Caroline Whyatt

toward Precision Psychiatry: statistical Platform for the Personalized Characterization of Natural Behaviors

There is a critical need for new analytics to personalize behavioral data analysis across different fields, including kinesiology, sports science, and behavioral neuroscience. Specifically, to better translate and integrate basic research into patient care, we need to radically transform the methods by which we describe and interpret movement data. Here, we show that hidden in the “noise,” smoothed out by averaging movement kinematics data, lies a wealth of information that selectively differentiates neurological and mental disorders such as Parkinson’s disease, deafferentation, autism spectrum disorders, and schizophrenia from typically developing and typically aging controls. In this report, we quantify the continuous forward-and-back pointing movements of participants from a large heterogeneous cohort comprising typical and pathological cases. We empirically estimate the statistical parameters of the probability distributions for each individual in the cohort and report the parameter ranges for each clinical group after characterization of healthy developing and aging groups. We coin this newly proposed platform for individualized behavioral analyses “precision phenotyping” to distinguish it from the type of observational–behavioral phenotyping prevalent in clinical studies or from the “one-size-fits-all” model in basic movement science. We further propose the use of this platform as a unifying statistical framework to characterize brain disorders of known etiology in relation to idiopathic neurological disorders with similar phenotypic manifestations.

Characterization of the Statistical Signatures of Micro-Movements Underlying Natural Gait Patterns in Children with Phelan McDermid Syndrome: Towards Precision-Phenotyping of Behavior in ASD

Background: There is a critical need for precision phenotyping across neurodevelopmental disorders, especially in individuals who receive a clinical diagnosis of autism spectrum disorder (ASD). Phelan-McDermid deletion syndrome (PMS) is one such example, as it has a high penetrance of ASD. At present, no biometric characterization of the behavioral phenotype within PMS exists. Methods: We introduce a data-type and statistical framework that permits the personalized profiling of naturalistic behaviors. Walking patterns were assessed in 30 participants (16 PMS, 3 idiopathic-ASD and 11 age- and sex-matched controls). Each individuals micro-movement signatures were recorded at 240 Hz. We empirically estimated the parameters of the continuous Gamma family of probability distributions and calculated their ranges. These estimated stochastic signatures were then mapped on the Gamma plane to obtain several statistical indexes for each child. To help visualize complex patterns across the cohort, we introduce new tools that enable the assessment of connectivity and modularity indexes across the peripheral network of rotational joints. Results: Typical walking signatures are absent in all children with PMS as well as in the children with idiopathic-ASD (iASD). Underlying these patterns are atypical leg rotational acceleration signatures that render participants with PMS unstable with rotations that are much faster than controls. The median values of the estimated Gamma parameters serve as a cutoff to automatically separate children with PMS 5–7 years old from adolescents with PMS 12–16 years old, the former displaying more randomness and larger noise. The fluctuations in the arms motions during the walking also have atypical statistics that separate males from females in PMS and show higher rates of noise accumulation in idiopathic ASD (iASD) children. Despite high heterogeneity, all iASD children have excess noise, a narrow range of probability-distribution shapes across the body joints and a distinct joint network connectivity pattern. Both PMS and iASD have systemic issues with noise in micro-motions across the body with specific signatures for each child that, as a cohort, selectively deviates from controls. Conclusions: We provide a new methodology for precision behavioral phenotyping with the potential to use micro-movement output noise as a natural classifier of neurodevelopmental disorders of known etiology. This approach may help us better understand idiopathic neurodevelopmental disorders and personalize the assessments of natural movements in these populations.

Stochastic Signatures of Involuntary Head Micro-movements Can Be Used to Classify Females of ABIDE into Different Subtypes of Neurodevelopmental Disorders

Background: The approximate 5:1 male to female ratio in clinical detection of Autism Spectrum Disorder (ASD) prevents research from characterizing the female phenotype. Current open access repositories [such as those in the Autism Brain Imaging Data Exchange (ABIDE I-II)] contain large numbers of females to help begin providing a new characterization of females on the autistic spectrum. Here we introduce new methods to integrate data in a scale-free manner from continuous biophysical rhythms of the nervous systems and discrete (ordinal) observational scores. Methods: New data-types derived from image-based involuntary head motions and personalized statistical platform were combined with a data-driven approach to unveil sub-groups within the female cohort. Further, to help refine the clinical DSM-based ASD vs. Aspergers Syndrome (AS) criteria, distributional analyses of ordinal score data from Autism Diagnostic Observation Schedule (ADOS)-based criteria were used on both the female and male phenotypes. Results: Separate clusters were automatically uncovered in the female cohort corresponding to differential levels of severity. Specifically, the AS-subgroup emerged as the most severely affected with an excess level of noise and randomness in the involuntary head micro-movements. Extending the methods to characterize males of ABIDE revealed ASD-males to be more affected than AS-males. A thorough study of ADOS-2 and ADOS-G scores provided confounding results regarding the ASD vs. AS male comparison, whereby the ADOS-2 rendered the AS-phenotype worse off than the ASD-phenotype, while ADOS-G flipped the results. Females with AS scored higher on severity than ASD-females in all ADOS test versions and their scores provided evidence for significantly higher severity than males. However, the statistical landscapes underlying female and male scores appeared disparate. As such, further interpretation of the ADOS data seems problematic, rather suggesting the critical need to develop an entirely new metric to measure social behavior in females. Conclusions: According to the outcome of objective, data-driven analyses and subjective clinical observation, these results support the proposition that the female phenotype is different. Consequently the “social behavioral male ruler” will continue to mask the female autistic phenotype. It is our proposition that new observational behavioral tests ought to contain normative scales, be statistically sound and combined with objective data-driven approaches to better characterize the females across the human lifespan.

Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control

The current rise of neurodevelopmental disorders poses a critical need to detect risk early in order to rapidly intervene. One of the tools pediatricians use to track development is the standard growth chart. The growth charts are somewhat limited in predicting possible neurodevelopmental issues. They rely on linear models and assumptions of normality for physical growth data – obscuring key statistical information about possible neurodevelopmental risk in growth data that actually has accelerated, non-linear rates-of-change and variability encompassing skewed distributions. Here, we use new analytics to profile growth data from 36 newborn babies that were tracked longitudinally for 5 months. By switching to incremental (velocity-based) growth charts and combining these dynamic changes with underlying fluctuations in motor performance – as the transition from spontaneous random noise to a systematic signal – we demonstrate a method to detect very early stunting in the development of voluntary neuromotor control and to flag risk of neurodevelopmental derail.

Autism Research: An Objective Quantitative Review of Progress and Focus Between 1994 and 2015

The nosology and epidemiology of Autism has undergone transformation following consolidation of once disparate disorders under the umbrella diagnostic, autism spectrum disorders. Despite this re-conceptualization, research initiatives, including the NIMH’s Research Domain Criteria and Precision Medicine, highlight the need to bridge psychiatric and psychological classification methodologies with biomedical techniques. Combining traditional bibliometric co-word techniques, with tenets of graph theory and network analysis, this article provides an objective thematic review of research between 1994 and 2015 to consider evolution and focus. Results illustrate growth in Autism research since 2006, with nascent focus on physiology. However, modularity and citation analytics demonstrate dominance of subjective psychological or psychiatric constructs, which may impede progress in the identification and stratification of biomarkers as endorsed by new research initiatives.

ADOS: The Physiology Approach to Assess Social Skills and Communication in Autism Spectrum Disorder

This paper examines evidence for a disorder of the intrinsic motive processes of the purposeful self in autism spectrum disorder (ASD), which leads to weakening of shared experience in early childhood. Changed motor and affective regulations that identify autism are traced to faults in neurogenesis in the core brainstem systems of the fetus. These fundamental systems have evolved to serve development of sensory guidance for motor activity and affective regulation of projects of thought and action, including communication of intentions and feelings with other human selves. Affective neuroscience describes subcortical organs in mammals that are responsible for the coherence of a primary conscious self-as-agent, with emotions that communicate feelings for selective sociability with other individuals. In humans this affective consciousness is adapted as the foundation for active engagement of an infant with a world of objects and people by expressions under the control of shared rhythms of an ‘intrinsic motive pulse’. We give primary importance to the disorder in autism of the accuracy of timing in this resonant central nervous system, responsible for coordination of movement with companions. We relate this understanding of the disorder to problems in the monitoring of prospective regulation of actions of the conscious Self by a body-related affective valence, which affects the arousal of personal satisfaction of purposes or anxiety at their failure, and engagement in affectionate or antagonistic relations. This leads to evaluation of participation in movements with shared feelings for therapy and teaching to helping the socio-emotional development and learning of children with autism, as well as advice for lifetime care. In autism, the essential embodiment of early childhood experience for growth of knowledge, skill and collaborative social understanding appears weakened by a sensorimotor deficit in motivation and its affective control. This has life-long developmental consequences, affecting the intersubjective responses of family, and then cooperative attentions of companions and teachers in the community. Mis-coordination of movements leads to frustration, distress, and anxiety, creating social withdrawal and avoidance, or over-compensations expressed as increased arousal and hyper-activity. Indeed, we propose that disabilities in cognitive intelligence and language are secondary to weakness in prospective control of movements with affective appraisal of anticipated experiences. We identify the origin of these symptoms in disorders of brainstem mechanisms that develop in the late embryo stage and that are essential for motor and affective regulations, as well as autonomic processing. In particular, data indicate an anatomical and functional disruption of the inferior olive, associated with control of motor timing by the cerebellum, and abnormal development of the neighbouring nucleus ambiguus, involved in expressions of social engagement and speech. These nuclei appear to be critical components of the core neuropsychological system that develops abnormally to produce the varied autistic spectrum disorders. We draw attention to the limitations of research methods in neuroscience and psychology that seek to identify a primary cognitive, information-processing and neocortically mediated disorder by testing the response of the individual in artificial situations. New research using micro-kinesic descriptive methods clarifies motor deficits that characterize autism. Furthermore, extensive imaging of brain activities supports a philosophical psychology of embodiment that elucidates how confusion in unconscious prospective control of actions from fetal stages impairs the child’s developing subjective agency. Finally, we offer information on movement-based therapies that can help to facilitate learning, self-regulation, and pleasure in social interaction for individuals with ASD.