditions in the right TPJ, demonstrating that children who showed a greater difference in brain response to live language versus recorded language had higher language skills.

Limitations

Findings should be considered preliminary until they are replicated in a larger sample.

Conclusions

Findings suggest that the brains of NT children, but not autistic children, process language differently during social and non-social contexts. Individual differences in how the brain processes language during social and non-social contexts may help to explain why language skills are so variable across children with and without autism.

Functional benefits of continuous vs. categorical listening strategies on the neural encoding and perception of noise-degraded speech

Acoustic information in speech changes continuously, yet listeners form discrete perceptual categories to ease the demands of perception. Being a more continuous/gradient as opposed to a discrete/categorical listener may be further advantageous for understanding speech in noise by increasing perceptual flexibility and resolving ambiguity. The degree to which a listener's responses to a continuum of speech sounds are categorical versus continuous can be quantified using visual analog scaling (VAS) during speech labeling tasks. Here, we recorded event-related brain potentials (ERPs) to vowels along an acoustic-phonetic continuum (/u/ to /a/) while listeners categorized phonemes in both clean and noise conditions. Behavior was assessed using standard two alternative forced choice (2AFC) and VAS paradigms to evaluate categorization under task structures that promote discrete (2AFC) vs. continuous (VAS) hearing, respectively. Behaviorally, identification curves were steeper under 2AFC vs. VAS categorization but were relatively immune to noise, suggesting robust access to abstract, phonetic categories even under signal degradation. Behavioral slopes were positively correlated with listeners' QuickSIN scores, suggesting a behavioral advantage for speech in noise comprehension conferred by gradient listening strategy. At the neural level, electrode level data revealed P2 peak amplitudes of the ERPs were modulated by task and noise; responses were larger under VAS vs. 2AFC categorization and showed larger noise-related delay in latency in the VAS vs. 2AFC condition. More gradient responders also had smaller shifts in ERP latency with noise, suggesting their neural encoding of speech was more resilient to noise degradation. Interestingly, source-resolved ERPs showed that more gradient listening was also correlated with stronger neural responses in left superior temporal gyrus. Our results demonstrate that listening strategy (i.e., being a discrete vs. continuous listener) modulates the categorical organization of speech and behavioral success, with continuous/gradient listening being more advantageous to speech in noise perception.

Neurodevelopment of children exposed to prolonged anesthesia in infancy: GABA study interim analysis of resting-state brain networks at 2, 4, and 10-months old

BACKGROUND

Previous studies have raised concerns regarding neurodevelopmental impacts of early exposures to general anesthesia and surgery. Electroencephalography (EEG) can be used to study ontogeny of brain networks during infancy. As a substudy of an ongoing study, we examined measures of functional connectivity in awake infants with prior early and prolonged anesthetic exposures and in control infants.

METHODS

EEG functional connectivity was assessed using debiased weighted phase lag index at source and sensor levels and graph theoretical measures for resting state activity in awake infants in the early anesthesia (n = 26 at 10 month visit, median duration of anesthesia = 4 [2, 7 h]) and control (n = 38 at 10 month visit) groups at ages approximately 2, 4 and 10 months. Theta and low alpha frequency bands were of primary interest. Linear mixed models incorporated impact of age and cumulative hours of general anesthesia exposure.

RESULTS

Models showed no significant impact of cumulative hours of general anesthesia exposure on debiased weighted phase lag index, characteristic path length, clustering coefficient or small-worldness (conditional R2 0.05-0.34). An effect of age was apparent in many of these measures.

CONCLUSIONS

We could not demonstrate significant impact of general anesthesia in the first months of life on early development of resting state brain networks over the first postnatal year. Future studies will explore these networks as these infants grow older.

Infant neuroscience: how to measure brain activity in the youngest minds

The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.

Resting-State Activity in Children: Replicating and Extending Findings of Early Maturation of Alpha Rhythms in Autism Spectrum Disorder

Resting-state alpha brain rhythms provide a foundation for basic as well as higher-order brain processes. Research suggests atypical maturation of the peak frequency of resting-state alpha activity (= PAF) in autism spectrum disorder (ASD). The present study examined resting-state alpha activity in young school-aged children, obtaining magnetoencephalographic (MEG) eyes-closed resting-state data from 47 typically developing (TD) males and 45 ASD males 6.0 to 9.3 years old. Results confirmed a higher PAF in ASD versus TD, and demonstrated that alpha power differences between groups were linked to the shift of PAF in ASD. Additionally, a higher PAF was associated with better cognitive performance in TD but not ASD. Finding thus suggested functional consequences of group differences in resting-state alpha activity.

Emotional abuse mediated by negative automatic thoughts impacts functional connectivity during adolescence

Background

Emotional abuse during childhood and adolescence is thought to be associated with the brain; however, the neural mechanism underlying the cognitive process remains unknown. Therefore, we aimed to investigate the mediating effect of negative automatic thoughts on the relationship between emotional abuse and resting-state functional connectivity (rsFC) during adolescence.

Method

Our community sample included 54 adolescents aged 13-17 years in the statistical analysis. Resting-state functional and structural magnetic resonance imaging (MRI) was performed, while emotional abuse and negative automatic thoughts were assessed using self-reported scales. A mediation analysis was used to assess the contributions of early traumatic events and negative automatic thoughts to resting functional connectivity.

Result

Higher negative automatic thoughts were associated with lower connectivity in the context of greater emotional abuse (i.e., suppression effect). Thus, the relationships between emotional abuse and connectivity in the precuneus (pCun)-medial prefrontal cortex, parahippocampal cortex-extrastriate cortex, and temporal cortex-temporal pole were decreased by negative automatic thoughts. In contrast, functional connections in the pCun-pCun, pCun-precuneus/posterior cingulate cortex, and nucleus accumbens-somatomotor areas were strongly mediated when emotionally abused adolescents reported a high tendency for negative automatic thoughts.

Conclusion

Negative automatic thoughts strengthened the relationship between emotional abuse and rsFC. These findings highlight the underlying cognitive processing of the traumatic event-neural system, supporting the use of cognitive therapy for post-traumatic symptoms.

Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release

Existing methods for voxelwise transient dopamine (DA) release detection rely on explicit kinetic modeling of the [11C]raclopride PET time activity curve, which at the voxel level is typically confounded by noise, leading to poor performance for detection of low-amplitude DA release-induced signals. Here we present a novel data-driven, task-informed method-referred to as Residual Space Detection (RSD)-that transforms PET time activity curves to a residual space where DA release-induced perturbations can be isolated and processed. Using simulations, we demonstrate that this method significantly increases detection performance compared to existing kinetic model-based methods for low-magnitude DA release (simulated +100% peak increase in basal DA concentration). In addition, results from nine healthy controls injected with a single bolus of [11C]raclopride performing a finger tapping motor task are shown as proof-of-concept. The ability to detect relatively low magnitudes of dopamine release in the human brain using a single bolus injection, while achieving higher statistical power than previous methods, may additionally enable more complex analyses of neurotransmitter systems. Moreover, RSD is readily generalizable to multiple tasks performed during a single PET scan, further extending the capabilities of task-based single-bolus protocols.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

The impact of caregiver inhibitory control on infant visual working memory

Visual working memory (VWM) emerges in the first year of life and has far-reaching implications for academic and later life outcomes. Given that caregivers play a significant role in shaping cognitive function in children, it is important to understand how they might impact VWM development as early as infancy. The current study investigated whether caregivers' efficiency of regulating inhibitory control was associated with VWM function in their infants. Eighty-eight caregivers were presented with a Go-NoGo task to assess inhibitory control. An efficiency score was calculated using their behavioural responses. Eighty-six 6-to-10-month-old infants were presented with a preferential looking task to assess VWM function. VWM load was manipulated across one (low load), two (medium load) and three (high load) items. Functional near-infrared spectroscopy was used to record brain activation from caregivers and their infants. We found no direct association between caregiver efficiency and infant VWM behaviour. However, we found an indirect association - caregiver efficiency was linked to infant VWM through left-lateralized fronto-parietal engagement. Specifically, infants with low efficiency caregivers showed decreasing left-lateralized parietal engagement with increasing VWM performance at the medium and high loads compared to infants with high efficiency caregivers, who did not show any load- or performance-dependent modulation. Our findings contribute to a growing body of literature examining the role that caregivers play in early neurocognitive development.

Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Segregated Dynamical Networks for Biological Motion Perception in the Mu and Beta Range Underlie Social Deficits in Autism

OBJECTIVE

Biological motion perception (BMP) correlating with a mirror neuron system (MNS) is attenuated in underage individuals with autism spectrum disorder (ASD). While BMP in typically-developing controls (TDCs) encompasses interconnected MNS structures, ASD data hint at segregated form and motion processing. This coincides with less fewer long-range connections in ASD than TDC. Using BMP and electroencephalography (EEG) in ASD, we characterized directionality and coherence (mu and beta frequencies). Deficient BMP may stem from desynchronization thereof in MNS and may predict social-communicative deficits in ASD. Clinical considerations thus profit from brain-behavior associations.

METHODS

Point-like walkers elicited BMP using 15 white dots (walker vs. scramble in 21 ASD (mean: 11.3 ± 2.3 years) vs. 23 TDC (mean: 11.9 ± 2.5 years). Dynamic Imaging of Coherent Sources (DICS) characterized the underlying EEG time-frequency causality through time-resolved Partial Directed Coherence (tPDC). Support Vector Machine (SVM) classification validated the group effects (ASD vs. TDC).

RESULTS

TDC showed MNS sources and long-distance paths (both feedback and bidirectional); ASD demonstrated distinct from and motion sources, predominantly local feedforward connectivity, and weaker coherence. Brain-behavior correlations point towards dysfunctional networks. SVM successfully classified ASD regarding EEG and performance.

CONCLUSION

ASD participants showed segregated local networks for BMP potentially underlying thwarted complex social interactions. Alternative explanations include selective attention and global-local processing deficits.

SIGNIFICANCE

This is the first study applying source-based connectivity to reveal segregated BMP networks in ASD regarding structure, cognition, frequencies, and temporal dynamics that may explain socio-communicative aberrancies.

HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations

We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm isotropic resolution for T1w, T2w, and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus are often impossible to identify using standard MRI protocols-can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with the existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high-quality individual brain. This serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical, and education settings.

Sensory processing of native and non-native phonotactic patterns in the alpha and beta frequency bands

The phonotactic patterns of one's native language are established within cortical network processing during development. Sensory processing of native language phonotactic patterns established in memory may be modulated by top-down signals within the alpha and beta frequency bands. To explore sensory processing of phonotactic patterns in the alpha and beta frequency bands, electroencephalograms (EEGs) were recorded from native Polish and native English-speaking adults as they listened to spoken nonwords within same and different nonword pairs. The nonwords contained three phonological sequence onsets that occur in the Polish and English languages (/pət/, /st/, /sət/) and one onset sequence /pt/, which occurs in Polish but not in English onsets. Source localization modeling was used to transform 64-channel EEGs into brain source-level channels. Spectral power values in the low frequencies (2-29 Hz) were analyzed in response to the first nonword in nonword pairs within the context of counterbalanced listening-task conditions, which were presented on separate testing days. For the with-task listening condition, participants performed a behavioral task to the second nonword in the pairs. For the without-task condition participants were only instructed to listen to the stimuli. Thus, in the with-task condition, the first nonword served as a cue for the second nonword, the target stimulus. The results revealed decreased spectral power in the beta frequency band for the with-task condition compared to the without-task condition in response to native language phonotactic patterns. In contrast, the task-related suppression effects in response to the non-native phonotactic pattern /pt/ for the English listeners extended into the alpha frequency band. These effects were localized to source channels in left auditory cortex, the left anterior temporal cortex and the occipital pole. This exploratory study revealed a pattern of results that, if replicated, suggests that native language speech perception is supported by modulations in the alpha and beta frequency bands.

Differential Maturation of Auditory Cortex Activity in Young Children with Autism and Typical Development

Maturation of auditory cortex neural encoding processes was assessed in children with typical development (TD) and autism. Children 6-9 years old were enrolled at Time 1 (T1), with follow-up data obtained ~ 18 months later at Time 2 (T2), and ~ 36 months later at Time 3 (T3). Findings suggested an initial period of rapid auditory cortex maturation in autism, earlier than TD (prior to and surrounding the T1 exam), followed by a period of faster maturation in TD than autism (T1-T3). As a result of group maturation differences, post-stimulus group differences were observed at T1 but not T3. In contrast, stronger pre-stimulus activity in autism than TD was found at all time points, indicating this brain measure is stable across time.

Multimodal study of the neural sources of error monitoring in adolescents and adults

The ability to monitor performance during a goal-directed behavior differs among children and adults in ways that can be measured with several tasks and techniques. As well, recent work has shown that individual differences in error monitoring moderate temperamental risk for anxiety and that this moderation changes with age. We investigated age differences in neural responses linked to performance monitoring using a multimodal approach. The approach combined functional MRI and source localization of event-related potentials (ERPs) in 12-year-old, 15-year-old, and adult participants. Neural generators of two components related to performance and error monitoring, the N2 and ERN, lay within specific areas of fMRI clusters. Whereas correlates of the N2 component appeared similar across age groups, age-related differences manifested in the location of the generators of the ERN component. The dorsal anterior cingulate cortex (dACC) was the predominant source location for the 12-year-old group; this area manifested posteriorly for the 15-year-old and adult groups. A fMRI-based ROI analysis confirmed this pattern of activity. These results suggest that changes in the underlying neural mechanisms are related to developmental changes in performance monitoring.

Maturation of auditory cortex neural responses during infancy and toddlerhood

The infant auditory system rapidly matures across the first years of life, with a primary goal of obtaining ever-more-accurate real-time representations of the external world. Our understanding of how left and right auditory cortex neural processes develop during infancy, however, is meager, with few studies having the statistical power to detect potential hemisphere and sex differences in primary/secondary auditory cortex maturation. Using infant magnetoencephalography (MEG) and a cross-sectional study design, left and right auditory cortex P2m responses to pure tones were examined in 114 typically developing infants and toddlers (66 males, 2 to 24 months). Non-linear maturation of P2m latency was observed, with P2m latencies decreasing rapidly as a function of age during the first year of life, followed by slower changes between 12 and 24 months. Whereas in younger infants auditory tones were encoded more slowly in the left than right hemisphere, similar left and right P2m latencies were observed by ∼21 months of age due to faster maturation rate in the left than right hemisphere. No sex differences in the maturation of the P2m responses were observed. Finally, an earlier left than right hemisphere P2m latency predicted better language performance in older infants (12 to 24 months). Findings indicate the need to consider hemisphere when examining the maturation of auditory cortex neural activity in infants and toddlers and show that the pattern of left-right hemisphere P2m maturation is associated with language performance.

A comparison of resting-state eyes-closed and dark-room alpha-band activity in children

In a relaxed and awake state with the eyes closed, 8-12 Hz neural oscillations are the dominant rhythm, most prominent in parietal-occipital regions. Resting-state (RS) alpha is associated with processing speed and is also thought to be central to how networks process information. Unfortunately, the RS eyes-closed (EC) exam can only be used with individuals who can remain awake with their eyes closed for an extended period. As such, infants, toddlers, and individuals with intellectual disabilities are usually excluded from RS alpha studies. Previous research suggests obtaining RS alpha measures in a dark room with the eyes open as a viable alternative to the traditional RS EC exam. To further explore this, RS EC and RS dark room (DR) eyes-open alpha activity was recorded using magnetoencephalography in children with typical development (TD; N = 37) and children with autism spectrum disorder (ASD; N = 30) 6.9-12.6 years old. Findings showed good reliability for the RS EC and DR peak alpha frequency (frequency with strongest alpha power; interclass correlation (ICC) = 0.83). ICCs for posterior alpha power were slightly lower (ICCs in the 0.70 s), with an ~ 5% reduction in posterior alpha power in the DR than EC condition. No differences in the EC and DR associations were observed between the TD and ASD groups. Finally, age was associated with both EC and DR peak alpha frequency. Findings thus indicate the DR exam as a viable way to obtain RS alpha measures in populations frequently excluded from electrophysiology RS studies.

Origin, synchronization, and propagation of sleep slow waves in children

STUDY OBJECTIVES

Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood.

METHODS

We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N=21, 10.3±1.5 years old) and young healthy adults (N=18, 31.1±4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p=0.05.

RESULTS

The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms.

CONCLUSIONS

Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.

A radiofrequency coil for infants and toddlers

Infants and toddlers are a challenging population upon which to perform magnetic resonance imaging (MRI) of the brain, both in research and clinical settings. Because of the large range in head size during the early years of development, paediatric neuro-MRI requires a radiofrequency (RF) coil, or set of coils, that is tailored to head size to provide the highest image quality. Mitigating techniques must also be employed to reduce and correct for subject motion. This manuscript describes an RF coil with a tailored mechanical-electrical design that can adapt to the head size of 3-month-old infants to 3-year-old toddlers. The RF coil was designed with tight-fitting coil elements to improve the signal-to-noise ratio (SNR) in comparison with commercially available adult head coils, while simultaneously aiding in immobilization. The coil was designed without visual obstruction to facilitate an unimpeded view of the child's face and the potential application of camera or motion-tracking systems. Despite the lack of elements over the face, the paediatric coil produced higher SNR over most of the brain compared with adult coils, including more than twofold in the periphery. Acceleration rates of fourfold in each Cartesian direction could be achieved. High SNR allowed for short acquisition times through accelerated imaging protocols and reduced the probability of motion during a scan. Modification of the acquisition protocol, with immobilization of the head through the adjustable coil geometry, and subsequently being combined with a motion-tracking system, provides a compelling platform for scanning paediatric populations without sedation and with improved image quality.

Frontal asymmetry assessed in infancy using functional near-infrared spectroscopy is associated with emotional and behavioral problems in early childhood

Frontal asymmetry (FA), the difference in brain activity between the left versus right frontal areas, is thought to reflect approach versus avoidance motivation. This study (2012-2021) used functional near-infrared spectroscopy to investigate if infant (Mage  = 7.63 months; N = 90; n = 48 male; n = 75 White) FA in the dorsolateral prefrontal cortex relates to psychopathology in later childhood (Mage  = 62.05 months). Greater right FA to happy faces was associated with increased internalizing (η2  = .09) and externalizing (η2  = .06) problems at age 5 years. Greater right FA to both happy and fearful faces was associated with an increased likelihood of a lifetime anxiety diagnosis (R2  > .13). FA may be an informative and early-emerging marker for psychopathology.

The first year in formal schooling improves working memory and academic abilities

Neurocognition and academic abilities during the period of 4 and 7 years of age are impacted by both the transition from kindergarten to primary school and age-related developmental processes. Here, we used a school cut-off design to tease apart the impact of formal schooling from age, on working memory (WM) function, vocabulary, and numeracy scores. We compared two groups of children with similar age, across two years: first-graders (FG), who were enrolled into primary school the year that they became eligible and kindergarteners (KG), who were deferred school entry until the following year. All children completed a change detection task while brain activation was recorded using portable functional near-infrared spectroscopy, a vocabulary assessment, and a numeracy screener. Our results revealed that FG children showed greater improvement in WM performance and greater engagement of a left-lateralized fronto-parietal network compared to KG children. Further, they also showed higher gains in vocabulary and non-symbolic numeracy scores. This improvement in vocabulary and non-symbolic numeracy scores following a year in primary school was predicted by WM function. Our findings contribute to a growing body of literature examining neurocognitive and academic benefits conferred to children following exposure to formal schooling.

Sensory Inhibition and Speech Perception-in-Noise Performance in Children With Normal Hearing

PURPOSE

This study investigated whether sensory inhibition in children may be associated with speech perception-in-noise performance. Additionally, gating networks associated with sensory inhibition were identified via standardized low-resolution brain electromagnetic tomography (sLORETA), and the detectability of the cortical auditory evoked potential (CAEP) N1 response was enhanced using a 4- to 30-Hz bandpass filter.

METHOD

CAEP gating responses, reflective of inhibition, were evoked via click pairs and recorded using high-density electroencephalography in neurotypical 5- to 8-year-olds and 22- to 24-year-olds. Amplitude gating indices were calculated and correlated with speech perception in noise. Gating generators were estimated using sLORETA. A 4- to 30-Hz filter was applied to detect the N1 gating component.

RESULTS

Preliminary findings indicate children showed reduced gating, but there was a correlational trend between better speech perception and decreased N2 gating. Commensurate with decreased gating, children presented with incomplete compensatory gating networks. The 4- to 30-Hz filter identified the N1 response in a subset of children.

CONCLUSIONS

There was a tenuous relationship between children's speech perception and sensory inhibition. This may suggest that sensory inhibition is only implicated in atypically poor speech perception. Finally, the 4- to 30-Hz filter settings are critical in N1 detectability.

SIGNIFICANCE

Gating may help evaluate reduced sensory inhibition in children with clinically poor speech perception using the appropriate methodology. Cortical gating generators in typically developing children are also newly identified.

Influence of oversimplifying the head anatomy on cerebral blood flow measurements with diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) is an emerging optical modality for non-invasive assessment of an index of regional cerebral blood flow. By the nature of this noninvasive measurement, light must pass through extracerebral layers (i.e., skull, scalp, and cerebral spinal fluid) before detection at the tissue surface. To minimize the contribution of these extracerebral layers to the measured signal, an analytical model has been developed that treats the head as a series of three parallel and infinitely extending slabs (mimicking scalp, skull, and brain). The three-layer model has been shown to provide a significant improvement in cerebral blood flow estimation over the typically used model that treats the head as a bulk homogenous medium. However, the three-layer model is still a gross oversimplification of the head geometry that ignores head curvature, the presence of cerebrospinal fluid (CSF), and heterogeneity in layer thickness.

Aim

Determine the influence of oversimplifying the head geometry on cerebral blood flow estimated with the three-layer model.

Approach

Data were simulated with Monte Carlo in a four-layer slab medium and a three-layer sphere medium to isolate the influence of CSF and curvature, respectively. Additionally, simulations were performed on magnetic resonance imaging (MRI) head templates spanning a wide-range of ages. Simulated data were fit to both the homogenous and three-layer model for CBF. Finally, to mitigate the errors in potential CBF estimation due to the difficulty in defining layer thickness, we investigated an approach to identify an equivalent, "optimized" thickness via a pressure modulation.

Results

Both head curvature and failing to account for CSF lead to significant errors in the estimation of CBF. However, the effect of curvature and CSF on relative changes in CBF is minimal. Further, we found that CBF was underestimated in all MRI-templates, although the magnitude of these underestimations was highly influenced by small variations in the source and detector optode positioning. The optimized thickness obtained from pressure modulation did not improve estimation accuracy of CBF, although it did significantly improve the estimation accuracy of relative changes in CBF.

Conclusions

In sum, these findings suggest that the three-layer model holds promise for improving estimation of relative changes in cerebral blood flow; however, estimations of absolute cerebral blood flow with the approach should be viewed with caution given that it is difficult to account for appreciable sources of error, such as curvature and CSF.

Cardiorespiratory fitness is associated with fMRI signal in right cerebellum lobule VIIa Crus I and II during spatial navigation in older adult women

Spatial navigation is a cognitive skill critical for accomplishing daily goal-directed behavior in a complex environment; however, older adults exhibit marked decline in navigation performance with age. Neuroprotective interventions that enhance the functional integrity of navigation-linked brain regions, such as those in the medial temporal lobe memory system, may preserve spatial navigation performance in older adults. Importantly, a well-established body of literature suggests that cardiorespiratory fitness has measurable effects on neurobiological integrity in the medial temporal lobes, as well as in other brain areas implicated in spatial navigation, such as the precuneus and cerebellum. However, whether cardiorespiratory fitness modulates brain activity in these regions during navigation in older adults remains unknown. Thus, the primary objective of the current study was to examine cardiorespiratory fitness as a modulator of fMRI activity in navigation-linked brain regions in cognitively healthy older adults. To accomplish this objective, cognitively intact participants (N = 22, aged 60-80 years) underwent cardiorespiratory fitness testing to estimate maximal oxygen uptake ( V · O_2max) and underwent whole-brain high-resolution fMRI while performing a virtual reality navigation task. Our older adult sample demonstrated significant fMRI signal in the right and left retrosplenial cortex, right precuneus, right and left inferior parietal cortex, right and left cerebellum lobule VIIa Crus I and II, right fusiform gyrus, right parahippocampal cortex, right lingual gyrus, and right hippocampus during encoding of a virtual environment. Most importantly, in women but not men (N = 16), cardiorespiratory fitness was positively associated with fMRI activity in the right cerebellum lobule VIIa Crus I and II, but not other navigation-linked brain areas. These findings suggest that the influence of cardiorespiratory fitness on brain function extends beyond the hippocampus, as observed in other work, to the cerebellum lobule VIIa Crus I and II, a component of the cerebellum that has recently been linked to cognition and more specifically, spatial processing.

Association of psychosocial adversity and social information processing in children raised in a low-resource setting: an fNIRS study

Social cognition skills and socioemotional development are compromised in children growing up in low SES contexts, however, the mechanisms underlying this association remain unknown. Exposure to psychosocial risk factors early in life alters the child's social milieu and in turn, could lead to atypical processing of social stimuli. In this study, we used functional Near Infrared Spectroscopy (fNIRS) to measure cortical responses to a social discrimination task in children raised in a low-resource setting at 6, 24, and 36 months. In addition, we assessed the relation between cortical responses to social and non-social information with psychosocial risk factors assessed using the Childhood Psychosocial Adversity Scale (CPAS). In line with previous findings, we observed specialization to social stimuli in cortical regions in all age groups. In addition, we found that risk factors were associated with social discrimination at 24 months (intimate partner violence and verbal abuse and family conflict) and 36 months (verbal abuse and family conflict and maternal depression) but not at 6 months. Overall, the results show that exposure to psychosocial adversity has more impact on social information processing in toddlerhood than earlier in infancy.

Challenges and new perspectives of developmental cognitive EEG studies

Despite shared procedures with adults, electroencephalography (EEG) in early development presents many specificities that need to be considered for good quality data collection. In this paper, we provide an overview of the most representative early cognitive developmental EEG studies focusing on the specificities of this neuroimaging technique in young participants, such as attrition and artifacts. We also summarize the most representative results in developmental EEG research obtained in the time and time-frequency domains and use more advanced signal processing methods. Finally, we briefly introduce three recent standardized pipelines that will help promote replicability and comparability across experiments and ages. While this paper does not claim to be exhaustive, it aims to give a sufficiently large overview of the challenges and solutions available to conduct robust cognitive developmental EEG studies.

Age-related changes of whole-brain dynamics in spontaneous neuronal coactivations

Human brains experience whole-brain anatomic and functional changes throughout the lifespan. Age-related whole-brain network changes have been studied with functional magnetic resonance imaging (fMRI) to determine their low-frequency spatial and temporal characteristics. However, little is known about age-related changes in whole-brain fast dynamics at the scale of neuronal events. The present study investigated age-related whole-brain dynamics in resting-state electroencephalography (EEG) signals from 73 healthy participants from 6 to 65 years old via characterizing transient neuronal coactivations at a resolution of tens of milliseconds. These uncovered transient patterns suggest fluctuating brain states at different energy levels of global activations. Our results indicate that with increasing age, shorter lifetimes and more occurrences were observed in the brain states that show the global high activations and more consecutive visits to the global highest-activation brain state. There were also reduced transitional steps during consecutive visits to the global lowest-activation brain state. These age-related effects suggest reduced stability and increased fluctuations when visiting high-energy brain states and with a bias toward staying low-energy brain states. These age-related whole-brain dynamics changes are further supported by changes observed in classic alpha and beta power, suggesting its promising applications in examining the effect of normal healthy brain aging, brain development, and brain disease.

Brain-wide neural co-activations in resting human

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of < 0.1 Hz. However, understanding of fast brain-wide networks at the timescales of neuronal events (milliseconds to sub-seconds) and their spatial, spectral, and transitional characteristics remain limited due to the temporal constraints of hemodynamic signals. With milli-second resolution and whole-head coverage, scalp-based electroencephalography (EEG) provides a unique window into brain-wide networks with neuronal-timescale dynamics, shedding light on the organizing principles of brain functions. Using the state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs). These cCAPs revealed brain-wide intrinsic networks and their dynamics, indicating the configuration/reconfiguration of resting human brains into recurring and transitional functional states, which are featured with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations. Rich oscillational structures across a wide frequency band (i.e., 0.6 Hz, 5 Hz, and 10 Hz) were embedded in the nonstationary dynamics of these functional states. We further identified a superstructure that regulated between-state immediate and long-range transitions involving the entire set of identified cCAPs and governed a significant aspect of brain-wide network dynamics. These findings demonstrated how resting-state EEG data can be functionally decomposed using cCAPs to reveal rich dynamic structures of brain-wide human neural activations.

Age-related changes in diffuse optical tomography sensitivity profiles from childhood to adulthood

SIGNIFICANCE

Diffuse optical tomography (DOT) uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the brain location that generates the hemodynamic signal require accurate descriptions of the DOT sensitivity to the underlying cortex. DOT sensitivity profiles are different in infants compared with adults. However, the descriptions of DOT sensitivity profiles from early childhood to adulthood are lacking despite the continuous head and brain development.

AIM

We aim to investigate age-related differences in DOT sensitivity profiles in individuals aged from 2 to 34 years with narrow age ranges of 0.5 or 1 year.

APPROACH

We implemented existing photon migration simulation methods and computed source-detector channel DOT sensitivity using age-appropriate, realistic head models.

RESULTS

DOT sensitivity profiles change systematically as a function of source-detector separation distance for all age groups. Children displayed distinctive DOT sensitivity profiles compared to older individuals, and the differences were enhanced at larger separation distances.

CONCLUSIONS

The findings have important implications for the design of source-detector placement and image reconstruction. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone DOT data. Using age-inappropriate head models will have more negative impacts on estimation accuracy in younger children.

Evaluating Head Models for Cortical Source Localization of the Face-Sensitive N290 Component in Infants

Accurate cortical source localization of event-related potentials (ERPs) requires using realistic head models constructed from the participant's structural magnetic resonance imaging (MRI). A challenge in developmental studies is the limited accessibility of participant-specific MRIs. The present study compared source localization of infants' N290 ERP activities estimated using participant-specific head models with a series of substitute head models. The N290 responses to faces relative to toys were measured in 36 infants aged at 4.5, 7.5, 9, and 12 months. The substitutes were individual-based head models constructed from age-matched MRIs with closely matched ("close") or different ("far") head measures with the participants, age-appropriate average template, and age-inappropriate average templates. The greater source responses to faces than toys at the middle fusiform gyrus (mFG) estimated using participant-specific head models were preserved in individual-based head models, but not average templates. The "close" head models yielded the best fit with the participant-specific head models in source activities at the mFG and across face-processing-related regions of interest (ROIs). The age-appropriate average template showed mixed results, not supporting the stimulus effect but showed topographical distributions across the ROIs like the participant-specific head models. The "close" head models are the most optimal substitute for participant-specific MRIs.

Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Different studies have suggested that during speech processing readers with dyslexia present atypical levels of neural entrainment as well as atypical functional hemispherical asymmetries in comparison with typical readers. In this study, we evaluated these differences in children and the variation with age before and after starting with formal reading instruction. Synchronized neural auditory processing activity was quantified based on auditory steady-state responses (ASSRs) from EEG recordings. The stimulation was modulated at syllabic and phonemic fluctuation rates present in speech. We measured the brain activation patterns and the hemispherical asymmetries in children at three age points (5, 7, and 9 years old). Despite the well-known heterogeneity during developmental stages, especially in children and in dyslexia, we could extract meaningful common oscillatory patterns. The analyses included (1) the estimations of source localization, (2) hemispherical preferences using a laterality index, measures of neural entrainment, (3) signal-to-noise ratios (SNRs), and (4) connectivity using phase coherence measures. In this longitudinal study, we confirmed that the existence of atypical levels of neural entrainment and connectivity already exists at pre-reading stages. Overall, these measures reflected a lower ability of the dyslectic brain to synchronize with syllabic rate stimulation. In addition, our findings reinforced the hypothesis of a later maturation of the processing of beta rhythms in dyslexia. This investigation emphasizes the importance of longitudinal studies in dyslexia, especially in children, where neural oscillatory patterns as well as differences between typical and atypical developing children can vary in the span of a year.

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.

Spatial normalization and quantification approaches of PET imaging for neurological disorders

Quantification approaches of positron emission tomography (PET) imaging provide user-independent evaluation of pathophysiological processes in living brains, which have been strongly recommended in clinical diagnosis of neurological disorders. Most PET quantification approaches depend on spatial normalization of PET images to brain template; however, the spatial normalization and quantification approaches have not been comprehensively reviewed. In this review, we introduced and compared PET template-based and magnetic resonance imaging (MRI)-aided spatial normalization approaches. Tracer-specific and age-specific PET brain templates were surveyed between 1999 and 2021 for ¹⁸F-FDG, ¹¹C-PIB, ¹⁸F-Florbetapir, ¹⁸F-THK5317, and etc., as well as adaptive PET template methods. Spatial normalization-based PET quantification approaches were reviewed, including region-of-interest (ROI)-based and voxel-wise quantitative methods. Spatial normalization-based ROI segmentation approaches were introduced, including manual delineation on template, atlas-based segmentation, and multi-atlas approach. Voxel-wise quantification approaches were reviewed, including voxel-wise statistics and principal component analysis. Certain concerns and representative examples of clinical applications were provided for both ROI-based and voxel-wise quantification approaches. At last, a recipe for PET spatial normalization and quantification approaches was concluded to improve diagnosis accuracy of neurological disorders in clinical practice.

Bilingualism alters infants' cortical organization for attentional orienting mechanisms

A bilingual environment is associated with changes in the brain's structure and function. Some suggest that bilingualism also improves higher-cognitive functions in infants as young as 6-months, yet whether this effect is associated with changes in the infant brain remains unknown. In the present study, we measured brain activity using functional near-infrared spectroscopy in monolingual- and bilingual-raised 6- and 10-month-old infants. Infants completed an orienting attention task, in which a cue was presented prior to an object appearing on the same (Valid) or opposite (Invalid) side of a display. Task performance did not differ between the groups but neural activity did. At 6-months, both groups showed greater activity for Valid (> Invalid) trials in frontal regions (left hemisphere for bilinguals, right hemisphere for monolinguals). At 10-months, bilinguals showed greater activity for Invalid (> Valid) trials in bilateral frontal regions, while monolinguals showed greater brain activity for Valid (> Invalid) trials in left frontal regions. Bilinguals' brain activity trended with their parents' reporting of dual-language mixing when speaking to their child. These findings are the first to indicate how early (dual) language experience can alter the cortical organization underlying broader, non-linguistic cognitive functions during the first year of life.

Systemic inflammation during the first year of life is associated with brain functional connectivity and future cognitive outcomes

The first years of life are a sensitive period of rapid neural and immune system development vulnerable to the impact of adverse experiences. Several studies support inflammation as a consequence of various adversities and an exposure negatively associated with developmental outcomes. The mechanism by which systemic inflammation may affect brain development and later cognitive outcomes remains unclear. In this longitudinal cohort study, we examine the associations between recurrent systemic inflammation, defined as C-reactive protein elevation on ≥ 2 of 4 measurements across the first year of life, electroencephalography (EEG) functional connectivity (FC) at 36 months, and composite cognitive outcomes at 3, 4, and 5 years among 122 children living in a limited-resource setting in Dhaka, Bangladesh. Recurrent systemic inflammation during the first year of life is significantly negatively associated with cognitive outcomes at 3, 4, and 5 years, after accounting for stunting and family care indicators (a measure of stimulation in the home environment). Recurrent systemic inflammation is significantly positively associated with parietal-occipital FC in the Beta band at 36 months, which in turn is significantly negatively associated with composite cognitive scores at 3 and 4 years. However, FC does not mediate the relationship between recurrent systemic inflammation and cognitive outcomes.

EEG Correlates of Active Stopping and Preparation for Stopping in Chronic Tic Disorder

Motor inhibition is an important cognitive process involved in tic suppression. As the right frontal lobe contains important inhibitory network nodes, we characterized right superior, middle, and inferior frontal gyral (RSFG, RMFG, RIFG) event-related oscillations during motor inhibition in youth with chronic tic disorders (CTD) versus controls. Fourteen children with CTD and 13 controls (10–17 years old) completed an anticipated-response stop signal task while dense-array electroencephalography was recorded. Between-group differences in spectral power changes (3–50 Hz) were explored after source localization and multiple comparisons correction. Two epochs within the stop signal task were studied: (1) preparatory phase early in the trial before motor execution/inhibition and (2) active inhibition phase after stop signal presentation. Correlation analyses between electrophysiologic data and clinical rating scales for tic, obsessive-compulsive symptoms, and inattention/hyperactivity were performed. There were no behavioral or electrophysiological differences during active stopping. During stop preparation, CTD participants showed greater event-related desynchronization (ERD) in the RSFG (γ-band), RMFG (β, γ-bands), and RIFG (θ, α, β, γ-bands). Higher RSFG γ-ERD correlated with lower tic severity (r = 0.66, p = 0.04). Our findings suggest RSFG γ-ERD may represent a mechanism that allows CTD patients to keep tics under control and achieve behavioral performance similar to peers.

Age Estimation from fMRI Data Using Recurrent Neural Network

Finding a biomarker that indicates the subject’s age is one of the most important topics in biology. Several recent studies tried to extract a biomarker from brain imaging data including fMRI data. However, most of them focused on MRI data, which do not provide dynamics and lack attempts to apply recently proposed deep learning models. We propose a deep neural network model that estimates the age of a subject from fMRI images using a recurrent neural network (RNN), more precisely, a gated recurrent unit (GRU). However, applying neural networks is not trivial due to the high dimensional nature of fMRI data. In this work, we propose a novel preprocessing technique using the Automated Anatomical Labeling (AAL) atlas, which significantly reduces the input dimension. The proposed dimension reduction technique allows us to train our model with 640 training and validation samples from different projects under mean squared error (MSE). Finally, we obtain the correlation value of 0.905 between the predicted age and the actual age on 155 test samples. The proposed model estimates the age within the range of ±12 on most of the test samples. Our model is written in Python and is freely available for download.

Acoustic-level and language-specific processing of native and non-native phonological sequence onsets in the low gamma and theta-frequency bands

Acoustic structures associated with native-language phonological sequences are enhanced within auditory pathways for perception, although the underlying mechanisms are not well understood. To elucidate processes that facilitate perception, time-frequency (T-F) analyses of EEGs obtained from native speakers of English and Polish were conducted. Participants listened to same and different nonword pairs within counterbalanced attend and passive conditions. Nonwords contained the onsets /pt/, /pət/, /st/, and /sət/ that occur in both the Polish and English languages with the exception of /pt/, which never occurs in the English language in word onset. Measures of spectral power and inter-trial phase locking (ITPL) in the low gamma (LG) and theta-frequency bands were analyzed from two bilateral, auditory source-level channels, created through source localization modeling. Results revealed significantly larger spectral power in LG for the English listeners to the unfamiliar /pt/ onsets from the right hemisphere at early cortical stages, during the passive condition. Further, ITPL values revealed distinctive responses in high and low-theta to acoustic characteristics of the onsets, which were modulated by language exposure. These findings, language-specific processing in LG and acoustic-level and language-specific processing in theta, support the view that multi scale temporal processing in the LG and theta-frequency bands facilitates speech perception.

Atypical processing in neural source analysis of speech envelope modulations in adolescents with dyslexia

Different studies have suggested that language and developmental disorders such as dyslexia are associated with a disturbance of auditory entrainment and of the functional hemispheric asymmetries during speech processing. These disorders typically result from an issue in the phonological component of language that causes problems to represent and manipulate the phonological structure of words at the syllable and/or phoneme level. We used Auditory Steady-State Responses (ASSRs) in EEG recordings to investigate the brain activation and hemisphere asymmetry of theta, alpha, beta and low-gamma range oscillations in typical readers and readers with dyslexia. The aim was to analyse whether the group differences found in previous electrode level studies were caused by a different source activation pattern or conversely was an effect that could be found on the active brain sources. We could not find differences in the brain locations of the main active brain sources. However, we observed differences in the extracted waveforms. The group average of the first DSS component of all signal-to-noise ratios of ASSR at source level was higher than the group averages at the electrode level. These analyses included a lower alpha synchronisation in adolescents with dyslexia and the possibility of compensatory mechanisms in theta, beta and low-gamma frequency bands. The main brain auditory sources were located in cortical regions around the auditory cortex. Thus, the differences observed in auditory EEG experiments would, according to our findings, have their origin in the intrinsic oscillatory mechanisms of the brain cortical sources related to speech perception.

The Influence of the Head Model Conductor on the Source Localization of Auditory Evoked Potentials

The accuracy of EEG source analysis reconstruction improves when a realistic head volume conductor is modeled. In this study we investigated how the progressively more complex head representations influence the spatial localization of auditory-evoked potentials (AEPs). Fourteen young-adult participants with normal hearing performed the AEP task. Individualized head models were obtained from structural MRI and diffusion-weighted imaging scans collected in a separate session. AEPs were elicited by 1 k Hz and 4 k Hz tone bursts during a passive-listening tetanizing paradigm. We compared the amplitude of the N1 and P2 components before and after 4 min of tetanic-stimulation with 1 k Hz sounds. Current density reconstruction values of both components were investigated in the primary auditory cortex and adjacent areas. Furthermore, we compared the signal topography and magnitude obtained with 10 different head models on the EEG forward solution. Starting from the simplest model (scalp, skull, brain), we investigated the influence of modeling the CSF, distinguishing between GM and WM conductors, and including anisotropic WM values. We localized the activity of AEPs within the primary auditory cortex, but not in adjacent areas. The inclusion of the CSF compartment had the strongest influence on the source reconstruction, whereas white matter anisotropy led to a smaller improvement. We conclude that individualized realistic head models provide the best solution for the forward solution when modeling the CSF conductor.

Diffusion Tensor Imaging Changes Do Not Affect Long-Term Neurodevelopment following Early Erythropoietin among Extremely Preterm Infants in the Preterm Erythropoietin Neuroprotection Trial

We aimed to evaluate diffusion tensor imaging (DTI) in infants born extremely preterm, to determine the effect of erythropoietin (Epo) on DTI, and to correlate DTI with neurodevelopmental outcomes at 2 years of age for infants in the Preterm Erythropoietin Neuroprotection (PENUT) Trial. Infants who underwent MRI with DTI at 36 weeks postmenstrual age were included. Neurodevelopmental outcomes were evaluated by Bayley Scales of Infant and Toddler Development (BSID-III). Generalized linear models were used to assess the association between DTI parameters and treatment group, and then with neurodevelopmental outcomes. A total of 101 placebo- and 93 Epo-treated infants underwent MRI. DTI white matter mean diffusivity (MD) was lower in placebo- compared to Epo-treated infants in the cingulate and occipital regions, and occipital white matter fractional isotropy (FA) was lower in infants born at 24-25 weeks vs. 26-27 weeks. These values were not associated with lower BSID-III scores. Certain decreases in clustering coefficients tended to have lower BSID-III scores. Consistent with the PENUT Trial findings, there was no effect on long-term neurodevelopment in Epo-treated infants even in the presence of microstructural changes identified by DTI.

devfOLD: a toolbox for designing age-specific fNIRS channel placement

Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source-detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research. Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD). Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups. Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups. Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.

The Association Between Hippocampal Volume and Level of Attention in Children and Adolescents

The hippocampus, which engages in the process of consolidating long-term memories and learning, shows active development during childhood and adolescence. The hippocampus also functionally influences attention. Based on the influence of hippocampal function on attention, it was expected that the volume of the hippocampus would be associated with the difference in attention during childhood and adolescence, in which the brain develops actively. Thus, this study examined the association between hippocampal volume and attention metrics measured by the continuous performance test (CPT) in 115 children and adolescents (mean age = 12.43 ± 3.0, 63 male and 52 female). In association studies with both auditory and visual attention, we found that the bilateral hippocampal volumes showed negative relationships with auditory omission errors. A smaller volume of the left hippocampus also led to a longer auditory response time. However, visual attention did not show any significant relationship with the hippocampal volume. These findings were consistent even after adjusting for the effects of the related covariates (e.g., age, insomnia, and depression). Taken together, this study suggested that the increase in hippocampal volume during childhood and adolescence was associated significantly with better auditory attention.

An Age-Specific Atlas for Delineation of White Matter Pathways in Children Aged 6-8 Years

Introduction

Diffusion MRI allows non-invasive assessment of white matter connectivity in typical development and of changes due to brain injury or pathology. Probabilistic white matter atlases allow diffusion metrics to be measured in specific white matter pathways, and are a critical component in spatial normalisation for group analysis. However, given the known developmental changes in white matter it may be sub-optimal to use an adult template when assessing data acquired from children.

Methods

By averaging subject-specific fibre bundles from 28 children aged from 6 to 8 years, we created an age-specific probabilistic white matter atlas for 12 major white matter tracts. Using both the newly developed and Johns Hopkins adult atlases, we compared the atlas to subject-specific fibre bundles in two independent validation cohorts, assessing accuracy in terms of volumetric overlap and measured diffusion metrics.

Results

Our age-specific atlas gave better overall performance than the adult atlas, achieving higher volumetric overlap with subject-specific fibre tracking and higher correlation of FA measurements with those measured from subject-specific fibre bundles. Specifically, estimates of FA values for cortico-spinal tract, uncinate fasciculus, forceps minor, cingulate gyrus part of the cingulum and anterior thalamic radiation were all significantly more accurate when estimated with an age-specific atlas.

Discussion

The age-specific atlas allows delineation of white matter tracts in children aged 6-8 years, without the need for tractography, more accurately than when normalising to an adult atlas. To our knowledge, this is the first publicly available probabilistic atlas of white matter tracts for this age group.