Centanni, T. M. | bioRxiv Science

bioRxiv2024

Use of a predictor cue during a speech sound discrimination task in a Cntnap2 knockout rat model of autism

Autism is a common neurodevelopmental disorder that despite its complex etiology, is marked by deficits in prediction that manifest in a variety of domains including social interactions, communication, and movement. The tendency of individuals with autism to focus on predictable schedules and interests that contain patterns and rules highlights the likely involvement of the cerebellum in this disorder. One candidate-autism gene is contact in associated protein 2 (CNTNAP2), and variants in this gene are associated with sensory deficits and anatomical differences. It is unknown, however, whether this gene directly impacts the brains ability to make and evaluate predictions about future events. The current study was designed to answer this question by training a genetic knockout rat on a rapid speech sound discrimination task. Rats with Cntnap2 knockout (KO) and their littermate wildtype controls (WT) were trained on a validated rapid speech sound discrimination task that contained unpredictable and predictable targets. We found that although both genotype groups learned the task in both unpredictable and predictable conditions, the KO rats responded more often to distractors during training as well as to the target sound during the predictable testing conditions compared to the WT group. There were only minor effects of sex on performance and only in the unpredictable condition. The current results provide preliminary evidence that removal of this candidate-autism gene may interfere with the learning of unpredictable scenarios and enhance reliance on predictability. Future research is needed to probe the neural anatomy and function that drives this effect.

animal behavior and cognition↗

bioRxiv2020

Distinct neural substrates of individual differences in components of reading comprehension in adults with or without dyslexia

Reading comprehension is a complex task that depends on multiple cognitive and linguistic processes. According to the updated Simple View of Reading framework, in adults, individual variation in reading comprehension can be largely explained by combined variance in three component abilities: (1) decoding accuracy, (2) fluency, and (3) language comprehension. Here we asked whether the neural correlates of the three components are different in adults with dyslexia as compared to typically-reading adults and whether the relative contribution of these correlates to reading comprehension is similar in the two groups. We employed a novel naturalistic fMRI reading task to identify the neural correlates of individual differences in the three components using whole-brain and literature-driven regions-of-interest approaches. Across all participants, as predicted by the simple view framework, we found distinct patterns of associations with linguistic and domain-general regions for the three components, and that the left-hemispheric neural correlates of language comprehension in the angular and posterior temporal gyri made the largest contributions to explaining out-of-scanner reading comprehension performance. These patterns differed between the two groups. In typical adult readers, better fluency was associated with greater activation of left occipitotemporal regions, better comprehension with lesser activation in prefrontal and posterior parietal regions, and there were no significant associations with decoding. In adults with dyslexia, better fluency was associated with greater activation of bilateral inferior parietal regions, better comprehension was associated with greater activation in some prefrontal clusters and lower in others, and better decoding skills were associated with lesser activation of bilateral prefrontal and posterior parietal regions. Extending the behavioral findings of skill-level differences in the relative contribution of the three components to reading comprehension, the relative contributions of the neural correlates to reading comprehension differed based on dyslexia status. These findings reveal some of the neural correlates of individual differences in the three components and the underlying mechanisms of reading comprehension deficits in adults with dyslexia.

neuroscience↗