Biology subjects

Puglia, M. H.

Publications and source records attributed to Puglia, M. H..

7 recordsLinked to original sources

bioRxiv2025

ALE Meta-Analysis Reveals Neural Substrates for the Impact of Prematurity on Executive Functioning in Children and Adults

Premature birth has known impacts on brain development, leading to sustained differences in cognitive function throughout the lifespan. Despite known deficits in executive functioning (EF) within individuals born premature, the extent to which neural engagement during executive functioning tasks differs between those born preterm and full-term is not fully understood. Additionally, it is unknown whether regions of differential engagement are the same in children and adults. This meta-analysis synthesizes fMRI results of activation differences between preterm and full-term subjects during executive functioning tasks in adult and child groups separately. Our results indicate that differences in neural engagement during EF tasks differ between pre-term (PT) and full term (FT) individuals in both age groups. Moreover, the regions affected contribute to well-known brain networks, including the fronto-striatal circuitry, the default mode network (DMN), and the salience network, all of which subserve broad EF capabilities. We found no differences between child and adult maps in a direct contrast, suggesting that effects of prematurity on executive functioning may persist from childhood into adulthood, although these findings should be interpreted in context of methodological limitations and potential confounding factors. This meta-analysis provides greater insight into the neural mechanisms behind EF disruption following premature birth. HighlightsO_LIDifferences in neural activation during executive function tasks exist in both children and adults with a history of premature birth. C_LIO_LIPT children show hyperactivity in fronto-striatal regions while PT adults show differential engagement of default mode network regions. C_LI

neuroscience↗

bioRxiv2025

Structural Determinants of Signal Speed: A Multimodal Investigation of Face Processing in Autism Spectrum Disorder

It has not previously been possible to investigate the fundamental relationship between axonal structure - which dictates action potential transmission - and human neuronal function in vivo. Here, we introduce a novel metric of axonal signal speed, estimated axonal latency (EAL), derived from the relationship between axonal diameter, myelination, and length measured via MRI. We validate EAL along two pathways of the face processing network by relating it to N170 latency, an electrophysiological marker of face processing speed measured via EEG. Our results show that EAL along these pathways predicts N170 latency specifically during face processing. Moreover, we demonstrate that individuals with and without autism rely upon different pathways, potentially providing a structural account for autism-related face processing differences. By establishing this relationship between EEG-based electrical function and MRI-based axonal microstructure, we provide a non-invasive, spatially detailed estimate of neuronal processing speed that can inform our understanding of brain function, development, and disorder. TeaserEstimated axonal latency is a non-invasive, spatially detailed measure of neuronal speed to inform brain function and disorder.

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bioRxiv2024

Parent attention-orienting behavior is associated with neural entropy in infancy

Parents play a significant role in directing infants attention to environmental stimuli via joint attention. We hypothesized that infants whose parents provide more bids for joint attention will display a more complex neural response when viewing social scenes. Sixty-one 8-month-old infants underwent electroencephalography (EEG) while viewing videos of joint-and parallel-play and participated in a parent-infant free play interaction. EEG data was analyzed using multiscale entropy, which quantifies moment-to-moment neural variability. Free play interactions were coded for parent alternating gaze, a behavioral mechanism for directing attention to environmental cues. We found a significant positive association between parent alternating gaze and neural entropy in frontal and central brain regions. These results suggest a relationship between parent behavior and infant neural mechanisms that regulate social attention, underlying the importance of parent cues in the formation of neural networks in infancy.

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bioRxiv2024

Infant neural sensitivity to affective touch is associated with maternal postpartum depression

Classic attachment theory emphasizes the sensitivity of the parent to perceive and appropriately respond to the infants cues. However, parent-child attachment is a dyadic interaction that is also dependent upon the sensitivity of the child to the early caregiving environment. Individual differences in infant sensitivity to parental cues is likely shaped by both the early caregiving environment as well as the infants neurobiology, such as perceptual sensitivity to social stimuli. Here, we investigated associations between maternal postpartum depression and infant neurological sensitivity to affective touch using brain signal entropy - a metric of the brains moment-to-moment variability related to signal processing. We recruited two independent samples of infants aged 0-5 months. In Sample 1 (n=79), we found increased levels of maternal postpartum depression were associated with diminished perceptual sensitivity - i.e. lower entropy - to affective tactile stimulation specifically within the primary somatosensory cortex. In Sample 2 (n=36), we replicated this finding and showed that this effect was not related to characteristics of the touch administered during the experiment. These results suggest that decreased affective touch early in life - a common consequence of postpartum depression - likely impacts the infants perceptual sensitivity to affective touch and ultimately the formation of experience-dependent neural networks that support the successful formation of attachment relationships.

neuroscience↗

bioRxiv2023

Epigenetic and neural correlates of selective social attention across adulthood

Social isolation is one of the strongest predictors of increased risk of mortality in older adulthood. The ability to form and maintain the social relationships that mitigate this risk is partially regulated by the oxytocinergic system and ones ability to attend to and process social information. We have previously shown that an epigenetic change to the DNA of the oxytocin receptor gene (OXTR methylation) affects the salience of social information in young adults. Little is known about how the oxytocinergic system ages and what effect this aging system has on social cognitive abilities throughout the lifespan. Here we explore age-related differences in the association between neural response during selective social attention and OXTR DNA methylation in young and older adults. We find that older adults activate diffuse areas of visual cortex and dorsolateral prefrontal cortex during selective social attention, consistent with the dedifferentiation and compensatory neural activation commonly reported in aging. We find a significant age-by-OXTR methylation interaction on neural response when attending to social stimuli in a complex display; young adults display a positive association between OXTR methylation and neural activation, replicating our prior finding that young adults with presumed diminished endogenous access to oxytocin recruit regions of the attentional cortex to a greater extent. This association does not hold for older adults. Instead, perceived social support interacts with OXTR methylation to influence neural response during selective social attention. These data suggest that environmental factors like social support moderate biological processes in aging and highlight the importance of a lifespan perspective for understanding associations between individual differences in the oxytocinergic system, neural function, and social behavior.

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bioRxiv2023

Functional brain connectivity during social attention predicts individual differences in social skill

Social attention involves selectively attending to and encoding socially relevant information. We investigated the neural systems underlying the wide range of variability in both social attention ability and social experience in a neurotypical sample. Participants performed a selective social attention task while undergoing fMRI and completed self-report measures of social functioning. Using connectome-based predictive modeling, we demonstrated that individual differences in whole-brain functional connectivity patterns during selective attention to faces predicted task performance. Individuals with more cerebellar-occipital connectivity performed better on the social attention task, suggesting more efficient social information processing. Then, we estimated latent communities of autistic and socially anxious traits using exploratory graph analysis to decompose heterogeneity in social functioning between individuals. Connectivity strength within the identified social attention network was associated with social skills, such that more temporal-parietal connectivity predicted fewer challenges with social communication and interaction. These findings demonstrate that individual differences in functional connectivity strength during a selective social attention task are related to varying levels of self-reported social skill.

neuroscience↗

bioRxiv2021

The Automated Preprocessing Pipe-Line for the Estimation of Scale-wise Entropy from EEG Data (APPLESEED): Development and validation for use in pediatric populations

It is increasingly understood that moment-to-moment brain signal variability - traditionally modeled out of analyses as mere "noise" - serves a valuable function role and captures properties of brain function related to development, cognitive processing, and psychopathology. Multiscale entropy (MSE) - a measure of signal irregularity across temporal scales - is an increasingly popular analytic technique in human neuroscience. MSE provides insight into the time-structure and (non)linearity of fluctuations in neural activity and network dynamics, capturing the brains moment-to-moment complexity as it operates on multiple time scales. MSE is emerging as a powerful predictor of developmental processes and outcomes. However, differences in data preprocessing and MSE computation make it challenging to compare results across studies. Here, we (1) provide an introduction to MSE for developmental researchers, (2) demonstrate the effect of preprocessing procedures on scale-wise entropy estimates, and (3) establish a standardized EEG preprocessing and entropy estimation pipeline that generates scale-wise entropy estimates that are reliable and capable of differentiating developmental stages and cognitive states. This novel pipeline - the Automated Preprocessing Pipe-Line for the Estimation of Scale-wise Entropy from EEG Data (APPLESEED) is fully automated, customizable, and freely available for download from https://github.com/mhpuglia/APPLESEED. The dataset used herein to develop and validate the pipeline is available for download from https://openneuro.org/datasets/ds003710.

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