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Smallwood, J.

Publications and source records attributed to Smallwood, J..

At least 37 records · Page 2Linked to original sources

Patterns of Ongoing Thought in the Real World and Their Link to Mental Health and Well-Being

The thoughts we experience in daily life have implications for our mental health and well-being. However, it is often difficult to measure thought patterns outside of laboratory conditions due to concerns about the voracity of measurements taken in daily life. To address this gap in the literature, our study set out to measure patterns of thought as they occur in daily life and assess the robustness of these measures and their associations with trait measurements of mental health and well-being. A sample of undergraduate participants completed multi-dimensional experience sampling surveys eight times per day for five days as they went around their normal lives. Principal component analysis reduced these data to identify the dimensions that explained the patterns of thought reported by our participants. We used linear modelling to map how these thought patterns related to the activities taking place at the time of the probe, highlighting good consistency within the sample, as well as substantial overlap with prior work. Multiple regression was used to examine associations between patterns of ongoing thought and aspects of mental health and well-being, highlighting a pattern of "Intrusive Distraction" that had a positive association with anxiety, and a negative association with social well-being. Notably, this thought pattern tended to be most prevalent in solo activities and was relatively suppressed when interacting with other people (either in person or virtually). Our study, therefore, highlights the use of multi-dimensional experience sampling as a tool to understand how ongoing thoughts in daily life impact on our mental health and well-being, and establishes the important role social connectedness plays in the etiology of intrusive thinking.

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Multimodal Precision Neuroimaging of the Individual Human Brain at Ultra-high fields

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

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The spatial layout of antagonistic brain regions are explicable based on geometric principles

Brain activity emerges in a dynamic landscape of regional increases and decreases that span the cortex. Increases in activity during a cognitive task are often assumed to reflect the processing of task-relevant information, while reductions can be interpreted as suppression of irrelevant activity to facilitate task goals. Here, we explore the relationship between task-induced increases and decreases in activity from a geometric perspective. Using a technique known as kriging, developed in earth sciences, we examined whether the spatial organisation of brain regions showing positive activity could be predicted based on the spatial layout of regions showing activity decreases (and vice versa). Consistent with this hypothesis we established the spatial distribution of regions showing reductions in activity could predict (i) regions showing task-relevant increases in activity in both groups of humans and single individuals; (ii) patterns of neural activity captured by calcium imaging in mice; and, (iii) showed a high degree of generalisability across task contexts. Our analysis, therefore, establishes that antagonistic relationships between brain regions are topographically determined, a spatial analog for the well documented anti-correlation between brain systems over time. Significance StatementIt is well documented that brain activity changes in response to the demands of different situations, although what gives rise to the observed cortical activity patterns remains poorly understood. Using analytic tools from earth sciences, we examined whether the landscape of regional changes in activity emerge from a set of common topographical causes. Using only regions showing decreases in activity, we could predict the landscape of regions showing increases in activity using fMRI in humans and calcium imaging in mice. Our results suggest topographical principles determine the landscape of peaks and valleys in brain activity -- a spatial analog for the well documented anti-correlation between sets of brain regions over time.

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Personality traits vary in their association with brain activity across situations.

Human cognition supports complex behaviour across a range of situations, and traits (such as personality) influence how we react in these different contexts. Although viewing traits as situationally grounded is common in social sciences it is often overlooked in neuroscience. Often studies focus on linking brain activity to trait descriptions of humans examine brain-trait associations in a single task, or, under passive conditions like wakeful rest. These studies, often referred to as brain wide association studies (BWAS) have recently become the subject of controversy because results are often unreliable even with large sample sizes. Although there are important statistical reasons why BWAS yield inconsistent results, we hypothesised that results are inconsistent because the situation in which brain activity is measured will impact the power in detecting a reliable link to a specific trait. To examine this possibility, we performed a state-space analysis in which tasks from the Human Connectome Project (HCP) were organized into a low-dimensional space based on how they activated different large-scale neural systems. We examined how individuals observed brain activity across these different contexts related to their personality. Our analysis found that for multiple personality traits (including Agreeableness, Openness to Experience and Conscientiousness) stronger associations with brain activity emerge in some tasks than others. These data establish that for specific personality traits there are situations in which reliable associations with brain activity can be identified with greater accuracy, highlighting the importance of context-bound views of understanding how brain activity links to trait variation in human behaviour. Significance statementAs a species humans act efficiently in many contexts, however, as individuals our personality makes us more specialised in some situations than others. This "if-then" view of personality is widely accepted in the social sciences but is often overlooked in neuroscience. Here we show adopting a situationally bound view of human traits provides more meaningful descriptions of a brain-trait associations than are possible in traditional brain wide association studies (BWAS) that measure brain activity in a single situation. Our results demonstrate multiple personality traits (including Agreeableness, Openness to Experience and Conscientiousness) show stronger associations with brain activity in some tasks than others, explaining why studies focusing on changes in brain activity at rest can lead to weak or contradictory results.

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MULTIMODAL GRADIENTS UNIFY LOCAL AND GLOBAL CORTICAL ORGANIZATION

AO_SCPLOWBSTRACTC_SCPLOWSpecialization of brain areas and subregions, as well as their integration into large-scale networks are key principles in neuroscience. Consolidating both local and global cortical organization, however, remains challenging. Our study developed a new approach to map global cortex-wise similarities of microstructure, structural connectivity, and functional interactions, and integrate these patterns with maps of cortical arealization. Our analysis combined repeated high-field in-vivo 7 tesla (7T) Magnetic Resonance Imaging (MRI) data collected in 10 healthy adults with a recently introduced probabilistic post-mortem atlas of cortical cytoarchitecture. We obtained multimodal eigenvectors describing cortex-wide gradients at the level of microstructural covariance, structural connectivity, and intrinsic functional interactions, and then assessed inter- and intra-area differences in cortex-wide embedding based on these multimodal eigenvectors. Inter-area similarities followed a canonical sensory-fugal gradient, with primary sensorimotor cortex being the most distinctive from all other areas, while paralimbic regions were least distinctive. This pattern largely corresponded to functional connectivity variations across different tasks collected in the same participants, suggesting that the degree of global cortical integration mirrors the functional diversity of brain areas across contexts. When studying heterogeneity within areas, we did not observe a similar relationship, despite overall higher heterogeneity in association cortices relative to paralimbic and idiotypic cortices. The results were replicated in a different dataset. Our findings highlight a close coupling between cortical arealization and global cortical motifs in shaping specialized versus integrative human brain function. SO_SCPLOWIGNIFICANCEC_SCPLOWOur work situates cytoarchitecture-derived cortical areas within multimodal gradients of cortical microstructure, connectivity, and function derived from high-definition multimodal neuroimaging. We demonstrated that primary sensory and motor areas show most distinctive gradient profiles while paralimbic areas were least distinctive, overall recapitulating a sensory-fugal axis. This axis was shown to relate to the diversity of cortical areas across different functional contexts, and findings could be replicated across an independent dataset. Overall, our work shows how frameworks of cortical arealization and macroscale gradients converge in shaping functional specialization versus integration in the human brain.

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Macroscale brain states support the control of semantic cognition

Understanding how the human brain adapts to varying cognitive demands is crucial in neuroscience. Here, we examined how networks involved in controlled semantic retrieval reconfigure themselves to generate neurocognitive states appropriate to different task contexts. We parametrically varied the demands of two semantic tasks - global association and feature matching judgments - and contrasted these effects of cognitive control with those of non-semantic tasks. We then characterized these effects on the cortical surface and within a whole-brain state space, anchored by the top three dimensions of intrinsic connectivity. Our results revealed that demanding semantic association tasks elicited more activation in the anterior regions of the prefrontal and temporal cortex. In contrast, difficult semantic feature matching tasks produced more posterior activation, aligning closely with regions engaged during multiple demanding non-semantic tasks. In both semantic feature matching and non-semantic contexts, the difficulty effects were situated towards the controlled end of a dimension capturing functional separation between cognitive control and default mode regions. Conversely, in semantic association tasks, the difficulty effects elicited similar responses across both cognitive control and default mode networks. Furthermore, controlled association and non-semantic control were located towards the heteromodal end of a heteromodal- unimodal dimension, while semantic feature matching involved a brain state that was more visual and unimodal. These findings demonstrate that a variety of brain states underpin controlled cognition. Specifically, cognitive control regions interact with heteromodal semantic knowledge system to identify contextually relevant conceptual overlaps (e.g., associating DOG with BEACH), and separate from heteromodal memory regions for modality-specific conceptual overlaps (e.g., connecting DALMATIAN with BLACK AND WHITE).

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Mapping patterns of thought onto brain activity during movie-watching

Movie-watching is a central aspect of our lives and an important paradigm for understanding the brain mechanisms behind cognition as it occurs in daily life. Contemporary views of ongoing thought argue that the ability to make sense of events in the here and now depend on the neural processing of incoming sensory information by auditory and visual cortex, which are kept in check by systems in association cortex. However, we currently lack an understanding of how patterns of ongoing thoughts map onto the different brain systems when we watch a film, partly because methods of sampling experience disrupt the dynamics of brain activity and the experience of movie-watching. Our study established a novel method for mapping thought patterns onto the brain activity that occurs at different moments of a film, which does not disrupt the time course of brain activity or the movie-watching experience. We found moments when experience sampling highlighted engagement with multi-sensory features of the film or highlighted thoughts with episodic features, regions of sensory cortex were more active and subsequent memory for events in the movie was better--on the other hand, periods of intrusive distraction emerged when activity in regions of association cortex within the frontoparietal system was reduced. These results highlight the critical role sensory systems play in the multi- modal experience of movie-watching and provide evidence for the role of association cortex in reducing distraction when we watch films. Significance statementStates like movie-watching provide a window into the brain mechanisms behind cognition in daily life. However, we know relatively little about the mapping between brain activity during movies and associated thought patterns because of difficulties in measuring cognition without disrupting how brain activity naturally unfolds. We establish a novel method to link different experiential states to brain activity during movie-watching with minimal interruptions to viewers or disruptions to brain dynamics. We found states of sensory engagement occur in moments of films when activity in visual and auditory cortex are high. In contrast, states of distraction are reduced when activity in frontoparietal regions is high. Our study, therefore, establishes both sensory and association cortex as core features of the movie-watching experience.

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Visual to default network pathways: A double dissociation between semantic and spatial cognition

Processing pathways between sensory and default mode network (DMN) regions support recognition, navigation, and memory but their organisation is not well understood. We show that functional subdivisions of visual cortex and DMN sit at opposing ends of parallel streams of information processing that support visually-mediated semantic and spatial cognition, providing convergent evidence from univariate and multivariate task responses, intrinsic functional and structural connectivity. Participants learned virtual environments consisting of buildings populated with objects, drawn from either a single semantic category or multiple categories. Later, they made semantic and spatial context decisions about these objects and buildings during functional magnetic resonance imaging. A lateral ventral occipital to frontotemporal DMN pathway was primarily engaged by semantic judgements, while a medial visual to medial temporal DMN pathway supported spatial context judgements. These pathways had distinctive locations in functional connectivity space: the semantic pathway was both further from unimodal systems and more balanced between visual and auditory-motor regions compared with the spatial pathway. When semantic and spatial context information could be integrated (in buildings containing objects from a single category), regions at the intersection of these pathways responded, suggesting that parallel processing streams interact at multiple levels of the cortical hierarchy to produce coherent memory-guided cognition.

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Memory control deficits in the sleep-deprived human brain

Sleep disturbances are associated with intrusive memories, but the neurocognitive mechanisms underpinning this relationship are poorly understood. Here, we show that an absence of sleep disrupts prefrontal inhibition of memory retrieval, and that the overnight restoration of this inhibitory mechanism is predicted by time spent in rapid eye movement (REM) sleep. The functional impairments arising from sleep loss are linked to a behavioural deficit in the ability to suppress unwanted memories, and coincide with a deterioration of deliberate patterns of self-generated thought. We conclude that sleep deprivation gives rise to intrusive memories via the disruption of neural circuits governing mnemonic inhibitory control, which may rely on REM sleep.

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Distinctive and complementary roles of default mode network subsystems in semantic cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and fronto-temporal (FT) subsystems, but its functional organisation is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial) and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based functional magnetic resonance imaging (fMRI) datasets, and localised these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more tuned states characterised by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually-coupled (scenes) and decoupled (autobiographical memory) tasks, and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally-oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks. Significance StatementWe delineate the functional organisation of DMN in semantic cognition, examining effects of perceptual coupling versus decoupling, input modality (visual/verbal), domain (social/spatial) and control demands across DMN subsystems in four fMRI datasets. These subsystems played complementary roles in semantic cognition related to their locations on gradients of intrinsic connectivity. Medial temporal and frontotemporal subsystems supported visuospatial and abstract conceptual information respectively, across both internally and externally-focussed tasks, while deactivation in core DMN was associated with focussed and externally-oriented semantic states. We conclude that both content and process are relevant to the functional architecture of DMN in semantic cognition.

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Default mode network shows distinct emotional and contextual responses yet common effects of retrieval demands across tasks

The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from sensory-motor cortex. It supports memory-based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of information to be retrieved, or both. In a picture association task, participants retrieved two types of semantic features about contexts and emotions: in the generate phase, these associations were retrieved from a novel picture, while in a switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of information being accessed. The fronto-temporal and medial temporal DMN showed a preference for emotional and contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient - a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands. Key pointsO_LIRetrieval of contextual and emotional features relies on distinct default mode subnetworks. C_LIO_LINovelty of visual input has an equivalent effect across default mode subnetworks. C_LIO_LISecondary associations retrieved from re-presented pictures activate heteromodal end of the principal gradient. C_LI

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Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE), as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. In the neocortex, alterations were characterized by reduced functional differentiation in patients in lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology are associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

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The brain's topographical organization shapes dynamic interaction patterns to support flexible behavior

Understanding how human cognition flexibly supports distinct forms of behavior is a key goal of neuroscience. Adaptive behavior relies on context-specific rules that vary across situations, as well as on stable knowledge gained from experience. However, the mechanisms that allow these influences to be appropriately balanced remain elusive. Here, we show that this cognitive flexibility is partly supported by the topographical organization of the cortex. The frontoparietal control network (FPCN) is located between regions implicated in top-down attention and memory-guided cognition. We hypothesized that the FPCN is topographically divided into discrete systems that support these distinct forms of behavior. These FPCN subsystems exhibit multiple anatomical and functional similarities to their neighboring systems (the dorsal attention network and default mode network respectively). This topographic architecture is also mirrored in the functional patterns that emerge in different situations: the FPCN subnetworks act as a unified system when long-term memory can support behavior, but they segregate into discrete units when working memory, rather than long term memory, is necessary for behavioral control. In this way, the topographic organization of brain function provides crucial insights into how the human cortex supports flexible behavior.

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Experience sampling reveals the role that covert goal states play in task-relevant behavior.

Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states, however, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state-space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established activity patterns within association cortex emphasizing the fronto-parietal network both during target detection and a covert state of deliberate task focus which was associated with better task performance. In contrast, periods of vigilance and a covert off-task state were both linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states.

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Reconfigurations of cortical manifold structure during reward-based motor learning

Adaptive motor behavior depends on the coordinated activity of multiple neural systems distributed across the brain. While the role of sensorimotor cortex in motor learning has been well-established, how higher-order brain systems interact with sensorimotor cortex to guide learning is less well understood. Using functional MRI, we examined human brain activity during a reward-based motor task where subjects learned to shape their hand trajectories through reinforcement feedback. We projected patterns of cortical and striatal functional connectivity onto a low-dimensional manifold space and examined how regions expanded and contracted along the manifold during learning. During early learning, we found that several sensorimotor areas in the Dorsal Attention Network exhibited increased covariance with areas of the salience/ventral attention network and reduced covariance with areas of the default mode network (DMN). During late learning, these effects reversed, with sensorimotor areas now exhibiting increased covariance with DMN areas. However, areas in posteromedial cortex showed the opposite pattern across learning phases, with its connectivity suggesting a role in coordinating activity across different networks over time. Our results establish the neural changes that support reward-based motor learning and identify distinct transitions in the functional coupling of sensorimotor to transmodal cortex when adapting behavior.

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The structural-functional neural architectures of implicit and explicit motor learning

Sensorimotor learning is supported by multiple competing processes that operate concurrently, making it a challenge to elucidate their neural underpinnings. Here, using human functional MRI, we identify three distinct axes of connectivity between the motor cortex and other brain regions during sensorimotor adaptation. These three axes uniquely correspond to subjects degree of implicit learning, performance errors and explicit strategy use, and involve different brain networks situated at increasing levels of the cortical hierarchy. We test the generalizability of these neural axes to a separate form of motor learning known to rely mainly on explicit processes, and show that it is only the Explicit neural axis, composed of higher-order areas in transmodal cortex, that predicts learning in this task. Together, our study uncovers multiple distinct patterns of functional connectivity with motor cortex during sensorimotor adaptation, the component processes that these patterns support, and how they generalize to other forms of motor learning.

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Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans

Core features of human cognition, for example, the experience of mind wandering, highlight the importance of the capacity to focus on information separate from the here and now. However, the brain mechanisms that underpin these self-generated states remain unclear. An emerging hypothesis is that self-generated states depend on the process of memory replay, which, in animals, is linked to sharp-wave ripples (SWRs) originating in the hippocampus. SWRs are transient high-frequency oscillations that exhibit circadian fluctuations and, in the laboratory, are important for memory and planning. Local field potentials were recorded from the hippocampus of 11 patients with epilepsy for up to 15 days, and experience sampling was used to describe their association with ongoing thought patterns. SWRs were correlated with patterns of vivid, intrusive ongoing thoughts unrelated to the task being performed, establishing their contribution to the ongoing thoughts that humans experience in daily life.

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Graded functional changes in ATL reflect both semantic content and process.

Recent work has focussed on how patterns of functional change within the temporal lobe relate to whole-brain dimensions of intrinsic connectivity variation (Margulies et al., 2016). We examined two such connectivity gradients reflecting the separation of (i) unimodal versus heteromodal and (ii) visual versus auditory-motor cortex, examining visually presented verbal associative and feature judgments, plus picture-based context and emotion generation. Functional responses along the first dimension sometimes showed graded change between modality-tuned and heteromodal cortex (in the verbal matching task), and other times showed sharp functional transitions, with deactivation at the extremes and activation in the middle of this gradient (internal generation). The second gradient revealed more visual than auditory-motor activation, regardless of content (associative, feature, context, emotion) or task process (matching/generation). We also uncovered subtle differences across each gradient for content type, which predominantly manifested as differences in relative magnitude of activation or deactivation.

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