Project DyAdd: Non-linguistic Theories of Dyslexia Predict Intelligence.

Two themes have puzzled the research on developmental and learning disorders for decades. First, some of the risk and protective factors behind developmental challenges are suggested to be shared and some are suggested to be specific for a given condition. Second, language-based learning difficulties like dyslexia are suggested to result from or correlate with non-linguistic aspects of information processing as well. In the current study, we investigated how adults with developmental dyslexia or ADHD as well as healthy controls cluster across various dimensions designed to tap the prominent non-linguistic theories of dyslexia. Participants were 18-55-year-old adults with dyslexia (n = 36), ADHD (n = 22), and controls (n = 35). Non-linguistic theories investigated with experimental designs included temporal processing impairment, abnormal cerebellar functioning, procedural learning difficulties, as well as visual processing and attention deficits. Latent profile analysis (LPA) was used to investigate the emerging groups and patterns of results across these experimental designs. LPA suggested three groups: (1) a large group with average performance in the experimental designs, (2) participants predominantly from the clinical groups but with enhanced conditioning learning, and (3) participants predominantly from the dyslexia group with temporal processing as well as visual processing and attention deficits. Despite the presence of these distinct patterns, participants did not cluster very well based on their original status, nor did the LPA groups differ in their dyslexia or ADHD-related neuropsychological profiles. Remarkably, the LPA groups did differ in their intelligence. These results highlight the continuous and overlapping nature of the observed difficulties and support the multiple deficit model of developmental disorders, which suggests shared risk factors for developmental challenges. It also appears that some of the risk factors suggested by the prominent non-linguistic theories of dyslexia relate to the general level of functioning in tests of intelligence.

Project DyAdd: implicit learning in adult dyslexia and ADHD.

In this study of the project DyAdd, implicit learning was investigated through two paradigms in adults (18-55 years) with dyslexia (n = 36) or with attention deficit/hyperactivity disorder (ADHD, n = 22) and in controls (n = 35). In the serial reaction time (SRT) task, there were no group differences in learning. However, those with ADHD exhibited faster RTs compared to other groups. In the artificial grammar learning (AGL) task, the groups did not differ from each other in their learning (i.e., grammaticality accuracy or similarity choices). Further, all three groups were sensitive to fragment overlap between learning and test-phase items (i.e., similarity choices were above chance). Grammaticality performance of control participants was above chance, but that of participants with dyslexia and participants with ADHD failed to differ from chance, indicating impaired grammaticality learning in these groups. While the main indices of AGL performance, grammaticality accuracy and similarity choices did not correlate with the neuropsychological variables that reflected dyslexia-related (phonological processing, reading, spelling, arithmetic) or ADHD-related characteristics (executive functions, attention), or intelligence, the explicit knowledge for the AGL grammar (i.e., ability to freely generate grammatical strings) correlated positively with the variables of phonological processing and reading. Further, SRT reaction times correlated positively with full scale intelligence quotient (FIQ). We conclude that, in AGL, learning difficulties of the underlying rule structure (as measured by grammaticality) are associated with dyslexia and ADHD. However, learning in AGL is not related to the defining neuropsychological features of dyslexia or ADHD. Instead, the resulting explicit knowledge relates to characteristics of dyslexia.

Simultaneity learning in vision, audition, tactile sense and their cross-modal combinations.

Latencies of sensory neurons vary depending on stimulus variables such as intensity, contrast, distance and adaptation. Therefore, different parts of an object and simultaneous environmental events could often elicit non-simultaneous neural representations. However, despite the neural discrepancies of timing, our actions and object perceptions are usually veridical. Recent results suggest that this temporal veridicality is assisted by the so-called simultaneity constancy which actively compensates for neural timing asynchronies. We studied whether a corresponding compensation by simultaneity constancy could be learned in natural interaction with the environment without explicit feedback. Brief stimuli, whose objective simultaneity/non-simultaneity was judged, consisted of flashes, clicks or touches, and their cross-modal combinations. The stimuli were presented as two concurrent trains. Twenty-eight adult participants practised unimodal (visual, auditory and tactile) and cross-modal (audiovisual, audiotactile and visuotactile) simultaneity judgement tasks in eight sessions, two sessions per week. Effects of practice were tested 7 months later. All tasks indicated improved judgements of simultaneity that were also long-lasting. This simultaneity learning did not affect relative temporal resolution (Weber fraction). Transfer of learning between practised tasks was minimal, which suggests that simultaneity learning mechanisms are not centralised but modally specific. Our results suggest that natural perceptual learning can generate simultaneity-constancy-like phenomena in a well-differentiated and long-lasting manner and concomitantly in several sensory systems. Hebbian learning can explain how experience with environmental simultaneity and non-simultaneity can develop the veridicality of perceived synchrony.