40 results found
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, A meta-analysis of functional magnetic resonance imaging studies of divergent thinking using activation likelihood estimation., Hum Brain Mapp, Vol: 41, Pages: 5057-5077
There are conflicting findings regarding brain regions and networks underpinning creativity, with divergent thinking tasks commonly used to study this. A handful of meta-analyses have attempted to synthesise findings on neural mechanisms of divergent thinking. With the rapid proliferation of research and recent developments in fMRI meta-analysis approaches, it is timely to reassess the regions activated during divergent thinking creativity tasks. Of particular interest is examining the evidence regarding large-scale brain networks proposed to be key in divergent thinking and extending this work to consider the role of the semantic control network. Studies utilising fMRI with healthy participants completing divergent thinking tasks were systematically identified, with 20 studies meeting the criteria. Activation Likelihood Estimation was then used to integrate the neuroimaging results across studies. This revealed four clusters: the left inferior parietal lobe; the left inferior frontal and precentral gyrus; the superior and medial frontal gyrus and the right cerebellum. These regions are key in the semantic network, important for flexible retrieval of stored knowledge, highlighting the role of this network in divergent thinking.
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>
Cogdell-Brooke L, Stampacchia S, Jefferies E, et al., 2020, Consistently inconsistent: Multimodal episodic deficits in semantic aphasia., Neuropsychologia, Vol: 140
Semantic Aphasia (SA) patients have difficulty accessing semantic knowledge in both verbal and non-verbal tasks appropriately for the current context. Automatically activated semantic knowledge overwhelms the system, because it is no longer able to inhibit interference from dominant meanings in order to select weaker alternatives. Episodic memory, like semantic memory, requires control to select relevant memories amongst competing episodes. For example, our memory for what we ate for breakfast last Saturday is affected by competition from numerous other breakfast meals eaten on other days. Where one is unable to guide retrieval, we may rely on automatically activated knowledge about "breakfast foods", and therefore experience false memories. Brain systems that support semantic control are also implicated in episodic control, and therefore deficits in semantic control are likely to cause more widespread problems. Despite this, nearly all research to date focuses on semantic performance alone. This study explored the impact of this semantic impairment on episodic recall. We used a verbal and non-verbal episodic memory task: participants remembered nursery rhymes in the verbal condition and logos and their associated products in the visual condition (e.g. bowl of cereal and coco-pops). For both tasks, we manipulated a) congruency with pre-existing knowledge (e.g. expectancy of trials: baa baa blackbuild - instead of sheep) and b) whether these trial types were blocked by congruency or mixed, as well as (c) distractor strength. If SA patients experience overwhelming automatic activation, they should find incongruent items more difficult to suppress, particularly when presented in an unpredictable task format. A total of 13 SA patients were compared to 33 controls across three experiments. In line with our predictions, SA patients found it more difficult to retrieve episodic memories which were in conflict with pre-existing semantic knowledge. This was true acr
Fagerholm ED, Moran RJ, Violante IR, et al., 2020, Dynamic causal modelling of phase-amplitude interactions., Neuroimage, Vol: 208
Models of coupled phase oscillators are used to describe a wide variety of phenomena in neuroimaging. These models typically rest on the premise that oscillator dynamics do not evolve beyond their respective limit cycles, and hence that interactions can be described purely in terms of phase differences. Whilst mathematically convenient, the restrictive nature of phase-only models can limit their explanatory power. We therefore propose a generalisation of dynamic causal modelling that incorporates both phase and amplitude. This allows for the separate quantifications of phase and amplitude contributions to the connectivity between neural regions. We show, using model-generated data and simulations of coupled pendula, that phase-amplitude models can describe strongly coupled systems more effectively than their phase-only counterparts. We relate our findings to four metrics commonly used in neuroimaging: the Kuramoto order parameter, cross-correlation, phase-lag index, and spectral entropy. We find that, with the exception of spectral entropy, the phase-amplitude model is able to capture all metrics more effectively than the phase-only model. We then demonstrate, using local field potential recordings in rodents and functional magnetic resonance imaging in macaque monkeys, that amplitudes in oscillator models play an important role in describing neural dynamics in anaesthetised brain states.
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
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
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
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
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
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.
Silva G, Ribeiro MJ, Costa GN, et al., 2016, Peripheral Attentional Targets under Covert Attention Lead to Paradoxically Enhanced Alpha Desynchronization in Neurofibromatosis Type 1, PLOS One, Vol: 11, ISSN: 1932-6203
The limited capacity of the human brain to process the full extent of visual information reaching the visual cortex requires the recruitment of mechanisms of information selection through attention. Neurofibromatosis type-1 (NF1) is a neurodevelopmental disease often exhibiting attentional deficits and learning disabilities, and is considered to model similar impairments common in other neurodevelopmental disorders such as autism. In a previous study, we found that patients with NF1 are more prone to miss targets under overt attention conditions. This finding was interpreted as a result of increased occipito-parietal alpha oscillations. In the present study, we used electroencephalography (EEG) to study alpha power modulations and the performance of patients with NF1 in a covert attention task. Covert attention was required in order to perceive changes (target offset) of a peripherally presented stimulus. Interestingly, alpha oscillations were found to undergo greater desynchronization under this task in the NF1 group compared with control subjects. A similar pattern of desynchronization was found for beta frequencies while no changes in gamma oscillations could be identified. These results are consistent with the notion that different attentional states and task demands generate different patterns of abnormal modulation of alpha oscillatory processes in NF1. Under covert attention conditions and while target offset was reported with relatively high accuracy (over 90% correct responses), excessive desynchronization was found. These findings suggest an abnormal modulation of oscillatory activity and attentional processes in NF1. Given the known role of alpha in modulating attention, we suggest that alpha patterns can show both abnormal increases and decreases that are task and performance dependent, in a way that enhanced alpha desynchronization may reflect a compensatory mechanism to keep performance at normal levels. These results suggest that dysregulation of alph
Lorenz R, Monti RP, Ribeiro Violante I, et al., 2016, The Automatic Neuroscientist: A framework for optimizing experimentaldesign with closed-loop real-time fMRI, Neuroimage, Vol: 129, Pages: 320-334, ISSN: 1095-9572
Functional neuroimaging typically explores how a particular task activates a set of brain regions. Importantly though, the same neural system can be activated by inherently different tasks. To date, there is no approach available that systematically explores whether and how distinct tasks probe the same neural system. Here, we propose and validate an alternative framework, the Automatic Neuroscientist, which turns the standard fMRI approach on its head. We use real-time fMRI in combination with modern machine-learning techniques to automatically design the optimal experiment to evoke a desired target brain state. In this work, we present two proof-of-principle studies involving perceptual stimuli. In both studies optimization algorithms of varying complexity were employed; the first involved a stochastic approximation method while the second incorporated a more sophisticated Bayesian optimization technique. In the first study, we achieved convergence for the hypothesized optimum in 11 out of 14 runs in less than 10 min. Results of the second study showed how our closed-loop framework accurately and with high efficiency estimated the underlying relationship between stimuli and neural responses for each subject in one to two runs: with each run lasting 6.3 min. Moreover, we demonstrate that using only the first run produced a reliable solution at a group-level. Supporting simulation analyses provided evidence on the robustness of the Bayesian optimization approach for scenarios with low contrast-to-noise ratio. This framework is generalizable to numerous applications, ranging from optimizing stimuli in neuroimaging pilot studies to tailoring clinical rehabilitation therapy to patients and can be used with multiple imaging modalities in humans and animals.
Lorenz R, Monti RP, Hampshire A, et al., 2016, Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization, 6th International Workshop on Pattern Recognition in Neuroimaging (PRNI), Publisher: IEEE, Pages: 49-52, ISSN: 2330-9989
Ribeiro MJ, Violante IR, Bernardino I, et al., 2015, Abnormal relationship between GABA, neurophysiology and impulsive behavior in neurofibromatosis type 1, CORTEX, Vol: 64, Pages: 194-208, ISSN: 0010-9452
Majewska P, Ribeiro Violante I, Lorenz R, et al., 2015, EEG characteristics of memory deficits in acute traumatic brain injury patients with post-traumatic amnesia, The Society of British Neurological Surgeons Meeting 2015
Mullins PG, McGonigle DJ, O'Gorman RL, et al., 2014, Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA, NEUROIMAGE, Vol: 86, Pages: 43-52, ISSN: 1053-8119
Duarte JV, Ribeiro MJ, Violante IR, et al., 2014, Multivariate Pattern Analysis Reveals Subtle Brain Anomalies Relevant to the Cognitive Phenotype in Neurofibromatosis Type 1, HUMAN BRAIN MAPPING, Vol: 35, Pages: 89-106, ISSN: 1065-9471
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.