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Numminen, J.

Publications and source records attributed to Numminen, J..

2 recordsLinked to original sources

Brain structures associated with reading and their abnormalities in dyslexia: a wholebrainanalysis

Developmental dyslexia (DD) is a highly prevalent neurodevelopmental disorder, which often has a devastating influence on the individuals academic achievement and career. Research on the neural origins of DD has continued for half a century, yielding, however, inconsistent results. The current study was set out to determine abnormalities of grey and white matter volumes in adults with DD and to shed light on neural architectures associated with reading and related skills. To this end, we conducted a whole-brain voxel based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing, to characterize the associations between neuroanatomy and skills vital for reading in DD. We found decreased volumes of grey matter in DD, comprising a left-hemispheric network including superior temporal and inferior frontal gyri, insula, the limbic system, and basal ganglia, and white matter, including the right middle temporal gyrus and hippocampus, as well as the right precuneus. These results are both consistent with the most robust previous findings on cortical abnormalities in DD and yield novel insight to the role of subcortical structures in DD, scarcely studied so far. Crucially, areas with decreased grey matter in DD overlapped with brain areas associated with technical reading skills. This supports the conclusion that the grey matter regions that we identified to have a low volume in DD are associated with the core areas vital for reading.

neuroscience↗

Spatio-temporal dynamics of face perception

The temporal and spatial neural processing of faces have been studied rigorously, but few studies have unified these dimensions to reveal the spatio-temporal dynamics postulated by the models of face processing. We used support vector machine decoding and representational similarity analysis to combine information from different locations (fMRI), timepoints (EEG), and theoretical models. By correlating information matrices derived from pair-wise decodings of neural responses to different facial expressions (neutral, happy, fearful, angry), we found early EEG timepoints (110-150 ms) to match fMRI data from early visual cortex (EVC), and later timepoints (170 - 250 ms) to match data from occipital and fusiform face areas (OFA/FFA) and posterior superior temporal sulcus (pSTS). The earliest correlations were driven by information from happy faces, and the later by more accurate decoding of fearful and angry faces. Model comparisons revealed systematic changes along the processing hierarchy, from emotional distance and visual feature coding in EVC to coding of intensity of expressions in right pSTS. The results highlight the importance of multimodal approach for understanding functional roles of different brain regions.

neuroscience↗