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Halai, A.

Publications and source records attributed to Halai, A..

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Distance-dependent distribution thresholding in probabilistic tractography

Tractography is widely used in human studies of connectivity with respect to every brain region, function, and is explored developmentally, in adulthood, aging, and in disease. However, the core issue of how to systematically threshold, taking into account the inherent differences in connectivity values for different track lengths, and to do this in a comparable way across studies has not been solved. The study adopted Monte Carlo derived distance-dependent distributions (DDDs) to generate distance-dependent thresholds with various levels of alpha for connections of varying lengths. As a test case, we applied the DDD approach to generate a language connectome. The resulting connectome showed expected short- and long-distance structural connectivity in the close and distant regions within the language network. The finding demonstrates that the DDD approach can be used for both individual and group thresholding. Critically, it offers a standard method that can be applied to various probabilistic tracking datasets.

neuroscience↗

Flexing the principal gradient of the cerebral cortex to suit changing semantic task demands

Understanding how thought emerges from the topographical structure of the cerebral cortex is a primary goal of cognitive neuroscience. Recent work has revealed a principal gradient of intrinsic connectivity capturing the separation of sensory-motor cortex from transmodal regions of the default mode network (DMN); this is thought to facilitate memory-guided cognition. However, studies have not explored how this dimension of connectivity changes when conceptual retrieval is controlled to suit the context. We used gradient decomposition of informational connectivity in a semantic association task to establish how the similarity in connectivity across brain regions changes during familiar and more original patterns of retrieval. Multivoxel activation patterns at opposite ends of the principal gradient were more divergent when participants retrieved stronger associations; therefore, when long-term semantic information is sufficient for ongoing cognition, regions supporting heteromodal memory are functionally separated from sensory-motor experience. In contrast, when less related concepts were linked, this dimension of connectivity was reduced in strength as semantic control regions separated from the DMN to generate more flexible and original responses. We also observed fewer dimensions within the neural response towards the apex of the principal gradient when strong associations were retrieved, reflecting less complex or varied neural coding across trials and participants. In this way, the principal gradient explains how semantic cognition is organised in the human cerebral cortex: the separation of DMN from sensory-motor systems is a hallmark of the retrieval of strong conceptual links that are culturally shared. Significance statementA central task in neuroscience is to understand how cognition emerges from the topographical structure of cerebral cortex. We used fMRI during a semantic task to assess informational connectivity as participants retrieved stereotypical or more unusual associations. The principal gradient of variation in informational connectivity captured the separation of heteromodal memory regions from unimodal cortex. This separation was reduced when weaker associations were retrieved; these trials also produced higher-dimensional neural responses in heteromodal regions. We conclude that the separation of DMN from sensory-motor systems is a hallmark of the retrieval of strong conceptual links that are culturally shared, while more complex and diverse cognition can be generated as this separation in connectivity is reduced.

neuroscience↗

Creativity in Verbal Associations is Linked to Semantic Control

While memory is known to play a key role in creativity, previous studies have not isolated the critical component processes and networks. We asked participants to generate links between words that ranged from strongly related to completely unrelated in long-term memory, delineating the neurocognitive processes that underpin more unique versus stereotypical patterns of retrieval. Less creative responses to strongly associated word pairs were associated with greater engagement of episodic memory: in highly familiar situations, semantic and episodic stores converge on the same information. This pattern of retrieval was associated with greater engagement of core default mode network. In contrast, more creative responses to weakly associated word pairs were associated with the controlled retrieval of less dominant semantic information and greater recruitment of the semantic control network, which overlaps with the dorsomedial subsystem of default mode network. Consequently, although both creative/controlled and stereotypical/more automatic patterns of retrieval are associated with activation within default mode network, these processes show little overlap in activation. These findings show that creativity emerges from controlled aspects of semantic cognition.

neuroscience↗

Mapping lesion, structural disconnection, and functional disconnection to symptoms in semantic aphasia

Patients with semantic aphasia have impaired control of semantic retrieval, often accompanied by executive dysfunction following left hemisphere stroke. Many but not all of these patients have damage to the left inferior frontal gyrus, important for semantic and cognitive control. Yet semantic and cognitive control networks are highly distributed, including posterior as well as anterior components. Accordingly, semantic aphasia might not only reflect local damage but also white matter structural and functional disconnection. Here we characterise the lesions and predicted patterns of structural and functional disconnection in individuals with semantic aphasia and relate these effects to semantic and executive impairment. Impaired semantic cognition was associated with infarction in distributed left- hemisphere regions, including in the left anterior inferior frontal and posterior temporal cortex. Lesions were associated with executive dysfunction within a set of adjacent but distinct left frontoparietal clusters. Performance on executive tasks was also associated with interhemispheric structural disconnection across the corpus callosum. In contrast, poor semantic cognition was associated with small left-lateralized structurally disconnected clusters, including in the left posterior temporal cortex. Little insight was gained from functional disconnection symptom mapping. These results demonstrate that while left- lateralized semantic and executive control regions are often damaged together in stroke aphasia, these deficits are associated with distinct patterns of structural disconnection, consistent with the bilateral nature of executive control and the left-lateralized yet distributed semantic control network.

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↗