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Lambon Ralph, M.

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

28 records · Page 2Linked to original sources

The convergence and divergence of episodic and semantic functions across lateral parietal cortex

Several decades of neuropsychological and neuroimaging research have highlighted the importance of lateral parietal cortex (LPC) across a myriad of cognitive domains. Yet, despite the prominence of this region the underlying function of LPC remains unclear. Two domains that have placed particular emphasis on LPC involvement are semantic memory and episodic memory retrieval. From each domain, sophisticated models have been proposed as to the underlying function, as well as the more domain-general assumption that LPC is engaged by any form of internally-directed cognition (episodic and semantic retrieval both being examples if this process). Here we directly address these alternatives using a combination of fMRI, functional connectivity and DTI white-matter connectivity data. The results show that ventral LPC (angular gyrus) was positively engaged during episodic retrieval but disengaged during semantic memory retrieval. In addition, the level of activity negatively varied with task difficulty in the semantic task whereas episodic activation was independent of difficulty. In contrast, dorsal LPC (intraparietal sulcus) showed domain general activation that was positively correlated with task difficulty. In terms of functional and structural connectivity, a dorsal-ventral and anterior-posterior gradient of connectivity was found to different processing networks (e.g., mid-angular gyrus (AG) connected with episodic retrieval). We propose a unifying model in which LPC as a whole might share a common underlying neurocomputation (e.g., multimodal buffering) with variations in the emergent, expressed cognitive functions across subregions arising from differences in the underlying white matter connectivity.

neuroscience↗

Comparing short and long batteries to assess deficits and their neural bases in stroke aphasia

Multiple language assessments are necessary for diagnosing, characterising and quantifying the multifaceted deficits observed in many patients post-stroke. Current language batteries, however, tend to be an imperfect trade-off between time and sensitivity of assessment. There have hitherto been two main types of battery. Extensive batteries provide thorough information but are impractically long for application in clinical settings or large-scale research studies. Clinically-targeted batteries tend to provide superficial information about a large number of language skills in a relatively short period of time by reducing the depth of each test but, consequently, can struggle to identify mild deficits, qualify the level of each impairment or reveal the underlying component structure. In the current study, we compared these batteries across a large group of individuals with chronic stroke aphasia to determine their utility. In addition, we developed a data-driven reduced version of an extensive battery that maintained sensitivity to mild impairment, ability to grade deficits and the component structure. The underlying structure of these three language batteries (extensive, shallow and data-reduced) was analysed using cross-validation analysis and principal component analysis. This revealed a four-factor solution for the extensive and data-reduced batteries, identifying phonology, semantic skills, fluency and executive function in contrast to a two-factor solution using the shallow battery (phonological/language severity and cognitive severity). Lesion symptom mapping using participants factor scores identified convergent neural structures based on existing language models for phonology (superior temporal gyrus), semantics (inferior temporal gyrus), speech fluency (precentral gyrus) and executive function (lateral occipitotemporal cortex) based on the extensive and data-reduced batteries. The two components in the shallow battery converged with the phonology and executive function clusters. In addition, we show that multivariate prediction models could be utilised to predict the component scores using neural data, however not for every component score within every test battery. Overall, the data-reduced battery appears to be an effective way to save assessment time yet retain the underlying structure of language and cognitive deficits observed in post stroke aphasia.

neuroscience↗

Distinct and Common Neural Coding of Semantic and Non-semantic Control Demands

The flexible retrieval of knowledge is critical in everyday situations involving problem solving, reasoning and social interaction. Current theories emphasise the importance of a left-lateralised semantic control network (SCN) in supporting flexible semantic behaviour, while a bilateral multiple-demand network (MDN) is implicated in executive functions across domains. No study, however, has examined whether semantic and non-semantic demands are reflected in a common neural code within regions specifically implicated in semantic control. Using functional MRI and univariate parametric modulation analysis as well as multivariate pattern analysis, we found that semantic and non-semantic demands gave rise to both similar and distinct neural responses across control-related networks. Though activity patterns in SCN and MDN could decode the difficulty of both semantic and verbal working memory decisions, there was no shared common neural coding of cognitive demands in SCN regions. In contrast, regions in MDN showed common patterns across manipulations of semantic and working memory control demands, with successful cross-classification of difficulty across tasks. Therefore, SCN and MDN can be dissociated according to the information they maintain about cognitive demands.

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Immediate impact of transcranial magnetic stimulation on brain structure: short-term neuroplasticity following one session of cTBS

Recent evidence demonstrates that activation-dependent neuroplasticity on a structural level can occur in a short time (2 hour or less) in humans. However, the exact time scale of structural plasticity in adult human brain remains unclear. Using voxel-based morphometry (VBM), we investigated changes in gray matter (GM) after one session of continuous theta-burst stimulation (cTBS) delivered to the anterior temporal lobe (ATL). Twenty-five participants were received cTBS over the left ATL or occipital pole as a control site outside of the scanner and had structural and functional imaging. During functional imaging, participants performed a semantic association task. VBM result revealed decreased GM in the left ATL and right cerebellum after ATL stimulation compared to the control stimulation. In addition, cTBS over the left ATL induced slower reaction time in sematic task performance, reduced regional activity at the target site, and altered functional connectivity between the left and right ATL during semantic processing. Furthermore, the ATL GM changes were associated with the functional connectivity changes in the ATL-connectivity during semantic processing. These structural alterations are mirrored by functional changes in cortical excitability attributed to the GM changes and demonstrate the rapid dynamics of cortical plasticity. Our findings support fast adjusting neuronal systems, such as postsynaptic morphology changes and neuronal turnover. Our results suggest that TBS is able to produce powerful changes in regional synaptic activity in human adult brain.

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Language networks in aphasia and health: a 1000 participant Activation Likelihood Estimate analysis

Aphasia recovery post-stroke is classically and most commonly hypothesised to rely on regions that were not involved in language premorbidly, through neurocomputational invasion or engagement of quiescent homologues. Contemporary accounts have suggested, instead, that recovery might be supported by under-utilised areas of the premorbid language network, which are downregulated in health to save neural resources ( variable neurodisplacement). Despite the importance of understanding the neural bases of language recovery clinically and theoretically, there is no consensus as to which specific regions are activated more consistently in post-stroke aphasia (PSA) than healthy individuals. Accordingly, we performed an Activation Likelihood Estimation analysis of language functional neuroimaging studies in PSA and linked control data. We obtained coordinate-based functional neuroimaging data for 481 individuals with aphasia following left hemisphere stroke (one third of which was previously unpublished) and for 530 healthy controls. Instead of the language network expanding by activating novel right hemisphere regions de novo post-stroke, as would be predicted by neurocomputational invasion/quiescent homologue engagement mechanisms of recovery, we found that multiple regions throughout both hemispheres were consistently activated during language tasks in PSA and controls. Multiple undamaged regions were less consistently activated in PSA than controls, including domain-general regions of medial superior frontal cortex and right fronto-temporal cortex. In the reverse direction, the right anterior insula and inferior frontal gyrus were more consistently activated in PSA than controls, particularly for executively-demanding comprehension tasks. These regions overlap with control networks known to be recruited during difficult tasks in healthy individuals and were more consistently activated by patients during higher than lower demand tasks in this meta-analysis. Overall, these findings run counter to neurocomputational invasion of the language network into new territory or engagement of quiescent homologues. Instead, many parts of the pre-existing language network are less consistently activated in PSA, except for more consistent use of spare capacity within right hemisphere executive-control related regions (cf. variable neurodisplacement). This study provides novel insights into the language network changes that occur post-stroke. Such knowledge is essential if we are to design neurobiologically-informed therapeutic interventions to facilitate language recovery.

neuroscience↗

Enhancing vs. inhibiting semantic performance with repetitive transcranial magnetic stimulation over the anterior temporal lobe: frequency- and task- specific effects

Accumulating, converging evidence indicates that the anterior temporal lobe (ATL) appears to be the transmodal hub for semantic representation. A series of repetitive transcranial magnetic stimulation (rTMS) investigations utilizing the virtual lesion approach have established the brain-behavioural relationship between the ATL and semantic processing by demonstrating that inhibitory rTMS over the ATL induced impairments in semantic performance in healthy individuals. However, a growing body of rTMS studies suggest that rTMS might also be a tool for cognitive enhancement and rehabilitation, though there has been no previous exploration in semantic cognition. Here, we explored a potential role of rTMS in enhancing and inhibiting semantic performance with contrastive rTMS protocols (1Hz vs. 20Hz) by controlling practice effects. Our results demonstrated that it is possible to modulate semantic performance positively or negatively depending on the ATL stimulation frequency: 20Hz rTMS was optimal for facilitating cortical processing (faster RT in a semantic task) contrasting with diminished semantic performance after 1Hz rTMS. In addition to cementing the importance of the ATL to semantic representation, our findings suggest that 20Hz rTMS leads to semantic enhancement in healthy individuals and potentially could be used for patients with semantic impairments as a therapeutic tool.

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Bipartite functional fractionation within the default network supports disparate forms of internally oriented cognition

The default network (DN) becomes active when the mind is steered internally towards self-generated thoughts but turns dormant when the mind is directed externally towards the outside world. While hypotheses have been proposed to characterise the association and dissociation between different component areas of the DN, it remains unclear how they coalesce into a unitary network and fractionate into different sub-networks. Here we identified two distinct subsystems within the DN - while both subsystems show common disinterest in externally-oriented visuospatial tasks, their functional profiles differ strikingly according to the preferred contents of thoughts, preferred modes of task requirement, and causative neural dynamics among network nodes. Specifically, one subsystem comprises key nodes of the frontotemporal semantic regions. This network shows moderate dislike to visuospatial tasks, shows proclivity for task-contexts with restraints on thoughts and responses, and prefers thoughts that are focused on other people. By contrast, the other subsystem comprises the cortical midline structure and angular gyri. This network shows strong aversion to visuospatial tasks, favours task-contexts allowing free self-generated thoughts without constraints, and prefers thoughts that are focused on self. Furthermore, causative connectivity reveals that task-contexts systematically alter the dynamics within and between subsystems, suggesting flexible adaption to situational demands. This self/inward vs. others/outward separation within the broad DN resembles recent discoveries regarding a dyadic structure within the frontoparietal network that comprises regions controlling memories/thoughts vs. regions controlling sensory-motoric processes, and echoes burgeoning views that the brain is organised with a spectrum-like architecture along gradational changes of inward vs. outward preferences. SignificanceRather than construing the default network (DN) as task-negative regions that passively react to off-task mind-wandering, researchers have begun to acknowledge the active role of the DN in supporting internally-directed cognition. Here we found a striking dichotomy within the DN in terms of the subsystems task-driven functional and connectivity profiles, extending beyond previous inferences using meta-analysis and resting-state fMRI. This dichotomy reflects a local manifestation of a macro-scale gradient representation spanning across the broad cerebral cortex. This cortical gradient increases its representational complexity, from primitive sensory and motoric processing, through lexical-semantic codes for language tasks, to abstract self-generated thoughts in task-free contexts. These findings enable a framework where the separate yet related literatures of semantic cognition and default-mode processes converge.

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A unified neurocognitive model of the anterior temporal lobe contributions to semantics, language, social behaviour & face recognition

AbstractThe anterior temporal lobes (ATL) have become a key brain region of interest in cognitive and clinical neuroscience. Contemporary explorations are founded upon neuropsychological investigations of semantic dementia (SD) that describe the patients selective semantic impairment and the variations in their language, behavioural and face recognition abilities. The purpose of this investigation was to generate a single unified model which captures the known cognitive-behavioural variations in SD, and integrates with the considerable database on healthy semantic function and other patient groups. A new analytical approach was able to capture the graded neuropsychological differences and map these to the patients distribution of frontotemporal atrophy. Multiple regression and principal component analyses confirmed that the degree of generalised semantic impairment was related to the patients total, bilateral ATL atrophy. Verbal production and word-finding abilities were related to total ATL atrophy as well as to the balance of left>right ATL atrophy. Behavioural apathy was found to relate positively to the degree of orbitofrontal atrophy and negatively to total temporal volumes. Disinhibited behaviour was related to right ATL and orbitofrontal atrophy and face recognition to right ATL volumes. Rather than positing mutually-exclusive sub-categories, the data-driven model repositions semantics, language, social behaviour and face recognition into a continuous frontotemporal neurocognitive space.

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A Computational Model of Normal and Impaired Lexical Decision: Graded Semantic Effects

Lexical decision is an important paradigm in studies of visual word recognition yet the underlying mechanisms supporting the activity are not well understood. While most models of visual word recognition focus on orthographic processing as the primary locus of the lexical decision, a number of behavioural studies have suggested a flexible role for semantic processing regulated by the similarity of the nonword foil to real words. Here we developed a computational model that interactively combines visual-orthographic, phonological and semantic processing to perform lexical decisions. Importantly, the model was able to differentiate words from nonwords by dynamically integrating measures of polarity across the key processing layers. The model was more reliant on semantic information when nonword foils were pseudowords as opposed to consonant strings. Moreover, the model was able to capture a range of standard reading effects in lexical decision. Damage to the model also resulted in reading patterns observed in patients with pure alexia, phonological dyslexia, and semantic dementia, demonstrating for the first time that both normal and neurologically-impaired lexical decision can be addressed in a connectionist computational model of reading.

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Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts

Reading a book, understanding the news reports or any other behaviour involving the processing of meaningful stimuli requires the semantic system to have two main features: being active during an extended period of time and flexibly adapting the internal representation according to the changing environment. Despite being key features of many everyday tasks, formation and updating of the semantic \"gestalt\" are still poorly understood. In this fMRI study we used naturalistic stimuli and task manipulations to identify the neural network that forms and updates conceptual gestalts during time-extended integration of meaningful stimuli. Univariate and multivariate techniques allowed at drawing a distinction between networks that are crucial for the formation of a semantic gestalt (meaning integration) and those that instead are important for linking incoming cues about the current context (e.g., time, space cues) into a schema representation. Specifically, we revealed that time-extended formation of the conceptual gestalt was reflected in the neurocomputations of the anterior temporal lobe accompanied by multi-demand areas and hippocampus, with a key role of brain structures in the right hemisphere. This \"semantic gestalt network\" was strongly recruited when an update of the current semantic representation was required during narrative processing. A distinct fronto-parietal network, instead, was recruited for context integration, independently from the meaning associations between words (semantic coherence). Finally, in contrast with accounts positing that the default-mode-network (DMN) may have a crucial role in semantic cognition, our findings revealed that DMN activity was sensitive to task difficulty, but not to semantic integration. The implications of these findings for neurocognitive models of semantic cognition and the literature on narrative processing are discussed.\n\nHighlightsO_LIfMRI revealed areas and networks for semantic integration during narrative reading\nC_LIO_LIATL has a key role in the formation of the conceptual gestalt\nC_LIO_LIIFG, pMTG and dAG reflect the update of the conceptual gestalt\nC_LIO_LILeft AG (Mid-PGp) has a key role in context integration\nC_LI

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