Lisa Cipolotti

The neuropsychological assessment of executive functions is an important part of the diagnostic process for many neurological diseases and for predicting the ability of neurological patients to function independently. Unfortunately, for the majority of commonly used executive function tests there is a paucity of updated normative data, particularly for older adults. This complicates the process of a clinically meaningful assessment. To help address this, we provide normative data for three well‐validated tests of executive functions, the Stroop Colour/Word Test, the Controlled Oral Word Association Test and the Hayling Sentence Completion Test, alongside scores from an estimate of general intellectual ability. These tests are sensitive to frontal lobe damage and provide clinicians with information about possible focal damage to the left and right frontal lobes. Percentiles are presented for five age cohorts across the adult lifespan (18–92 years). A regression equation with age and predicted full‐scale IQ also allows for the categorisation of normal and defective performance on the Stroop and Hayling tests. Given the increasing proportion of older adults requiring neuropsychological assessment, we investigated separately two groups in the older adult range: 65–79 years and 80–92 years. We found a decline in performance for older adults on all three tests. This decline was more marked amongst lower scoring older adults. We did not find a significant relationship between sex and performance on any of the three tests. The findings are discussed in the light of the cognitive reserve theory of ageing.

Raven's Advanced Progressive Matrices (APM) Set I is a validated and brief test of fluid intelligence, ideal for use in busy clinical settings. However, there is a dearth of normative data allowing an accurate interpretation of APM scores. To address this, we present normative data from across the adult lifespan (18–89 years) for the APM Set I. Data are presented in five age cohorts (total N = 352), including two older adult cohorts (65–79 years and 80–89 years), which allows age‐standardized assessment. We also present data from a validated measure of premorbid intellectual ability, which was absent from previous standardizations of longer forms of the APM. In line with previous findings, a striking age‐related decline was noted, beginning relatively early in adulthood and most marked amongst lower‐scoring individuals. Older adults did not demonstrate difficulty with specific test items or make an increased proportion of specific errors. Sex was not a significant predictor of performance. The data set is of particular use in the neuropsychological assessment of older adults, given the known susceptibility of fluid intelligence to both the effects of normal ageing and acquired brain injury in older age. The results are discussed in light of theories of neurological ageing.

Fluid intelligence is arguably the defining feature of human cognition. Yet the nature of its relationship with the brain remains a contentious topic. Influential proposals drawing primarily on functional imaging data have implicated ‘multiple demand’ frontoparietal and more widely distributed cortical networks, but extant lesion-deficit studies with greater causal power are almost all small, methodologically constrained, and inconclusive. The task demands large samples of patients, comprehensive investigation of performance, fine-grained anatomical mapping, and robust lesion-deficit inference, yet to be brought to bear on it. We assessed 165 healthy controls and 227 frontal or non-frontal patients with unilateral brain lesions on the best-established test of fluid intelligence, Raven’s Advanced Progressive Matrices, employing an array of lesion-deficit inferential models responsive to the potentially distributed nature of fluid intelligence. Non-parametric Bayesian stochastic block models were used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. Impaired performance was confined to patients with frontal lesions [F(2,387) = 18.491; P < 0.001; frontal worse than non-frontal and healthy participants P < 0.01, P F(4,385) = 12.237; P < 0.001; right worse than left and healthy participants P < 0.01, P < 0.001]. Patients with non-frontal lesions were indistinguishable from controls and showed no modulation by laterality. Neither the presence nor the extent of multiple demand network involvement affected performance. Both conventional network-based statistics and non-parametric Bayesian stochastic block modelling heavily implicated the right frontal lobe. Crucially, this localization was confirmed on explicitly disentangling functional from pathology-driven effects within a layered stochastic block model, prominently highlighting a right frontal network involving middle and inferior frontal gyrus, pre- and post-central gyri, with a weak contribution from right superior parietal lobule. Similar results were obtained with standard lesion-deficit analyses. Our study represents the first large-scale investigation of the distributed neural substrates of fluid intelligence in the focally injured brain. Combining novel graph-based lesion-deficit mapping with detailed investigation of cognitive performance in a large sample of patients provides crucial information about the neural basis of intelligence. Our findings indicate that a set of predominantly right frontal regions, rather than a more widely distributed network, is critical to the high-level functions involved in fluid intelligence. Further they suggest that Raven’s Advanced Progressive Matrices is a useful clinical index of fluid intelligence and a sensitive marker of right frontal lobe dysfunction.

Fluid intelligence is arguably the defining feature of human cognition. Yet the nature of its relationship with the brain remains a contentious topic. Influential proposals drawing primarily on functional imaging data have implicated “multiple demand” frontoparietal and more widely distributed cortical networks, but extant lesion-deficit studies with greater causal power are almost all small, methodologically constrained, and inconclusive. The task demands large samples of patients, comprehensive investigation of performance, fine-grained anatomical mapping, and robust lesion-deficit inference, yet to be brought to bear on it. We assessed 165 healthy controls and 227 frontal or non-frontal patients with unilateral brain lesions on the best-established test of fluid intelligence, Raven’s Advanced Progressive Matrices, employing an array of lesion-deficit inferential models responsive to the potentially distributed nature of fluid intelligence. Non-parametric Bayesian stochastic block models were used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. Impaired performance was confined to patients with frontal lesions ( F (2,387) = 18.491; p < .001; frontal worse than non-frontal and healthy participants p < .01; p <.001), more marked on the right than left ( F (4,385) = 12.237; p < .001; right worse than left and healthy participants p <.01; p <.001). Patients with non-frontal lesions were indistinguishable from controls and showed no modulation by laterality. Neither the presence nor the extent of multiple demand network involvement affected performance. Both conventional network-based statistics and non-parametric Bayesian stochastic block modelling heavily implicated the right frontal lobe. Crucially, this localisation was confirmed on explicitly disentangling functional from pathology-driven effects within a layered stochastic block model, prominently highlighting a right frontal network involving middle and inferior frontal gyrus, pre- and post-central gyri, with a weak contribution from right superior parietal lobule. Similar results were obtained with standard lesion-deficit analyses. Our study represents the first large-scale investigation of the distributed neural substrates of fluid intelligence in the focally injured brain. Combining novel graph-based lesion-deficit mapping with detailed investigation of cognitive performance in a large sample of patients provides crucial information about the neural basis of intelligence. Our findings indicate that a set of predominantly right frontal regions, rather than a more widely distributed network, is critical to the high-level functions involved in fluid intelligence. Further they suggest that Raven’s Advanced Progressive Matrices is a useful clinical index of fluid intelligence and a sensitive marker of right frontal lobe dysfunction.

Fabry disease (FD) is an X-linked lysosomal storage disorder with multi-system involvement including cerebrovascular disease. Patients with FD also have a high risk of ischaemic stroke and TIA. White matter hyperintensities are common, but their clinical impact on cognition remains uncertain. Previous studies have examined the neuropsychological profile of FD, but have been inconclusive in part due to methodological limitations including small sample sizes. We sought to address these limitations in a case-control study of 26 patients with Fabry disease with mild to moderate disease symptoms matched with 18 healthy controls for age and premorbid intellectual level. We obtained detailed neuropsychological data and MRI neuroimaging data on the severity of white matter changes. Mood was accounted for as a possible confounder. Our results showed significant compromise of executive functions and information processing speed for the FD group. Error analyses suggested that the compromise of executive functions could not be entirely accounted for by slowed information processing speed. We demonstrated significant correlations between cognitive decline and the overall volume of white matter hyperintensities in the FD group. Our results point to significant compromise of cognition in FD even without stroke or mood difficulties. This suggests that neuropsychological assessment and rehabilitation should be routinely offered to patients with FD.

The voluntary generation of non-overlearned responses is usually assessed with phonemic fluency. Like most frontal tasks, it draws upon different complex processes and systems whose precise nature is still incompletely understood. Many claimed aspects regarding the pattern of phonemic fluency performance and its underlying anatomy remain controversial. Major limitations of past investigations include small sample size, scant analysis of phonemic output and methodologically insufficient lesion analysis approaches. We investigated a large number of patients with focal unilateral right or left frontal (n = 110) or posterior (n = 100) or subcortical (n = 65) lesions imaged with magnetic resonance or computed tomography and compared their performance on the number of overall responses, words produced over time, extremely infrequent/unknown words and inappropriate words generated. We also employed, for the first time parcel‐based lesion-symptom mapping, tract-wise statistical analysis as well as Bayesian multi-variate analysis based on meta-analytically defined functional region of interest, including their interactions. We found that left frontal damage was associated with greater impairment than right frontal or posterior damage on overall fluency performance, suggesting that phonemic fluency shows specificity to frontal lesions. We also found that subcorticals, similar to frontals, performed significantly worse than posteriors on overall performance suggesting that subcortical regions are also involved. However, only frontal effects were found for words produced over time, extremely infrequent/unknown and inappropriate words. Parcel‐based lesion-symptom mapping analysis found that worse fluency performance was associated with damage to the posterior segment of the left frontal middle and superior gyrus, the left dorsal anterior cingulate gyrus and caudate nucleus. Tract-wise statistical analysis revealed that disconnections of left frontal tracts are critical. Bayesian multi-variate models of lesions and disconnectome maps implicated left middle and inferior frontal and left dorsomedial frontal regions. Our study suggests that a set of well localized left frontal areas together with subcortical regions and several left frontal tracts are critical for word generation. We speculate that a left lateralized network exists. It involves medial, frontal regions supporting the process of ‘energization’, which sustains activation for the duration of the task and middle and inferior frontal regions concerned with ‘selection’, required due to the competition produced by associated stored words, respectively. The methodology adopted represents a promising and empirically robust approach in furthering our understanding of the neurocognitive architecture underpinning executive processes.

Cerebral white matter pathology is a common CNS manifestation of Fabry disease, visualized as white matter hyperintensities on MRI in 42–81% of patients. Diffusion tensor imaging (DTI) MRI is a sensitive technique to quantify microstructural damage within the white matter with potential value as a disease biomarker. We evaluated the pattern of DTI abnormalities in Fabry disease, and their correlations with cognitive impairment, mood, anxiety, disease severity and plasma lyso-Gb3 levels in 31 patients with genetically proven Fabry disease and 19 age-matched healthy control subjects. We obtained average values of fractional anisotropy and mean diffusivity within the white matter and performed voxelwise analysis with tract-based spatial statistics. Using a standardized neuropsychological test battery, we assessed processing speed, executive function, anxiety, depression and disease severity. The mean age (% male) was 44.1 (45%) for patients with Fabry disease and 37.4 (53%) for the healthy control group. In patients with Fabry disease, compared to healthy controls the mean average white matter fractional anisotropy was lower in [0.423 (standard deviation, SD 0.023) versus 0.446 (SD 0.016), P = 0.002] while mean average white matter mean diffusivity was higher (749 × 10⁻⁶ mm²/s (SD 32 × 10⁻⁶) versus 720 × 10⁻⁶ mm²/s (SD 21 × 10⁻⁶), P = 0.004]. Voxelwise statistics showed that the diffusion abnormalities for both fractional anisotropy and mean diffusivity were anatomically widespread. A lesion probability map showed that white matter hyperintensities also had a wide anatomical distribution with a predilection for the posterior centrum semiovale. However, diffusion abnormalities in Fabry disease were not restricted to lesional tissue; compared to healthy controls, the normal appearing white matter in patients with Fabry disease had reduced fractional anisotropy [0.422 (SD 0.022) versus 0.443 (SD 0.017) P = 0.003] and increased mean diffusivity [747 × 10⁻⁶ mm²/s (SD 26 × 10⁻⁶) versus 723 × 10⁻⁶ mm²/s (SD 22 × 10⁻⁶), P = 0.008]. Within patients, average white matter fractional anisotropy and white matter lesion volume showed statistically significant correlations with Digit Symbol Coding Test score (r = 0.558, P = 0.001; and r = −0.633, P ≤ 0.001, respectively). Average white matter fractional anisotropy correlated with the overall Mainz Severity Score Index (r = −0.661, P ≤ 0.001), while average white matter mean diffusivity showed a strong correlation with plasma lyso-Gb3 levels (r = 0.559, P = 0.001). Our findings using DTI confirm widespread areas of microstructural white matter disruption in Fabry disease, extending beyond white matter hyperintensities seen on conventional MRI. Moreover, diffusion measures show strong correlations with cognition (processing speed), clinical disease severity and a putative plasma biomarker of disease activity, making them promising quantitative biomarkers for monitoring Fabry disease severity and progression.