scholarly journals Visual motion and decision-making in dyslexia: Evidence of reduced accumulation of sensory evidence and related neural dynamics

2021 ◽  
Author(s):  
Catherine Manning ◽  
Cameron D Hassall ◽  
Laurence T Hunt ◽  
Anthony M Norcia ◽  
Eric-Jan Wagenmakers ◽  
...  
Keyword(s):  
Decision Making ◽  
Visual Information ◽  
Visual Motion ◽  
Motion Processing ◽  
Global Motion ◽  
Perceptual Decision Making ◽  
Behavioural Responses ◽  
Visual Motion Processing ◽  
Decision Making Processes ◽  
Sensory Evidence

Children with and without dyslexia differ in their behavioural responses to visual information, particularly when required to pool dynamic signals over space and time. Importantly, multiple processes contribute to behavioural responses. Here we investigated which processing stages are affected in children with dyslexia when performing visual motion processing tasks, by combining two methods that are sensitive to the dynamic processes leading to responses. We used a diffusion model which decomposes response time and accuracy into distinct cognitive constructs, and high-density EEG. 50 children with dyslexia and 50 typically developing children aged 6 to 14 years judged the direction of motion as quickly and accurately as possible in two global motion tasks, which varied in their requirements for segregating signal-from-noise. Following our pre-registered analyses, we fitted hierarchical Bayesian diffusion models to the data, blinded to group membership. Unblinding revealed reduced evidence accumulation in children with dyslexia compared to typical children for both tasks. We also identified a response-locked EEG component which was maximal over centro-parietal electrodes which indicated a neural correlate of reduced drift-rate in dyslexia, thereby linking brain and behaviour. We suggest that children with dyslexia are slower to extract sensory evidence from global motion displays, regardless of whether they are required to segregate signal-from-noise, thus furthering our understanding of atypical perceptual decision-making processes in dyslexia.

scholarly journals Bridging sensory and language theories of dyslexia: towards a multifactorial model

2019 ◽  
Author(s):  
Gabrielle O’Brien ◽  
Jason Yeatman
Keyword(s):  
Decision Making ◽  
Phonological Processing ◽  
Visual Motion ◽  
Reading Skill ◽  
Motion Processing ◽  
List Type ◽  
Deficit Model ◽  
Visual Motion Processing ◽  
Core Deficit ◽  
Sensory Encoding

AbstractCompeting theories of dyslexia posit that reading disability arises from impaired sensory, phonological, or statistical learning mechanisms. Importantly, many theories posit that dyslexia reflects a cascade of impairments emanating from a “core deficit”. Here we collect a battery of psychophysical and language measures in 106 school-aged children to investigate whether dyslexia is best conceptualized under a core-deficit model, or as a disorder with heterogenous origins. Specifically, by capitalizing on the drift diffusion model to separate sensory encoding from task-related influences on performance in a visual motion discrimination experiment, we show that deficits in motion perception, decision making and phonological processing manifest largely independently. Based on statistical models of how variance in reading skill is parceled across measures of sensory encoding, phonological processing and decision-making, our results challenge the notion that a unifying deficit characterizes dyslexia. Instead, these findings indicate a model where reading skill is explained by several distinct, additive predictors, or risk factors, of reading (dis)ability.Research HighlightsOur research provides direct evidence that a single-mechanism, or core-deficit, model of dyslexia cannot account for the range of linguistic and sensory outcomes in children.Individual differences in visual motion processing, perceptual decision making, phonological awareness and rapid naming each account for unique variance in reading skill.Our data support an additive risk-factor model, in which multiple independent dimensions each confer risk for reading difficulties.

Motion Segmentation in Artificial and Biological Systems

1998 ◽  
Vol 53 (7-8) ◽  
pp. 622-627
Author(s):  
Walter J. Gillner
Keyword(s):  
Visual Information ◽  
Visual Motion ◽  
Obstacle Detection ◽  
Object Motion ◽  
Motion Processing ◽  
Motion Field ◽  
Detection Systems ◽  
Visual Motion Processing ◽  
Retinal Motion ◽  
Technical Vision

Abstract In the early steps of visual information processing motion is one of the most important queues for the development of spatial representations. Obstacle detection and egomotion estimation are only two examples of the powerfulness of visual motion detection systems. The underlying process of information extraction has to be active due to the observer’s capabilities of egomotion. This means that the observer’s motion has an impact on the pro­jected retinal motion field. Therefore one of the challenging tasks for biological as well as for technical vision systems is to couple retinal motion and egomotion and to uncouple egomotion and object motion. The following sections describe a model that couples visual motion processing with the egomotion parameters of a moving observer. Beneath a theoreti­cal introduction of the model an application to traffic scene analysis is presented. A t last the paper relates the model to biological motion processing systems.

scholarly journals Memory and Decision Making in the Frontal Cortex during Visual Motion Processing for Smooth Pursuit Eye Movements

Neuron ◽  
2009 ◽  
Vol 62 (5) ◽  
pp. 717-732 ◽  
Author(s):  
Natsuko Shichinohe ◽  
Teppei Akao ◽  
Sergei Kurkin ◽  
Junko Fukushima ◽  
Chris R.S. Kaneko ◽  
...  
Keyword(s):  
Decision Making ◽  
Eye Movements ◽  
Frontal Cortex ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Motion Processing ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Visual Motion Processing

scholarly journals Self-operated stimuli improve subsequent visual motion processing

2020 ◽  
Author(s):  
Giulia Sedda ◽  
David J. Ostry ◽  
Vittorio Sanguineti ◽  
Silvio P. Sabatini
Keyword(s):  
Visual Information ◽  
Visual Motion ◽  
Internal Representation ◽  
Fine Tuning ◽  
Motion Processing ◽  
Stimulus Motion ◽  
Directional Information ◽  
Movement Training ◽  
Visual Motion Processing ◽  
Perceptual Changes

Proper interpretation of visual information requires capturing the structural regularities in the visual signal and this frequently occurs in conjunction with movement. Perceptual interpretation is complicated both by transient perceptual changes that accompany motor activity, and as found in audition and somatosensation, by more persistent changes that accompany the learning of new movements. Here we asked whether motor learning also results in sustained changes to visual perception. We designed a reaching task in which participants directly controlled the visual information they received, which we term self-operated stimuli. Specifically, they trained to make movements in a number of directions. Directional information was provided by the motion of an intrinsically ambiguous moving stimulus which was directly tied to motion of the hand. We find that movement training improves perception of coherent stimulus motion, and that changes in movement are correlated with the perceptual change. No perceptual changes are observed in passive observers even when they are provided with an explicit strategy to solve perceptual grouping. Comparison of empirical perceptual data with simulations based on a Bayesian generative model of motion perception suggests that movement training promotes the fine-tuning of the internal representation of stimulus geometry. These results emphasize the role of sensorimotor interaction in determining the persistent properties in space and time that define a percept.

scholarly journals Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

2021 ◽  
Author(s):  
Catherine Manning ◽  
Cameron Dale Hassall ◽  
Laurence Hunt ◽  
Anthony Norcia ◽  
Eric-Jan Wagenmakers ◽  
...  
Keyword(s):  
Decision Making ◽  
Visual Motion ◽  
Sensory Information ◽  
Decision Time ◽  
Motion Processing ◽  
Autistic Children ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Diffusion Modelling ◽  
Evidence Accumulation

Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Our results also provide weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.

scholarly journals Flexible categorization in perceptual decision making

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Network Models ◽  
Drift Diffusion Model ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Sensory Evidence ◽  
Winner Take All

AbstractPerceptual decisions rely on accumulating sensory evidence. This computation has been studied using either drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both models can account for a large amount of data, it remains unclear whether their dynamics are qualitatively equivalent. Here we show that in the attractor model, but not in the drift diffusion model, an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision states. The increase in the number of transitions leads to a crossover between weighting mostly early evidence (primacy) to weighting late evidence (recency), a prediction we validate with psychophysical data. Between these two limiting cases, we found a novel flexible categorization regime, in which fluctuations can reverse initially-incorrect categorizations. This reversal asymmetry results in a non-monotonic psychometric curve, a distinctive feature of the attractor model. Our findings point to correcting decision reversals as an important feature of perceptual decision making.

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