Investigating Sensory Prediction in Autism Spectrum Conditions

Autism is the umbrella term for a family of neurodevelopmental disorders characterised by heterogeneous clinical presentations affecting social interaction, communication, sensory atypicalities and restricted and repetitive behaviours (DSM 5). The idea of a unifying explanation that can account for the range of cognitive, behavioural and neurological features associated with autism is attractive, but as of yet no such cognitive or physiological underpinnings have been identified. However, the last years have seen a growing interest in using approaches within the nascent field of the predictive processing framework to explore the potential causal role of aberrant prediction for the autistic phenotype. While hypothesised differences in predictive abilities have demonstrated some explanatory power for symptoms of psychotic spectrum disorders, empirical investigations into autism are still sparse. In this thesis I follow up on the theoretical work about difficulties with expectation generation in autism with three empirical studies on prediction in perception and sensory processing (Chapters 2-4). My results did not support the idea of autism as a generalised disorder of prediction; however better phenotyping in future work might help to tease apart some of the variability observed in the autism group. Furthermore I also examined the psychometric properties of two widely-used self-report questionnaires assessing autistic traits and schizotypy (Chapter 5). If latent traits are not measured equivalently across clinical and non-clinical populations, this could have implications for studies using high self-reported traits in healthy participants as proxies for the clinical condition as well as for correlational studies.Christ's College, Cambridg

Follow-up Imaging of Disk Candidates from the Disk Detective Citizen Science Project: New Discoveries and False Positives in WISE Circumstellar Disk Surveys

The Disk Detective citizen science project aims to find new stars with excess 22 m emission from circumstellar dust in the All WISE data release from the Wide-field Infrared Survey Explorer. We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5 m telescope at Palomar Observatory and with RetroCam on the 2.5 m du Pont Telescope at Las Campanas Observatory to search for background objects at 0 1512 separations from each target. Our analysis of these data leads us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most7.9%0.2% of All WISE-selected infrared excesses are good disk candidates. Applying our false-positive rates to other surveys, we find that the infrared excess searches of McDonald et al. and Marton et al. all have false-positiverates >70%. Moreover, we find that all 13 disk candidates in Theissen & West with W4 signal-to-noise ratio >3are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these,213 are newly identified disk systems. Twelve of these are candidate members of comoving pairs based on Gaia astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 m excess around two known members of the ScorpiusCentaurus association, and we identifyknown disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty of these disk candidates arecloser than 125 pc (including 26 debris disks), making them good targets for both direct-imaging exoplanetsearches

Follow-up Imaging of Disk Candidates from the Disk Detective Citizen Science Project: New Discoveries and False Positives in WISE Circumstellar Disk Surveys

The Disk Detective citizen science project aims to find new stars with excess 22 μm emission from circumstellar dust in the AllWISE data release from the Wide-field Infrared Survey Explorer. We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5 m telescope at Palomar Observatory and with RetroCam on the 2.5 m du Pont Telescope at Las Campanas Observatory to search for background objects at 0.”15–12'' separations from each target. Our analysis of these data leads us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most 7.9% ± 0.2% of AllWISE-selected infrared excesses are good disk candidates. Applying our false-positive rates to other surveys, we find that the infrared excess searches of McDonald et al. and Marton et al. all have false-positive rates >70%. Moreover, we find that all 13 disk candidates in Theissen & West with W4 signal-to-noise ratio >3 are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these, 213 are newly identified disk systems. Twelve of these are candidate members of comoving pairs based on Gaia astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 μm excess around two known members of the Scorpius–Centaurus association, and we identify known disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty of these disk candidates are closer than ~125 pc (including 26 debris disks), making them good targets for both direct-imaging exoplanet searches

The Filter Detection Task for measurement of breathing-related interoception and metacognition

The study of the brain’s processing of sensory inputs from within the body (‘interoception’) has been gaining rapid popularity in neuroscience, where interoceptive disturbances are thought to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity, decision bias, metacognitive bias, and metacognitive performance. Two major developments address some of the challenges presented by low trial numbers in interoceptive experiments: (i) a novel adaptive algorithm to maintain task performance at 70–75% accuracy; (ii) an extended hierarchical metacognitive model to estimate regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of the task and analysis developments, using both simulated data and three empirical datasets. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with clinical settings

The Filter Detection Task for measurement of breathing-related interoception and metacognition

The study of the brain’s processing of sensory inputs from within the body (‘interoception’) has been gaining rapid popularity in neuroscience, where interoceptive disturbances are thought to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity, decision bias, metacognitive bias, and metacognitive performance. Two major developments address some of the challenges presented by low trial numbers in interoceptive experiments: (i) a novel adaptive algorithm to maintain task performance at 70–75% accuracy; (ii) an extended hierarchical metacognitive model to estimate regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of the task and analysis developments, using both simulated data and three empirical datasets. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with clinical settings.ISSN:0301-0511ISSN:1873-624