Dyslexia is a severe and persistent reading and spelling disorder caused by impairment to manipulate speech sounds. Here, we combine functional magnetic resonance brain imaging with multi-voxel pattern analysis and functional and structural connectivity analysis to disentangle whether dyslexics' phonological deficits are caused by poor quality of the phonetic representations or by difficulties in accessing intact phonetic representations. We show that phonetic representations are hosted bilaterally in primary and secondary auditory cortices, and that their neural quality is intact in adults with dyslexia. However, the functional and structural connectivity between bilateral auditory cortices and left inferior frontal gyrus (a region involved in higher-level phonological processing) is significantly hampered in dyslexics, suggesting deficient access to otherwise intact phonetic representations.Speech perception involves the mapping of spectrally complex and rapidly changing acoustic signals onto discrete and abstract phonetic sound categories or phonemes (1). Developmental dyslexia is a hereditary neurological disorder characterized by severe and persistent reading and/or spelling impairments (2). Individuals with dyslexia perform poorly on tasks that require phonological awareness, verbal short-term memory and lexical access. Performance on these phonological tasks predicts reading acquisition in both normal and dyslexic readers (3). One view is that success on these tasks reflects the quality of underlying phonological (phonetic) representations (4) and that these representations of speech sounds are distorted or less well specified in individuals with dyslexia (5). An alternative view holds that representations are intact, but access to the representations is problematic in people with dyslexia (6, 7). Here, we combine functional magnetic resonance imaging (fMRI) with multi-voxel pattern analysis (MVPA) (8-10) and functional and structural connectivity analysis to disentangle whether dyslexia is caused by poor quality of the phonetic representation or by difficulties in accessing an intact phonetic representation.We collected whole-brain functional images in 23 adults with a diagnosis of dyslexia and 22 matched normal readers (Table S1, 11-13), while they listened to different versions of four sublexical speech sounds (Fig. S1) and performed an easy phoneme discrimination task. The selection of stimuli allowed us to investigate both vowel and stop consonant discrimination, which relies on spectral versus spectrotemporal acoustic feature processing, respectively. If dyslexia is related to a deficit in the quality of phonetic representations, then we expect that the neural representations would be less robust and distinct in individuals with dyslexia than in normal readers. Given dyslexics' particular problems processing temporal cues, such as those involved in consonant discrimination (11), we expected the most prominent group differences for neural patterns distinguishing between consonants.We analyzed...

Neuroimaging studies in the last 20 years have tried to unravel the neural correlates of number processing across formats in humans and non-human primates. Results point to the intraparietal sulcus as the core area for an abstract representation of numerical quantity. On the other hand, there exist a variety of behavioral and neuroimaging data that are difficult to reconcile with the existence of such an abstract representation. In this study, we addressed this issue by applying multi-voxel pattern analysis (MVPA) to functional Magnetic Resonance Imaging (fMRI) data to unravel the neural representations of symbolic (digits) and non-symbolic (dots) numbers and their possible overlap on three different spatial scales (entire lobules, smaller regions of interest and a searchlight analysis with 2-voxel radius). Results showed that numbers in both formats are decodable in occipital, frontal, temporal and parietal regions. However, there were no overlapping representations between dots and digits on any of the spatial scales. These data suggest that the human brain does not contain an abstract representation of numerical magnitude.

In numerical cognition, there is a well-known but contested hypothesis that proposes an abstract representation of numerical magnitude in human intraparietal sulcus (IPS). On the other hand, researchers of object cognition have suggested another hypothesis for brain activity in IPS during the processing of number, namely that this activity simply correlates with the number of visual objects or units that are perceived. We contrasted these two accounts by analyzing multivoxel activity patterns elicited by dot patterns and Arabic digits of different magnitudes while participants were explicitly processing the represented numerical magnitude. The activity pattern elicited by the digit "8" was more similar to the activity pattern elicited by one dot (with which the digit shares the number of visual units but not the magnitude) compared to the activity pattern elicited by eight dots, with which the digit shares the represented abstract numerical magnitude. A multivoxel pattern classifier trained to differentiate one dot from eight dots classified all Arabic digits in the one-dot pattern category, irrespective of the numerical magnitude symbolized by the digit. These results were consistently obtained for different digits in IPS, its subregions, and many other brain regions. As predicted from object cognition theories, the number of presented visual units forms the link between the parietal activation elicited by symbolic and nonsymbolic numbers. The current study is difficult to reconcile with the hypothesis that parietal activation elicited by numbers would reflect a format-independent representation of number.

Humans are highly adept at multisensory processing of object shape in both vision and touch. Previous studies have mostly focused on where visually perceived object-shape information can be decoded, with haptic shape processing receiving less attention. Here, we investigate visuo-haptic shape processing in the human brain using multivoxel correlation analyses. Importantly, we use tangible, parametrically defined novel objects as stimuli. Two groups of participants first performed either a visual or haptic similarity-judgment task. The resulting perceptual object-shape spaces were highly similar and matched the physical parameter space. In a subsequent fMRI experiment, objects were first compared within the learned modality and then in the other modality in a one-back task. When correlating neural similarity spaces with perceptual spaces, visually perceived shape was decoded well in the occipital lobe along with the ventral pathway, whereas haptically perceived shape information was mainly found in the parietal lobe, including frontal cortex. Interestingly, ventrolateral occipito-temporal cortex decoded shape in both modalities, highlighting this as an area capable of detailed visuo-haptic shape processing. Finally, we found haptic shape representations in early visual cortex (in the absence of visual input), when participants switched from visual to haptic exploration, suggesting top-down involvement of visual imagery on haptic shape processing.

Brain disorders are often investigated in isolation, but very different conclusions might be reached when studies directly contrast multiple disorders. Here, we illustrate this in the context of specific learning disorders, such as dyscalculia and dyslexia. While children with dyscalculia show deficits in arithmetic, children with dyslexia present with reading difficulties. Furthermore, the comorbidity between dyslexia and dyscalculia is surprisingly high. Different hypotheses have been proposed on the origin of these disorders (number processing deficits in dyscalculia, phonological deficits in dyslexia) but these have never been directly contrasted in one brain imaging study. Therefore, we compared the brain activity of children with dyslexia, children with dyscalculia, children with comorbid dyslexia/dyscalculia and healthy controls during arithmetic in a design that allowed us to disentangle various processes that might be associated with the specific or common neural origins of these learning disorders.Participants were 62 children aged 9 to 12, 39 of whom had been clinically diagnosed with a specific learning disorder (dyscalculia and/or dyslexia). All children underwent fMRI scanning while performing an arithmetic task in different formats (dot arrays, digits and number words). At the behavioral level, children with dyscalculia showed lower accuracy when subtracting dot arrays, and all children with learning disorders were slower in responding compared to typically developing children (especially in symbolic formats). However, at the neural level, analyses pointed towards substantial neural similarity between children with learning disorders: Control children demonstrated higher activation levels in frontal and parietal areas than the three groups of children with learning disorders, regardless of the disorder. A direct comparison between the groups of children with learning disorders revealed similar levels of neural activation throughout the brain across these groups. Multivariate subject generalization analyses were used to statistically test the degree of similarity, and confirmed that the neural activation patterns of children with dyslexia, dyscalculia and dyslexia/dyscalculia were highly similar in how they deviated from neural activation patterns in control children. Collectively, these results suggest that, despite differences at the behavioral level, the brain activity profiles of children with different learning disorders during arithmetic may be more similar than initially thought.