Clinical phenotyping of primary progressive aphasia has largely focused on speech and language presentations, leaving other cognitive domains under-examined. This study investigated the diagnostic utility of visuospatial profiles and examined their neural basis among the three main primary progressive aphasia variants. We studied the neuropsychological performances of 118 primary progressive aphasia participants and 30 cognitively normal controls, across 11 measures of visuospatial cognition, and investigated their neural correlates via voxel-based morphometry analysis using visuospatial composite scores derived from principal component analysis. The principal component analysis identified three main factors: visuospatial-executive, visuospatial-memory and visuomotor components. Logopenic variant primary progressive aphasia performed significantly worst across all components; nonfluent/agrammatic variant primary progressive aphasia showed deficits in the visuospatial-executive and visuomotor components compared with controls; and the semantic variant primary progressive aphasia scored significantly lower than nonfluent/agrammatic variant primary progressive aphasia and control in the visuospatial-memory component. Grey matter volumes over the right parieto-occipital cortices correlated with visuospatial-executive performance; volumetric changes in the right anterior parahippocampal gyrus and amygdala were associated with visuospatial-memory function, and visuomotor composite scores correlated significantly with the grey matter volume at the right precentral gyrus. Discriminant function analysis identified three visuospatial measures: Visual Object and Space Perception and Benson figure copy and recall test, which classified 79.7% (94/118) of primary progressive aphasia into their specific variant. This study shows that each primary progressive aphasia variant also carries a distinctive visuospatial cognitive profile that corresponds with grey matter volumetric changes and in turn can be largely represented by their performance on the visuomotor, visuospatial-memory and executive functions.

Introduction

Most studies of dyslexia focus on domains of impairment (e.g., reading and phonology, among others), but few examine possible strengths. In the present study, we investigated semantic fluency as a cognitive strength in English-speaking children with dyslexia aged 8-13.

Methods

Ninety-seven children with dyslexia completed tests of letter and semantic verbal fluency, standardized measures of reading and cognitive functions, and task-free resting-state functional magnetic resonance imaging (rs-fMRI). First, we adjusted performance on semantic fluency by letter fluency and created a residual score that was used to separate participants into high (residual >0) or average (residual <0) semantic performance groups. We then employed a psycholinguistic clustering and switching approach to the semantic fluency task and performed dynamic task-free rs-fMRI connectivity analysis to reveal group differences in brain dynamics.

Results

High and average semantic fluency groups were well-matched on demographics and letter fluency but differed on their psycholinguistic patterns on the semantic fluency task. The high semantic fluency group, compared to the average semantic fluency group, produced a higher number of words within each cluster, a higher max cluster size, and a higher number of switches. Differential dynamic rs-fMRI connectivity (shorter average dwell time and greater brain state switches) was observed between the high and average groups in a large-scale bilateral frontal-temporal-occipital network.

Discussion

These data demonstrate that a subgroup of children with dyslexia perform above average on semantic fluency tasks and their performance is strongly linked to distinct psycholinguistic patterns and differences in a task-free resting-state brain network, which includes regions previously implicated in semantic processing. This work highlights that inter-individual differences should be taken into account in dyslexia and reveals a cognitive area of strength for some children with dyslexia that could be leveraged for reading interventions.

Diagnostic criteria for dyslexia describe specific reading difficulties, and single-deficit models, including the phonological deficit theory, have prevailed. Children seeking diagnosis, however, do not always show phonological deficits, and may present with strengths and challenges beyond reading. Through extensive neurological, neuropsychological, and academic evaluation, we describe four children with visuospatial, socio-emotional, and attention impairments and spared phonology, alongside long-standing reading difficulties. Diffusion tensor imaging revealed white matter alterations in inferior longitudinal, uncinate, and superior longitudinal fasciculi versus neurotypical children. Findings emphasize that difficulties may extend beyond reading in dyslexia and underscore the value of deep phenotyping in learning disabilities.

Prior research has revealed distinctive patterns of impaired language abilities across the three variants of Primary Progressive Aphasia (PPA): nonfluent/agrammatic (nfvPPA), logopenic (lvPPA) and semantic (svPPA). However, little is known about whether, and to what extent, non-verbal cognitive abilities, such as processing speed, are impacted in PPA patients. This is because neuropsychological tests typically contain linguistic stimuli and require spoken output, being therefore sensitive to verbal deficits in aphasic patients. The aim of this study is to investigate potential differences in processing speed between PPA patients and healthy controls, and among the three PPA variants, using a brief non-verbal tablet-based task (Match) modeled after the WAIS-III digit symbol coding test, and to determine its neural correlates. Here, we compared performance on the Match task between PPA patients (n = 61) and healthy controls (n = 59) and across the three PPA variants. We correlated performance on Match with voxelwise gray and white matter volumes. We found that lvPPA and nfvPPA patients performed significantly worse on Match than healthy controls and svPPA patients. Worse performance on Match across PPA patients was associated with reduced gray matter volume in specific parts of the left middle frontal gyrus, superior parietal lobule, and precuneus, and reduced white matter volume in the left parietal lobe. To conclude, our behavioral findings reveal that processing speed is differentially impacted across the three PPA variants and provide support for the potential clinical utility of a tabled-based task (Match) to assess non-verbal cognition. In addition, our neuroimaging findings confirm the importance of a set of fronto-parietal regions that previous research has associated with processing speed and executive control. Finally, our behavioral and neuroimaging findings combined indicate that differences in processing speed are largely explained by the unequal distribution of atrophy in these fronto-parietal regions across the three PPA variants.