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1The advent of open access to genomic data offers new opportunities to revisit old clinical debates while approaching them from a different angle. We examine anew the question of whether psychiatric and neurological disorders are... more
1The advent of open access to genomic data offers new opportunities to revisit old clinical debates while approaching them from a different angle. We examine anew the question of whether psychiatric and neurological disorders are different from each other by assessing the pool of genes associated with disorders that are understood as psychiatric or as neurological. We do so in the context of transcriptome data tracked as human embryonic stem cells differentiate and become neurons. Building upon probabilistic layers of increasing complexity, we describe the dynamics and stochastic trajectories of the full transcriptome and the embedded genes associated with psychiatric and/or neurological disorders. From marginal distributions of a gene’s expression across hundreds of cells, to joint interactions taken globally to determine degree of pairwise dependency, to networks derived from probabilistic graphs along maximal spanning trees, we have discovered two fundamentally different classes ...
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Neurodevelopmental disorders are on the rise worldwide, with diagnoses that detect derailment from typical milestones by 3-4.5 years of age. By then, the circuitry in the brain has already reached some level of maturation that inevitably... more
Neurodevelopmental disorders are on the rise worldwide, with diagnoses that detect derailment from typical milestones by 3-4.5 years of age. By then, the circuitry in the brain has already reached some level of maturation that inevitably takes neurodevelopment through a different course. There is a critical need then to develop analytical methods that detect problems much earlier and identify targets for treatment. We integrate data from multiple sources, including neonatal auditory brainstem responses (ABR), clinical criteria detecting autism years later in those neonates, and similar ABR information for young infants and children who also received a diagnosis of autism spectrum disorders, to produce the earliest known digital screening biomarker to flag neurodevelopmental derailment in neonates. This work also defines concrete targets for treatment and offers a new statistical approach to aid in guiding a personalized course of maturation in line with the highly nonlinear, acceler...
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The recent revolution in wearable sensors poses new problems to develop analytics that handle large volumes of rapidly accumulating data from continuous recordings. We develop new analytical techniques to handle big data to process... more
The recent revolution in wearable sensors poses new problems to develop analytics that handle large volumes of rapidly accumulating data from continuous recordings. We develop new analytical techniques to handle big data to process various physiological signals such as motion and temperature output from wearable sensor technology. Subjects performed tasks including dancing, walking, sleeping, performing decision-making tasks, and tasks in response to perceptual stimuli, while wearing sensors on various parts of the body. Sensors that register motion and surface skin temperature are worn for up to 15 hours. Inertial measurement units recorded acceleration, gyration, and temperature. A graphical user interface (GUI) was designed and implemented to automatically process large amounts of data and to provide longitudinal tracking of the subjects' physiological signals. A GUI is a human-computer interface wherein users give commands to electronic devices using visual indicators such as push buttons, drop-down menus, etc. They can be designed to show outputs in the form of text or visual graphs based on parameters input by the user. Using GUIs to analyze large volumes of data creates ease and efficiency. We paired the GUI with 6 inertial measurement units, IMUs (APDM 128Hz, Oregon). A Matlab program was designed to analyze data captured from the IMUs. In addition to the use of the GUI in typical populations, here we demonstrate the use of this GUI in a variety of clinical populations with neurological disorders and mental illnesses. The latter include schizophrenia, bipolar disorder, and general executive dysfunction. The former included autism, sensory processing disorder, and a genetic disorder that causes a deletion in SHANK-3, resulting in the presence of autistic traits in some cases). We propose the use of the GUI interface to characterize bodily responses during the performance of perceptual tasks to provide real-time, objective read-outs of a subject's perceptual state. Meeting abstract presented at VSS 2015.
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The brain integrates streams of sensory input and builds accurate predictions, while arriving at stable percepts under disparate time scales. This stochastic process bears different dynamics for different people, yet statistical learning... more
The brain integrates streams of sensory input and builds accurate predictions, while arriving at stable percepts under disparate time scales. This stochastic process bears different dynamics for different people, yet statistical learning (SL) currently averages out, as noise, individual fluctuations in data streams registered from the brain as the person learns. We here adopt the motor systems perspective to reframe SL. Specifically, we rethink this problem using the demands that the person’s brain faces to predict, and control variations in biorhythmic activity akin to those present in bodily motions. This new approach harnesses gross data as the important signals, to reassess how individuals learn predictive information in stable and unstable environments. We find two types of learners: narrow-variance learners, who retain explicit knowledge of the regularity embedded in the stimuli -the goal. They seem to use an error-correction strategy steadily present in both stable and unstab...
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Multimodal digital data registered with wearable biosensors has emerged as highly complementary of clinical pencil-and-paper criteria, offering new insights in ways to detect and diagnose various aspects of Parkinson’s disease. A pressing... more
Multimodal digital data registered with wearable biosensors has emerged as highly complementary of clinical pencil-and-paper criteria, offering new insights in ways to detect and diagnose various aspects of Parkinson’s disease. A pressing question is how to combine both the clinical knowledge of PD and the new technology to create interpretable digital biomarkers easily obtainable with off-the-shelf technology. Several challenges concerning disparity in biophysical units, anatomical differences across participants, sensor positioning, and sampling resolution are addressed in this work, along with identification of optimal parameters to automatically differentiate patients with PD from controls. We combine data from a multitude of biosensors registering signals from the central (EEG) and peripheral (magnetometry, kinematics) nervous systems, inclusive of the autonomic nervous system (EKG), as the participants perform natural tasks requiring different levels of intentional planning an...
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Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective... more
Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective diagnosis, capturing finer degrees of motor deficits, while retaining the information of traditional clinical tests. We aim at digitizing traditional tests of cognitive and memory performance to derive motor biometrics of pen-strokes and voice, thereby complementing clinical tests with objective criteria, while enhancing the overall characterization of Parkinson’s disease (PD). 35 participants including patients with PD, healthy young and age-matched controls performed a series of drawing and memory tasks, while their pen movement and voice were digitized. We examined the moment-to-moment variability of time series reflecting the pen speed and voice amplitude. The stochastic signatures of the fluctuations in pen drawing speed and voice amplitude of patients ...
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Research Interests: Neuroscience, Psychology, Philosophy, Behavioral Sciences, Autism, and 12 moreNonlinear Dynamics and Stochasticity, Autism Spectrum Disorders, Embodied Cognition, Theory of Mind, Embodied Mind and Cognition, Sensory-motor adaptation, Social Neuroscience, Cognitive Neuroscience, Behavioral Neuroscience, Stochastic processes, CRC, and Autism Spectrum Treatment
The current assessment of behaviors in the inventories to diagnose autism spectrum disorders (ASD) focus on observation and discrete categorizations. Behaviors require movements, yet measurements of physical movements are seldom included.... more
The current assessment of behaviors in the inventories to diagnose autism spectrum disorders (ASD) focus on observation and discrete categorizations. Behaviors require movements, yet measurements of physical movements are seldom included. Their inclusion however, could provide an objective characterization of behavior to help unveil interactions between the peripheral and the central nervous systems (CNSs). Such interactions are critical for the development and maintenance of spontaneous autonomy, self-regulation, and voluntary control. At present, current approaches cannot deal with the heterogeneous, dynamic and stochastic nature of development. Accordingly, they
We bring together researchers who apply a variety of mathematical tools in their research on human performance. Travis Wiltshire examines the social interactions of team members. Chris Sims pushes forward in the assessment of... more
We bring together researchers who apply a variety of mathematical tools in their research on human performance. Travis Wiltshire examines the social interactions of team members. Chris Sims pushes forward in the assessment of computational rationality by individuals. Rahman and Gray shine their Spotlight on the dips and leaps of performance during skill acquisition. Elizabeth Torres examines stochastic shifts in learning across the lifespan. We maintain that these lines of research show common ground and we have challenged each of our panelists to look for and highlight that common ground in their presentation.
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Strategies to develop putative biomarkers to characterize the female phenotype with 3 Autism Spectrum Disorders 4 Elizabeth B. Torres1,2, Robert W. Isenhower1, Polina Yanovich3, Gwendolyn Rehrig1, Kimberly 5 Stigler4, John Nurnberger4,... more
Strategies to develop putative biomarkers to characterize the female phenotype with 3 Autism Spectrum Disorders 4 Elizabeth B. Torres1,2, Robert W. Isenhower1, Polina Yanovich3, Gwendolyn Rehrig1, Kimberly 5 Stigler4, John Nurnberger4, Jorge V. José5, 6 1 Rutgers University – Psychology Dept. 7 8 2 Rutgers University –Rutgers Center for Cognitive Science, Center for Computational 9 Biomedicine Imaging and Modeling (Computer Science), Movement Disorders, Neurology, 10 Indiana University Medical School Indianapolis. 11 12 3 Rutgers University – Computer Science Department 13 14 4 Indiana University – Dept. of Psychiatry, Indiana University School of Medicine, Christian 15 Sarkine Autism Treatment Center, Riley Hospital for Children, Indianapolis 16 17 5 Indiana University – Department of Physics, Department of Cellular & Integrative 18 Physiology, Medical School, Indiana University. 19 20 Corresponding Author: Elizabeth B Torres 21 Rutgers University, Psychology Department 22 152 Frel...
There is a disconnect between the clinical behavioral definition of autism and the genomic science that this definition largely informs and steers. But the digital sensor revolution paired with open access to genomics data has the... more
There is a disconnect between the clinical behavioral definition of autism and the genomic science that this definition largely informs and steers. But the digital sensor revolution paired with open access to genomics data has the potential to bridge the gap between these two layers of knowledge. Here we use the SFARI genes module and interrogate the human genome upon removing those genes. We then compare the remaining genes’ expression on tissues responsible for brain, heart and organs function to its counterpart in well-known neurological disorders of genetic origins. Despite clinical criteria emphasizing a behavioral definition of Autism, over a neurological one, here we find convergence between Autism and the neurological disorders. Tissues involved in motor control, emotions and memory are the most affected by the removal of the SFARI Autism genes. Congruent with this picture, the Ataxias, Parkinson’s disease and Fragile X share 76.9% of the most affected tissues, including tho...
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The research-grade ADOS is a broadly used instrument that informs and steers much of the science of Autism. Despite its broad use, little is known about the empirical variability inherently present in the scores of the ADOS scale, or... more
The research-grade ADOS is a broadly used instrument that informs and steers much of the science of Autism. Despite its broad use, little is known about the empirical variability inherently present in the scores of the ADOS scale, or their appropriateness to define change, to repeatedly use this test to characterize neurodevelopmental trajectories. Here we examine the empirical distributions of research-grade ADOS scores from 1,324 records in a cross-section of the population comprising participants with autism between 5-65 years of age. We find that these empirical distributions violate the theoretical requirements of normality and homogeneous variance, essential for independence between bias and sensitivity. Further, we assess a subset of 52 typical controls vs. those with autism and find lack of proper elements to characterize neurodevelopmental trajectories in a coping nervous system changing at non-uniform, non-linear rates. Lastly, longitudinally repeating the assessments over...
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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... more
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. Asperger's Syndrome (AS) criteria, distributional analyses of ordinal score data from Autism Diagnostic Observation Schedule (ADOS)-based criteria were used on both the fem...
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This movie can be seen at http://youtu.be/2DKc6aSgd20
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Intended reaches triggered by exogenous targets often coexist with spontaneous, automated movements that are endogenously activated. It has been posited that Parkinson's disease (PD) primarily impairs automated movements, but it is... more
Intended reaches triggered by exogenous targets often coexist with spontaneous, automated movements that are endogenously activated. It has been posited that Parkinson's disease (PD) primarily impairs automated movements, but it is unknown to what extent this may affect multijoint/limb control, particularly when patients are off their dopaminergic medications. Here we tested nine human patients with PD while off dopaminergic medication versus nine age-matched normal controls (NCs). Participants performed intentional reaches forward to a target in a dark room and then transitioned back to their initial posture. Upon target flash, three forms of guidance were used: (1) memory with eyes closed, (2) continuous target vision only, and (3) vision of their moving finger only. The trajectories of their arm joints were measured and their joint velocities decomposed into the (intended) task-relevant and the (spontaneous) task-incidental degrees of freedom (DOF). We also measured the bala...
Research Interests: Neuroscience, Medicine, Intention, Physical Medicine and Rehabilitation, Memory, and 15 moreHumans, Movement, Female, Male, Posture, Aged, Middle Aged, Analysis of Variance, Basal ganglia, Hand, Parkinson Disease, Biomechanical Phenomena, Neuropsychological Tests, dopaminergic, and Medical and Health Sciences
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While attempting to bridge motor control and cognitive science, the nascent field of embodied cognition has primarily addressed intended, goal-oriented actions. Less explored, however, have been unintended motions. Such movements tend to... more
While attempting to bridge motor control and cognitive science, the nascent field of embodied cognition has primarily addressed intended, goal-oriented actions. Less explored, however, have been unintended motions. Such movements tend to occur largely beneath awareness, while contributing to the spontaneous control of redundant degrees of freedom across the body in motion. We posit that the consequences of such unintended actions implicitly contribute to our autonomous sense of action ownership and agency. We question whether biorhythmic activities from these motions are separable from those which intentionally occur. Here we find that fluctuations in the biorhythmic activities of the nervous systems can unambiguously differentiate across levels of intent. More important yet, this differentiation is remarkable when we examine the fluctuations in biorhythmic activity from the autonomic nervous systems. We find that when the action is intended, the heart signal leads the body kinemati...
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In the last decade, Autism has broadened and often shifted its diagnostics criter a, allowing several neuropsychiatric and neurological disorders of known etiology. This has resulted in a highly heterogeneous spectrum with apparent... more
In the last decade, Autism has broadened and often shifted its diagnostics criter a, allowing several neuropsychiatric and neurological disorders of known etiology. This has resulted in a highly heterogeneous spectrum with apparent exponential rates in prevalence. I ask if it is possible to leverage existing genetic information about those disorders making up Autism today and use it to stratify this spectrum. To that end, I combine genes linked to Autism in the SFARI database and genomic information from the DisGeNet portal on 25 diseases, inclusive of non-neurological ones. I use the GTEx data on genes’ expression on 54 human tissues and ask if there are overlapping genes across those associated to these diseases and those from SFARI-Autism. I find a compact set of genes across all brain-disorders which express highly in tissues fundamental for somatic-sensory-motor function, self-regulation, memory, and cognition. Then, I offer a new stratification that provides a distance-based o...
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Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing... more
Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing question thus is how to automatically stratify a given random cohort of the population, such that treatment can be better tailored to each cluster’s symptoms, and severity of any given group forecasted to provide neuroprotective therapies. In this work we introduce new methods to automatically stratify a random cohort of the population composed of healthy controls of different ages and patients with different disorders of the nervous systems. Using a simple walking task and measuring micro-fluctuations in their biorhythmic motions, we combine non-linear causal network connectivity analyses in the temporal and frequency domains with stochastic mapping. The methods define a new type of internal motor timings. These are amenable to create personalized clini...
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The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales... more
The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as nois...
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The art of observing and describing behaviors has driven diagnosis and informed basic science in Psychiatry. In recent times, studies of mental illness are focused on understanding the brain’s neurobiology but there is a paucity of... more
The art of observing and describing behaviors has driven diagnosis and informed basic science in Psychiatry. In recent times, studies of mental illness are focused on understanding the brain’s neurobiology but there is a paucity of information on the potential contributions from peripheral activity to mental health. In Precision Medicine, this common practice leaves a gap between bodily behaviors and genomics that we here propose to address with a new layer of inquiry that includes genes’ expression on tissues inclusive of brain, heart, muscle-skeletal and organs for vital bodily functions. We interrogate genes’ expression on human tissue as a function of disease-associated genes. By removing genes linked to disease from the typical human set, and recomputing the genes’ expressions on the tissues, we can compare the outcomes across mental illnesses, well-known neurological conditions, and non-neurological ones. We find that major neuropsychiatric conditions that are behaviorally def...
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The complexity and non-linear dynamics of socio-motor phenomena underlying social interactions are often missed by observation methods that attempt to capture, describe, and rate the exchange in real time. Unknowingly to the rater,... more
The complexity and non-linear dynamics of socio-motor phenomena underlying social interactions are often missed by observation methods that attempt to capture, describe, and rate the exchange in real time. Unknowingly to the rater, socio-motor behaviors of a dyad exert mutual influence over each other through subliminal mirroring and shared cohesiveness that escape the naked eye. Implicit in these ratings nonetheless is the assumption that the other participant of the social dyad has an identical nervous system as that of the interlocutor, and that sensory-motor information is processed similarly by both agents’ brains. What happens when this is not the case? We here use the Autism Diagnostic Observation Schedule (ADOS) to formally study social dyadic interactions, at the macro- and micro-level of behaviors, by combining observation with digital data from wearables. We find that integrating subjective and objective data reveals fundamentally new ways to improve standard clinical too...
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Autism has been largely portrayed as a psychiatric and childhood disorder. However, autism is a lifelong neurological condition that evolves over time through highly heterogeneous trajectories. These trends have not been studied in... more
Autism has been largely portrayed as a psychiatric and childhood disorder. However, autism is a lifelong neurological condition that evolves over time through highly heterogeneous trajectories. These trends have not been studied in relation to normative aging trajectories, so we know very little about aging with autism. One aspect that seems to develop differently is the sense of movement, inclusive of sensory kinesthetic-reafference emerging from continuously sensed self-generated motions. These include involuntary micro-motions eluding observation, yet routinely obtainable in fMRI studies to rid images of motor artifacts. Open-access repositories offer thousands of imaging records, covering 5–65 years of age for both neurotypical and autistic individuals to ascertain the trajectories of involuntary motions. Here we introduce new computational techniques that automatically stratify different age groups in autism according to probability distance in different representational spaces...
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Dyadic interactions are ubiquitous in our lives, yet they are highly challenging to study. Many subtle aspects of coupled bodily dynamics continuously unfolding during such exchanges have not been empirically parameterized. As such, we... more
Dyadic interactions are ubiquitous in our lives, yet they are highly challenging to study. Many subtle aspects of coupled bodily dynamics continuously unfolding during such exchanges have not been empirically parameterized. As such, we have no formal statistical methods to describe the spontaneously self-emerging coordinating synergies within each actor’s body and across the dyad. Such cohesive motion patterns self-emerge and dissolve largely beneath the awareness of the actors and the observers. Consequently, hand coding methods may miss latent aspects of the phenomena. The present paper addresses this gap and provides new methods to quantify the moment-by-moment evolution of self-emerging cohesiveness during highly complex ballet routines. We use weighted directed graphs to represent the dyads as dynamically coupled networks unfolding in real-time, with activities captured by a grid of wearable sensors distributed across the dancers’ bodies. We introduce new visualization tools, s...
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Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to... more
Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on human heuristics, the analyses become computationally expensive and rather subjective. Further, there is no standardized scale or set of tasks amenable to take advantage of such technology in ways that permit broad dissemination and reproducibility of results. Indeed, there is a critical need for fully objective automated analytical methods that easily handle the deluge of data these sensors output, while providing standardized scales amenable to apply across large sections of the population, to help promote personalized-mobile medicine. Here we use an open-access data set from Kaggle.com to illustrate the use of a new statistical platform and standardized data types applied to smart phone acce...
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The field of enacted/embodied cognition has emerged as a contemporary attempt to connect the mind and body in the study of cognition. However, there has been a paucity of methods that enable a multi-layered approach tapping into different... more
The field of enacted/embodied cognition has emerged as a contemporary attempt to connect the mind and body in the study of cognition. However, there has been a paucity of methods that enable a multi-layered approach tapping into different levels of functionality within the nervous systems (e.g., continuously capturing in tandem multi-modal biophysical signals in naturalistic settings). The present study introduces a new theoretical and statistical framework to characterize the influences of cognitive demands on biophysical rhythmic signals harnessed from deliberate, spontaneous and autonomic activities. In this study, nine participants performed a basic pointing task to communicate a decision while they were exposed to different levels of cognitive load. Within these decision-making contexts, we examined the moment-by-moment fluctuations in the peak amplitude and timing of the biophysical time series data (e.g., continuous waveforms extracted from hand kinematics and heart signals)....
The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access... more
The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls. Further, statistical analyses of groups from different diagnoses and demographics may be challenging, owing to the disparate number of participants across different clinical subgroups. In this paper, we examine the noise signatures of head motion data extracted from resting state fMRI data harnessed under different sampling resolutions. We characterize the quality of the noise in the variability of the raw linear and angular speeds for differ...
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Despite great advances in neuroscience and genetic studies, our understanding of neurodevelopmental disorders is still quite limited. An important reason is not having objective psychiatric clinical tests. Here we propose a quantitative... more
Despite great advances in neuroscience and genetic studies, our understanding of neurodevelopmental disorders is still quite limited. An important reason is not having objective psychiatric clinical tests. Here we propose a quantitative neurodevelopment assessment by studying natural movement outputs. Movement is central to behaviors: It involves complex coordination, temporal alterations, and precise dynamic controls. We carefully analyzed the continuous movement output data, collected with high definition electromagnetic sensors at millisecond time scales. We unraveled new metrics containing striking physiological information that was unseen neither by using traditional motion assessments nor by naked eye observations. Our putative biomarker leads to precise individualized classifications. It illustrates clear differences between Autism Spectrum Disorder (ASD) subjects from mature typical developing (TD) individuals. It provides an ASD complementary quantitative classification, wh...
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Traditionally conceived of and studied as a disorder of cognitive and emotional functioning, schizophrenia (SZ) is also characterized by alterations in bodily sensations. These have included subjective reports based on self-evaluations... more
Traditionally conceived of and studied as a disorder of cognitive and emotional functioning, schizophrenia (SZ) is also characterized by alterations in bodily sensations. These have included subjective reports based on self-evaluations and/or clinical observations describing motor, as well as sensory-based corporeal anomalies. There has been, however, a paucity of objective methods to capture and characterize bodily issues in SZ. Here we present a new research method and statistical platform that enables precise evaluation of peripheral activity and its putative contributions to the cognitive control of visuomotor actions. Specifically, we introduce new methods that facilitate the individualized characterization of the function of sensory-motor systems so as to detect if subjects perform outside of normal limits. In this paper, we report data from a cohort of patients with a clinical diagnosis of SZ. First, we characterize neurotypical subjects performing a visually guided pointing ...