Biology subjects

Halai, A.

Publications and source records attributed to Halai, A..

8 recordsLinked to original sources

bioRxiv2026

Establishing parallel and scalar measures of executive and semantic demand: an online norming study of matched, cross-domain judgement tasks

Task demand has a long-standing history in experimental psychology, with numerous investigations of the capacity of different systems and processes under varying cognitive load. Whilst demand is a broadly used term in the literature, it is limited by a lack of cross-domain operationalisation, and thus can be a confound in many inter-domain investigations. To address this, we generated and validated two large-scale, open-source, widely applicable stimuli sets that: (i) can probe a wide, continuous range of objective behaviourally-measured processing demand, and (ii) can be directly matched across two highly contrastive cognitive domains (semantic and visuospatial processing). We normed these tasks in a large, online cohort of healthy adults, enabling future studies to utilise and benefit from reliable baseline measures of demand. Using a matching algorithm that takes into account both speed and accuracy, we then closely paired each semantic judgement trial with a trial of comparable difficulty from the corresponding visuospatial task to produce a cross domain matched set of over 400 items. Finally, we analysed the psycholinguistic and perceptual properties of these stimuli to explore some of the underlying factors driving demand.

neuroscience↗

bioRxiv2024

Distributed and integrated representations of tools in human parietal and anterior temporal regions revealed by fMRI-RSA

Classical models of tool knowledge and use are centred on dorsal and ventral parietal pathways. Theories of semantic cognition implicate a "hub-and-spoke" network, centred on the anterior temporal lobe (ATL), that underpins all concepts including tools. Despite their prominence, the two theoretical frameworks have never been brought together and the large discrepancy in the functional neuroanatomy addressed. We undertook a multiple-regression Representational Similarity Analysis (RSA) of task fMRI data with four (motor action, broad function, mechanical function, object structure) feature-based models. The motor action model correlated with the activation patterns in bilateral superior parietal lobules (SPL), while the models of broad function and mechanical effect aligned with the activation patterns in bilateral ATLs. The object-structure model correlated with activation patterns in bilateral middle occipital gyri. The results also showed that the ventral ATL activation patterns corresponded simultaneously with all RDM models except object structure. Furthermore, a standard univariate analysis using tool-familiarity ratings for parametric modulation revealed that classical tool-network regions (frontal, inferior parietal, and posterior middle temporal cortices) were increasingly active as the tool familiarity reduced. These results demonstrate that parietal and ATL regions are both crucial and motivate a major extension and revision of the neuroanatomical framework for tool use. Significance StatementThis study provides definitive evidence for convergent tool representation in human anterior temporal lobe (ATL), outside the traditionally focused parietal lobe as the critical centre for human tool-use ability. For many years the parietal lobe was considered crucial in recognizing and planning use of familiar objects, while regions in temporal lobe received little attention. Our advanced multi-voxel analysis with artefact-resistive fMRI scanning revealed that both non-motor (tool-function) and motor (kinematics for tool use) information convergently represented in the left ventral ATL, while showing other distributed regions encoding distinct types of tool information in anterior temporal and parietal regions. These findings highlight the ATLs crucial role in tool representation and necessitate a significant expansion of neuroanatomical framework for human tool-use ability.

neuroscience↗

bioRxiv2024

Comparing the effect of multi gradient echo and multi band fMRI during a semantic task

The Blood Oxygenation Level Dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is known to vary in sensitivity across the brain due to magnetic susceptibility artefacts. In particular, the ventral anterior temporal lobes (vATL) have been implicated with semantic cognition using convergent methods (i.e., neuropsychology, PET, MEG, brain stimulation) but less so with fMRI using conventional gradient-echo protocols. There are methods to alleviate signal loss but multi-echo fMRI has gained popularity. Here, additional volumes are collected that span across a range of T2* values, however, this results sub-optimum parameters (i.e., repetition times, resolution, acceleration). "Multi-band" imaging has been used with multi-echo to speed up data acquisition; however, it is unclear how these modifications contribute to fMRI sensitivity across the brain and for univariate/multivariate analyses. In the current study, we used a factorial design where we manipulated the echo and/or band to assess how well the semantic network can be detected. When comparing the precision with which activations were detected (i.e, average T-statistics), we found that multi-band protocols were beneficial, with no evidence of signal leakage artefacts. When comparing the magnitude of activations, multi-echo protocols increased activations in regions prone to susceptibility artefacts (specifically the anterior temporal lobes, ATLs). Both multi-banding and independent component analysis (ICA)-denoising of multi-echo data tended to improve multi-voxel decoding of conditions. However, multi-echo protocols reduced activation magnitude in more central regions, such as the medial temporal lobes, possibly due to higher in-plane acceleration required to collect multiple-echoes. Nonetheless, the multi-echo multi-band protocol is a promising default option for fMRI on most regions, particularly those that suffer from susceptibility artefacts, as well as offering the potential to apply advanced post-processing methods to take advantage of the increased temporal (or spatial) resolution of multi-band protocols and more principled ICA-denoising based on TE-dependence of BOLD signals.

neuroscience↗

bioRxiv2022

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↗

bioRxiv2022

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↗

bioRxiv2022

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↗

bioRxiv2021

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↗

bioRxiv2020

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↗