Biology subjects

Lambon Ralph, M. A.

Publications and source records attributed to Lambon Ralph, M. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Multidimensional semantic representations emerge from multi-frequency representational similarity learning

Current theories of semantic representation are agnostic about how fine-grained neurophysiological activity corresponds to representation of multidimensional semantic information. By applying an innovative multivariate technique (representational similarity learning; RSL), we adjudicated three hypotheses: (1) that multidimensional semantic structure is represented within a single frequency range (e.g., gamma/high gamma); (2) that each semantic dimension is independently represented within a different frequency range; and (3) that multidimensional semantic information is "transfrequency" (at least some information emerges only when multiple frequencies are considered together). RSL was applied to time-frequency power and phase data extracted from electrocorticography (ECoG) grid electrodes on the surface of human ventral anterior temporal lobe (vATL). We found significant decoding of graded, multidimensional semantic information from a wide range of frequencies (4 - 200 Hz), but not from individual frequency bands, providing clear evidence that multidimensional semantic information is coded in a transfrequency fashion.

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bioRxiv2025

Adjudicating competing theories of semantic representation with 7T-fMRI and multivariate decoding

The anterior temporal lobes (ATLs) are known to support semantic cognition, but theories about their precise representational coding vary. We collected 7T-fMRI data with a novel acquisition sequence designed to improve signal quality in the ATLs, then employed a pioneering analytical approach (comparative multivariate decoding) to adjudicate between theories. Specifically, we applied multiple decoding methods, each making different assumptions about the content, nature or location of representations within the ATLs, then used the pattern of results across methods to adjudicate competing hypotheses. The results suggest that the ATLs represent domain-general semantic information via a multidimensional inchoate vector-space code that is anatomically clustered within and across individuals, and that posterior temporal and occipitotemporal regions utilise a similar domain-general, inchoate vector-space code. More generally, the comparative multivariate analytical framework utilised here has the potential to reveal how the brain represents, not just semantic knowledge, but any kind of information.

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bioRxiv2025

All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex

Intracranial electrophysiology offers a unique insight into the nature of information representation in the brain - it can be used to disentangle information encoded in local neuronal activity (gamma and high gamma frequencies) from information encoded via long-range interactions (lower frequencies). We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human vATL. Power in gamma (30 - 60 Hz) and high gamma (60 - 200 Hz) produced reliable decoding, indicating that semantic information is indeed expressed by local populations in vATL. However, power from a wide range of frequencies (4 - 200 Hz) produced significantly higher decoding accuracy and also exhibited the same rapidly-changing dynamic code previously observed when decoding voltage. These findings support the theory that semantic information is encoded by a local vATL "hub" that interacts with distributed cortical "spokes".

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bioRxiv2024

Word-selective EEG/MEG responses in the English language obtained with Fast Periodic Visual Stimulation (FPVS)

Fast periodic visual stimulation (FPVS) allows the recording of objective brain responses of human word discrimination (i.e., reproducible word-category-selective responses) with a high signal-to-noise ratio. This approach has been successfully employed over the last decade in a number of scalp electroencephalography (EEG) studies. Three important advances were achieved in this study: (1) robust measures of written word-selective responses with this approach have not been reported in English; (2) responses have only been reported in EEG but not with MEG, and (3) without source localization. Thus, we presented English words periodically (2 Hz) among different types of letter strings (10Hz; consonant strings, non-words, pseudowords) whilst recording simultaneous EEG and MEG in 25 participants who performed a simple non-linguistic color detection task. Data were analyzed in sensor and in source space (L2-minimum-norm estimation, MNE). With only 4 minutes of stimulation we observed a robust word discrimination response in each condition including, importantly, even when words were embedded in word-like pseudowords. This response was larger in nonwords and largest in consonant strings. We observed left-lateralized responses in all conditions in the majority of our participants. Cluster-based permutation tests revealed that these responses were left-lateralized in sensor as well as in source space, with peaks in left posterior regions. Our results demonstrate that the FPVS paradigm can elicit robust English word-discrimination responses in EEG and MEG within only a few minutes of recording time. Together with source estimation, this can provide novel insights into the neural basis of visual word recognition in healthy and clinical populations.

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bioRxiv2023

Disentangling the neural correlates of semantic and domain-general control: The roles of stimulus domain and task process

Control processes are critical for the context-appropriate use of meaningful stimuli. Similar definitions have been adopted in two distinct literatures focusing on identifying the neural correlates of semantic control and of executive control across domains (the multiple demand network). Surprisingly, despite their proposed functions varying only in relation to domain-specificity, these networks appear to differ anatomically. However, prior comparisons are confounded by variations in task design. To what extent might varying task requirements drive differences in activation patterns that are typically attributed to stimulus domain? Here, for the first time, we use functional MRI to disentangle the effects of task process and stimulus domain during cognitively demanding tasks. Participants performed an odd-one-out task requiring rule-switching, inhibition and selection processes, and an n-back working memory task, each with meaningful semantic and non-semantic stimuli, in a factorial design. Both stimulus domain and task process affected the control regions activated, indicating that task process is indeed a key factor confounding prior studies. However, core semantic control regions (left inferior frontal gyrus, left posterior temporal cortex) also showed a preference for semantic stimuli even with matched task processes, while more peripheral semantic control regions, overlapping the multiple demand network (dorsomedial prefrontal cortex, right inferior frontal gyrus), showed little preference across task or stimulus. Conversely, most multiple demand network regions were preferentially engaged for non-semantic stimuli. These results highlight the mutual importance of stimulus domain and task process in driving variation in control region engagement, both across and between semantic control and multiple demand networks. SIGNIFICANCE STATEMENTThe flexible, context-appropriate use of concepts requires the selection, inhibition and manipulation of meaningful information. These control processes are thought to be supported by different areas for conceptual processing compared to other task domains. This proposed special character of semantic control has important ramifications for the nature of executive control. However, prior assessments confound the presence of meaningful stimuli with the task operations performed. Here we disentangle the effects of task process and stimulus domain for the first time, finding critical effects of both factors on the pattern of activated control regions. The results enhance our understanding of the semantic control network and how it differs from and interacts with the domain-general multiple demand network, functionally characterising each control region.

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bioRxiv2023

The multidimensional neurocognitive geometry in Alzheimer's disease and posterior cortical atrophy

Background and ObjectivesAlzheimers disease spans heterogeneous typical and atypical phenotypes. Posterior cortical atrophy is one striking example, characterised by prominent impairment in visual and other posterior functions in contrast to typical, amnestic Alzheimers disease. The primary study objective was to establish how the similarities and differences of cognition and brain volumes within Alzheimers disease and posterior cortical atrophy (and by extension other Alzheimers disease variants), can be conceptualised as systematic variations across a transdiagnostic, graded multidimensional space. MethodsThis was a cross-sectional, single-center, observational, cohort study performed at the National Hospital for Neurology & Neurosurgery, London, UK. Data were collected from a cohort of PCA and AD patients, matched for age, disease duration and MMSE scores. There were two sets of outcome measures: (1) scores on a neuropsychological battery containing 22 tests spanning visuoperceptual and visuospatial processing, episodic memory, language, executive functions, calculation, and visuospatial processing; and (2) measures extracted from high-resolution T1-weighted volumetric MRI scans. Principal component analysis was used to extract the transdiagnostic dimensions of phenotypical variation from the detailed neuropsychological data. Voxel-based morphometry was used to examine associations between the PCA-derived clinical phenotypes and the structural measures. ResultsWe enrolled 93 PCA participants (mean: age = 59.9 yrs, MMSE = 21.2; 59/93 female) and 58 AD participants (mean: age = 57.1 yrs, MMSE = 19.7; 22/58 female). The principal component analysis for posterior cortical atrophy (sample adequacy confirmed: Kaiser-Meyer-Olkin = 0.865) extracted three dimensions accounting for 61.0% of variance in patients performance, reflecting general cognitive impairment, visuoperceptual deficits and visuospatial impairments. Plotting Alzheimers disease cases into the posterior cortical atrophy-derived multidimensional space, and vice versa, revealed graded, overlapping variations between cases along these dimensions, with no evidence for categorical-like patient clustering. Likewise, the relationship between brain volumes and scores on the extracted dimensions was overlapping for posterior cortical atrophy and Alzheimers disease cases. DiscussionThese results provide evidence supporting a reconceptualization of clinical and radiological variation in these heterogenous Alzheimers disease phenotypes as being along shared phenotypic continua spanning posterior cortical atrophy and Alzheimers disease, arising from systematic graded variations within a transdiagnostic, multidimensional neurocognitive geometry.

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bioRxiv2022

Systematic evaluation of high level visual deficits and lesions in posterior cerebral artery stroke

Knowledge about the consequences of stroke on high level vision comes primarily from single case studies of patients selected based on their behavioural profiles with deficits in the recognition of a specific visual category such as faces or words. There are, however, no systematic, detailed, large-scale evaluations of the more typical clinical behavioural and lesion profiles of impairments in high level vision that may follow posterior cerebral artery (PCA) stroke. These goals were met by the current study through the data collected in the Back of the Brain (BoB) project: to date, the largest (N=64) and most detailed examination of patients with cortical PCA strokes selected based on lesion location rather than behavioural symptoms. We present here two complementary analyses of the structural neuroimaging data and key indices of behavioural performance with the visual processing words, objects and faces: (1) a multivariate multiple regression analysis to establish the relationships between lesion volume, lesion laterality or the presence of a bilateral lesion with performance on words, objects and faces; and, (2) a voxel-based correlational method (VBCM) analysis to establish whether there are distinct or separate regions within the PCA territory that underpin the visual processing of these categories. In contrast to the characterization of specific stroke syndromes like pure alexia or prosopagnosia in the literature, most patients in our cohort showed more general deficits in high level vision (n=22) or no deficits at all (n=21). Category-selective deficits were rare (n=6), and were only found for words, which, interestingly could follow left or right hemisphere lesions. The lesion analyses mainly confirmed the pattern reported in more selective cases: word recognition impairments are associated with a left-sided pattern of damage and face recognition deficits with a bilateral albeit right-dominant lesion pattern. Importantly, however, both general and more selective impairment may follow from left or right unilateral as well as bilateral lesions. While the findings provide partial support for the relative laterality of posterior brain regions supporting reading in the left and, to a lesser extent, face processing in the right hemisphere, the results suggest that both hemispheres are involved in the visual processing of faces, words and objects. This has ramifications for researchers studying the healthy brain and for clinicians working with patients with PCA stroke. Clinicians are recommended to carry out formal assessment of face, word and object recognition as most patients are expected to present with a mixed picture of deficits.

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bioRxiv2022

Late maturation of executive control promotes conceptual development

Control processes underpinned by the prefrontal cortex are critical for generating task-appropriate behaviour across cognitive domains, yet this region develops extremely late. Traditionally, this developmental pattern is considered negative but necessary. However, an alternative (yet perhaps complementary) view suggests that a developmental period without control could support learning, particularly in the semantic domain. Here, we exploit a recent computational model to test formally whether late development of the context-sensitive use of conceptual knowledge, or semantic control, would promote concept acquisition. Simulations show that late maturation of semantic control and anatomical connectivity conspire to promote conceptual learning. Delayed control speeds conceptual learning without compromising conceptual representations, particularly when control connects to intermediate layers. To assess whether semantic control also develops late in human children, we conducted a meta-analysis of the classic triadic matching task where participants decide which of two options best matches a third. Matching can be based on taxonomic or thematic relations. When these conflict, participants must exert semantic control to determine which relation is task appropriate. Context-sensitivity develops later than conceptual knowledge with large increases between 3 and 6 years. Thus, the protracted PFC development leads to a delay in acquiring semantic control processes, benefiting conceptual learning.

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bioRxiv2021

Distinct but cooperating brain networks supporting semantic cognition

Semantic cognition is a complex brain function involving multiple processes from sensory systems, semantic systems, to domain-general cognitive systems, reflecting its multifaceted nature. However, it remain unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we investigated the neural networks involved in semantic cognition using independent component analysis (ICA). We used a semantic judgement task and a pattern matching task as a control task with two levels of difficulty to disentangle task-specific networks from domain-general networks and to delineate task-specific involvement of these networks. ICA revealed that semantic processing recruited two task-specific networks (semantic network [SN] and extended semantic network [ESN]) as well as domain general networks including the frontoparietal network (FPN) and default mode network (DMN). Specifically, two distinct semantic networks were differently modulated by task difficulty. The SN was coupled with the extended semantic network and FPN but decoupled with the DMN, whereas the ESN was synchronised with the FPN and DMN. Furthermore, the degree of decoupling between the SN and DMN was associated with semantic performance. Our findings suggest that human higher cognition is achieved by the neural dynamics of brain networks, serving distinct and shared cognitive functions depending on task demands.

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bioRxiv2021

A computational model of typical and impaired reading: the role of visual processing

Computational modelling has served as a powerful tool to advance our understanding of language processes by making theoretical ideas rigorously specified and testable (a form of " open science" for theory building). In reading research, one of the most influential computational modelling frameworks is the triangle model of reading that characterises the mappings between orthography, phonology and semantics. Currently, most instantiations of the triangle modelling framework start the processes from orthographic levels which abstract away visual processing. Moreover, without visual processing, most models do not provide an opportunity to investigate visual-related dyslexia. To bridge this crucial gap, the present study extended the existing triangle models by implementing an additional visual input. We trained the model to learn to read from visual input without pre-defined orthographic representations. The model was assessed by reading tasks in both intact and after damage (to mimic acquire alexias). The simulation results demonstrated that the model was able to name word and nonwords as well as make lexical decisions. Damage to the visual, phonological or semantic components of the model resulted in the expected reading impairments associated with pure alexia, phonological dyslexia, and surface dyslexia, respectively. The simulation results demonstrated for the first time that both typical and neurologically-impaired reading including both central and peripheral dyslexia could be addressed in this extended triangle model of reading. The findings are consistent with the primary systems account.

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bioRxiv2021

Direct neural evidence for the contrastive roles of the complementary learning systems in adult acquisition of native vocabulary.

The Complementary Learning Systems (CLS) theory provides a powerful framework for considering the acquisition, consolidation and generalisation of new knowledge. We tested this proposed neural division of labour in adults through an investigation of the consolidation and long-term retention of newly-learned native vocabulary with post-learning functional neuroimaging. Newly-learned items were compared to two conditions: (i) previously known items to highlight the similarities and differences with established vocabulary; and (ii) unknown/untrained items to provide a control for non-specific perceptual and motor-speech output. Consistent with the CLS, retrieval of newly-learned items was supported by a combination of regions associated with episodic memory (including left hippocampus) and the language-semantic areas that support established vocabulary (left inferior frontal gyrus and left anterior temporal lobe). Furthermore, there was a shifting division of labour across these two networks in line with the items consolidation status; faster naming was associated with more activation of language-semantic areas and lesser activation of episodic memory regions. Hippocampal activity during naming predicted more than half the variation in naming retention six months later.

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bioRxiv2021

The Coherent Default Mode Network is not involved in Episodic Recall or Social Cognition

Resting-state network research is extremely influential, yet the functions of many networks remain unknown. In part, this is due to typical (e.g., univariate) analyses testing the function of individual regions and not the full set of co-activated regions that form a network. Connectivity is dynamic and the function of a region may change based on its current connections. Therefore, determining the function of a network requires assessment at the network-level. Yet popular theories implicating the default mode network (DMN) in episodic memory and social cognition, rest principally upon analyses performed at the level of individual brain regions. Here we use independent component analysis to formally test the role of the DMN in episodic and social processing at the network level. As well as an episodic retrieval task, two independent datasets were employed to assess DMN function across the breadth of social cognition; a person knowledge judgement and a theory of mind task. Each task dataset was separated into networks of co-activated regions. In each, the co-activated DMN, was identified through comparison to an a priori template and its relation to the task model assessed. This co-activated DMN did not show greater activity in episodic or social tasks than high-level baseline conditions. Thus, no evidence was found to support hypotheses that the co-activated DMN is involved in explicit episodic or social processing tasks at a network-level. The networks associated with these processes are described. Implications for prior univariate findings and the functional significance of the co-activated DMN are considered.

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bioRxiv2020

Auditory beat perception is related to speech output fluency in post-stroke aphasia

Aphasia affects at least one third of stroke survivors, and there is increasing awareness that more fundamental deficits in auditory processing might contribute to impaired language performance in such individuals. We performed a comprehensive battery of psychoacoustic tasks assessing the perception of tone pairs and sequences across the domains of pitch, rhythm and timbre in 17 individuals with post-stroke aphasia and 17 controls. At the group level, we showed a significant difference in auditory perception in only one test (Dynamic Modulation detection). At the level of individual differences we demonstrated a correlation between metrical pattern (beat) perception and speech output fluency with strong effect (Spearmans rho = 0.72). This was specific in terms of the auditory tests and dissociated from more basic auditory timing perception, which did not correlate with output fluency. This was also specific in terms of the language and cognitive measures, amongst which phonological, semantic and executive function did not correlate with beat detection. We interpret the data in terms of a requirement for the analysis of the metrical structure of sound to construct fluent output, with both being a function of higher-order "temporal scaffolding". The beat perception task herein allows measurement of timing analysis without any need to account for motor output deficit, and could be a potential clinical tool to examine this. This work suggests strategies to improve fluency after stroke by training in metrical pattern perception.

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bioRxiv2020

A unified neurocomputational bilateral pathway model of spoken language production in healthy participants and recovery in post-stroke aphasia

Understanding the processes underlying normal, impaired and recovered language performance has been a long-standing goal for cognitive and clinical neuroscience. Many verbally-described hypotheses about language lateralisation and recovery have been generated. However, they have not been considered within a single, unified and implemented computational framework, and the literatures on healthy participants and patients are largely separated. These investigations also span different types of data, including behavioural results and fMRI brain activations, which augment the challenge for any unified theory. Consequently, many key issues, apparent contradictions and puzzles remain to be solved. We developed a neurocomputational, bilateral pathway model of spoken language production, designed to provide a unified framework to simulate different types of data from healthy participants and aphasic patients. The model encapsulates key computational principles (differential computational capacity, emergent division of labour across pathways, experience-dependent plasticity-related recovery) and provides an explanation for the bilateral yet asymmetric lateralisation of language in healthy participants, chronic aphasia after left rather than right hemisphere lesions, and the basis of partial recovery in patients. The model provides a formal basis for understanding the relationship between behavioural performance and brain activation. The unified model is consistent with the degeneracy and variable neuro-displacement theories of language recovery, and adds computational insights to these hypotheses regarding the neural machinery underlying language processing and plasticity-related recovery following damage. Significance StatementStudies of healthy and impaired language have generated many verbally-described hypotheses. Whilst these verbal descriptions have advanced our understanding of language processing, some explanations are mutually incompatible and it is unclear how they work mechanistically. We constructed a neurocomputational bilateral model of spoken language production to simulate a range of phenomena in healthy participants and patients with aphasia simultaneously, including language lateralisation, impaired performance after left but not right damage, and hemispheric involvement in plasticity-dependent recovery. The model demonstrates how seemly contradictory findings can be simulated within a single framework. To our knowledge, this provides the first coherent mechanistic account of language lateralisation and recovery from post-stroke aphasia.

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bioRxiv2019

Graded, multi dimensional intragroup and intergroup variations in primary progressive aphasia and post stroke aphasia.

Language impairments caused by stroke (post-stroke aphasia) and neurodegeneration (primary progressive aphasia) have overlapping symptomatology, nomenclature and are classically divided into categorical subtypes. Surprisingly, primary progressive aphasia (PPA) and post-stroke aphasia (PSA) have rarely been directly compared in detail. Rather previous studies have compared certain subtypes (e.g., semantic variants) or have focussed on a specific cognitive/linguistic task (e.g., reading). This study assessed a large range of linguistic and cognitive tasks across the full spectra of PSA and PPA. We applied varimax-rotated principal component analysis to explore the underlying structure of the variance in the assessment scores. Similar phonological, semantic and fluency-related components were found for PSA and PPA. A combined principal component analysis across the two aetiologies revealed graded intragroup and intergroup variations on all four extracted components. Classification analysis was employed to test, formally, whether there were any categorical boundaries for any subtypes of PPA or PSA. Semantic dementia proved to form a true diagnostic category (i.e., within group homogeneity and distinct between group differences), whereas there was considerable overlap and graded variations within and between other subtypes of PPA and PSA. These results suggest that (a) a multi-dimensional rather than categorical classification system may be a better conceptualisation of aphasia from both causes, and (b) despite the very different types of pathology, these broad classes of aphasia have considerable features in common.

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bioRxiv2019

Reverse-Engineering the Cortical Architecture for Controlled Semantic Cognition

We present a reverse engineering approach to deconstruct cognition into neurocomputational mechanisms and their underlying cortical architecture, using controlled semantic cognition as a test case. By systematically varying the structure of a computational model and assessing the functional consequences, we identified architectural properties necessary for generating the core functions of the semantic system. Semantic cognition presents a challenging test case as the brain must achieve two seemingly contradictory functions: abstracting context-invariant conceptual representations across time and modalities, whilst producing specific context-sensitive behaviours appropriate for the immediate task. These functions were best achieved in models possessing a single, deep multimodal hub with sparse connections from modality-specific inputs, and control systems acting on peripheral rather than deep network layers. These architectural features correspond well with those suggested by neural data, strongly supporting the efficacy of the reverse engineering approach, and further generating novel hypotheses about the neuroanatomy of controlled semantic cognition.

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bioRxiv2019

Evaluating the granularity and statistical structure of lesions and behaviour in post-stroke aphasia

The pursuit of relating the location of neural damage to the pattern of acquired language and general cognitive deficits post-stroke stems back to 19th century behavioural neurology. Whilst spatial specificity has improved dramatically over time, from the large areas of damage specified by post-mortem investigation to the millimetre precision of modern MRI, there is an underlying issue that is rarely addressed, which relates to the fact that damage to a given area of the brain is not random but constrained by the brains vasculature. Accordingly, the aim of this study was to uncover the statistical structure underlying the lesion profile in chronic aphasia post-stroke. By applying varimax-rotated principal component analysis to the lesions of 70 patients with chronic post-stroke aphasia, we identified 17 interpretable clusters, largely reflecting the vascular supply of middle cerebral artery sub-branches and other sources of individual variation in vascular supply as shown in classical angiography studies. This vascular parcellation produced smaller displacement error in simulated lesion-symptom analysis compared with individual voxels and Brodmann regions. A second principal component analysis of the patients detailed neuropsychological data revealed a four factor solution reflecting phonological, semantic, executive-demand and speech fluency abilities. As a preliminary exploration, stepwise regression was used to relate behavioural factor scores to the lesion principal components. Phonological ability was related to two components, which covered the posterior temporal region including the posterior segment of the arcuate fasciculus, and the inferior frontal gyrus. Three components were linked to semantic ability and were located in the white matter underlying the anterior temporal lobe, the supramarginal gyrus and angular gyrus. Executive-demand related to two components covering the dorsal edge of the middle cerebral artery territory, while speech fluency was linked to two components that were located in the middle frontal gyrus, precentral gyrus, and subcortical regions (putamen and thalamus). Future studies can explore in formal terms the utility of these PCA-derived lesion components for relating post-stroke lesions and symptoms.

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bioRxiv2019

Establishing two principal dimensions of cognitive variation in Logopenic Progressive Aphasia

Logopenic Progressive Aphasia (LPA) is a neurodegenerative syndrome characterised by sentence repetition and naming difficulties arising from left-lateralised temporoparietal atrophy. Clinical descriptions of LPA largely concentrate on profiling language deficits, however, accumulating evidence points to the presence of cognitive deficits, even on tasks with minimal language demands. Although non-linguistic cognitive deficits in LPA are thought to scale with disease severity, patients at discrete stages of language dysfunction display overlapping cognitive profiles, suggesting individual-level variation in cognitive performance, independent of primary language dysfunction. To address this issue, we used principal component analysis to decompose individual-level variation in cognitive performance in 43 well-characterised LPA patients who underwent multi-domain neuropsychological assessments and structural neuroimaging. The principal component analysis solution revealed the presence of two, statistically independent factors, providing stable and clinically intuitive explanations for the majority of variance in cognitive performance in the syndrome. Factor 1 reflected speech production and verbal memory deficits which typify LPA. Systematic variations were also confirmed on a second, orthogonal factor mainly comprising visuospatial and executive processes. Adopting a case-comparison approach, we further demonstrate that pairs of patients with comparable Factor 1 scores, regardless of their severity, diverge considerably on visuo-executive test performance, underscoring the inter-individual variability in cognitive profiles in comparably logopenic patients. Whole-brain voxel-based morphometry analyses revealed that speech production and verbal memory factor scores correlated with left middle frontal gyrus, while visuospatial and executive factor scores were associated with grey matter intensity of right-lateralised temporoparietal, middle frontal regions and their underlying white matter connectivity. Importantly, LPA patients with poorer visuospatial and executive factor scores demonstrated greater right-lateralised temporoparietal and frontal atrophy. Our findings demonstrate the inherent variation in cognitive performance at an individual- and group-level in LPA, suggesting the presence of a genuine co-occurring cognitive impairment that is independent of language function and disease severity.

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