Faculty Bibliography

Altricial infants (i.e., requiring parental care for survival), such as humans and rats, form an attachment to their caregiver and receive the nurturing and protections needed for survival. Learning has a strong role in attachment, as is illustrated by strong attachment formed to non-biological caregivers of either sex. Here we summarize and integrate results from animal and human infant attachment research that highlights the important role of social buffering (social presence) of the stress response by the attachment figure and its effect on infant processing of threat and fear through modulation of the amygdala. Indeed, this work suggests the caregiver switches off amygdala function in rodents, although recent human research suggests a similar process in humans and nonhuman primates. This cross-species analysis helps provide insight and unique understanding of attachment and its role in the neurobiology of infant behavior within attachment.

BACKGROUND: Restricted and repetitive behaviors are defining features of autism spectrum disorder (ASD). Under revised diagnostic criteria for ASD, this behavioral domain now includes atypical responses to sensory stimuli. To date, little is known about the neural circuitry underlying these features of ASD early in life. METHODS: Longitudinal diffusion tensor imaging data were collected from 217 infants at high familial risk for ASD. Forty-four of these infants were diagnosed with ASD at age 2. Targeted cortical, cerebellar, and striatal white matter pathways were defined and measured at ages 6, 12, and 24 months. Dependent variables included the Repetitive Behavior Scale-Revised and the Sensory Experiences Questionnaire. RESULTS: Among children diagnosed with ASD, repetitive behaviors and sensory response patterns were strongly correlated, even when accounting for developmental level or social impairment. Longitudinal analyses indicated that the genu and cerebellar pathways were significantly associated with both repetitive behaviors and sensory responsiveness but not social deficits. At age 6 months, fractional anisotropy in the genu significantly predicted repetitive behaviors and sensory responsiveness at age 2. Cerebellar pathways significantly predicted later sensory responsiveness. Exploratory analyses suggested a possible disordinal interaction based on diagnostic status for the association between fractional anisotropy and repetitive behavior. CONCLUSIONS: Our findings suggest that restricted and repetitive behaviors contributing to a diagnosis of ASD at age 2 years are associated with structural properties of callosal and cerebellar white matter pathways measured during infancy and toddlerhood. We further identified that repetitive behaviors and unusual sensory response patterns co-occur and share common brain-behavior relationships. These results were strikingly specific given the absence of association between targeted pathways and social deficits.

The increased number of challenges for comparative evaluation of biomedical image analysis procedures clearly reflects a need for unbiased assessment of the state-of-the-art methodological advances. Moreover, the ultimate translation of novel image analysis procedures to the clinic requires rigorous validation and evaluation of alternative schemes, a task that is best outsourced to the international research community. We commonly see an increase of the number of metrics to be used in parallel, reflecting alternative ways to measure similarity. Since different measures come with different scales and distributions, these are often normalized or converted into an individual rank ordering, leaving the problem of combining the set of multiple rankings into a final score. Proposed solutions are averaging or accumulation of rankings, raising the question if different metrics are to be treated the same or if all metrics would be needed to assess closeness to truth. We address this issue with a data-driven method for automatic estimation of weights for a set of metrics based on unsupervised rank aggregation. Our method requires no normalization procedures and makes no assumptions about metric distributions. We explore the sensitivity of metrics to small changes in input data with an iterative perturbation scheme, to prioritize the contribution of the most robust metrics in the overall ranking. We show on real anatomical data that our weighting scheme can dramatically change the ranking

Recent advances in neuroimaging have offered a rich array of structural and functional markers to probe the organization of regional and large-scale brain networks. The current chapter provides a brief introduction into these techniques and overviews their contribution to the understanding of autism spectrum disorder (ASD), a neurodevelopmental condition associated with atypical social cognition, language function, and repetitive behaviors/interests. While it is generally recognized that ASD relates to structural and functional network anomalies, the extent and overall pattern of reported findings have been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD (e.g., 'early brain overgrowth hypothesis', 'amygdala theory', 'disconnectivity hypothesis'), none of these frameworks has been without controversy. Methodological sources of inconsistent results may include differences in subject inclusion criteria, variability in image processing, and analysis methodology. However, inconsistencies may also relate to high heterogeneity across the autism spectrum itself. It, therefore, remains to be investigated whether a consistent imaging phenotype that adequately describes the entire autism spectrum can, in fact, be established. On the other hand, as previous findings clearly emphasize the value of neuroimaging in identifying atypical brain morphology, function, and connectivity, they ultimately support its high potential to identify biologically and clinically relevant endophenotypes.

[This corrects the article DOI: 10.1371/journal.pone.0054463.].