The time is ripe to integrate burgeoning evidence of the important role of sensory and motor functioning in mental health within the National Institute of Mental Health’s [NIMH] Research Domain Criteria [RDoC] framework (National Institute of Mental Health, n.d.a), a multi-dimensional method of characterizing mental functioning in health and disease across all neurobiological levels of analysis ranging from genetic to behavioral. As the importance of motor processing in psychopathology has been recognized (Bernard and Mittal, 2015; Garvey and Cuthbert, 2017; National Institute of Mental Health, 2019), here we focus on sensory processing. First, we review the current design of the RDoC matrix, noting sensory features missing despite their prevalence in multiple mental illnesses. We identify two missing classes of sensory symptoms that we widely define as (1) sensory processing, including sensory sensitivity and active sensing, and (2) domains of perceptual signaling, including interoception and proprioception, which are currently absent or underdeveloped in the perception construct of the cognitive systems domain. Then, we describe the neurobiological basis of these psychological constructs and examine why these sensory features are important for understanding psychopathology. Where appropriate, we examine links between sensory processing and the domains currently included in the RDoC matrix. Throughout, we emphasize how the addition of these sensory features to the RDoC matrix is important for understanding a range of mental health disorders. We conclude with the suggestion that a separate sensation and perception domain can enhance the current RDoC framework, while discussing what we see as important principles and promising directions for the future development and use of the RDoC.

Sensory processing and motor coordination atypicalities are not commonly identified as primary characteristics of autism spectrum disorder (ASD), nor are they well captured in the NIMH’s original Research Domain Criteria (RDoC) framework. Here, motor and sensory features performed similarly to RDoC features in support vector classification of 30 ASD youth against 33 typically developing controls. Combining sensory with RDoC features boosted classification performance, achieving a Matthews Correlation Coefficient (MCC) of 0.949 and balanced accuracy (BAcc) of 0.971 (p = 0.00020, calculated against a permuted null distribution). Sensory features alone successfully classified ASD (MCC = 0.565, BAcc = 0.773, p = 0.0222) against a clinically relevant control group of 26 youth with Developmental Coordination Disorder (DCD) and were in fact required to decode against DCD above chance. These findings highlight the importance of sensory and motor features to the ASD phenotype and their relevance to the RDoC framework.

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