In clinical practice, many individuals with psychiatric disorders report difficulties in sensory processing, including increased awareness or sensitivity to external stimuli. In this meta-analysis, ...we examined the sensory processing patterns of adolescent and adult individuals with a broad spectrum of different psychiatric conditions. A systematic search in various databases resulted in the inclusion of 33 studies (N=2008), all using the Adolescent/Adult Sensory Profile (AASP). By comparing diagnostic subgroups to the corresponding reference group of the AASP, we detected a general pattern of sensory processing, indicating elevated levels of low registration, sensory sensitivity and sensory avoiding and lowered sensory seeking behavior in patients with different types of psychiatric disorders. The majority of effect sizes were large to very large. In conclusion, sensory processing difficulties can be considered as a non-specific transdiagnostic phenotype associated with a broad spectrum of psychiatric conditions. Further research into the relevance and role of sensory processing difficulties in psychiatric disorders may improve long-term prognosis and treatment.
•Many individuals with psychiatric disorders report difficulties in sensory processing.•This meta-analysis examined sensory processing patterns in psychiatric conditions.•We detected a general pattern of sensory processing difficulties in psychopathology.•Sensory processing difficulties are considered to be a transdiagnostic phenotype.•Further research may improve long-term prognosis and treatment in psychiatry.
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.
How Do Expectations Shape Perception? de Lange, Floris P.; Heilbron, Micha; Kok, Peter
Trends in cognitive sciences,
September 2018, 2018-09-00, 20180901, Letnik:
22, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Perception and perceptual decision-making are strongly facilitated by prior knowledge about the probabilistic structure of the world. While the computational benefits of using prior expectation in ...perception are clear, there are myriad ways in which this computation can be realized. We review here recent advances in our understanding of the neural sources and targets of expectations in perception. Furthermore, we discuss Bayesian theories of perception that prescribe how an agent should integrate prior knowledge and sensory information, and investigate how current and future empirical data can inform and constrain computational frameworks that implement such probabilistic integration in perception.
Expectations play a strong role in determining the way we perceive the world.
Prior expectations can originate from multiple sources of information, and correspondingly have different neural sources, depending on where in the brain the relevant prior knowledge is stored.
Recent findings from both human neuroimaging and animal electrophysiology have revealed that prior expectations can modulate sensory processing at both early and late stages, and both before and after stimulus onset. The response modulation can take the form of either dampening the sensory representation or enhancing it via a process of sharpening.
Theoretical computational frameworks of neural sensory processing aim to explain how the probabilistic integration of prior expectations and sensory inputs results in perception.
•According to Vantage Sensitivity people differ in their sensitivity to intervention.•Sensory-Processing Sensitivity (SPS) may reflect high sensitivity to the environment.•SPS moderated treatment ...efficacy of a school-based prevention program.•Positive treatment effects emerged only in individuals scoring high on SPS.•Measurement of SPS may prove valuable in the prediction of treatment response.
Treatment effects of preventative mental health interventions for adolescents tend to be relatively small. One reason for the small effects may be individual differences in the response to psychological treatment as a function of inherent characteristics, a notion proposed in the concept of Vantage Sensitivity. The current study investigated whether the personality trait Sensory-Processing Sensitivity moderated the efficacy of a new school-based intervention aimed at the prevention of depression.
Using a two-cohort treatment/control design with one cohort serving as the control group (N=197) and a subsequent cohort as the treatment group (N=166) it was tested whether Sensory-Processing Sensitivity predicted depression trajectories from pre-treatment up to a 12months follow-up assessment in 11-year-old girls from an at-risk population in England.
Sensory-Processing Sensitivity emerged as a significant predictor of treatment response. The prevention program successfully reduced depression scores in girls scoring high on Sensory-Processing Sensitivity but was not effective at all in girls scoring low on the same measure.
This study provides first empirical evidence for Vantage Sensitivity as a function of the personality trait Sensory-Processing Sensitivity regarding treatment response to a school-based depression prevention intervention.
•29–36% of Dutch second graders has non-optimal sensory processing.•Sensory processing tool use did not improve attention or arithmetic performance.•Sensory processing ability is related to attention ...and arithmetic performance.
Behavior caused by nonoptimal sensory processing possibly affects school performance. Sensory processing is the ability of the nervous system to process and modulate sensory input and to give an appropriate response. Children with nonoptimal sensory processing are sometimes given tools that are expected to help them concentrate better and achieve better school performance. However, whether these tools are effective and whether the effects depend on children’s sensory processing are unknown. To investigate this, a randomized controlled trial was executed. Children attending Grade 2 (N = 271) performed a sustained attention test (the Bourdon–Vos test) and an arithmetic test once a week 4 weeks in a row with a different sensory processing tool every session: tangle, wobble cushion, earmuffs, or nothing (control condition). Sensory processing was assessed with the Sensory Profile NL. To test the effects of sensory processing tools on the Bourdon–Vos and arithmetic test performance, mixed-model analyses were executed. Negative effects of the use of the tangle, earmuffs, and wobble cushion on the Bourdon–Vos total, the use of the tangle and wobble cushion on the Bourdon–Vos correct, and the use of the tangle on the arithmetic test were shown. When children’s sensory processing pattern was considered, a negative effect of the use of all tools was shown on the Bourdon–Vos correct for children who already received an optimal amount of stimuli. Considering these results, more research is needed to investigate the effect of longer-term personalized sensory processing tool use on attention and arithmetic performance of children.
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•SPS captures sensitivity to environment in a heritable, evolutionary-conserved trait, associated with increased information processing in the brain.•SPS moderates sensitivity to ...environments in a for-better-and-for-worse fashion.•Interaction with negative experiences, increases risk for psychopathology.•Interaction with positive experiences (including interventions), increases positive outcomes.•Objective assessment, mechanistic understanding and evidence-based interventions for high scoring individuals on SPS need to be improved.
Sensory Processing Sensitivity (SPS) is a common, heritable and evolutionarily conserved trait describing inter-individual differences in sensitivity to both negative and positive environments. Despite societal interest in SPS, scientific knowledge is lagging behind. Here, we critically discuss how SPS relates to other theories, how to measure SPS, whether SPS is a continuous vs categorical trait, its relation to other temperament and personality traits, the underlying aetiology and neurobiological mechanisms, and relations to both typical and atypical development, including mental and sensory disorders. Drawing on the diverse expertise of the authors, we set an agenda for future research to stimulate the field. We conclude that SPS increases risk for stress-related problems in response to negative environments, but also provides greater benefit from positive and supportive experiences. The field requires more reliable and objective assessment of SPS, and deeper understanding of its mechanisms to differentiate it from other traits. Future research needs to target prevention of adverse effects associated with SPS, and exploitation of its positive potential to improve well-being and mental health.
Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset ...creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.
This perspective describes predictive processing as a computational framework for understanding cortical function in the context of emerging evidence, with a focus on sensory processing. We discuss ...how the predictive processing framework may be implemented at the level of cortical circuits and how its implementation could be falsified experimentally. Lastly, we summarize the general implications of predictive processing on cortical function in healthy and diseased states.
In this perspective, Keller and Mrsic-Flogel describe the advantages of predictive processing as a computational framework for understanding cortical function in the context of emerging evidence with a focus on sensory processing.
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