Biology subjects

Duncan, J.

Publications and source records attributed to Duncan, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Dynamic layer-specific processing in the prefrontal cortex during working memory

The dorsolateral prefrontal cortex (dlPFC) is reliably engaged in working memory (WM). Evidence from non-human primates indicates that the dlPFC comprises different cytoarchitectonic layers that play distinct roles in WM subprocesses; yet the functional role of the dlPFCs laminar circuitry in human WM is not well understood. In this study, participants completed a delayed-match-to-sample WM task while undergoing functional magnetic resonance imaging (fMRI) at ultra-high resolution, which allowed us to examine layer-specific responses of the dlPFC to manipulations in WM load and motor response. We conducted univariate and multivariate analyses across all periods of the WM task: encoding, delay and retrieval. First, we observed that superficial layers activate stronger than deep layers to higher WM load during the delay period. This aligns with earlier work showing preferential superficial layer activation to WM manipulation and as such may indicate lamina-specific activation of the frontoparietal network to heightened task demands more generally. Second, we found that superficial layers show higher decoding of WM load differences than deep layers during the retrieval period. In this context, we could show that decoding of WM load in the superficial layer exhibited dynamic changes across the encoding, delay and retrieval period of the task, indicative of separate WM control processes that occur on the WM content. Last, we found that superficial and deep layers are both non-differentially involved in the motor response, contradicting earlier findings of a preferential deep layer activation in humans. Taken together, our results provide new insights into the functional laminar circuitry of the dlPFC during WM and provide further support for a dynamic account of dlPFC coding.

neuroscience↗

bioRxiv2023

Ignorance is bliss: effects of noise and metaboliccost on cortical task representations

Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits. Using mathematical analyses and task-optimized recurrent neural networks, we show that neural circuits can exhibit a range of representational geometries depending on the strength of neural noise and metabolic cost. By comparing these results with recordings from primate prefrontal cortex (PFC) over the course of learning, we show that neural activity in PFC changes in line with a minimal representational strategy. Specifically, our analyses reveal that the suppression of dynamically irrelevant stimuli is achieved by activity-silent, sub-threshold dynamics. Our results provide a normative explanation as to why PFC implements an adaptive, minimal representational strategy.

neuroscience↗

bioRxiv2023

Learning shapes neural geometry in the prefrontal cortex

The relationship between the geometry of neural representations and the task being performed is a central question in neuroscience1-6. The primate prefrontal cortex (PFC) is a primary focus of inquiry, as it can encode information with geometries that either rely on past experience7-13 or are experience agnostic3,14-16. One hypothesis is that PFC representations should evolve with learning4,17,18, from a format that supports exploration of all possible task rules to a format that minimises the encoding of task-irrelevant features4,17,18 and supports generalisation7,8. Here we test this idea by recording neural activity from PFC when learning a new rule ( XOR rule) from scratch. We show that PFC representations progress from being high dimensional, nonlinear and randomly mixed to low dimensional and rule selective. Upon generalising the rule to novel stimuli, these representations further evolve into an abstract, stimulus-invariant geometry. These findings reconcile previously conflicting accounts of PFC function by demonstrating how neural representations adapt across distinct stages of learning.

neuroscience↗

bioRxiv2022

Basis of executive functions in fine-grained architecture of cortical and subcortical human brain networks

Theoretical models suggest that executive functions rely on both domain-general and domain-specific processes. Supporting this view, prior brain imaging studies have revealed that executive activations converge and diverge within broadly characterized brain networks. However, the lack of precise anatomical mappings has impeded our understanding of the interplay between domain-general and domain-specific processes. To address this challenge, we used the high-resolution multimodal MRI approach of the Human Connectome Project to scan participants performing three canonical executive tasks: n-back, rule switching, and stop signal. The results reveal that, at the individual level, different executive activations converge within 9 domain-general territories distributed in frontal, parietal and temporal cortices. Each task exhibits a unique topography characterized by finely detailed activation gradients within domain-general territory shifted towards adjacent resting-state networks; n-back activations shift towards the default mode, rule switching towards dorsal attention and stop signal towards cingulo-opercular networks. Importantly, the strongest activations arise at multimodal neurobiological definitions of network borders. Matching results are seen in circumscribed regions of the caudate nucleus, thalamus and cerebellum. The shifting peaks of local gradients at the intersection of task-specific networks provide a novel mechanistic insight into how partially-specialised networks interact with neighbouring domain-general territories to generate distinct executive functions.

neuroscience↗

bioRxiv2022

Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings

Brain networks exist within the confines of resource limitations. As a result, a brain network must overcome metabolic costs of growing and sustaining the network within its physical space, while simultaneously implementing its required information processing. To observe the effect of these processes, we introduce the spatially-embedded recurrent neural network (seRNN). seRNNs learn basic task-related inferences while existing within a 3D Euclidean space, where the communication of constituent neurons is constrained by a sparse connectome. We find that seRNNs, similar to primate cerebral cortices, naturally converge on solving inferences using modular small-world networks, in which functionally similar units spatially configure themselves to utilize an energetically-efficient mixed-selective code. As all these features emerge in unison, seRNNs reveal how many common structural and functional brain motifs are strongly intertwined and can be attributed to basic biological optimization processes. seRNNs can serve as model systems to bridge between structural and functional research communities to move neuroscientific understanding forward.

neuroscience↗

bioRxiv2022

Neural contributions to reduced fluid intelligence across the adult lifespan

Fluid intelligence - the ability to solve novel, complex problems - declines steeply during healthy human aging. Using functional magnetic resonance imaging (fMRI), fluid intelligence has been repeatedly associated with activation of a frontoparietal brain network, and focal damage to these regions suggests that fluid intelligence depends on their integrity. It is therefore possible that age-related functional differences in frontoparietal activity contribute to the reduction in fluid intelligence. This paper reports on analysis of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data, a large, population-based, healthy, adult lifespan cohort. The data support a model in which age-related differences in fluid intelligence are partially mediated by the responsiveness of frontoparietal regions to novel problem-solving. We first replicate a prior finding of such mediation using an independent sample. We then precisely localise the mediating brain regions, and show that mediation is specifically associated with voxels most activated by cognitive demand, but not with voxels suppressed by cognitive demand. We quantify the robustness of this result to potential unmodelled confounders, and estimate the causal direction of the effects. Finally, exploratory analyses suggest that neural mediation of age-related differences in fluid intelligence is moderated by the variety of regular physical activities, more reliably than by their frequency or duration. An additional moderating role of the variety of non-physical activities emerged when controlling for head motion. A better understanding of the mechanisms that link healthy aging with lower fluid intelligence may suggest strategies for mitigating such decline. Significance StatementGlobal populations are living longer, driving urgency to understand age-related cognitive declines. Fluid intelligence is of prime importance, because it reflects performance across many domains, and declines especially steeply during healthy aging. Despite consensus that fluid intelligence is associated with particular frontoparietal brain regions, little research has investigated suggestions that under-responsiveness of these regions mediates age-related decline. We replicate a recent demonstration of such mediation, showing specific association with brain regions most activated by cognitive demand, and robustness to moderate confounding by unmodelled variables. By showing that this mediation model is moderated by the variety of regular physical activities, more reliably than by their frequency or duration, we identify a potential modifiable lifestyle factor that may help promote successful aging.

neuroscience↗

bioRxiv2022

Causal contributions of the domain-general (Multiple Demand) and the language-selective brain networks to perceptual and semantic challenges in speech comprehension

1.Listening to spoken language engages domain-general Multiple Demand (MD, fronto-parietal) regions of the human brain, in addition to domain-selective (fronto-temporal) language regions, particularly when comprehension is challenging. However, there is limited evidence that the MD network makes a functional contribution to core aspects of comprehension. In a behavioural study of volunteers (n=19) with chronic brain lesions, but without aphasia, we assessed the causal role of these networks in perceiving, comprehending and adapting to challenging spoken sentences. A first task measured word report for acoustically degraded (noise-vocoded) sentences before and after training. Participants with greater damage to MD but not language regions required more vocoder channels to achieve 50% word report indicating impaired perception. Perception improved following training, reflecting adaptation to acoustic degradation, but perceptual learning was unrelated to lesion location or extent. A second task used sentence coherence judgements to measure the speed and accuracy of comprehension of spoken sentences using lower-frequency meanings of semantically ambiguous words. Comprehension accuracy was high and unaffected by lesion location or extent. The availability of the lower-frequency meaning, as measured in a subsequent word association task, increased following comprehension (word-meaning priming). Word-meaning priming was reduced for participants with greater damage to language but not MD regions. We conclude that language and MD networks make dissociable contributions to challenging speech comprehension: using recent experience to update word meaning preferences depends on language specialised regions, whereas the domain-general MD network plays a causal role in reporting words from degraded speech.

neuroscience↗

bioRxiv2022

Functional architecture of cerebral cortex during naturalistic movie-watching

Characterizing the functional organization of cerebral cortex is a fundamental step in understanding how different kinds of information are processed in the brain. Neuroimaging studies over the past decades have uncovered the function of many cortical areas in response to selected stimulus categories. However, it is still unclear how cortical areas are organized during naturalistic visual and auditory stimulation. Here we used high-resolution functional MRI data from 176 human subjects to map the macro-architecture of the entire cerebral cortex based on responses to a 60-minute audiovisual movie stimulus. A data-driven clustering approach revealed a map of 24 functional areas/networks, each related to a specific aspect of sensory or cognitive processing. The map included three distinct executive control (domain-general) networks which showed a strong push-pull interaction with domain-specific regions in visual, auditory, and language cortex. The cortical parcellation scheme presented here provides a comprehensive and unified map of functionally defined areas, which could replace a large set of functional localizer maps.

neuroscience↗

bioRxiv2021

Comparative Analysis and Data Provenance for 1,113 Bacterial Genome Assemblies

The quality and traceability of microbial genomics data in public databases is deteriorating as they rapidly expand and struggle to cope with data curation challenges. While the availability of public genomic data has become essential for modern life sciences research, the curation of the data is a growing area of concern that has significant real-world impacts on public health epidemiology, drug discovery, and environmental biosurveillance research1-6. While public microbial genome databases such as NCBIs RefSeq database leverage the scalability of crowd sourcing for growth, they do not require data provenance to the original biological source materials or accurate descriptions of how the data was produced7. Here, we describe the de novo assembly of 1,113 bacterial genome references produced from authenticated materials sourced from the American Type Culture Collection (ATCC), each with full data provenance. Over 98% of these ATCC Standard Reference Genomes (ASRGs) are superior to assemblies for comparable strains found in NCBIs RefSeq database. Comparative genomics analysis revealed significant issues in RefSeq bacterial genome assemblies related to genome completeness, mutations, structural differences, metadata errors, and gaps in traceability to the original biological source materials. For example, nearly half of RefSeq assemblies lack details on sample source information, sequencing technology, or bioinformatics methods. We suggest there is an intrinsic connection between the quality of genomic metadata, the traceability of the data, and the methods used to produce them with the quality of the resulting genome assemblies themselves. Our results highlight common problems with " reference genomes" and underscore the importance of data provenance for precision science and reproducibility. These gaps in metadata accuracy and data provenance represent an " elephant in the room" for microbial genomics research, but addressing these issues would require raising the level of accountability for data depositors and our own expectations of data quality.

genomics↗

bioRxiv2021

Couching the brain's multiple-demand and language-specific systems within a macroscale gradient of cortical connectivity

Semantic control is the capability to operate on meaningful representations, selectively focusing on certain aspects of meaning while purposefully ignoring other aspects based on ones behavioural aim. This ability is especially vital for comprehending figurative/ambiguous language. It remains unclear, at the topographical level, why/how regions involved in semantic control seem reliably juxtaposed alongside other functionally specialised regions in the association cortex. We investigated this issue by characterising how semantic control regions topographically relate to the default-mode network (associated with memory and abstract cognition) and multiple-demand network (associated with executive control). Topographically, we confirmed that semantic control areas were sandwiched by the default-mode and multi-demand networks, forming an orderly arrangement observed both at the individual- and group-level. Functionally, semantic control regions exhibited hybrid responses, fusing a preference for cognitively demanding processing (multiple-demand) and a preference for meaningful representations (default-mode) into a domain-specific preference for difficult operations on meaningful representations. When projected onto the principal gradient of human connectome, the neural activity of semantic control showed a robustly dissociable trajectory from visuospatial control, implying different roles in the functional transition from sensation to cognition. We discuss why the hybrid functional profile of semantic control regions might result from their intermediate topographical positions.

neuroscience↗

bioRxiv2021

Fluid intelligence and naturalistic task impairments after focal brain lesions

Classical executive tasks, such as Wisconsin card-sorting and verbal fluency, are widely used as tests of frontal lobe control functions. Since the pioneering work of Shallice and Burgess (1991), it has been known that complex, naturalistic tasks can capture deficits that are missed in these classical tests. Matching this finding, deficits in several classical tasks are predicted by loss of fluid intelligence, linked to damage in a specific cortical "multiple-demand" (MD) network, while deficits in a more naturalistic task are not. To expand on these previous results, we examined the effect of focal brain lesions on three new tests - a modification of the previously-used Hotel task, a new test of task switching after extended delays, and a test of decision-making in imagined real-life scenarios. As potential predictors of impairment we measured volume of damage to a priori MD and default mode (DMN) networks, as well as cortical damage outside these networks. Deficits in the three new tasks were substantial, but were not explained by loss of fluid intelligence, or by volume of damage to either MD or DMN networks. Instead, deficits were associated with diverse lesions, and not strongly correlated with one another. The results confirm that naturalistic tasks capture cognitive deficits beyond those measured by fluid intelligence. We suggest, however, that these deficits may not arise from specific control operations required by complex behaviour. Instead, like everyday activities, complex tasks combine a rich variety of interacting cognitive components, bringing many opportunities for processing to be disturbed.

neuroscience↗

bioRxiv2021

Precise topology of adjacent domain-general and sensory-biased regions in the human brain

Recent functional MRI studies identified sensory-biased regions across much of the association cortices and cerebellum. However, their anatomical relationship to multiple-demand (MD) regions, characterized as domain-general due to their co-activation during multiple cognitive demands, remains unclear. For a better anatomical delineation, we used multimodal MRI techniques of the Human Connectome Project to scan subjects performing visual and auditory versions of a working memory (WM) task. The contrast between hard and easy WM showed strong domain generality, with essentially identical patterns of cortical, subcortical and cerebellar MD activity for visual and auditory materials. In contrast, modality preferences were shown by contrasting easy WM with baseline; most MD regions showed visual preference while immediately adjacent to cortical MD regions, there were interleaved regions of both visual and auditory preference. The results may exemplify a general motif whereby domain-specific regions feed information into and out of an adjacent, integrative MD core.

neuroscience↗

bioRxiv2021

Modulating the left inferior frontal cortex by task domain, cognitive challenge and tDCS

The left inferior frontal cortex (LIFC) is a key region for spoken language processing, but its neurocognitive architecture remains controversial. Here we assess the domain-generality vs. domain-specificity of the LIFC from behavioural, functional neuroimaging and neuromodulation data. Using concurrent fMRI and transcranial direct current stimulation (tDCS) delivered to the LIFC, we investigated how brain activity and behavioural performance are modulated by task domain (naming vs. non-naming), cognitive challenge (low vs. high), and tDCS (anodal vs. sham). The data revealed: (1) co-existence of neural signatures both common and distinct across tasks within the LIFC; (2) domain-preferential effects of task (naming); (3) significant tDCS modulations of activity in a LIFC sub-region selectively during high-challenge naming. The presence of both domain-specific and domain-general signals, and the existence of a gradient of activation where naming relied more on sub-regions within the LIFC, may help reconcile both perspectives on spoken language processing.

neuroscience↗

bioRxiv2020

A one-shot learning signal in monkey prefrontal cortex

Much animal learning is slow, with cumulative changes in behavior driven by reward prediction errors. When the abstract structure of a problem is known, however, both animals and formal learning models can rapidly attach new items to their roles within this structure, sometimes in a single trial. Frontal cortex is likely to play a key role in this process. To examine information seeking and use in a known problem structure, we trained monkeys in a novel explore/exploit task, requiring the animal first to test objects for their association with reward, then, once rewarded objects were found, to re-select them on further trials for further rewards. Many cells in the frontal cortex showed an explore/exploit preference, changing activity in a signal trial to align with one-shot learning in the monkeys behaviour. In contrast to this binary switch, these cells showed little evidence of continuous changes linked to expectancy or prediction error. Explore/exploit preferences were independent for two stages of the trial, object selection and receipt of feedback. Within an established task structure, frontal activity may control the separate operations of explore and exploit, switching in one trial between the two. Significance statementMuch animal learning is slow, with cumulative changes in behavior driven by reward prediction errors. When the abstract structure a problem is known, however, both animals and formal learning models can rapidly attach new items to their roles within this structure. To address transitions in neural activity during one-shot learning, we trained monkeys in an explore/exploit task using familiar objects and a highly familiar task structure. In contrast to continuous changes reflecting expectancy or prediction error, frontal neurons showed a binary, one-shot switch between explore and exploit. Within an established task structure, frontal activity may control the separate operations of exploring alternative objects to establish their current role, then exploiting this knowledge for further reward.

neuroscience↗

bioRxiv2020

Kinome Profiling of Gastrointestinal Stromal Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies Wee1 as Candidate Therapeutic Target

Management of gastrointestinal stromal tumor (GIST) has been revolutionized by the identification of activating mutations in KIT and PDGFRA, and the clinical application of receptor tyrosine kinase (RTK) inhibitors in the advanced disease setting. Stratification of GIST into molecularly defined subsets provides insight into clinical behavior and response to approved targeted therapies. Although these RTK inhibitors are effective in the majority of GIST, resistance to these agents remains a significant clinical problem. Development of effective treatment strategies for refractory GIST subtypes requires identification of novel targets to provide additional therapeutic options. Global kinome profiling has the potential to identify critical signaling networks and reveal protein kinases that are essential in GIST. Using Multiplexed Inhibitor Beads and Mass Spectrometry, we explored the majority of the kinome in GIST specimens from the three most common molecular subtypes to identify novel kinase targets. Kinome profiling revealed distinct signatures in GIST subtypes and identified kinases that are universally activated in all GIST, as well as kinases that are unique to each subtype. Kinome profiling in combination with loss-of-function assays identified a significant role for the G2-M tyrosine kinase, Wee1, in GIST cell survival. In vitro and in vivo studies revealed significant efficacy of MK-1775 (Wee1 inhibitor) in combination with avapritinib in KIT and PDGFRA-mutant GIST cell lines, and notable efficacy of MK-1775 as a single agent in the PDGFRA-mutant line. These studies provide strong preclinical justification for the use of MK-1775 in GIST.

cancer biology↗

bioRxiv2020

BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis

Understanding which brain regions are related to a specific neurological disorder or cognitive stimuli has been an important area of neuroimaging research. We propose BrainGNN, a graph neural network (GNN) framework to analyze functional magnetic resonance images (fMRI) and discover neurological biomarkers. Considering the special property of brain graphs, we design novel ROI-aware graph convolutional (Ra-GConv) layers that leverage the topological and functional information of fMRI. Motivated by the need for transparency in medical image analysis, our BrainGNN contains ROI-selection pooling layers (R-pool) that highlight salient ROIs (nodes in the graph), so that we can infer which ROIs are important for prediction. Furthermore, we propose regularization terms--unit loss, topK pooling (TPK) loss and group-level consistency (GLC) loss--on pooling results to encourage reasonable ROI-selection and provide flexibility to encourage either fully individual- or patterns that agree with group-level data. We apply the BrainGNN framework on two independent fMRI datasets: an Autism Spectrum Disorder (ASD) fMRI dataset and data from the Human Connectome Project (HCP) 900 Subject Release. We investigate different choices of the hyper-parameters and show that BrainGNN outperforms the alternative fMRI image analysis methods in terms of four different evaluation metrics. The obtained community clustering and salient ROI detection results show a high correspondence with the previous neuroimaging-derived evidence of biomarkers for ASD and specific task states decoded for HCP. We will make BrainGNN codes public available after acceptance.

neuroscience↗

bioRxiv2020

Prefrontal neural dynamics for behavioral decisions and attentional control

Complex neural dynamics in the prefrontal cortex contribute to context-dependent decisions and attentional competition. To analyze these dynamics, we apply demixed principal component analysis to activity of a primate prefrontal cell sample recorded in a cued target detection task. The results track dynamics of cue and object coding, feeding into movements along a target present-absent decision axis in a low-dimensional subspace of population activity. For a single stimulus, object and cue coding are seen mainly in the contralateral hemisphere. Later, a developing decision code in both hemispheres may reflect interhemispheric communication. With a target in one hemifield and a competing nontarget in the other, each hemisphere initially encodes the contralateral object, but finally, decision coding is dominated by the task-relevant target. These findings further suggest that exchange of information between hemispheres plays a key role when attentional competition resolves. Tracking complex neural events in a low-dimensional activity subspace illuminates integration of neural codes towards task-appropriate behavior, comprising a building block of learned task structure in the prefrontal cortex. AUTHOR SUMMARYFlexible adaptive processing of information is integral for everyday goal-directed behavior. To unravel dynamic representation of task-relevant information, we analyzed population activity of a primate prefrontal cell sample in a cued target detection task. In a low-dimensional neural subspace, with separate axes for cue, object identity and decision, trajectories showed initial coding of cue and object in the contralateral hemisphere, followed by coding of the behavioral decision across both hemispheres. With target and nontarget stimuli in opposite hemifields, the data suggest initial coding of the contralateral object in each hemisphere. Object coding is then rapidly shut off for the nontarget, and followed by bilateral coding of the target decision. The results bring detailed insight into task structure and information flow within and between the two frontal lobes as a decision is made and attentional competition is resolved.

neuroscience↗

bioRxiv2020

Perceived ambiguity of social interactions increases coupling between frontal and temporal nodes of the social brain

Social behaviour is coordinated by a network of brain regions, including those involved in the perception of social stimuli and those involved in complex functions like inferring perceptual and mental states and controlling social interactions. The properties and function of many of these regions in isolation is relatively well understood but little is known about how these regions interact whilst processing dynamic social interactions. To investigate whether social network connectivity is modulated by social context we collected fMRI data from monkeys viewing "affiliative", "aggressive", or "ambiguous" social interactions. We show activation relating to the perception of social interactions along both banks of the superior temporal sulcus, parietal, medial and lateral PFC and caudate nucleus. Within this network we demonstrate that fronto-temporal connectivity are significantly modulated by social context. Crucially, we link the observation of specific behaviours to changes in connectivity within our network. Viewing aggressive or affiliative behaviour was associated with a limited increase in temporo-temporal and premotor-temporal connectivity respectively. By contrast, viewing ambiguous interactions was associated with a pronounced increase in cingulate-cingulate, temporo-temporal, and cingulate-temporal connectivity. We hypothesise that this widespread network synchronisation occurs when cingulate and temporal areas coordinate their activity when more difficult social inferences are made.

neuroscience↗