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Rhythmic temporal expectation boosts neural activity by increasing neural gain.
Temporal orienting improves sensory processing, akin to other top-down biases. However, it is unknown whether these improvements reflect increased neural gain to any stimuli presented at expected time points, or specific tuning to task-relevant stimulus aspects. Furthermore, while other top-down biases are selective, the extent of trade-offs across time is less well characterised. Here, we tested whether gain and/or tuning of auditory frequency processing in humans is modulated by rhythmic temporal expectations, and whether these modulations are specific to time points relevant for task performance. Healthy participants (N=23) of either sex performed an auditory discrimination task while their brain activity was measured using magneto- and electroencephalography (M/EEG). Acoustic stimulation consisted of sequences of brief distractors interspersed with targets, presented in a rhythmic or jittered way. Target rhythmicity not only improved behavioural discrimination accuracy and M/EEG-based decoding of targets, but also of irrelevant distractors preceding these targets. To explain this finding in terms of increased sensitivity and/or sharpened tuning to auditory frequency, we estimated tuning curves based on M/EEG decoding results, with separate parameters describing gain and sharpness. The effect of rhythmic expectation on distractor decoding was linked to gain increase only, suggesting increased neural sensitivity to any stimuli presented at relevant time points.SIGNIFICANCE STATEMENTBeing able to predict when an event may happen can improve perception and action related to this event, likely due to alignment of neural activity to the temporal structure of stimulus streams. However, it is unclear whether rhythmic increases in neural sensitivity are specific to task-relevant targets, and whether they competitively impair stimulus processing at unexpected time points. By combining magneto/encephalographic (M/EEG) recordings, neural decoding of auditory stimulus features, and modelling, we found that rhythmic expectation improved neural decoding of both relevant targets and irrelevant distractors presented and expected time points, but did not competitively impair stimulus processing at unexpected time points. Using a quantitative model, these results were linked to non-specific neural gain increases due to rhythmic expectation.
The economy of anatomy: Discovering the turbulent homogeneous isotropic functional core organisation of the human brain
<jats:title>Abstract</jats:title><jats:p>Using large-scale neuroimaging data from 1003 healthy participants, we demonstrate empirically and theoretically that human brain dynamics is organised around a <jats:italic>homogeneous isotropic functional core</jats:italic>. More importantly, this homogeneous isotropic functional core follows a <jats:italic>turbulent-like power scaling law</jats:italic> for functional correlations in a broad spatial range suggestive of a <jats:italic>cascade</jats:italic> of information processing. The underlying anatomy of the brain is expensive in terms of material and metabolic costs and it has been suggested that the trade-offs between wiring cost and topological value change over many timescales but exactly how is not known (<jats:italic>1</jats:italic>). Here, we demonstrate how the economy of anatomy has evolved a <jats:italic>homogeneous isotropic functional core</jats:italic> by using whole-brain modelling with the <jats:italic>exponential Markov-Kennedy distance rule</jats:italic> of anatomical connections as the cost-of-wiring principle demonstrated in the massive retrograde tract tracing studies in non-human primates by Markov, Kennedy and colleagues (<jats:italic>2</jats:italic>). Overall, our results reveal a novel way of analysing and modelling whole-brain dynamics that establishes a fundamental basic principle of brain organisation.</jats:p>
Revisiting the Global Workspace: Orchestration of the functional hierarchical organisation of the human brain
<jats:title>Abstract</jats:title><jats:p>A central, unsolved challenge in neuroscience is how the brain orchestrates function by organising the flow of information necessary for the underlying computation. It has been argued that this whole-brain orchestration is carried out by a core subset of integrative brain regions, commonly referred to as the ‘global workspace’, although quantifying the constitutive brain regions has proven elusive. We developed a <jats:italic>normalised directed transfer entropy</jats:italic> (NDTE) framework for determining the pairwise bidirectional causal flow between brain regions and applied it to multimodal whole-brain neuroimaging from over 1000 healthy participants. We established the full brain hierarchy and common regions in a ‘functional rich club’ (FRIC) coordinating the functional hierarchical organisation during rest and task. FRIC contains the core set of regions, which similar to a ‘club’ of functional hubs are characterized by a tendency to be more densely functionally connected among themselves than to the rest of brain regions from where they integrate information. The invariant <jats:italic>global workspace</jats:italic> is the intersection of FRICs across rest and seven tasks, and was found to consist of the precuneus, posterior and isthmus cingulate cortices, nucleus accumbens, putamen, hippocampus and amygdala that orchestrate the functional hierarchical organisation based on information from perceptual, long-term memory, evaluative and attentional systems. We confirmed the causal significance and robustness of this invariant global workspace by systematically lesioning a generative whole-brain model accurately simulating the functional hierarchy defined by NDTE. Overall, this is a major step forward in understanding the complex choreography of information flow within the functional hierarchical organisation of the human brain.</jats:p>
Cognitive Impairment in Patients with Bipolar Disorder: Impact of Pharmacological Treatment.
Bipolar disorder is an illness characterised by periods of elated and depressed mood. These mood episodes are associated with changes in cognitive function and there is evidence to suggest that cognitive dysfunction persists during euthymia. The extent to which this is a function of the illness or a result of treatment is less clear. In this narrative review, we explore the impact of commonly used medications for bipolar disorder on cognitive function. Specific impairments in executive function and verbal memory have been noted in bipolar disorder. The impact of pharmacological treatments upon cognitive function is mixed with a number of studies reporting conflicting results. Interpretation of the data is further complicated by the variety of cognitive tests employed, study design, the relatively small numbers of patients included and confounding by indication. Overall, there is some evidence that while lithium improves some cognitive domains, it impedes others. Antipsychotics may be deleterious to cognition, although this may relate to the patient population in which they are prescribed. Sodium valproate is also associated with worse cognitive outcomes, while the impact of other antiepileptics is unclear. Overall the quality of evidence is poor and is derived from a relatively small number of studies that often do not account for the significant heterogeneity of the disorder or common comorbidities. The use of consistent methodologies and measures of cognition across studies, as well as in naturalistic settings, would enable more certain conclusions to be drawn.
Tianeptine in an experimental medicine model of antidepressant action.
Changes in emotional processing have been shown following acute administration of a range of monoaminergic antidepressants, and may represent an important common neuropsychological mechanism underpinning their therapeutic effects. Tianeptine is an agent that challenges the traditional monoaminergic hypothesis of antidepressant action, though its exact mode of action remains controversial. Healthy volunteers were randomised to receive a single dose of tianeptine (12.5 mg) or placebo, and subsequently completed a battery of tasks measuring emotional processing, including facial expression recognition, emotional memory and attentional vigilance, as well as working and verbal memory. Tianeptine-treated subjects were less accurate at identifying facial expressions, though this was not valence specific. The tianeptine group also showed reduced positive affective memory and reduced attentional vigilance to positive stimuli. There were no effects on emotional categorization or non-emotional cognition. The negative biases in aspects of emotional processing observed following acute tianeptine administration are at variance with the positive biases generally seen after acute administration of conventional antidepressant drugs, despite tianeptine's putative antidepressant efficacy. This is an intriguing finding in the context of the lack of consensus regarding tianeptine's mechanism of action; however, it may be consistent with the reported ability of acute tianeptine to increase the re-uptake of serotonin.
Temporal anticipation based on memory
<jats:title>Abstract</jats:title><jats:p>The fundamental role that our long-term memories play in guiding perception is increasingly recognised, but the functional and neural mechanisms are just beginning to be explored. Though experimental approaches are being developed to investigate the influence of long-term memories on perception, these remain mostly static and neglect their temporal and dynamic nature. Here we show we show that our long-term memories can guide attention proactively and dynamically based on learned temporal associations. Across two experiments we found that detection and discrimination of targets appearing within previously learned contexts are enhanced when the timing of target appearance matches the learned temporal contingency. Neural markers of temporal preparation revealed that the learned temporal associations trigger specific temporal predictions. Our findings emphasize the ecological role that memories play in predicting and preparing perception of anticipated events, calling for revision of the usual conceptualisation of contextual associative memory as a reflective and retroactive function.</jats:p>
A systematic review of impulse control disorders in Parkinson's disease.
Throughout the past decade it has been recognized that dopaminergic medication administered to remedy motor symptoms in Parkinson's disease is associated with an enhanced risk for impulse control disorders and related compulsive behaviors such as hobbyism, punding, and the dopamine dysregulation syndrome. These complications are relatively frequent, affecting 6-15.5% of patients, and they most often appear, or worsen, after initiation of dopaminergic therapy or dosage increase. Recently, impulse control disorders have also been associated with subthalamic nucleus deep brain stimulation. Here we present a systematic overview of literature published between 2000 and January 2013 reporting impulse control disorders in Parkinson's disease. We consider prevalence rates and discuss the functional neuroanatomy, the impact of dopamine-serotonin interactions, and the cognitive symptomatology associated with impulse control disorders in Parkinson's disease. Finally, perspectives for future research and management of impulse control disorders in Parkinson's disease are discussed.
The Developmental Origins of Health and Disease and Sustainable Development Goals: mapping the way forward
<jats:p>In this paper, meant to stimulate debate, we argue that there is considerable benefit in approaching together the implementation of two seemingly separate recent developments. First, on the global development agenda, we have the United Nations General Assembly’s 2015 finalized list of 17 Sustainable Development Goals (SDGs). Several of the SDGs are related to health. Second, the field of Developmental Origins of Health and Disease (DOHaD) has garnered enough compelling evidence demonstrating that early exposures in life affect not only future health, but that the effects of that exposure can be transmitted across generations – necessitating that we begin to focus on prevention. We argue that implementing the SDGs and DOHaD together will be beneficial in several ways; and will require attending to multiple, complex and multidisciplinary approaches as we reach the point of translating science to policy to impact. Here, we begin by providing the context for our work and making the case for a mutually reinforcing, synergistic approach to implementing SDGs and DOHaD, particularly in Africa. To do this, we initiate discussion via an early mapping of some of the overlapping considerations between SDGs and DOHaD.</jats:p>
https://www.sgim.org/web-only/medical-humanities/star-gazing
Journal of General Internal Medicine (JGIM): Medical Humanities - Web Edition Publication
Kajee N, Bovijn J, Van Schalkwyk S. A Tangled Web of Definitions: Deconstructing Health Science Students’ Concept of Research.
Stellenbosch University Annual Academic Day: Health Systems Strengthening Track:
Angiotensin Regulation of Amygdala Response to Threat in High-Trait-Anxiety Individuals.
BACKGROUND: The antihypertensive drug losartan has been shown to improve memory in humans as well as learning and fear extinction in rodent models, highlighting its potential to have similar synergistic effects on exposure-based cognitive behavioral therapy for anxiety disorders. This study investigated the effect of losartan on neural correlates of processing threat versus safety stimuli in highly anxious individuals to identify potential pathways of how the drug might facilitate psychological treatment. METHODS: Thirty healthy volunteers high in trait anxiety were randomly assigned to a single dose of losartan (50 mg) versus placebo before undergoing functional magnetic resonance imaging. We measured brain response to happy and fearful faces presented for 80 seconds to assess emotional processing and habituation over time. RESULTS: The placebo group showed similarly high left amygdala activation early on during presentation of fearful and happy faces, which decreased over time. In contrast, losartan reduced amygdala response to happy faces early on. In response to fearful faces, the drug prevented habituation, caused sustained amygdala activation, and led to increased activation in other brain areas associated with threat processing, such as the insula and putamen. CONCLUSIONS: Our findings suggest two distinct effects of losartan on emotional processing, including an improvement of early discrimination of stimuli as threatening versus safe, and facilitation of threat processing. Both processes are known to be relevant for successful exposure, highlighting two potential pathways by which losartan might exert facilitative effects on psychological treatment.
Magnetoencephalography as a Tool in Psychiatric Research: Current Status and Perspective.
The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. We propose that recent technological and analytic advances in magnetoencephalography (MEG), a technique that allows measurement of neuronal events directly and noninvasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as schizophrenia, autism spectrum disorders, and the dementias. We summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then surveyed recent studies that have used MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This was followed by links with preclinical research that has highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, that could account for measured changes in neural oscillations. Finally, we discuss challenges as well as novel methodological developments that could pave the way for widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis.
Personalise antidepressant treatment for unipolar depression combining individual choices, risks and big data (PETRUSHKA): rationale and protocol.
INTRODUCTION: Matching treatment to specific patients is too often a matter of trial and error, while treatment efficacy should be optimised by limiting risks and costs and by incorporating patients' preferences. Factors influencing an individual's drug response in major depressive disorder may include a number of clinical variables (such as previous treatments, severity of illness, concomitant anxiety etc) as well demographics (for instance, age, weight, social support and family history). Our project, funded by the National Institute of Health Research, is aimed at developing and subsequently testing a precision medicine approach to the pharmacological treatment of major depressive disorder in adults, which can be used in everyday clinical settings. METHODS AND ANALYSIS: We will jointly synthesise data from patients with major depressive disorder, obtained from diverse datasets, including randomised trials as well as observational, real-world studies. We will summarise the highest quality and most up-to-date scientific evidence about comparative effectiveness and tolerability (adverse effects) of antidepressants for major depressive disorder, develop and externally validate prediction models to produce stratified treatment recommendations. Results from this analysis will subsequently inform a web-based platform and build a decision support tool combining the stratified recommendations with clinicians and patients' preferences, to adapt the tool, increase its' reliability and tailor treatment indications to the individual-patient level. We will then test whether use of the tool relative to treatment as usual in real-world clinical settings leads to enhanced treatment adherence and response, is acceptable to clinicians and patients, and is economically viable in the UK National Health Service. DISCUSSION: This is a clinically oriented study, coordinated by an international team of experts, with important implications for patients treated in real-world setting. This project will form a test-case that, if effective, will be extended to non-pharmacological treatments (either face-to-face or internet-delivered), to other populations and disorders in psychiatry (for instance, children and adolescents, or schizophrenia and treatment-resistant depression) and to other fields of medicine.
Dynamical informational structures characterize the different human brain states of wakefulness and deep sleep
<jats:title>ABSTRACT</jats:title><jats:p>The dynamical activity of the human brain describes an extremely complex energy landscape changing over time and its characterisation is central unsolved problem in neuroscience. We propose a novel mathematical formalism for characterizing how the landscape of attractors sustained by a dynamical system evolves in time. This mathematical formalism is used to distinguish quantitatively and rigorously between the different human brain states of wakefulness and deep sleep. In particular, by using a whole-brain dynamical ansatz integrating the underlying anatomical structure with the local node dynamics based on a Lotka-Volterra description, we compute analytically the <jats:italic>global attractors</jats:italic> of this cooperative system and their associated directed graphs, here called the <jats:italic>informational structures</jats:italic>. The informational structure of the global attractor of a dynamical system describes precisely the past and future behaviour in terms of a directed graph composed of invariant sets (nodes) and their corresponding connections (links). We characterize a brain state by the time variability of these informational structures. This theoretical framework is potentially highly relevant for developing reliable biomarkers of patients with e.g. neuropsychiatric disorders or different levels of coma.</jats:p>