FOXG1 variants can be associated with milder phenotypes than congenital Rett syndrome with unassisted walking and language development.

Since 2008, FOXG1 haploinsufficiency has been linked to a severe neurodevelopmental phenotype resembling Rett syndrome but with earlier onset. Most patients are unable to sit, walk, or speak. For years, FOXG1 sequencing was only prescribed in such severe cases, limiting insight into the full clinical spectrum associated with this gene. Next-generation sequencing (NGS) now enables unbiased diagnostics. Through the European Reference Network for Rare Malformation Syndromes, Intellectual and Other Neurodevelopmental Disorders, we gathered data from patients with heterozygous FOXG1 variants presenting a mild phenotype, defined as able to speak and walk independently. We also reviewed data from three previously reported patients meeting our criteria. We identified five new patients with pathogenic FOXG1 missense variants, primarily in the forkhead domain, showing varying nonspecific intellectual disability and developmental delay. These features are not typical of congenital Rett syndrome and were rarely associated with microcephaly and epilepsy. Our findings are consistent with a previous genotype-phenotype analysis by Mitter et al. suggesting the delineation of five different FOXG1 genotype groups. Milder phenotypes were associated with missense variants in the forkhead domain. This information may facilitate prognostic assessments in children carrying a FOXG1 variant and improve the interpretation of new variants identified with genomic sequencing.

Asymmetry in sleep spindles and motor outcome in infants with unilateral brain injury.

AIM: To determine whether interhemispheric difference in sleep spindles in infants with perinatal unilateral brain injury could link to a pathological network reorganization that underpins the development of unilateral cerebral palsy (CP). METHOD: This was a multicentre retrospective study of 40 infants (19 females, 21 males) with unilateral brain injury. Sleep spindles were detected and quantified with an automated algorithm from electroencephalograph records performed at 2 months to 5 months of age. The clinical outcomes after 18 months were compared to spindle power asymmetry (SPA) between hemispheres in different brain regions. RESULTS: We found a significantly increased SPA in infants who later developed unilateral CP (n=13, with the most robust interhemispheric difference seen in the central spindles. The best individual-level prediction of unilateral CP was seen in the centro-occipital spindles with an overall accuracy of 93%. An empiric cut-off level for SPA at 0.65 gave a positive predictive value of 100% and a negative predictive value of 93% for later development of unilateral CP. INTERPRETATION: Our data suggest that automated analysis of interhemispheric SPA provides a potential biomarker of unilateral CP at a very early age. This holds promise for guiding the early diagnostic process in infants with a perinatally identified brain injury. WHAT THIS PAPER ADDS: Unilateral perinatal brain injury may affect the development of electroencephalogram (EEG) sleep spindles. Interhemispheric asymmetry in sleep spindles can be quantified with automated EEG analysis. Spindle power asymmetry can be a potential biomarker of unilateral cerebral palsy.

Expanding the Spectrum of Oculocutaneous Albinism: Does Isolated Foveal Hypoplasia Really Exist?

Oculocutaneous albinism is an autosomal recessive disorder characterized by the presence of typical ocular features, such as foveal hypoplasia, iris translucency, hypopigmented fundus oculi and reduced pigmentation of skin and hair. Albino patients can show significant clinical variability; some individuals can present with only mild depigmentation and subtle ocular changes. Here, we provide a retrospective review of the standardized clinical charts of patients firstly addressed for evaluation of foveal hypoplasia and slightly subnormal visual acuity, whose diagnosis of albinism was achieved only after extensive phenotypic and genotypic characterization. Our report corroborates the pathogenicity of the two common TYR polymorphisms p.(Arg402Gln) and p.(Ser192Tyr) when both are located in trans with a pathogenic TYR variant and aims to expand the phenotypic spectrum of albinism in order to increase the detection rate of the albino phenotype. Our data also suggest that isolated foveal hypoplasia should be considered a clinical sign instead of a definitive diagnosis of an isolated clinical entity, and we recommend deep phenotypic and molecular characterization in such patients to achieve a proper diagnosis.

Automated pose estimation captures key aspects of General Movements at eight to 17 weeks from conventional videos.

AIM: General movement assessment requires substantial expertise for accurate visual interpretation. Our aim was to evaluate an automated pose estimation method, using conventional video records, to see if it could capture infant movements using objective biomarkers. METHODS: We selected archived videos from 21 infants aged eight to 17 weeks who had taken part in studies at the IRCCS Fondazione Stella Maris (Italy), from 2011 to 2017. Of these, 14 presented with typical low-risk movements, while seven presented with atypical movements and were later diagnosed with cerebral palsy. Skeleton videos were produced using a computational pose estimation model adapted for infants and these were blindly assessed to see whether they contained the information needed for classification by human experts. Movements of skeletal key points were analysed using kinematic metrics to provide a biomarker to distinguish between groups. RESULTS: The visual assessments of the skeleton videos were very accurate, with Cohen's K of 0.90 when compared with the classification of conventional videos. Quantitative analysis showed that arm movements were more variable in infants with typical movements. CONCLUSION: It was possible to extract automated estimation of movement patterns from conventional video records and convert them to skeleton footage. This could allow quantitative analysis of existing footage.

Early Intervention to Improve Sucking in Preterm Newborns: A Systematic Review of Quantitative Studies.

BACKGROUND: Premature birth is associated with feeding difficulties due to inadequate coordination of sucking, swallowing, and breathing. Nonnutritive sucking (NNS) and oral stimulation interventions may be effective for oral feeding promotion, but the mechanisms of the intervention effects need further clarifications. PURPOSE: We reviewed preterm infant intervention studies with quantitative outcomes of sucking performance to summarize the evidence of the effect of interventions on specific components of sucking. METHODS: PubMed, CINAHL, MEDLINE, EMBASE, and PSYCOLIST databases were searched for English language publications through August 2017. Studies were selected if they involved preterm infants, tested experimental interventions to improve sucking or oral feeding skills, and included outcome as an objective measure of sucking performance. Specific Medical Subject Headings (MeSH) terms were utilized. RESULTS: Nineteen studies were included in this review: 15 randomized, 1 quasi-randomized, and 3 crossover randomized controlled trials. Intervention types were grouped into 6 categories (i) NNS, (ii) NNS with auditory reinforcement, (iii) sensorimotor stimulation, (iv) oral support, (v) combined training, and (vi) nutritive sucking. Efficiency parameters were positively influenced by most types of interventions, though appear to be less affected by trainings based on NNS alone. IMPLICATIONS FOR PRACTICE: These findings may be useful in the clinical care of infants requiring support to achieve efficient sucking skills through NNS and oral stimulation interventions. IMPLICATIONS FOR RESEARCH: Further studies including quantitative measures of sucking performance outcome measures are needed in order to best understand the needs and provide more tailored interventions to preterm infants.

Brain representation of action observation in human infants.

Imitative learning has long been established as extremely important for early development. However, neural mechanisms involved in early imitative behaviours are still areas of active research. Neurophysiological and brain-imaging studies have been recently performed that provide initial evidence of brain activation associated with action observation in the first months of life. In this review we examine all studies exploring the effects of action observation on brain function assessed by means of non-invasive brain-mapping techniques. Seventeen papers were selected as a result of our literature search. The strongest evidence for a neural signature of action observation comes from studies exploring the desynchronization of the µ-rhythm, which was reported for both occluded and visible goal-directed grasp, and was correlated with the totality of the infant's own action experience. The effects of action observation were reported on event-related potentials (ERPs) or near infrared spectroscopy. Taken together, these studies suggest that, in early infancy, a direct visual-motor matching process is already detectable as early as 6 months, suggesting a matching between action perception and execution already in infancy. If confirmed by future studies, these findings will shed light on the mechanisms of early motor development and imitation, and will be key to informing novel rehabilitation strategies in infants with congenital brain damage.

Corrigendum: Building an open source classifier for the neonatal EEG background: a systematic feature-based approach from expert scoring to clinical visualization.

[This corrects the article DOI: 10.3389/fnhum.2021.675154.].

The amplitude of fNIRS hemodynamic response in the visual cortex unmasks autistic traits in typically developing children.

Autistic traits represent a continuum dimension across the population, with autism spectrum disorder (ASD) being the extreme end of the distribution. Accumulating evidence shows that neuroanatomical and neurofunctional profiles described in relatives of ASD individuals reflect an intermediate neurobiological pattern between the clinical population and healthy controls. This suggests that quantitative measures detecting autistic traits in the general population represent potential candidates for the development of biomarkers identifying early pathophysiological processes associated with ASD. Functional near-infrared spectroscopy (fNIRS) has been extensively employed to investigate neural development and function. In contrast, the potential of fNIRS to define reliable biomarkers of brain activity has been barely explored. Features of non-invasiveness, portability, ease of administration, and low-operating costs make fNIRS a suitable instrument to assess brain function for differential diagnosis, follow-up, analysis of treatment outcomes, and personalized medicine in several neurological conditions. Here, we introduce a novel standardized procedure with high entertaining value to measure hemodynamic responses (HDR) in the occipital cortex of adult subjects and children. We found that the variability of evoked HDR correlates with the autistic traits of children, assessed by the Autism-Spectrum Quotient. Interestingly, HDR amplitude was especially linked to social and communication features, representing the core symptoms of ASD. These findings establish a quick and easy strategy for measuring visually-evoked cortical activity with fNIRS that optimize the compliance of young subjects, setting the background for testing the diagnostic value of fNIRS visual measurements in the ASD clinical population.

An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.

BACKGROUND: Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions and outcome predictions. EEG's larger-scale implementation is, however, hindered by the shortage of expertise needed for the interpretation of spontaneous cortical activity, the EEG background. We developed an automated algorithm that transforms EEG recordings to quantified interpretations of EEG background and provides simple intuitive visualisations in patient monitors. METHODS: In this method-development and proof-of-concept study, we collected visually classified EEGs from infants recovering from birth asphyxia or stroke. We used unsupervised learning methods to explore latent EEG characteristics, which guided the supervised training of a deep learning-based classifier. We assessed the classifier performance using cross-validation and an external validation dataset. We constructed a novel measure of cortical function, brain state of the newborn (BSN), from the novel EEG background classifier and a previously published sleep-state classifier. We estimated clinical utility of the BSN by identification of two key items in newborn brain monitoring, the onset of continuous cortical activity and sleep-wake cycling, compared with the visual interpretation of the raw EEG signal and the amplitude-integrated (aEEG) trend. FINDINGS: We collected 2561 h of EEG from 39 infants (gestational age 35·0-42·1 weeks; postnatal age 0-7 days). The external validation dataset included 105 h of EEG from 31 full-term infants. The overall accuracy of the EEG background classifier was 92% in the whole cohort (95% CI 91-96; range 85-100 for individual infants). BSN trend values were closely related to the onset of continuous EEG activity or sleep-wake cycling, and BSN levels showed robust difference between aEEG categories. The temporal evolution of the BSN trends showed early diverging trajectories in infants with severely abnormal outcomes. INTERPRETATION: The BSN trend can be implemented in bedside patient monitors as an EEG interpretation that is intuitive, transparent, and clinically explainable. A quantitative trend measure of brain function might harmonise practices across medical centres, enable wider use of brain monitoring in neurocritical care, and might facilitate clinical intervention trials. FUNDING: European Training Networks Funding Scheme, the Academy of Finland, Finnish Pediatric Foundation (Lastentautiensäätiö), Aivosäätiö, Sigrid Juselius Foundation, HUS Children's Hospital, HUS Diagnostic Center, National Health and Medical Research Council of Australia.

Looking for "fNIRS Signature" in Autism Spectrum: A Systematic Review Starting From Preschoolers.

Accumulating evidence suggests that functional Near-Infrared Spectroscopy (fNIRS) can provide an essential bridge between our current understanding of neural circuit organization and cortical activity in the developing brain. Indeed, fNIRS allows studying brain functions through the measurement of neurovascular coupling that links neural activity to subsequent changes in cerebral blood flow and hemoglobin oxygenation levels. While the literature offers a multitude of fNIRS applications to typical development, only recently this tool has been extended to the study of neurodevelopmental disorders (NDDs). The exponential rise of scientific publications on this topic during the last years reflects the interest to identify a "fNIRS signature" as a biomarker of high translational value to support both early clinical diagnosis and treatment outcome. The purpose of this systematic review is to describe the updating clinical applications of fNIRS in NDDs, with a specific focus on preschool population. Starting from this rationale, a systematic search was conducted for relevant studies in different scientific databases (Pubmed, Scopus, and Web of Science) resulting in 13 published articles. In these studies, fNIRS was applied in individuals with Autism Spectrum Disorder (ASD) or infants at high risk of developing ASD. Both functional connectivity in resting-state conditions and task-evoked brain activation using multiple experimental paradigms were used in the selected investigations, suggesting that fNIRS might be considered a promising method for identifying early quantitative biomarkers in the autism field.

Towards multimodal brain monitoring in asphyxiated newborns with amplitude-integrated EEG and simultaneous somatosensory evoked potentials.

BACKGROUND: Somatosensory evoked potentials (SEPs) offer an additional bedside tool for outcome prediction after perinatal asphyxia. AIMS: To assess the reliability of SEPs recorded with bifrontoparietal amplitude-integrated electroencephalography (aEEG) brain monitoring setup for outcome prediction in asphyxiated newborns undergoing therapeutic hypothermia. STUDY DESIGN: Retrospective observational single-center study. SUBJECTS: 27 consecutive asphyxiated full- or near-term newborns (25 under hypothermia) that underwent median nerve aEEG-SEPs as part of their clinical evaluation at the neonatal intensive care unit of Helsinki University Hospital. OUTCOME MEASURES: aEEG-SEP classification (present, absent or unreliable) was compared to classification of SEPs recorded with a full EEG montage (EEG-SEP), and outcome determined from medical records at approximately 12-months-age. Unfavorable outcome included death, cerebral palsy, or severe epilepsy. RESULTS: The aEEG-SEP and EEG-SEP classifications were concordant in 21 of the 22 newborns with both recordings available. All five newborns with bilaterally absent aEEG-SEPs had absent EEG-SEPs and the four with outcome information available had an unfavorable outcome (one was lost to follow-up). Of the newborns with aEEG-SEPs present, all with follow-up exams available had bilaterally present EEG-SEPs and a favorable outcome (one was lost to follow-up). One newborn with unilaterally absent aEEG-SEP at 25 h of age had bilaterally present EEG-SEPs on the next day, and a favorable outcome. CONCLUSIONS: aEEG-SEPs recorded during therapeutic hypothermia on the first postnatal days are reliable for assessing brain injury severity. Adding SEP into routine aEEG brain monitoring offers an additional tool for very early outcome prediction after birth asphyxia.

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization.

Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous review of the spontaneous cortical activity, i.e., the electroencephalograph (EEG) background activity. This needs development of bedside methods for an automated assessment of the EEG background activity. In this paper, we present development of the key components of a neonatal EEG background classifier, starting from the visual background scoring to classifier design, and finally to possible bedside visualization of the classifier results. A dataset with 13,200 5-minute EEG epochs (8-16 channels) from 27 infants with birth asphyxia was used for classifier training after scoring by two independent experts. We tested three classifier designs based on 98 computational features, and their performance was assessed with respect to scoring system, pre- and post-processing of labels and outputs, choice of channels, and visualization in monitor displays. The optimal solution achieved an overall classification accuracy of 97% with a range across subjects of 81-100%. We identified a set of 23 features that make the classifier highly robust to the choice of channels and missing data due to artefact rejection. Our results showed that an automated bedside classifier of EEG background is achievable, and we publish the full classifier algorithm to allow further clinical replication and validation studies.

Neonatal neuroimaging and neurophysiology predict infantile onset epilepsy after perinatal hypoxic ischemic encephalopathy.

PURPOSE: To evaluate the accuracy of hypoxic ischemic encephalopathy (HIE) grade, and neonatal neurophysiological and neuroimaging measures for predicting development of infantile spasms syndrome (IS) or other postneonatal, infantile onset epilepsy after perinatal HIE. METHODS: We examined a population-based cohort of 92 consequent infants with moderate-to-severe HIE. The HIE grade and neonatal neuroimaging (MRI) and neurophysiology (EEG and somatosensory evoked potentials, SEPs) findings were compared to the development of IS or other epilepsy within the first year of life. RESULTS: Out of 74 surviving infants with follow-up information, five developed IS and one developed a focal onset epilepsy. They all had recovered from severe HIE. All survivors with inactive neonatal EEG (recorded within the first few postnatal days, n = 4) or the most severe type of brain injury in MRI (n = 3) developed epilepsy (positive predictive value, PPV 100 %). Bilaterally absent SEPs had 100 % sensitivity and 75 % PPV for epilepsy. A combination of absent SEPs and a poor MRI finding (combined deep and cortical gray matter injury) resulted in higher PPV (86 %) without lowering sensitivity (100 %). Follow-up EEGs showed recurrent epileptiform activity already between 1- and 2-months age in those that developed epilepsy, distinguishing them from those surviving without epilepsy. CONCLUSIONS: Poor neonatal neuroimaging and neurophysiological findings provide accurate prediction for development of infantile onset epilepsy after HIE. Of the neonates with severe HIE, the ones with severe neonatal MRI and neurophysiological abnormalities need frequent follow-up, including repeated EEGs, for early detection of IS.

Measuring Cot-Side the Effects of Parenteral Nutrition on Preterm Cortical Function.

Early nutritional compromise after preterm birth is shown to affect long-term neurodevelopment, however, there has been a lack of early functional measures of nutritional effects. Recent progress in computational electroencephalography (EEG) analysis has provided means to measure the early maturation of cortical activity. Our study aimed to explore whether computational metrics of early sequential EEG recordings could reflect early nutritional care measured by energy and macronutrient intake in the first week of life. A higher energy or macronutrient intake was assumed to associate with improved development of the cortical activity. We analyzed multichannel EEG recorded at 32 weeks (32.4 ± 0.7) and 36 weeks (36.6 ± 0.9) of postmenstrual age in a cohort of 28 preterm infants born before 32 weeks of postmenstrual age (range: 24.3-32 weeks). We computed several quantitative EEG measures from epochs of quiet sleep (QS): (i) spectral power; (ii) continuity; (iii) interhemispheric synchrony, as well as (iv) the recently developed estimate of maturational age. Parenteral nutritional intake from day 1 to day 7 was monitored and clinical factors collected. Lower calories and carbohydrates were found to correlate with a higher reduction of spectral amplitude in the delta band. Lower protein amount associated with higher discontinuity. Both higher proteins and lipids intake correlated with a more developmental increase in interhemispheric synchrony as well as with better progress in the estimate of EEG maturational age (EMA). Our study shows that early nutritional balance after preterm birth may influence subsequent maturation of brain activity in a way that can be observed with several intuitively reasoned and transparent computational EEG metrics. Such measures could become early functional biomarkers that hold promise for benchmarking in the future development of therapeutic interventions.

Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors.

Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.

Cerebral Palsy: Early Markers of Clinical Phenotype and Functional Outcome.

The Prechtl General Movement Assessment (GMA) has become a cornerstone assessment in early identification of cerebral palsy (CP), particularly during the fidgety movement period at 3-5 months of age. Additionally, assessment of motor repertoire, such as antigravity movements and postural patterns, which form the Motor Optimality Score (MOS), may provide insight into an infant's later motor function. This study aimed to identify early specific markers for ambulation, gross motor function (using the Gross Motor Function Classification System, GMFCS), topography (unilateral, bilateral), and type (spastic, dyskinetic, ataxic, and hypotonic) of CP in a large worldwide cohort of 468 infants. We found that 95% of children with CP did not have fidgety movements, with 100% having non-optimal MOS. GMFCS level was strongly correlated to MOS. An MOS > 14 was most likely associated with GMFCS outcomes I or II, whereas GMFCS outcomes IV or V were hardly ever associated with an MOS > 8. A number of different movement patterns were associated with more severe functional impairment (GMFCS III-V), including atypical arching and persistent cramped-synchronized movements. Asymmetrical segmental movements were strongly associated with unilateral CP. Circular arm movements were associated with dyskinetic CP. This study demonstrated that use of the MOS contributes to understanding later CP prognosis, including early markers for type and severity.

Evaluation of SEPs in asphyxiated newborns using a 4-electrode aEEG brain monitoring set-up.

OBJECTIVE: To evaluate the reliability of recording cortical somatosensory evoked potentials (SEPs) in asphyxiated newborns using the 4-electrode setup applied in routine long-term amplitude-integrated EEG (aEEG) brain monitoring and to assess the number of averages needed for reliably detecting the cortical responses. METHODS: We evaluated median nerve SEPs in 50 asphyxiated full-term newborns. The SEP interpretation (present or absent) from the original recordings with 21-electrodes and approximately 600 trials served as the reference. This was compared to SEP classification (absent, present, or unreliable) based on a reduced (300 or 150) number of averages, and to classification based on only four electrodes (F3, P3, F4, P4). RESULTS: Compared to the original classification, cortical SEPs were uniformly interpreted as present or absent in all 50 newborns with the 4-electrode setup and 600 averages. Reducing number of averages to 300 still resulted in correct SEP interpretation in 49/50 newborns with 21-electrode setup, and 46/50 newborns with 4-electrode setup. CONCLUSIONS: Evaluation of early cortical neonatal SEPs is reliable from the 4-electrode setup commonly used in aEEG monitoring. SEP is discernible in most newborns with 300 averages. SIGNIFICANCE: Adding SEP into routine aEEG monitoring offers an additional tool for early neonatal neurophysiological evaluation.

Evoked potentials recorded during routine EEG predict outcome after perinatal asphyxia.

OBJECTIVE: To evaluate the added value of somatosensory (SEPs) and visual evoked potentials (VEPs) recorded simultaneously with routine EEG in early outcome prediction of newborns with hypoxic-ischemic encephalopathy under modern intensive care. METHODS: We simultaneously recorded multichannel EEG, median nerve SEPs, and flash VEPs during the first few postnatal days in 50 term newborns with hypoxic-ischemic encephalopathy. EEG background was scored into five grades and the worst two grades were considered to indicate poor cerebral recovery. Evoked potentials were classified as absent or present. Clinical outcome was determined from the medical records at a median age of 21months. Unfavorable outcome included cerebral palsy, severe mental retardation, severe epilepsy, or death. RESULTS: The accuracy of outcome prediction was 98% with SEPs compared to 90% with EEG. EEG alone always predicted unfavorable outcome when it was inactive (n=9), and favorable outcome when it was normal or only mildly abnormal (n=17). However, newborns with moderate or severe EEG background abnormality could have either favorable or unfavorable outcome, which was correctly predicted by SEP in all but one newborn (accuracy in this subgroup 96%). Absent VEPs were always associated with an inactive EEG, and an unfavorable outcome. However, presence of VEPs did not guarantee a favorable outcome. CONCLUSIONS: SEPs accurately predict clinical outcomes in newborns with hypoxic-ischemic encephalopathy and improve the EEG-based prediction particularly in those newborns with severely or moderately abnormal EEG findings. SIGNIFICANCE: SEPs should be added to routine EEG recordings for early bedside assessment of newborns with hypoxic-ischemic encephalopathy.

The first 1000 days of the autistic brain: a systematic review of diffusion imaging studies.

There is overwhelming evidence that autism spectrum disorder (ASD) is related to altered brain connectivity. While these alterations are starting to be well characterized in subjects where the clinical picture is fully expressed, less is known on their earlier developmental course. In the present study we systematically reviewed current knowledge on structural connectivity in ASD infants and toddlers. We searched PubMed and Medline databases for all English language papers, published from year 2000, exploring structural connectivity in populations of infants and toddlers whose mean age was below 30 months. Of the 264 papers extracted, four were found to be eligible and were reviewed. Three of the four selected studies reported higher fractional anisotropy values in subjects with ASD compared to controls within commissural fibers, projections fibers, and association fibers, suggesting brain hyper-connectivity in the earliest phases of the disorder. Similar conclusions emerged from the other diffusion parameters assessed. These findings are reversed to what is generally found in studies exploring older patient groups and suggest a developmental course characterized by a shift toward hypo-connectivity starting at a time between two and four years of age.