Publications
47 results found
Kurtin DL, Araña-Oiarbide G, Lorenz R, et al., 2023, Planning ahead: Predictable switching recruits task-active and resting-state networks., Hum Brain Mapp, Vol: 44, Pages: 5030-5046
Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task pe
Kurtin DL, Giunchiglia V, Vohryzek J, et al., 2023, Moving from phenomenological to predictive modelling: Progress and pitfalls of modelling brain stimulation in-silico, NeuroImage, Vol: 272, ISSN: 1053-8119
Brain stimulation is an increasingly popular neuromodulatory tool used in both clinical and research settings; however, the effects of brain stimulation, particularly those of non-invasive stimulation, are variable. This variability can be partially explained by an incomplete mechanistic understanding, coupled with a combinatorial explosion of possible stimulation parameters. Computational models constitute a useful tool to explore the vast sea of stimulation parameters and characterise their effects on brain activity. Yet the utility of modelling stimulation in-silico relies on its biophysical relevance, which needs to account for the dynamics of large and diverse neural populations and how underlying networks shape those collective dynamics. The large number of parameters to consider when constructing a model is no less than those needed to consider when planning empirical studies. This piece is centred on the application of phenomenological and biophysical models in non-invasive brain stimulation. We first introduce common forms of brain stimulation and computational models, and provide typical construction choices made when building phenomenological and biophysical models. Through the lens of four case studies, we provide an account of the questions these models can address, commonalities, and limitations across studies. We conclude by proposing future directions to fully realise the potential of computational models of brain stimulation for the design of personalized, efficient, and effective stimulation strategies.
Kurtin DL, Scott G, Hebron H, et al., 2023, Task-based differences in brain state dynamics and their relation to cognitive ability, NeuroImage, Vol: 271, ISSN: 1053-8119
Transient patterns of interregional connectivity form and dissipate in response to varying cognitive demands. Yet, it is not clear how different cognitive demands influence brain state dynamics, and whether these dynamics relate to general cognitive ability. Here, using functional magnetic resonance imaging (fMRI) data, we characterised shared, recurrent, global brain states in 187 participants across the working memory, emotion, language, and relation tasks from the Human Connectome Project. Brain states were determined using Leading Eigenvector Dynamics Analysis (LEiDA). In addition to the LEiDA-based metrics of brain state lifetimes and probabilities, we also computed information-theoretic measures of Block Decomposition Method of complexity, Lempel-Ziv complexity and transition entropy. Information theoretic metrics are notable in their ability to compute relationships amongst sequences of states over time, compared to lifetime and probability, which capture the behaviour of each state in isolation. We then related task-based brain state metrics to fluid intelligence. We observed that brain states exhibited stable topology across a range of numbers of clusters (K = 2:15). Most metrics of brain state dynamics, including state lifetime, probability, and all information theoretic metrics, reliably differed between tasks. However, relationships between state dynamic metrics and cognitive abilities varied according to the task, the metric, and the value of K, indicating that there are contextual relationships between task-dependant state dynamics and trait cognitive ability. This study provides evidence that the brain reconfigures across time in response to cognitive demands, and that there are contextual, rather than generalisable, relationships amongst task, state dynamics, and cognitive ability.
Hebron H, Lugli B, Dimitrova R, et al., 2022, Perfect Timing: Effects of Auditory Stimulation on Alpha Oscillations During Wakefulness and the Transition to Sleep are Phase-dependent in Humans
<jats:title>ABSTRACT</jats:title><jats:p>The waking brain’s ubiquitous alpha oscillations are thought to play an important role in managing the brain’s resources, inhibiting neural activity as a function of their phase and amplitude. In accordance with this physiological excitability, perceptual and cognitive processes fluctuate with alpha oscillations. Here we demonstrate that the alpha rhythm can be manipulated with sound in a phase-dependent manner, showing that repeated phase-locked sounds alter the frequency of these oscillations in a spatially localised manner. We draw on oscillator theory to explore the origin of this frequency change, using phase-locked auditory evoked potentials to show a putative phase-reset mechanism, which is dependent on the amplitude of the endogenous alpha oscillations. Finally, we demonstrate the functional relevance of this approach by showing that we can modulate the transition to sleep, using sound, in an alpha phase-dependent manner. Overall, we conclude that the phase of alpha oscillations can be exploited in real-time, and highlight alpha phase-locked auditory stimulation as a powerful method by which to both selectively augment and investigate the brain’s pertinent oscillations.</jats:p>
Soleimani G, Nitsche MA, Bergmann TO, et al., 2022, Closing the loop between brain and electrical stimulation: Towards precision neuromodulation treatments
<p>One of the most critical challenges in using non-invasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. The optimal way to target and apply NIBS in an individual way is yet to be determined while there is a growing body of evidence for its feasibility and effectiveness. Transcranial electrical stimulation (tES) as one of the NIBS techniques has shown promising results in modulating treatment outcomes in several psychiatric and neurologic disorders while faces the same challenge for individual optimization. With the new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to make closed-loop tES-fMRI for individually optimized neuromodulation. The closed-loop tES-fMRI systems can optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing pers
Mayes W, Gentle J, Parisi I, et al., 2021, Top-down Inhibitory Motor Control Is Preserved in Adults with Developmental Coordination Disorder, DEVELOPMENTAL NEUROPSYCHOLOGY, Vol: 46, Pages: 409-424, ISSN: 8756-5641
Soreq E, Violante IR, Daws R, et al., 2021, Neuroimaging evidence for a network sampling theory of individual differences in human intelligence, Nature Communications, Vol: 12, ISSN: 2041-1723
Despite a century of research, it remains unclear whether human intelligence should be studied as one dominant, several major, or many distinct abilities, and how such abilities relate to the functional organisation of the brain. Here, we combine psychometric and machine learning methods to examine in a data-driven manner how factor structure and individual variability in cognitive-task performance relate to dynamic-network connectomics. We report that 12 sub-tasks from an established intelligence test can be accurately multi-way classified (74%, chance 8.3%) based on the network states that they evoke. The proximities of the tasks in behavioural-psychometric space correlate with the similarities of their network states. Furthermore, the network states were more accurately classified for higher relative to lower performing individuals. These results suggest that the human brain uses a high-dimensional network-sampling mechanism to flexibly code for diverse cognitive tasks. Population variability in intelligence test performance relates to the fidelity of expression of these task-optimised network states.
Cogdell-Brooke LS, Sowden PT, Violante IR, et al., 2020, Ameta-analysisof functional magnetic resonance imaging studies of divergent thinking using activation likelihood estimation, HUMAN BRAIN MAPPING, Vol: 41, Pages: 5057-5077, ISSN: 1065-9471
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- Citations: 14
Araña-Oiarbide G, Daws RE, Lorenz R, et al., 2020, Preferential activation of the posterior Default-Mode Network with sequentially predictable task switches
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
Beppi C, Violante IR, Hampshire A, et al., 2020, Patterns of Focal- and Large-Scale Synchronization in Cognitive Control and Inhibition: A Review, FRONTIERS IN HUMAN NEUROSCIENCE, Vol: 14, ISSN: 1662-5161
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- Citations: 4
Cogdell-Brooke L, Stampacchia S, Jefferies E, et al., 2020, Consistently inconsistent: Multimodal episodic deficits in semantic aphasia, NEUROPSYCHOLOGIA, Vol: 140, ISSN: 0028-3932
Fagerholm ED, Moran RJ, Violante IR, et al., 2020, Dynamic causal modelling of phase-amplitude interactions, NEUROIMAGE, Vol: 208, ISSN: 1053-8119
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- Citations: 6
Lorenz R, Simmons LE, Monti RP, et al., 2019, Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization, BRAIN STIMULATION, Vol: 12, Pages: 1484-1489, ISSN: 1935-861X
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- Citations: 27
Li L, Violante I, Zimmerman K, et al., 2019, Traumatic axonal injury influences the cognitive effect of non-invasive brain stimulation, Brain, Vol: 142, Pages: 3280-3293, ISSN: 1460-2156
Non-invasive brain stimulation has been widely investigated for as a potentialtreatment for a range of neurological and psychiatric conditions, including braininjury. However, the behavioural effects of brain stimulation are very variable, forreasons that are poorly understood. This is a particular challenge for traumatic braininjury, where patterns of damage and their clinical effects are heterogenous. Here wetest the hypothesis that the response to transcranial direct current stimulationfollowing traumatic brain injury is dependent on white matter damage within thestimulated network. We used a novel simultaneous stimulation-MRI protocolapplying anodal, cathodal and sham stimulation to 24 healthy and 35 moderate/severetraumatic brain injury patients. Stimulation was applied to the right inferior frontalgyrus/anterior insula node of the Salience Network, which was targeted because ourprevious work had shown its importance to executive function. Stimulation wasapplied during performance of the Stop Signal Task, which assesses responseinhibition, a key component of executive function. Structural MRI was used to assessthe extent of brain injury, including diffusion MRI assessment of post-traumaticaxonal injury. Functional MRI, which was simultaneously acquired to delivery ofstimulation, assessed the effects of stimulation on cognitive network function. Anodalstimulation improved response inhibition in control participants, an effect that was notobserved in the patient group. The extent of traumatic axonal injury within theSalience Network strongly influenced the behavioural response to stimulation.Increasing damage to the tract connecting the stimulated right inferior frontalgyrus/anterior insula to the rest of the SN was associated with reduced beneficialeffects of stimulation. In addition, anodal stimulation normalised Default ModeNetwork activation in patients with poor response inhibition, suggesting thatstimulation modulates communication between the networks invo
Hampshire A, Daws RE, Neves ID, et al., 2019, Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics, NeuroImage, Vol: 192, Pages: 88-100, ISSN: 1053-8119
Diverse cortical networks and striatal brain regions are implicated in instruction-based learning (IBL); however, their distinct contributions remain unclear. We use a modified fMRI paradigm to test two hypotheses regarding the brain mechanisms that underlie IBL. One hypothesis proposes that anterior caudate and frontoparietal regions transiently co-activate when new rules are being bound in working memory. The other proposes that they mediate the application of the rules at different stages of the consolidation process. In accordance with the former hypothesis, we report strong activation peaks within and increased connectivity between anterior caudate and frontoparietal regions when rule-instruction slides are presented. However, similar effects occur throughout a broader set of cortical and sub-cortical regions, indicating a metabolically costly reconfiguration of the global brain state. The distinct functional roles of cingulo-opercular, frontoparietal and default-mode networks are apparent from their activation throughout, early and late in the practice phase respectively. Furthermore, there is tentative evidence of a peak in anterior caudate activity mid-way through the practice stage. These results demonstrate how performance of the same simple task involves a steadily shifting balance of brain systems as learning progresses. They also highlight the importance of distinguishing between regional specialisation and global dynamics when studying the network mechanisms that underlie cognition and learning.
Li L, Ribeiro Violante I, Leech R, et al., 2019, Brain state and polarity dependent modulation of brain networks by transcranial direct current stimulation, Human Brain Mapping, Vol: 40, Pages: 904-915, ISSN: 1065-9471
Despite its widespread use in cognitive studies, there is still limited understanding of whether and how transcranial direct current stimulation (tDCS) modulates brain network function. To clarify its physiological effects, we assessed brain network function using functional magnetic resonance imaging (fMRI) simultaneously acquired during tDCS stimulation. Cognitive state was manipulated by having subjects perform a Choice Reaction Task or being at “rest.” A novel factorial design was used to assess the effects of brain state and polarity. Anodal and cathodal tDCS were applied to the right inferior frontal gyrus (rIFG), a region involved in controlling activity large‐scale intrinsic connectivity networks during switches of cognitive state. tDCS produced widespread modulation of brain activity in a polarity and brain state dependent manner. In the absence of task, the main effect of tDCS was to accentuate default mode network (DMN) activation and salience network (SN) deactivation. In contrast, during task performance, tDCS increased SN activation. In the absence of task, the main effect of anodal tDCS was more pronounced, whereas cathodal tDCS had a greater effect during task performance. Cathodal tDCS also accentuated the within‐DMN connectivity associated with task performance. There were minimal main effects of stimulation on network connectivity. These results demonstrate that rIFG tDCS can modulate the activity and functional connectivity of large‐scale brain networks involved in cognitive function, in a brain state and polarity dependent manner. This study provides an important insight into mechanisms by which tDCS may modulate cognitive function, and also has implications for the design of future stimulation studies.
Li L, Ribeiro Violante I, Leech R, et al., 2019, Cognitive enhancement with Salience Network electrical stimulation is influenced by network structural connectivity, NeuroImage, Vol: 185, Pages: 425-433, ISSN: 1053-8119
The Salience Network (SN) and its interactions are important for cognitive control. We have previously shown that structural damage to the SN is associated with abnormal functional connectivity between the SN and Default Mode Network (DMN), abnormal DMN deactivation, and impaired response inhibition, which is an important aspect of cognitive control. This suggests that stimulating the SN might enhance cognitive control. Here, we tested whether non-invasive transcranial direct current stimulation (TDCS) could be used to modulate activity within the SN and enhance cognitive control. TDCS was applied to the right inferior frontal gyrus/anterior insula cortex during performance of the Stop Signal Task (SST) and concurrent functional (f)MRI. Anodal TDCS improved response inhibition. Furthermore, stratification of participants based on SN structural connectivity showed that it was an important influence on both behavioural and physiological responses to anodal TDCS. Participants with high fractional anisotropy within the SN showed improved SST performance and increased activation of the SN with anodal TDCS, whilst those with low fractional anisotropy within the SN did not. Cathodal stimulation of the SN produced activation of the right caudate, an effect which was not modulated by SN structural connectivity. Our results show that stimulation targeted to the SN can improve response inhibition, supporting the causal influence of this network on cognitive control and confirming it as a target to produce cognitive enhancement. Our results also highlight the importance of structural connectivity as a modulator of network to TDCS, which should guide the design and interpretation of future stimulation studies.
d'Almeida OC, Violante IR, Quendera B, et al., 2018, Mitochondrial pathophysiology beyond the retinal ganglion cell: occipital GABA is decreased in autosomal dominant optic neuropathy, GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY, Vol: 256, Pages: 2341-2348, ISSN: 0721-832X
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- Citations: 2
Pereira AC, Violante IR, Mouga S, et al., 2018, Medial Frontal Lobe Neurochemistry in Autism Spectrum Disorder is Marked by Reduced N-Acetylaspartate and Unchanged Gamma-Aminobutyric Acid and Glutamate plus Glutamine Levels, JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS, Vol: 48, Pages: 1467-1482, ISSN: 0162-3257
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- Citations: 13
Lorenz R, Ribeiro Violante I, Monti R, et al., 2018, Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization, Nature Communications, Vol: 9, ISSN: 2041-1723
Understanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because they overlap spatially and are co-activated by diverse tasks. Characterizing these networks therefore involves studying their activation across many different cognitive tasks, which previously was only possible with meta-analyses. Here, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that segregate ventral and dorsal FPN activity. We identify and subsequently refine two cognitive tasks, Deductive Reasoning and Tower of London, which maximally dissociate the dorsal from ventral FPN. We subsequently investigate these two FPNs in the context of a wider range of FPNs and demonstrate the importance of studying the whole activity profile across tasks to uniquely differentiate any FPN. Our findings deviate from previous meta-analyses and hypothesized functional labels for these FPNs. Taken together the results form the starting point for a neurobiologically-derived cognitive taxonomy.
Silva G, Duarte IC, Bernardino I, et al., 2018, Oscillatory motor patterning is impaired in neurofibromatosis type 1: a behavioural, EEG and fMRI study, JOURNAL OF NEURODEVELOPMENTAL DISORDERS, Vol: 10, ISSN: 1866-1947
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- Citations: 2
Goncalves J, Violante IR, Sereno J, et al., 2017, Testing the excitation/inhibition imbalance hypothesis in a mouse model of the autism spectrum disorder: in vivo neurospectroscopy and molecular evidence for regional phenotypes, MOLECULAR AUTISM, Vol: 8, ISSN: 2040-2392
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- Citations: 38
Li LM, Violante IR, Leech R, et al., 2017, Brain state and polarity dependent modulation of brain networks by transcranial direct current stimulation
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
Sliwinska M, Ribeiro Violante I, Wise R, et al., 2017, Stimulating Multiple-Demand Cortex Enhances Vocabulary Learning, Journal of Neuroscience, Vol: 37, Pages: 7606-7618, ISSN: 1529-2401
It is well established that domain general networks (DGNs) in the human brain become active when diverse novel skills and behaviors are being learnt. However, their causal role in learning remains to be established. In the present study, we first performed functional magnetic resonance imaging on healthy participants to confirm that DGNs were most active in the initial stages of learning a novel vocabulary, consisting of pronounceable nonwords (pseudowords), each associated with a picture of a real object. We then examined, in healthy participants, whether repetitive transcranial magnetic stimulation of a frontal midline node of the cingulo-opercular DGN affected learning rates during the initial stages of learning. We report that stimulation of this node, but not a control brain region, substantially improved both accuracy and response times during the earliest stage of learning pseudowords-object associations. This stimulation had no effect on the processing of established vocabulary, tested by the accuracy and response times when participants decided whether a real word was accurately paired with a picture of an object. These results provide evidence that non-invasive stimulation to DGN nodes can enhance learning rates, thereby demonstrating their causal role in the learning process. We propose that this causal role makes DGNs candidate targets for experimental therapeutics; for example, in stroke patients with aphasia attempting to reacquire a vocabulary.
Lorenz R, Simmons LE, Monti RP, et al., 2017, Assessing tACS-induced phosphene perception using closed-loop Bayesian optimization
<jats:title>Abstract</jats:title><jats:p>Transcranial alternating current stimulation (tACS) can evoke illusory flash-like visual percepts known as <jats:italic>phosphenes</jats:italic>. The perception of phosphenes represents a major experimental challenge when studying tACS-induced effects on cognitive performance. Besides growing concerns that retinal phosphenes themselves could potentially have neuromodulatory effects, the perception of phosphenes may also modify the alertness of participants. Past research has shown that stimulation intensity, frequency and electrode montage affect phosphene perception. However, to date, the effect of an additional tACS parameter on phosphene perception has been completely overlooked: the relative phase difference between stimulation electrodes. This is a crucial and timely topic given the confounding nature of phosphene perception and the increasing number of studies reporting changes in cognitive function following tACS phase manipulations. However, studying phosphene perception for different frequencies and phases simultaneously is not tractable using standard approaches, as the physiologically plausible range of parameters results in a combinatorial explosion of experimental conditions, yielding impracticable experiment durations. To overcome this limitation, here we applied a Bayesian optimization approach to efficiently sample an exhaustive tACS parameter space. Moreover, unlike conventional methodology, which involves subjects judging the perceived phosphene intensity on a rating scale, our study leveraged the strength of human perception by having the optimization driven based on a subject’s relative judgement. Applying Bayesian optimization for two different montages, we found that phosphene perception was affected by differences in the relative phase between cortical electrodes. The results were replicated in a second study involving new participants and validated using computationa
Lorenz R, Violante IR, Monti RP, et al., 2017, Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
Violante IR, Li LM, Carmichael DW, et al., 2017, Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance, ELIFE, Vol: 6, ISSN: 2050-084X
Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.
Datta G, Violante IR, Scott G, et al., 2016, Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis., Multiple Sclerosis, Vol: 23, Pages: 1469-1478, ISSN: 1352-4585
BACKGROUND: Multiple sclerosis (MS) is characterised by a diffuse inflammatory response mediated by microglia and astrocytes. Brain translocator protein (TSPO) positron-emission tomography (PET) and [myo-inositol] magnetic resonance spectroscopy (MRS) were used together to assess this. OBJECTIVE: To explore the in vivo relationships between MRS and PET [(11)C]PBR28 in MS over a range of brain inflammatory burden. METHODS: A total of 23 patients were studied. TSPO PET imaging with [(11)C]PBR28, single voxel MRS and conventional magnetic resonance imaging (MRI) sequences were undertaken. Disability was assessed by Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC). RESULTS: [(11)C]PBR28 uptake and [ myo-inositol] were not associated. When the whole cohort was stratified by higher [(11)C]PBR28 inflammatory burden, [ myo-inositol] was positively correlated to [(11)C]PBR28 uptake (Spearman's ρ = 0.685, p = 0.014). Moderate correlations were found between [(11)C]PBR28 uptake and both MRS creatine normalised N-acetyl aspartate (NAA) concentration and grey matter volume. MSFC was correlated with grey matter volume (ρ = 0.535, p = 0.009). There were no associations between other imaging or clinical measures. CONCLUSION: MRS [ myo-inositol] and PET [(11)C]PBR28 measure independent inflammatory processes which may be more commonly found together with more severe inflammatory disease. Microglial activation measured by [(11)C]PBR28 uptake was associated with loss of neuronal integrity and grey matter atrophy.
Ribeiro Violante I, 2016, GABA deficiency in NF1: a multimodal [11C]-Flumazenil and spectroscopy study, Neurology
Ribeiro Violante I, Patricio M, Bernardino I, et al., 2016, GABA deficiency in NF1: a multimodal [11C]-Flumazenil and spectroscopy study, Neurology, ISSN: 0028-3878
Objective: To provide a comprehensive investigation of the GABA system inpatients with Neurofibromatosis type 1 (NF1) that allows understanding thenature of the GABA imbalance in humans at pre- and post-synaptic levels.Methods: In this cross-sectional study, we employed multimodal imaging andspectroscopy measures to investigate GABAA receptor binding, using [11C]-Flumazenil positron emission tomography (PET), and GABA concentration,using magnetic resonance spectroscopy (MRS). 14 adult patients with NF1 and13 matched controls were included in the study. MRS was performed in theoccipital cortex and in a frontal region centered in the functionally localizedfrontal-eye fields. PET and MRS acquisitions were performed in the same day.Results: Patients with NF1 have reduced concentration of GABA+ in theoccipital cortex (P = 0.004) and frontal-eye fields (P = 0.026). PET resultsshowed decreased binding of GABAA receptors in patients in the parietooccipitalcortex, midbrain and thalamus, which are not explained by decreasedgrey matter levels.Conclusions: Abnormalities in the GABA system in NF1 involve both GABAconcentration and GABAA receptor density suggestive of neurodevelopmentalsynaptopathy with both pre- and post-synaptic involvement.
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