Biology subjects

Hampshire, A.

Publications and source records attributed to Hampshire, A..

15 recordsLinked to original sources

bioRxiv2026

Multimodal imaging suggests potential immune-vascular contributions to altered regional brain perfusion and oxygen metabolism in Post-COVID-19 Syndrome

Post-COVID-19 Syndrome (PCS) frequently presents with persistent fatigue, cognitive impairment, and emotional symptoms. Although structural brain changes remain subtle, growing evidence implicates functional and metabolic disruptions in ongoing symptomatology. We used multimodal MRI to investigate cerebral perfusion and oxygen metabolism in PCS and examined their associations with cognitive function and peripheral biomarkers. We enrolled 40 individuals with prior mild SARS-CoV-2 infection, including 20 with persistent fatigue and 20 recovered controls matched for age, sex, BMI, and acute COVID-19 severity. Participants underwent structural MRI, arterial spin labelling (ASL) to quantify regional cerebral blood flow (CBF), and asymmetric spin echo imaging to estimate oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO{square}). We assessed cognition using an online battery and measured serum levels of TNF-, IL-6, IL-8, IL-13, IFN-{gamma}, GFAP, and S100{beta}, alongside blood routine tests. We performed ANCOVAs on predefined regions of interest (hippocampus, anterior cingulate cortex [ACC], insula, amygdala, striatum), followed by Bayesian inference and exploratory whole-brain analyses. PCS participants showed increased CMRO{square} in the hippocampus and decreased CMRO{square} in the ACC. Subfield analysis revealed elevated OEF and CMRO{square} across most hippocampal regions, excluding the entorhinal cortex. Whole-brain analyses identified increased perfusion in salience-related regions (insula, ACC, thalamus) and decreased perfusion in posterior cortical and cerebellar areas, in the absence of grey matter volume differences. Higher hippocampal metabolism positively correlated with cognitive performance, suggesting compensatory adaptation to sustain function. In contrast, lower ACC CMRO{square} correlated with depressive symptoms, reduced motivation, and elevated TNF- and GFAP, consistent with neurovascular uncoupling possibly driven by immune-glial activation. These findings reveal distinct physiological disruptions in PCS, with potential implications for stratified, metabolism-focused interventions.

neuroscience↗

bioRxiv2026

Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in Post-COVID-19 Syndrome

BackgroundPost-COVID-19 Syndrome (PCS) is characterised by persistent fatigue, cognitive impairments, and affective symptoms, yet its underlying neural mechanisms remain poorly understood. While static neuroimaging studies have identified resting-state connectivity abnormalities in PCS, such approaches fail to capture the brains dynamic functional organisation. This represents a missed opportunity to understand how alterations at the dynamic macroscale interactions give rise to the complex and fluctuating symptom profile of PCS. Cognitive and emotional processes rely on the brains capacity to flexibly reconfigure large-scale networks over time; disruptions in the exploration and transition between brain states may therefore play a central role in PCS pathophysiology. MethodsResting-state fMRI data were acquired from 20 individuals with PCS (mean age = 41.8 years, SD = 9.4) and 20 age- and sex-matched healthy controls (mean age = 40.6 years, SD = 8.1) using a multi-echo sequence. Following denoising with multi-echo independent component analysis, we applied Leading Eigenvector Dynamics Analysis (LEiDA) to identify recurrent patterns of whole-brain phase synchrony. The optimal number of dynamic brain states was determined using the Dunn index. For each state, we quantified probability of occurrence, lifetime, and transition probabilities, and mapped spatial topographies onto canonical functional networks. Group differences were assessed using ANCOVAs controlling for age, sex, and handedness. Exploratory associations with clinical symptoms, cognitive performance, and inflammatory markers were examined using both frequentist and Bayesian approaches. ResultsFive recurrent dynamic brain states were identified. Compared with controls, PCS participants showed reduced probability of occurrence and shorter lifetime of a visual/dorsal attention state, alongside increased probability of a limbic/default mode network (DMN) state. PCS was also characterised by reduced transitions between visual/dorsal attention and frontoparietal-DMN states, and increased transitions from somatomotor/visual states toward the limbic-DMN configuration. Exploratory analyses revealed that greater expression of the limbic-DMN state was negatively associated with global cognitive performance (MoCA) and positively associated with serum IL-1{beta} levels. ConclusionsPCS is associated with a reorganisation of intrinsic brain dynamics, marked by a shift from externally oriented attentional states toward limbic-DMN configurations. This imbalance may reflect reduced cognitive flexibility and increased sensitivity to interoceptive or affective signals. The observed links between dynamic brain-state expression, cognitive impairment, and peripheral inflammation support a systems-level mechanism through which immune signalling may influence neural function in PCS. Dynamic functional connectivity offers a sensitive framework for capturing these alterations and may inform future mechanistic models of post-viral dysfunction and therapeutic targeting. HighlightsO_LIPost-COVID-19 Syndrome (PCS) is linked to altered intrinsic brain dynamics at rest. C_LIO_LIPatients show reduced engagement of visual and attentional brain states. C_LIO_LIIncreased recruitment of limbic-DMN states suggests a shift toward more internally, emotionally charged focussed brain activity. C_LIO_LIBrain-state dynamics are putatively associated with global cognition and IL-1{beta}. C_LIO_LIReduced brain-state flexibility may underlie cognitive and emotional symptoms in PCS. C_LI

neuroscience↗

bioRxiv2024

Human brain changes after first psilocybin use

Psychedelics have robust effects on acute brain function and long-term behavior but whether they also cause enduring functional and anatomical brain changes is unknown. In a placebo-controlled, within-subjects, electroencephalography, and magnetic resonance imaging study in 28 healthy, entirely psychedelic-naive participants, anatomical and functional brain changes were detected from one-hour to one-month after a single high-dose (25 mg) of psilocybin. Increases in cognitive flexibility, psychological insight, and well-being were seen at one-month. Diffusion imaging done before and one-month after 25mg psilocybin revealed decreased axial diffusivity bilaterally in prefrontal-subcortical tracts that correlated with decreased brain network modularity over the same time period. Decreased modularity also correlated with improved well-being. Increased cortical signal entropy at 1- and 2-hours post-dosing predicted improved psychological well-being at one-month. Next-day psychological insight mediated the entropy to well-being relationship. All effects were exclusive to 25mg psilocybin; no effects occurred with a 1mg psilocybin placebo dose.

neuroscience↗

bioRxiv2023

Just a phase? Causal probing reveals spurious phasic dependence of sensory perception

For over a decade, electrophysiological studies have reported correlations between sensory perception and the phase of spontaneous pre-stimulus brain oscillations. To date, these findings have been interpreted as evidence that the brain uses neural oscillations to sample and predict upcoming stimuli. Yet, evidence from simulations have shown that analysis artefacts could also lead to spurious pre-stimulus oscillations that appear to predict future brain responses. To address this discrepancy, we conducted an experiment in which visual stimuli were presented timed to specific phases of spontaneous alpha and theta oscillations. This allowed us to causally probe the role of ongoing neural activity in visual processing independent of the stimulus-evoked dynamics. Our findings did not support a causal link between spontaneous alpha / theta rhythms and behaviour. However, spurious correlations between theta phase and behaviour emerged offline using gold-standard acausal time-frequency analyses. These findings demonstrate that care should be taken when inferring causal relationships between neural activity and behaviour using acausal analyses. HIGHLIGHTSO_LIWe causally probed the role of spontaneous EEG rhythms in visual attention via phase-locking. C_LIO_LITheta phase predicted behaviour offline, but cues presented in real-time with theta had no effect on behaviour. C_LIO_LISpurious theta rhythmic sampling is an artefact of the evoked potential and acausal filtering. C_LIO_LIecHT accurately computes the phase in real-time and mitigates erroneous phase-behaviour correlations. C_LI

neuroscience↗

bioRxiv2022

Non-invasive temporal interference electrical stimulation of the human hippocampus

Deep brain stimulation (DBS) via implanted electrodes is used worldwide to treat patients with severe neurological and psychiatric disorders however its invasiveness precludes widespread clinical use and deployment in research. Temporal interference (TI) is a strategy for non-invasive steerable DBS using multiple kHz-range electric fields with a difference frequency within the range of neural activity. Here we report the validation of the non-invasive DBS concept in humans. We used electric field modelling and measurements in a human cadaver to verify that the locus of the transcranial TI stimulation can be steerably focused in the hippocampus with minimal exposure to the overlying cortex. We then used functional magnetic resonance imaging (fMRI) and behaviour experiments to show that TI stimulation can focally modulate hippocampal activity and enhance the accuracy of episodic memories in healthy humans. Our results demonstrate targeted, non-invasive electrical stimulation of deep structures in the human brain.

neuroscience↗

bioRxiv2020

Mapping the common and distinct neural correlates of visual, rule and motor conflict

Flexible behaviour requires cognitive-control mechanisms to efficiently resolve conflict between competing information and alternative actions. Whether a global neural resource mediates all forms of conflict or this is achieved within domainspecific systems remains debated. We use a novel fMRI paradigm to orthogonally manipulate rule, response and stimulus-based conflict within a full-factorial design. Whole-brain voxelwise analyses show that activation patterns associated with these conflict types are distinct but partially overlapping within Multiple Demand Cortex (MDC), the brain regions that are most commonly active during cognitive tasks. Region of interest analysis shows that most MDC sub-regions are activated for all conflict types, but to significantly varying levels. We propose that conflict resolution is an emergent property of distributed brain networks, the functional-anatomical components of which place on a continuous, not categorical, scale from domain-specialised to domain general. MDC brain regions place towards one end of that scale but display considerable functional heterogeneity.

neuroscience↗

bioRxiv2020

Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity

BackgroundTranscranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure. ObjectivesIn this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity. MethodsWe applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n=22) and TBI participants (n=34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure. ResultsWe find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional - in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region. ConclusionsOur results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation.

neuroscience↗

bioRxiv2020

Preferential activation of the posterior Default-Mode Network with sequentially predictable task switches.

The default-mode network (DMN) has been primarily associated with internally-directed and self-relevant cognition. This perspective is expanding to recognise its importance in executive behaviours like switching. We investigated the effect different task-switching manipulations have on DMN activation in two studies with novel fMRI paradigms. In the first study, the paradigm manipulated visual discriminability, visuo-perceptual distance and sequential predictability during switching. Increased posterior cingulate/precuneus (PCC/PrCC) activity was evident during switching; critically, this was strongest when the occurrence of the switch was predictable. In the second study, we sought to replicate and further investigate this switch-related effect with a fully factorial design manipulating sequential, spatial and visual-feature predictability. Whole-brain analysis again identified a PCC/PrCC-centred cluster that was more active for sequentially predictable versus unpredictable switches, but not for the other predictability dimensions. We propose PCC/PrCC DMN subregions may play a prominent executive role in mapping the sequential structure of complex tasks.

neuroscience↗

bioRxiv2020

A Bayesian optimisation approach for rapidly mapping residual network function in stroke

Post-stroke cognitive and linguistic impairments are debilitating conditions, with current therapies only showing small improvements. Domain-general brain networks seem to play a critical role in stroke recovery and characterising their residual function with functional neuroimaging (fMRI) has the potential to yield biomarkers capable of guiding patient-specific rehabilitation. However, this is currently challenging in patients as such detailed characterisation requires too many different cognitive tasks. Here, we use neuroadaptive Bayesian optimisation to overcome this problem, an approach combining real-time fMRI with machine-learning. By intelligently searching across many tasks, this approach rapidly maps out patient-specific profiles of residual domain-general network function. Whereas controls have highly similar profiles, patients show idiosyncratic profiles of network abnormalities that are associated with behavioural performance. This approach can be extended to diverse brain networks and combined with brain stimulation or other therapeutics, thereby opening new avenues for precision medicine targeting diverse neurological and psychiatric conditions.

neuroscience↗

bioRxiv2020

Contrasting hierarchical and multiple-demand accounts of frontal lobe functional organisation during task-switching

There is an unresolved discrepancy between popular hierarchical and multiple-demand perspectives on the functional organisation of the human frontal lobes. Here, we tested alternative predictions of these perspectives with a novel fMRI switching paradigm. Each trial involved switching attention between stimuli, but at different levels of difficulty and abstraction. As expected, increasing response times were evident when comparing low-level perceptual switching to more abstract dimension, rule and task-switching. However, there was no evidence of an abstraction hierarchy within the prefrontal cortex (PFC). Nor was there recruitment of additional anterior PFC regions under increased switching demand. Instead, switching activated a widespread network of frontoparietal and cerebellar regions. Critically, the activity within PFC sub-regions uniformly increased with behavioural switch costs. We propose that both perspectives have some validity, but neither is complete. Too many studies have reported dissociations within MD for this volume to be functionally uniform, and the recruitment of more anterior regions with increased general difficulty cannot explain those results. Conversely, whilst reproducible evidence for a hierarchical functional organisation has been reported, this cannot be explained in terms of abstraction of representation or reconfiguration per se, because those interpretations generalise poorly to other task contexts.

neuroscience↗

bioRxiv2020

Concurrent optimisation of brain states and behavioural strategies when learning complex tasks

We developed two novel self-ordered switching (SOS) fMRI paradigms to investigate how human behaviour and underlying network resources are optimised when learning to perform complex tasks with multiple goals. SOS was performed with detailed feedback and minimal pretraining (study 1) or with minimal feedback and substantial pretraining (study 2). In study 1, multiple-demand (MD) system activation became less responsive to routine trial demands but more responsive to the executive switching events with practice. Default Mode Network (DMN) activation showed the opposite relationship. Concomitantly, reaction time learning curves correlated with increased connectivity between functional brain networks and subcortical regions. This fine-tuning of network resources correlated with progressively more routine and lower complexity behavioural structure. Furthermore, overall task performance was superior for people who applied structured behavioural routines with low algorithmic complexity. These behavioural and network signatures of learning were less evident in study 2, where task structure was established prior to entering the scanner. Together, these studies demonstrate how detailed feedback monitoring enables network resources to be progressively redeployed in order to efficiently manage concurrent demands. HighlightsO_LIWe examine the optimisation of behaviour and brain-network resources during a novel "self-ordered switching" (SOS) paradigm. C_LIO_LITask performance depended on generating behavioural routines with low algorithmic complexity (i.e., structured behaviours). C_LIO_LIBehaviour became more structured and reaction time decreased as SOS was practised. C_LIO_LIAs behaviour became more structured, activation in multiple-demand regions decreased for simple trial events but increased for executive switching events C_LIO_LIIncreases in between-network functional connectivity correlate with reaction time decreases. C_LI

neuroscience↗

bioRxiv2018

Are working memory training effects paradigm-specific?

A randomized controlled trial compared complex span and n-back training regimes to investigate the generality of training benefits across materials and paradigms. The memory items and training intensities were equated across programs, providing the first like-with-like comparison of transfer in these two widely-used training paradigms. The stimuli in transfer tests of verbal and visuo-spatial n-back and complex span differed from the trained tasks, but were matched across the untrained paradigms. Pre-to-post changes were observed for untrained n-back tasks following n-back training. Following complex span training there was equivocal evidence for improvements on a verbal complex span task, but no evidence for changes on an untrained visuo-spatial complex span activity. Relative to a no intervention group, the evidence supported no change on an untrained verbal complex span task following either n-back or complex span training. Equivocal evidence was found for improvements on visuo-spatial complex span and verbal and visuo-spatial n-back tasks following both training regimes. Evidence for selective transfer (comparing the two active training groups) was only found for an untrained visuo-spatial n-back task following n-back training. There was no evidence for cross-paradigm transfer. Thus transfer is constrained by working memory paradigm and the nature of individual processes executed within complex span tasks. However, within-paradigm transfer can occur when the change is limited to stimulus category, at least for n-back.

neuroscience↗

bioRxiv2018

A randomised exploratory investigation of the effects of Attention vs Working Memory Training on cognitive performance and everyday functioning following stroke.

Difficulties with attention are common following stroke and are associated with poor outcome. Home-based online cognitive training may have to the potential to provide an efficient and effective way to improve attentional functions in such patients. Little work has been carried out to assess the efficacy of this approach in stroke patients, and the lack of studies with active control conditions and rigorous evaluations of cognitive functioning pre and post training means understanding is limited as to whether and how such interventions may be effective. Here we compare the effects of 20 days of active cognitive training using either novel Selective Attention Training (SAT) or commercial Working Memory Training (WMT) programme, versus a waitlist control group, on a wide range of attentional and working memory tasks, as well as on self-reported everyday functioning. We demonstrate separable effects of each of the active training conditions, with SAT leading to improvements in both spatial and non-spatial aspects of attention and WMT leading to improvements only on very closely related working memory tasks. Both training groups reported improvements in everyday functioning, which were associated with improvements in attentional functions, suggesting that improving attention may be of particular importance in maximising functional recovery in this patient group.

clinical trials↗

bioRxiv2017

Brain state and polarity dependent modulation of brain networks by transcranial direct current stimulation

Transcranial direct current stimulation (TDCS) has been widely used to improve cognitive function. However, current deficiencies in mechanistic understanding hinders wider applicability. To clarify its physiological effects, we acquired fMRI whilst simultaneously acquiring TDCS to the right inferior frontal gyrus (rIFG) of healthy human participants, a region involved in coordinating activity within brain networks. TDCS caused widespread modulation of network activity depending on brain state ( rest or choice reaction time task) and polarity (anodal or cathodal). During task, TDCS increased salience network activation and default mode network deactivation, but had the opposite effect during rest. Furthermore, there was an interaction between brain state and TDCS polarity, with cathodal effects more pronounced during task performance and anodal effects more pronounced during rest. Overall, we show that rIFG TDCS produces brain state and polarity dependent effects within large-scale cognitive networks, in a manner that goes beyond predictions from the current literature.

neuroscience↗

bioRxiv2017

Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

Understanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because different FPNs spatially overlap and are co-activated for diverse tasks. In order to characterize these networks involves studying how they activate across many different cognitive tasks, which previously has only been possible with meta-analyses. Here, building upon meta-analyses as a starting point, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that dissociate ventral and dorsal FPN activity from a large pool of tasks. We identify and subsequently refine two cognitive tasks (Deductive Reasoning and Tower of London) that are optimal for dissociating the FPNs. The identified cognitive tasks are not those predicted by meta-analysis, highlighting a different mapping between cognitive tasks and FPNs than expected. The optimization approach converged on a similar neural dissociation independently for the two different tasks, suggesting a possible common underlying functional mechanism and the need for neurally-derived cognitive taxonomies.

neuroscience↗