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Torres EB. Connecting movement and cognition through different modes of learning. PSYCHOLOGY OF LEARNING AND MOTIVATION 2022. [DOI: 10.1016/bs.plm.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify Its "Epidemic Rates". J Pers Med 2021; 11:jpm11111119. [PMID: 34834471 PMCID: PMC8620644 DOI: 10.3390/jpm11111119] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 12/16/2022] Open
Abstract
In the last decade, Autism has broadened and often shifted its diagnostics criteria, 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 orderly clustering into possible Autism subtypes, amenable to design personalized targeted therapies within the framework of Precision Medicine. I conclude that viewing Autism through this physiological (Precision) lens, rather than viewing it exclusively from a psychological behavioral construct, may make it a more manageable condition and dispel the Autism epidemic myth.
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Singh RS, Singh KK, Singh SM. Origin of Sex-Biased Mental Disorders: An Evolutionary Perspective. J Mol Evol 2021; 89:195-213. [PMID: 33630117 PMCID: PMC8116267 DOI: 10.1007/s00239-021-09999-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 02/06/2021] [Indexed: 12/12/2022]
Abstract
Sexual dimorphism or sex bias in diseases and mental disorders have two biological causes: sexual selection and sex hormones. We review the role of sexual selection theory and bring together decades of molecular studies on the variation and evolution of sex-biased genes and provide a theoretical basis for the causes of sex bias in disease and health. We present a Sexual Selection-Sex Hormone theory and show that male-driven evolution, including sexual selection, leads to: (1) increased male vulnerability due to negative pleiotropic effects associated with male-driven sexual selection and evolution; (2) increased rates of male-driven mutations and epimutations in response to early fitness gains and at the cost of late fitness; and (3) enhanced female immunity due to antagonistic responses to mutations that are beneficial to males but harmful to females, reducing female vulnerability to diseases and increasing the thresholds for disorders such as autism. Female-driven evolution, such as reproduction-related fluctuation in female sex hormones in association with stress and social condition, has been shown to be associated with increased risk of certain mental disorders such as major depression disorder in women. Bodies have history, cells have memories. An evolutionary framework, such as the Sexual Selection–Sex Hormone theory, provides a historical perspective for understanding how the differences in the sex-biased diseases and mental disorders have evolved over time. It has the potential to direct the development of novel preventive and treatment strategies.
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Affiliation(s)
- Rama S Singh
- Department of Biology, McMaster University, Hamilton, Canada.
| | - Karun K Singh
- Stem Cell and Cancer Research Institute, McMaster University, Hamilton, Canada.,Krembil Research Institute, University Health Network, Toronto, Canada
| | - Shiva M Singh
- Department of Biology, University of Western Ontario, London, Canada
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Digitized Autism Observation Diagnostic Schedule: Social Interactions beyond the Limits of the Naked Eye. J Pers Med 2020; 10:jpm10040159. [PMID: 33050080 PMCID: PMC7711822 DOI: 10.3390/jpm10040159] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 10/01/2020] [Accepted: 10/01/2020] [Indexed: 12/14/2022] Open
Abstract
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 tools, even to differentiate females from males using the digital version of the test. More generally, this work offers a way to turn a traditional, gold-standard clinical instrument into an objective outcome measure of human social behaviors and treatment effectiveness.
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Torres EB, Caballero C, Mistry S. Aging with Autism Departs Greatly from Typical Aging. SENSORS 2020; 20:s20020572. [PMID: 31968701 PMCID: PMC7014496 DOI: 10.3390/s20020572] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/13/2020] [Accepted: 01/14/2020] [Indexed: 01/01/2023]
Abstract
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. Further, we show that autistic cross-sectional population trajectories in probability space fundamentally differ from those of neurotypical controls and that after 40 years of age, there is an inflection point in autism, signaling a monotonically increasing difference away from age-matched normative involuntary motion signatures. Our work offers new age-appropriate stochastic analyses amenable to redefine basic research and provide dynamic diagnoses as the person's nervous systems age.
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Affiliation(s)
- Elizabeth B. Torres
- Psychology Department Center for Biomedicine Imaging and Modelling, CS Department and Rutgers Center for Cognitive Science, Rutgers University, Camden, NJ 08854, USA
- Correspondence: ; Tel.: +1-732-208-3158
| | - Carla Caballero
- Sports Science Department, Miguel Hernandez University of Elche, 03202 Alicante, Spain;
| | - Sejal Mistry
- Biomathematics Department, Rutgers University, Camden, NJ 08854, USA;
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Torres EB, Rai R, Mistry S, Gupta B. Hidden Aspects of the Research ADOS Are Bound to Affect Autism Science. Neural Comput 2020; 32:515-561. [PMID: 31951797 DOI: 10.1162/neco_a_01263] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The research-grade Autism Diagnostic Observational Schedule (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 and its rate, to repeatedly use this test to characterize neurodevelopmental trajectories. Here we examine the empirical distributions of research-grade ADOS scores from 1324 records in a cross-section of the population comprising participants with autism between five and 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 versus those with autism and find a lack of proper elements to characterize neurodevelopmental trajectories in a coping nervous system changing at nonuniform, nonlinear rates. Repeating the assessments over four visits in a subset of the participants with autism for whom verbal criteria retained the same appropriate ADOS modules over the time span of the four visits reveals that switching the clinician changes the cutoff scores and consequently influences the diagnosis, despite maintaining fidelity in the same test's modules, room conditions, and tasks' fluidity per visit. Given the changes in probability distribution shape and dispersion of these ADOS scores, the lack of appropriate metric spaces to define similarity measures to characterize change and the impact that these elements have on sensitivity-bias codependencies and on longitudinal tracking of autism, we invite a discussion on readjusting the use of this test for scientific purposes.
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Affiliation(s)
- Elizabeth B Torres
- Psychology Department; Computer Science, Center for Biomedical Imagining and Modeling; and Rutgers University Center for Cognitive Science, Rutgers University, Piscataway, NJ 08854, U.S.A.
| | - Richa Rai
- Psychology Department, Rutgers University, Piscataway, NJ 08854, U.S.A.
| | - Sejal Mistry
- Mathematics Department, Rutgers University, Piscataway, NJ 08854, U.S.A.
| | - Brenda Gupta
- Montclair State University, Montclair, NJ 07043, U.S.A.
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Ryu J, Torres EB. Characterization of Sensory-Motor Behavior Under Cognitive Load Using a New Statistical Platform for Studies of Embodied Cognition. Front Hum Neurosci 2018; 12:116. [PMID: 29681805 PMCID: PMC5897674 DOI: 10.3389/fnhum.2018.00116] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 03/12/2018] [Indexed: 11/13/2022] Open
Abstract
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). These spike-trains data offered high statistical power for personalized empirical statistical estimation and were well-characterized by a Gamma process. Our approach enabled the identification of different empirically estimated families of probability distributions to facilitate inference regarding the continuous physiological phenomena underlying cognitively driven decision-making. We found that the same pointing task revealed shifts in the probability distribution functions (PDFs) of the hand kinematic signals under study and were accompanied by shifts in the signatures of the heart inter-beat-interval timings. Within the time scale of an experimental session, marked changes in skewness and dispersion of the distributions were tracked on the Gamma parameter plane with 95% confidence. The results suggest that traditional theoretical assumptions of stationarity and normality in biophysical data from the nervous systems are incongruent with the true statistical nature of empirical data. This work offers a unifying platform for personalized statistical inference that goes far beyond those used in conventional studies, often assuming a “one size fits all model” on data drawn from discrete events such as mouse clicks, and observations that leave out continuously co-occurring spontaneous activity taking place largely beneath awareness.
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Affiliation(s)
- Jihye Ryu
- Sensory Motor Integration Laboratory, Department of Psychology, Rutgers University, Piscataway, NJ, United States
| | - Elizabeth B Torres
- Computational Biomedical Imaging and Modeling Center, Department of Psychology and Computer Science, Rutgers University Center for Cognitive Science, Rutgers University, Piscataway, NJ, United States
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Torres EB, Mistry S, Caballero C, Whyatt CP. Stochastic Signatures of Involuntary Head Micro-movements Can Be Used to Classify Females of ABIDE into Different Subtypes of Neurodevelopmental Disorders. Front Integr Neurosci 2017. [PMID: 28638324 PMCID: PMC5461345 DOI: 10.3389/fnint.2017.00010] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
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 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.
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Affiliation(s)
- Elizabeth B Torres
- Department of Psychology, Rutgers UniversityPiscataway, NJ, United States.,Computer Science Department and Rutgers Center for Cognitive Science, Center for Biomedical Imaging and ModelingNew Brunswick, NJ, United States
| | - Sejal Mistry
- Department of Biomathematics, Rutgers UniversityPiscataway, NJ, United States
| | - Carla Caballero
- Department of Psychology, Rutgers UniversityPiscataway, NJ, United States.,Computer Science Department and Rutgers Center for Cognitive Science, Center for Biomedical Imaging and ModelingNew Brunswick, NJ, United States
| | - Caroline P Whyatt
- Department of Psychology, Rutgers UniversityPiscataway, NJ, United States.,Computer Science Department and Rutgers Center for Cognitive Science, Center for Biomedical Imaging and ModelingNew Brunswick, NJ, United States
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Grecucci A, Rubicondo D, Siugzdaite R, Surian L, Job R. Uncovering the Social Deficits in the Autistic Brain. A Source-Based Morphometric Study. Front Neurosci 2016; 10:388. [PMID: 27630538 PMCID: PMC5005369 DOI: 10.3389/fnins.2016.00388] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Accepted: 08/09/2016] [Indexed: 11/17/2022] Open
Abstract
Autism is a neurodevelopmental disorder that mainly affects social interaction and communication. Evidence from behavioral and functional MRI studies supports the hypothesis that dysfunctional mechanisms involving social brain structures play a major role in autistic symptomatology. However, the investigation of anatomical abnormalities in the brain of people with autism has led to inconsistent results. We investigated whether specific brain regions, known to display functional abnormalities in autism, may exhibit mutual and peculiar patterns of covariance in their gray-matter concentrations. We analyzed structural MRI images of 32 young men affected by autistic disorder (AD) and 50 healthy controls. Controls were matched for sex, age, handedness. IQ scores were also monitored to avoid confounding. A multivariate Source-Based Morphometry (SBM) was applied for the first time on AD and controls to detect maximally independent networks of gray matter. Group comparison revealed a gray-matter source that showed differences in AD compared to controls. This network includes broad temporal regions involved in social cognition and high-level visual processing, but also motor and executive areas of the frontal lobe. Notably, we found that gray matter differences, as reflected by SBM, significantly correlated with social and behavioral deficits displayed by AD individuals and encoded via the Autism Diagnostic Observation Schedule scores. These findings provide support for current hypotheses about the neural basis of atypical social and mental states information processing in autism.
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Affiliation(s)
- Alessandro Grecucci
- Department of Psychology and Cognitive Sciences, University of Trento Trento, Italy
| | - Danilo Rubicondo
- Department of Psychology and Cognitive Sciences, University of TrentoTrento, Italy; Center for Mind/Brain Sciences, University of TrentoTrento, Italy
| | - Roma Siugzdaite
- Department of Experimental Psychology, Faculty of Psychological and Pedagogical Sciences, Ghent University Ghent, Belgium
| | - Luca Surian
- Department of Psychology and Cognitive Sciences, University of Trento Trento, Italy
| | - Remo Job
- Department of Psychology and Cognitive Sciences, University of Trento Trento, Italy
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Rethinking the Study of Volition for Clinical Use. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 957:229-254. [PMID: 28035569 DOI: 10.1007/978-3-319-47313-0_13] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Volition, the acquired voluntary control of our actions (at will), requires from birth to development and beyond a proper balance across multiple layers of the nervous systems. These levels range from the autonomic, to the automatic, to the voluntary control level, providing as well taxonomy with phylogenetic order of appearance in evolution. In the past few decades of movement research at the behavioral and systems levels, there has been a paucity of studies focusing on the possible contributions of involuntary movements to volitional control. Moreover, the work focusing on voluntary behavior has given us a valuable body of knowledge about constrained and highly over practiced activities while work involving unrestrained, naturalistic behaviors remains scarce. Perhaps in making theoretical assumptions about our data acquisition and analyses without properly empirically verifying, these assumptions have left us with a somewhat skewed notion of how we think the brain may be realizing the neural control of bodily motions; a notion that does not exactly correspond to the outcome of the extant empirical work assessing unrestrained movements as the nervous system acquires them and modifies skillful behaviors on demand. This chapter takes advantage of new technological advances and new analytics to invite rethinking some of the problems that we study in movement science by enforcing somewhat oversimplified assumptions on the data that we model, acquire, and analyze. I show that by relaxing our a priori assumptions of normality, linearity and stationarity in data from biophysical rhythms of the nervous systems, we would gain better insights into the motor phenomena. Further, we would shy away from a "self-fulfilling prophesy" paradigm with a tendency to a priori handcraft the outcome of our inquiry. The new lens to study natural movements and their control includes as well involuntary motions that take place largely beneath deliberate awareness. I present examples of solutions amenable to the habilitation and rehabilitation of volition in patient populations and discuss a new vision for movement science in light of making a seamless transition from volitional to intentional control of actions and thoughts.
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Lai MC, Lombardo MV, Auyeung B, Chakrabarti B, Baron-Cohen S. Sex/gender differences and autism: setting the scene for future research. J Am Acad Child Adolesc Psychiatry 2015; 54:11-24. [PMID: 25524786 PMCID: PMC4284309 DOI: 10.1016/j.jaac.2014.10.003] [Citation(s) in RCA: 556] [Impact Index Per Article: 61.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2014] [Revised: 10/10/2014] [Accepted: 10/13/2014] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The relationship between sex/gender differences and autism has attracted a variety of research ranging from clinical and neurobiological to etiological, stimulated by the male bias in autism prevalence. Findings are complex and do not always relate to each other in a straightforward manner. Distinct but interlinked questions on the relationship between sex/gender differences and autism remain underaddressed. To better understand the implications from existing research and to help design future studies, we propose a 4-level conceptual framework to clarify the embedded themes. METHOD We searched PubMed for publications before September 2014 using search terms "'sex OR gender OR females' AND autism." A total of 1,906 articles were screened for relevance, along with publications identified via additional literature reviews, resulting in 329 articles that were reviewed. RESULTS Level 1, "Nosological and diagnostic challenges," concerns the question, "How should autism be defined and diagnosed in males and females?" Level 2, "Sex/gender-independent and sex/gender-dependent characteristics," addresses the question, "What are the similarities and differences between males and females with autism?" Level 3, "General models of etiology: liability and threshold," asks the question, "How is the liability for developing autism linked to sex/gender?" Level 4, "Specific etiological-developmental mechanisms," focuses on the question, "What etiological-developmental mechanisms of autism are implicated by sex/gender and/or sexual/gender differentiation?" CONCLUSIONS Using this conceptual framework, findings can be more clearly summarized, and the implications of the links between findings from different levels can become clearer. Based on this 4-level framework, we suggest future research directions, methodology, and specific topics in sex/gender differences and autism.
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Affiliation(s)
- Meng-Chuan Lai
- National Taiwan University Hospital and College of Medicine, Taipei, Taiwan and the Autism Research Centre, University of Cambridge, Cambridge, UK.
| | - Michael V Lombardo
- University of Cyprus, Nicosia, Cyprus and the Autism Research Centre, University of Cambridge
| | - Bonnie Auyeung
- University of Edinburgh and the Autism Research Centre, University of Cambridge
| | - Bhismadev Chakrabarti
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK and the Autism Research Centre, University of Cambridge
| | - Simon Baron-Cohen
- Cambridge Lifespan Asperger Syndrome Service (CLASS) Clinic, Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, and the Autism Research Centre, University of Cambridge
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Torres EB, Cole J, Poizner H. Motor output variability, deafferentation, and putative deficits in kinesthetic reafference in Parkinson's disease. Front Hum Neurosci 2014; 8:823. [PMID: 25374524 PMCID: PMC4204460 DOI: 10.3389/fnhum.2014.00823] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Accepted: 09/26/2014] [Indexed: 11/23/2022] Open
Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder defined by motor impairments that include rigidity, systemic slowdown of movement (bradykinesia), postural problems, and tremor. While the progressive decline in motor output functions is well documented, less understood are impairments linked to the continuous kinesthetic sensation emerging from the flow of motions. There is growing evidence in recent years that kinesthetic problems are also part of the symptoms of PD, but objective methods to readily quantify continuously unfolding motions across different contexts have been lacking. Here we present evidence from a deafferented subject (IW) and a new statistical platform that enables new analyses of motor output variability measured as a continuous flow of kinesthetic reafferent input. Systematic increasing similarities between the patterns of motor output variability in IW and the participants with increasing degrees of PD severity suggest potential deficits in kinesthetic sensing in PD. We propose that these deficits may result from persistent, noisy, and random motor patterns as the disorder progresses. The stochastic signatures from the unfolding motions revealed levels of noise in the motor output fluctuations of these patients bound to decrease the kinesthetic signal’s bandwidth. The results are interpreted in light of the concept of kinesthetic reafference ( Von Holst and Mittelstaedt, 1950). In this context, noisy motor output variability from voluntary movements in PD leads to a returning stream of noisy afference caused, in turn, by those faulty movements themselves. Faulty efferent output re-enters the CNS as corrupted sensory motor input. We find here that severity level in PD leads to the persistence of such patterns, thus bringing the statistical signatures of the subjects with PD systematically closer to those of the subject without proprioception.
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Affiliation(s)
- Elizabeth B Torres
- Sensory Motor Integration Laboratory and Department of Psychology, Department of Computer Science and Rutgers University Center for Cognitive Science, Rutgers University-New Brunswick New Brunswick, NJ, USA
| | | | - Howard Poizner
- Institute for Neural Computation, University of California at San Diego San Diego, CA, USA
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