Search

Large-scale recordings of neural activity over days and weeks have revealed that neural representations of familiar tasks, precepts and actions continually evolve without obvious changes in behaviour. We hypothesise that this steady drift in neural activity and accompanying physiological changes is due in part to the continuous application of a learning rule at the cellular and population level. Explicit predictions of this drift can be found in neural network models that use iterative learning to optimise weights. Drift therefore provides a measurable signal that can reveal systems-level properties of biological plasticity mechanisms, such as their precision and effective learning rates.

Abstract. Emotion recognition ability of emotions expressed by other people (ERA-O) can be important for job performance, leadership, bargaining, and career success. Traditional personnel assessment tools of this ability, however, are contaminated by linguistic skills. In a time of global work migration, more and more people speak a language at work that is not their mother tongue. Consequently, we developed and validated the Face-Based Emotion Matching Test (FEMT), a nonlinguistic objective test of ERA-O in gainfully employed adults. We demonstrate the FEMT’s validity with psychological constructs (cognitive and emotional intelligence, Big Five personality traits) and its criterion validity and interethnic fit.

Neurons utilize plasticity of dendritic arbors as part of a larger suite of adaptive plasticity mechanisms. This explicitly manifests with motoneurons in the Drosophila embryo and larva, where dendritic arbors are exclusively postsynaptic and are used as homeostatic devices, compensating for changes in synaptic input through adapting their growth and connectivity. We recently identified reactive oxygen species (ROS) as novel plasticity signals instrumental in this form of dendritic adjustment. ROS correlate with levels of neuronal activity and negatively regulate dendritic arbor size. Here, we investigated NADPH oxidases as potential sources of such activity-regulated ROS and implicate Dual Oxidase (but not Nox), which generates hydrogen peroxide extracellularly. We further show that the aquaporins Bib and Drip, but not Prip, are required for activity-regulated ROS-mediated adjustments of dendritic arbor size in motoneurons. These results suggest a model whereby neuronal activity leads to activation of the NADPH oxidase Dual Oxidase, which generates hydrogen peroxide at the extracellular face; aquaporins might then act as conduits that are necessary for these extracellular ROS to be channeled back into the cell where they negatively regulate dendritic arbor size.

This scientific commentary refers to ‘Physiological alterations of pineal recess crowding in symptomatic non-hydrocephalic pineal cysts’ by Eide et al. (https://doi.org/10.1093/braincomms/fcad078).

Cerebral vasculature plays an important role in maintaining brain function and homeostasis. In ageing, a number of genetic and environmental risk factors can compromise brain vascular health and contribute to multiple neurological disorders. White matter (WM) is more vulnerable in cerebrovascular ageing compared with grey matter. With the development of automated and reproducible neuroimaging techniques, there is an opportunity to detect many ageing-related or diseases-related WM changes at an early stage with greater sensitivity. The overall objective of this PhD project is, therefore, to develop reliable neuroimaging biomarkers for characterising WM integrity and examine their relationships with cerebrovascular burden. Four separate studies were carried out to investigate this topic in depth. In the first study, a new diffusion-weighted imaging (DWI) measure, Difference in Distribution Functions (DDF), was developed to overcome the limitations of existing DWI measures in characterising the white matter (WM) microstructural integrity. DDF showed a stronger correlation with age and cognition than other DWI measures investigated. The second study extended the first study by employing longitudinal datasets to examine the effects of various risk factors on WM microstructural integrity over time. Results showed that older age is the primary risk factor for decline in WM integrity in a healthy general population sample. In the third study, a new imaging metric, WM brain age, was introduced to comprehensively assess the health of WM and cerebrovascular disease burdens for each individual. WM brain age was calculated by using a three-dimensional convolutional neural network (3D-CNN) deep learning model. Findings showed that WM brain age is sensitive to most vascular risk factors and cognitive domains related to vascular dysfunction. In the fourth study, the impacts of high blood pressure on grey matter (GM) and WM, respectively, were examined using 3D-CNN to construct GM and WM ages. Findings revealed that hypertension is associated with both GM and WM impairment, and that WM integrity is more vulnerable to hypertension. In conclusion, by developing novel neuroimaging biomarkers for the changes in cerebrovascular ageing, this thesis provides novel contributions to the existing literature. These findings have the potential to better quantify the vascular burden in future research work and in clinical practice.

ObjectiveTo determine whether mild cognitive impairment with Lewy bodies or mild cognitive impairment with Alzheimer disease differ in their rates of clinical progression to dementia, we undertook longitudinal observation of mild cognitive impairment cases with detailed clinical assessment of Lewy body diagnostic characteristics.MethodsTwo prospective longitudinal cohorts including 111 individuals ≥60 years of age with mild cognitive impairment were assessed annually to track cognitive and clinical progression, including the presence or absence of core clinical features and proposed biomarkers of dementia with Lewy bodies. Multistate modeling was used to assess the associations of diagnostic characteristics of dementia with Lewy bodies with clinical progression from mild cognitive impairment to dementia, with death as a competing outcome.ResultsAfter a mean follow-up of 2.2 years (range 1–6.7 years), 38 of the 111 (34%) participants progressed to dementia: 10 with AD, 3 with possible dementia with Lewy bodies, and 25 with probable dementia with Lewy bodies. The presence of any Lewy body disease characteristic was associated with an increased hazard of transition to dementia; this risk further increased as more diagnostic characteristics were observed (hazard ratio 1.33 per characteristic, 95% confidence interval [CI] 1.11–1.60) and was especially high for those experiencing complex visual hallucinations (hazard ratio 1.98, 95% CI 0.92–4.29) or cognitive fluctuations (hazard ratio 3.99, 95% CI 2.03–7.84).ConclusionsDiagnostic characteristics of Lewy body disease are associated with an increased risk of transition from mild cognitive impairment to dementia.

Variations in neuronal connectivity occur widely in nervous systems from invertebrates to mammals. Yet, it is unclear how neuronal variability originates, to what extent and at what time scales it exists, and what functional consequences it might carry. To assess inter- and intraindividual neuronal variability, it would be ideal to analyze the same identified neuron across different brain hemispheres and individuals. Here, using genetic labeling and electron microscopy connectomics, we show that an identified inhibitory olfactory local interneuron, TC-LN, exhibits extraordinary variability in its glomerular innervation patterns. Moreover, TC-LN’s innervation of the VL2a glomerulus, which processes food signals and modulates mating behavior, is sexually dimorphic, is influenced by female’s courtship experience, and correlates with food intake in mated females. Mating also affects output connectivity of TC-LN to specific local interneurons. We propose that mating-associated variability of TC-LNs regulates how food odor is interpreted by an inhibitory network to modulate feeding.

The interaction of descending neocortical outputs and subcortical premotor circuits is critical for shaping skilled movements. Two broad classes of motor cortical output projection neurons provide input to many subcortical motor areas: pyramidal tract (PT) neurons, which project throughout the neuraxis, and intratelencephalic (IT) neurons, which project within the cortex and subcortical striatum. It is unclear whether these classes are functionally in series or whether each class carries distinct components of descending motor control signals. Here, we combine large-scale neural recordings across all layers of motor cortex with cell type–specific perturbations to study cortically dependent mouse motor behaviors: kinematically variable manipulation of a joystick and a kinematically precise reach-to-grasp. We find that striatum-projecting IT neuron activity preferentially represents amplitude, whereas pons-projecting PT neurons preferentially represent the variable direction of forelimb movements. Thus, separable components of descending motor cortical commands are distributed across motor cortical projection cell classes.

Introduction: Prediagnostic features of Parkinson’s Disease are well described but prediagnostic Progressive Supranuclear Palsy (PSP) is less understood. The diagnosis of PSP is delayed by an average of three years after symptom onset. Understanding the changes that occur in the prediagnostic period will aid earlier diagnosis, clarify the natural history, and may aid the design of early disease-modifying therapy trials. We set out to identify motor and cognitive markers of prediagnostic PSP, with Parkinson’s disease as a comparator condition, in a large prospective cohort. Methods: Baseline UK Biobank data from 502,504 individuals were collected between 2006 and 2010. Subsequent PSP and Parkinson’s disease cases were identified from primary and secondary care electronic health records’ diagnostic coding data and death registry, with 5,404 matched controls. Results: 176 PSP cases (time to diagnosis 7.8±2.8 years) and 2,526 Parkinson’s disease cases (time to diagnosis 7.8±2.9 years) were identified. At baseline, those later diagnosed with PSP had slower reaction times, weaker hand grip, lower fluid intelligence, prospective memory, self-rated health scores and digit recall than controls. Reaction times were correlated with time to diagnosis. The PSP group had higher mortality than both Parkinson’s disease and control groups. Conclusions: Motor slowing, cognitive dysfunction, and postural instability are clinical diagnostic features of PSP that are typically symptomatic three years before diagnosis. Objective markers of these features were evident on average 7.8 years before diagnosis. Our findings suggest the existence of a long prediagnostic phase in PSP, with subtle changes in motor and cognitive function.

This thesis focuses on the development and applications of magnetic resonance electrical properties tomography (MREPT), which is an emerging imaging modality to noninvasively obtain the electrical properties of tissues, such as conductivity and permittivity. Chapter 2 describes the general information about human research ethics, MRI scanner, MR sequence and the method of phase-based MREPT implemented in this thesis. Chapter 3 examines the repeatability of phase-based MREPT in the brain conductivity measurement using balanced fast field echo (bFFE) and turbo spin echo (TSE) sequences, and investigate the effects of compressed SENSE, whole-head B_1 shimming and video watching during scan on the measurement precision. Chapter 4 investigates the conductivity signal in response to short-duration visual stimulus, compares the signal and functional activation pathway with that of BOLD, and tests the consistency of functional conductivity imaging (funCI) with visual stimulation across participants. Chapter 5 extends the use of functional conductivity imaging to somatosensory stimulation and trigeminal nerve stimulation to evaluate the consistency of functional conductivity activation across different types of stimuli. In addition, visual adaptation experiment is performed to test if the repetition suppression effect can be observed using funCI. Chapter 6 explores if resting state conductivity networks can be reliably constructed using resting state funCI, evaluates the consistency of persistent homology architectures, and compares the links between nodes in the whole brain. Chapter 7 investigates the feasibility of prostate conductivity imaging using MREPT, and distinctive features in the conductivity distribution between healthy participants and participants with suspected abnormalities.

Among emerging technologies developed to interface neuronal signaling, engineering electrodes at the nanoscale would yield more precise biodevices opening to progress in neural circuit investigations and to new therapeutic potential. Despite remarkable progress in miniature electronics for less invasive neurostimulation, most nano-enabled, optically triggered interfaces are demonstrated in cultured cells, which precludes the studies of natural neural circuits. We exploit here free-standing silicon-based nanoscale photodiodes to optically modulate single, identified neurons in mammalian spinal cord explants. With near-infrared light stimulation, we show that activating single excitatory or inhibitory neurons differently affects sensory circuits processing in the dorsal horn. We successfully functionalize nano-photodiodes to target single molecules, such as glutamate AMPA receptor subunits, thus enabling light activation of specific synaptic pathways. We conclude that nano-enabled neural interfaces can modulate selected sensory networks with low invasiveness. The use of nanoscale photodiodes can thus provide original perspective in linking neural activity to specific behavioral outcome. We thank M. Gigante, G. Cellot, S. Mortal, and M. Lazzarino for help with setting up the laser stimulation setup; the group of P. Heppenstall for help with the AAV production; M. Giugliano for MATLAB code optimization; R. Owen for suggestions in antibody nPD characterization; and S. Usmani for help with initial experiments. This project was funded by HFSP program grant RGP0004/2019 (to L.B., B.T., and L.F.).

BACKGROUND: Scientific and societal interest is growing in understanding links between sports concussion and neurodegeneration. When multiple symptoms, such as memory loss, anxiety and headaches, persist after head impact(s), this is defined as post-concussion syndrome (PCS). Aetiology of PCS is poorly understood and there is no specific pharmacological cure. This study aimed to generate a novel sports PCS model in Drosophila melanogaster to facilitate further understanding of the syndrome. METHODS: The HIT device was constructed as per prior methods1 , but with protractor added and impact forces measured with a pancake load cell for repeatable trauma application to fly subgroups at 0° (control), 30°, 45° or 60° release angles, measured as 0N, 1.1N, 1.8N and 2.1N respectively. Hits were repeated five times with 48-72 hour intervals to model multiple traumas contact-sports players experience during their careers. To evaluate effects of impacts, motor ability, survival and reactive oxygen nitrogen species (RONS) levels were measured. Motor ability was reported as a percentage of the number of flies that climbed above 5.5cm in 5.5 seconds. Flies were frozen at 21-22 days post-eclosure (middle-age), heads and bodies separated and homogenised, then post-centrifugation supernatant was assayed with DCF-DA: condensed into highly fluorescent DCF in the presence of RONS, quantified by fluorescence spectroscopy. RESULTS: As with most human mild head trauma cases, fly motor ability was not significantly different acutely or long-term following HIT device impacts. Similarly, with 1.8N impacts, lifespan was not significantly different compared to non-trauma controls. Meanwhile, RONS levels increased in both fly heads (brains) and bodies (periphery) with five 1.8N impacts, representative of physiological stress in contact sportspeople with PCS. CONCLUSIONS: Five 1.8N hits (at 45° release angle) produced the most suitable Drosophila sports PCS model. This novel model offers a rapid, inexpensive drug screening approach for prospective PCS treatments, and shows promise in investigating the oxidative stress mechanisms underlying PCS. Additional analyses, including neurodegeneration biomarker quantification and behavioural monitoring, are currently being explored to validate this model. Reference: 1 Katzenberger RJ et al. (2013) PNAS 110, 4152-4159.

OBJECTIVE: To determine the prevalence and risk factors for cerebral microbleeds (CMB) at different locations in a large healthy community population. METHODS: 8159 subjects from UK Biobank with MRI scans suitable for CMB analysis were included. Brain susceptibility weighted imaging (SWI) data was acquired on two identical 3.0 T scanners. The Microbleed Anatomical Rating Scale (MARS) was used to identify definite CMB. Generalized linear models were used to determine independent associations with all CMB and lobar, deep and infratentorial CMB. RESULTS: The mean age at scan was 62.1±7.4 years. One of more definite CMB were detected in 572 (7.0%) of subjects. Of those with CMB 439 (76.7%) had lobar CMB, 103 (18.0%) had deep CMB, and 83 (14.5%) had infratentorial CMB. Age was an independent risk factor for CMB in all locations. ApoE4 and male sex were positively, and higher BMI were negatively associated, with lobar CMB. In contrast, hypertension, smoking and alcohol consumption were associated with deep CMB, but not with lobar CMB. Only age was associated with infratentorial CMB. The associations were unchanged after controlling for WMH lesion volume as a marker of small vessel disease severity. CONCLUSIONS: In this large population based study, the CMB prevalence detected using a low sensitivity and high specificity system was 7%. There were distinct risk factor profiles for CMB in lobar and deep locations consistent with different underlying pathophysiological processes.

Constipation is a common but not a universal feature in early PD, suggesting that gut involvement is heterogeneous and may be part of a distinct PD subtype with prognostic implications. We analysed data from the Parkinson’s Incidence Cohorts Collaboration, composed of incident community-based cohorts of PD patients assessed longitudinally over 8 years. Constipation was assessed with the MDS-UPDRS constipation item or a comparable categorical scale. Primary PD outcomes of interest were dementia, postural instability and death. PD patients were stratified according to constipation severity at diagnosis: none (n = 313, 67.3%), minor (n = 97, 20.9%) and major (n = 55, 11.8%). Clinical progression to all three outcomes was more rapid in those with more severe constipation at baseline (Kaplan–Meier survival analysis). Cox regression analysis, adjusting for relevant confounders, confirmed a significant relationship between constipation severity and progression to dementia, but not postural instability or death. Early constipation may predict an accelerated progression of neurodegenerative pathology.

Funder: Guangci Professorship Program, OBJECTIVES: Surgical procedures targeting the anterior limb of the internal capsule (aLIC) can be effective in patients with selected treatment-refractory obsessive-compulsive disorder (OCD). The aLIC consists of white-matter tracts connecting cortical and subcortical structures and show a topographical organisation. Here we assess how aLIC streamlines are affected in OCD compared with healthy controls (HCs) and which streamlines are related with post-capsulotomy improvement. METHODS: Diffusion-weighted MRI was used to compare white-matter microstructure via the aLIC between patients with OCD (n=100, 40 women, mean of age 31.8 years) and HCs (n=88, 39 women, mean of age 29.6 years). For each individual, the fractional anisotropy (FA) and streamline counts were calculated for each white-matter fibre bundle connecting a functionally defined prefrontal and subcortical region. Correlations between tractography measures and pre-capsulotomy and post-capsulotomy clinical outcomes (in obsessive-compulsive, anxiety and depression scores 6 months after surgery) were assessed in 41 patients with OCD. RESULTS: Hierarchical clustering dendrograms show an aLIC organisation clustering lateral and dissociating ventral and dorsal prefrontal-thalamic streamlines, findings highly relevant to surgical targeting. Compared with HCs, patients with OCD had lower aLIC FA across multiple prefrontal cortical-subcortical regions (p

Genetic, epidemiological and post-mortem studies implicate inflammation in the pathogenesis of schizophrenia. While inflammation can regulate neurogenesis, and is associated with brain structural and functional abnormalities, research addressing the link between inflammation and neurobiology in schizophrenia is limited. In the subependymal zone (SEZ), the brain’s largest niche for neurogenesis, I discovered vast differences across the whole transcriptome in schizophrenia compared to controls (post-mortem cohort n=20-21/group). CD163, a macrophage marker, had significantly increased expression in schizophrenia. Overall, genes in immune pathways were significantly upregulated, whereas genes in neurogenesis promoting pathways were significantly downregulated in schizophrenia along with reduced markers for all stages of neurogenesis. In a larger cohort, including bipolar disorder (n=29-32/group), macrophage cell density was increased specifically in schizophrenia. Cluster analysis of inflammation genes defined heightened inflammation subgroups comprising 37% of schizophrenia cases, 32% of bipolar disorder cases and only 10% of controls. The high inflammation schizophrenia subgroup had increased peripheral immune cell marker mRNAs, increased macrophage density, and altered markers for neurogenesis in the neurogenic niche suggesting increased stem cell quiescence and reduced neuronal progenitor cells and newborn neurons. These findings were replicated in an independent cohort (n=20-22). An analysis comparing the transcriptomes of high and low inflammation schizophrenia subgroups revealed that heightened inflammation alters the SEZ microenvironment by increasing angiogenesis and extracellular matrix stiffness, suggesting a fibrotic state. These changes likely increase blood-brain-barrier permeability and immune cell infiltration, and alter neuronal differentiation and migration. Allowing for translation potential of this research, I identified that peripheral inflammation marker, C-reactive protein (CRP), was increased in schizophrenia in a living cohort (n=1143). Increased CRP was associated with poorer attention ability and reduced cortical thickness in the caudal middle frontal, pars opercularis and posterior cingulate cortices in schizophrenia (MRI subset n=293). This thesis elucidated the molecular and cellular contribution of inflammation to aberrant neurogenesis in schizophrenia. Future manipulation of the identified cells and processes may enable the restoration of neurogenesis in schizophrenia and allow us to harness its potential for regenerative treatments. Further, inflammation biomarkers that have cognitive and brain structural relevance could identify schizophrenia patients who may benefit most from adjunctive treatment of inflammation.

Topographic maps are a brain structure connecting pre-synpatic and post-synaptic brain regions. Topographic development is dependent on Hebbian-based plasticity mechanisms working in conjunction with spontaneous patterns of neural activity generated in the pre-synaptic regions. Studies performed in mouse have shown that these spontaneous patterns can exhibit complex spatial-temporal structures which existing models cannot incorporate. Neural field theories are appropriate modelling paradigms for topographic systems due to the dense nature of the connections between regions and can be augmented with a plasticity rule general enough to capture complex time-varying structures. We propose a theoretical framework for studying the development of topography in the context of complex spatial-temporal activity fed-forward from the pre-synaptic to post-synaptic regions. Analysis of the model leads to an analytic solution corroborating the conclusion that activity can drive the refinement of topographic projections. The analysis also suggests that biological noise is used in the development of topography to stabilise the dynamics. MCMC simulations are used to analyse and understand the differences in topographic refinement between wild-type and the $\beta2$ knock-out mutant in mice. The time scale of the synaptic plasticity window is estimated as $0.56$ seconds in this context with a model fit of $R^2 = 0.81$., Comment: 15 pages, 5 figures

Cerebrovascular disease (CVD) is a leading cause of morbidity and mortality, with manifold clinical consequences including vascular dementia (VaD), the second most common dementia subtype. CVD also worsens the risk and expression of Alzheimer’s disease (AD). Diagnosing VaD requires determining whether a patient’s cognitive deficits can be explained by the current CVD burden. However, CVD is markedly pleomorphic and its full extent has been difficult to determine. Traditional markers of CVD such as white matter hyperintensities (WMH) are inconsistently associated with clinical outcomes. There is an unmet need to better quantify total CVD burden and relate it to cognition and dementia. CVD indices have been published, which combine information from several neuroimaging markers, in the hope to better capture the variability seen on neuroimaging and lead to more robust associations with cognition. In this thesis, the existing literature on neuroimaging and neuropathological indices of CVD was systematically reviewed. The contributions of two common but under-researched MRI CVD markers, cerebral microbleeds (CMB) and dilated perivascular spaces (PVS), were then assessed. The second chapter examines the association of CMB with both cross sectional and longitudinal impairment, finding associations with executive function and visuospatial function respectively. There was no existing reliable rating scale for quantification of PVS and the development of this is the theme of the third chapter. The fourth chapter examines the associations of dilated PVS with longitudinal cognitive impairment and incident dementia. I found that individuals with the most severe PVS had declines in Global Cognition and their presence triples the risk of developing dementia over 8 years. The fifth chapter describes the development of an MRI-based composite CVD index and its validation in two independent cohorts. Peak skeletonised mean diffusivity, a DTI measure, and WMH volume contributed most to the variability seen in Global Cognition. The Index explained 9% of the proportion of the variance seen in the development sample and 5 and 13 % in the validation cohorts respectively. It performed better than the most widely used CVD index in all cohorts examined. This work broadens the range of vascular pathologies used in the determination of the total CVD burden. The resulting composite index, while needing further refinement, represents a promising step-forward in the assessment of such burden in an individual, which could potentially help clinicians and researchers in determining the vascular contributions to dementia.

ObjectiveDepression and trauma are associated with changes in brain regions implicated in Alzheimer’s disease. The present study examined associations between childhood trauma, depression, adult cognitive functioning and risk of dementia.MethodsData from 378 participants in the PREVENT Dementia Study aged 40–59 years. Linear and logistic models were used to assess associations between childhood trauma, depression, dementia risk, cognitive test scores and hippocampal volume.ResultsChildhood trauma was associated with depression and reduced hippocampal volume but not current cognitive function or dementia risk. Poorer performance on a delayed face/name recall task was associated with depression. Childhood trauma was associated with lower hippocampal volume however poorer cognitive performance was mediated by depression rather than structural brain differences.ConclusionDepressive symptomatology may be associated with dementia risk via multiple pathways, and future studies should consider subtypes of depressive symptomatology when examining its relationship to dementia.

IntroductionAssociations between cerebral small vessel disease (SVD) and inflammation have been largely examined using peripheral blood markers of inflammation, with few studies measuring inflammation within the brain. We investigated the cross-sectional relationship between SVD and in vivo neuroinflammation using [11C]PK11195 positron emission tomography (PET) imaging.MethodsForty-two participants were recruited (according to NIA-AA guidelines, 14 healthy controls, 14 mild Alzheimer’s disease, 14 amyloid-positive mild cognitive impairment). Neuroinflammation was assessed using [11C]PK11195 PET imaging, a marker of microglial activation. To quantify SVD, we assessed white matter hyperintensities (WMH), enlarged perivascular spaces, cerebral microbleeds and lacunes. Composite scores were calculated for global SVD burden, and SVD subtypes of hypertensive arteriopathy and cerebral amyloid angiopathy (CAA). General linear models examined associations between SVD and [11C]PK11195, adjusting for sex, age, education, cognition, scan interval, and corrected for multiple comparisons via false discovery rate (FDR). Dominance analysis directly compared the relative importance of hypertensive arteriopathy and CAA scores as predictors of [11C]PK11195.ResultsGlobal [11C]PK11195 binding was associated with SVD markers, particularly in regions typical of hypertensive arteriopathy: deep microbleeds (β=0.63, F(1,35)=35.24, p11C]PK11195 binding globally and in 28 out of 37 regions of interest, especially the medial temporal lobe (β=0.66–0.76, t=3.90–5.58, FDR-corrected p (pFDR)=FDR=0.001–0.004).ConclusionMicroglial activation is associated with SVD, particularly with the hypertensive arteriopathy subtype of SVD. Although further research is needed to determine causality, our study suggests that targeting neuroinflammation might represent a novel therapeutic strategy for SVD.

We agree with the authors that the MSSS was devised as a descriptor of disease severity for groups of patients and was intended to be used for statistical comparisons between such groups, and thence also to be useful for stratification in clinical trials or just as a population disease severity descriptor. Other researchers have made claims for it as a prognostic measure for individuals.

Introduction Comorbid Alzheimer disease pathologies are frequently found in people with Down syndrome (DS). We report a deep phenotyping study undertaken over 7 years in a participant with DS who was nondemented at baseline but developed dementia after 5 years. Methods Throughout the course of the study, the participant was seen 4 times (2010, 2013, 2015, and 2017). Multimodal neuroimaging, including three serial scans of [11C]-PiB-PET, four structural magnetic resonance imagings, as well as a [18F]-AV1451 scan, was interpreted alongside detailed neuropsychological assessments over the study period. Results Amyloid beta accumulation preceded the onset of dementia and cognitive decline, which in turn corresponded to the predominant deposition of tau in temporoparietal cortices. Discussion Until now, data on the longitudinal trajectories of amyloid accumulation, tau pathology, and brain atrophy over multiple time points remain scarce in DS. This case report highlights the potential for deep phenotyping imaging to elucidate the substrates of cognitive decline in DS, although further longitudinal studies are necessary to clarify the relative contributions of both amyloid and tau.

not available

Background: Chronic stimulant use has been associated with disruptions in fronto-striatal systems implicated in as- sociative learning [1]. Experimental studies have also shown that individuals with stimulant drug addiction experience difficulties in selecting the appropriate action following feedback [2]. However, the precise impairments in feedback learning in stimulant-addicted individuals are still unclear. A possible explanation might lie in an abnormal prediction error mechanism, as stimulant drugs directly target striatal dopaminergic neurons [3].

TO THE EDITOR: We read with great interest the article by Chen et al.1 (Chen YC, Kuo CH, Cheng CM, Wu JC. Recent advances in the management of cervical spondylotic myelopathy: bibliometric analysis and surgical perspectives. JNSPG 75th Anniversary Invited Review Article. J Neurosurg Spine. September 2019;31(3):299–309).

The hues or the colorimetric purities of a pair of colored targets can be compared with similar precision whether the targets are juxtaposed or fall at well-separated positions in the visual field. This is the case even if the stimuli are 10° apart and fall in opposite hemifields. What could be the neural processes that underlie such comparisons? We are led to ask whether the long-range, white-matter tracts of the brain constitute a neural net (where representations are embodied in the weightings and signs of connections between the nodes of the net) or a communication network (where the same physical substrate carries different information from moment to moment).

BackgroundPain is modulated by expectation. Event-related potential (ERP) studies of the influence of expectation on pain typically utilise laser heat stimulation to provide a controllable nociceptive-specific stimulus. Short painful electric stimulation has a number of practical advantages, but is less nociceptive-specific. We compared the modulation of electric versus laser-evoked pain by expectation, and their corresponding pain-evoked and anticipatory ERPs.New MethodWe developed understanding of recognised methods of laser and electric stimulation. We tested whether pain perception and neural activity induced by electric stimulation was modulated by expectation, whether this expectation elicited anticipatory neural correlates, and how these measures compared to those associated with laser stimulation. We elicited cue-evoked expectations of high and low pain and compared subjective ratings and corresponding ERPs in response to the delivery of laser and electric stimulation in a within-participant design.ResultsDespite sensory and affective differences between laser and electric pain, intensity ratings and pain-evoked potentials were modulated equivalently by expectation, though ERPs only correlated with pain ratings in the laser pain condition. Anticipatory correlates significantly differentiated pain intensity expectation to laser but not electric pain.Comparison with Existing MethodPrevious studies have consistently shown that laser-evoked potentials are modulated by expectation. We extend this by showing electric pain-evoked potentials are equally modulated by expectation, within the same participants. We also show a difference between the pain types in anticipation.ConclusionsThough laser-evoked potentials express a stronger relationship with pain perception, both laser and electric stimulation may be used to study the modulation of pain-evoked potentials by expectation. Anticipatory-evoked potentials are elicited by both pain types, but they may reflect different processes and did not correlate with pain perception.

Whether smoking is causally associated with risk of ischemic stroke and intracerebral hemorrhage is unknown. We used the Mendelian randomization design to explore the associations of genetic predisposition to smoking with ischemic stroke and its subtypes as well as intracerebral hemorrhage. Up to 372 single-nucleotide polymorphisms were used as instrumental variables for smoking initiation. We used summary statistics data for 438 847 individuals in the analyses of ischemic stroke (34 217 cases and 404 630 non-cases) and 3026 individuals in analyses of intracerebral hemorrhage (1545 cases and 1481 non-cases). Genetic predisposition to smoking initiation was statistically significantly positively associated with any ischemic stroke, large artery stroke, and small vessel stroke but not cardioembolic stroke or intracerebral hemorrhage. The odds ratios per one standard deviation higher log-odds of ever smoking regularly (smoking initiation) were 1.24 (95% CI 1.16-1.32; p = 1.310-10) for any ischemic stroke, 1.64 (95% CI 1.40-1.91; p = 2.810-10) for large artery stroke, 1.47 (95% CI 1.26-1.71; p = 1.110-6) for small vessel stroke, 1.12 (95% CI 0.99-1.27; p = 0.08) for cardioembolic stroke, and 1.13 (95% CI 0.81-1.58; p = 0.47) for intracerebral hemorrhage. This study provides genetic support for a causal association of smoking with ischemic stroke, particularly large artery and small vessel stroke.

Reinforcement Learning describes a general method for trial-and-error learning, and has emerged as a dominant framework both for optimal control in autonomous robots, and understanding decision-making in the brain. Despite their common roots, however, these two fields have evolved largely independently. In this perspective we consider how each now face problems that could potentially be addressed by insights from the other, and argue that an interdisciplinary approach could greatly accelerate progress in both.

We agree with the authors that the MSSS was devised as a descriptor of disease severity for groups of patients and was intended to be used for statistical comparisons between such groups, and thence also to be useful for stratification in clinical trials or just as a population disease severity descriptor. Other researchers have made claims for it as a prognostic measure for individuals.

The PET ligand [18F]AV‐1451 was developed to bind tau pathology in Alzheimer's disease, but increased binding has been shown in both genetic tauopathies and in semantic dementia, a disease strongly associated with TDP‐43 pathology. Here we assessed [18F]AV‐1451 binding in behavioral variant frontotemporal dementia due to a hexanucleotide repeat expansion in C9orf72, characterized by TDP‐43 pathology. We show that the C9orf72 mutation increases binding in frontotemporal cortex, with a distinctive distribution of binding compared with healthy controls.

We have known for many years that the spinal cord can generate some basic locomotor outputs under specific experimental conditions without any input from the brain or the periphery (Stuart and Hultborn, 2008). However, when inputs from the brain are lost following spinal cord injury (SCI), the mammalian spinal cord is unable to generate normal, goal-directed locomotor outputs. In contrast, lower vertebrates spontaneously regenerate axons across lesion sites and recover locomotor function after complete spinal cord lesions (Cohen et al., 1988). The major focus of research into SCI in mammals has been to replicate this lower vertebrate capability by promoting the regeneration of lesioned axons or the sprouting of processes from spared axons, with the aim of reconnecting the spinal cord and thus repairing the damage caused by the injury (Steward et al., 2012). It is not that regeneration cannot occur in mammals, but it is instead actively inhibited. Why this inhibition has evolved in mammals is unknown. It would be useful to consider this question as it may help to explain why the various regeneration strategies that can successfully overcome this inhibition have so far failed to translate into an effective treatment for SCI (Steward et al., 2012). This article reviews work that we have done on the functional changes after recovery from SCI in the lamprey (Parker, 2017), and how these changes may relate to functional recovery in mammalian systems

Objectives: Glial fibrillary acidic protein (GFAP) and ubiquitin Cterminal hydrolase-L1 (UCH-L1) have been studied as potential biomarkers of mild traumatic brain injury (mTBI). We report the levels of GFAP and UCH-L1 in patients with acute orthopedic injuries without central nervous system involvement and relate them to the levels in patients with CT-negative mTBI. Methods: Serum UCH-L1 and GFAP were measured from 73 patients with acute orthopedic injury. The injury types were recorded and most of the patients underwent also a head MRI. The results were compared to those found in patients with CT-negative mTBI (n = 93). Results: The levels of GFAP were higher in patients with acute orthopedic trauma than in patients with CT-negative mTBI (p = 0.026). The levels of UCH-L1 were not significantly different between these two groups. Those patients with orthopedic trauma, who had levels of either or both of these biomarkers in the upper quartile, had significantly higher levels of both biomarkers than patients with CT-negative mTBI (p < 0.001). Conclusions: Levels of GFAP and UCH-L1 were not able to distinguish patients with CT negative mTBI from patients with orthopedic trauma. Patients with orthopedic trauma and high levels of UCH-L1 or GFAP values may be falsely diagnosed as having a concomitant mTBI. This casts a significant doubt on their diagnostic value in cases with mTBI. Keywords: GFAP, UCH-L1, orthopedic injury

This talk will cover our recent progress in understanding mechanisms of neurodegeneration and how this is informing new therapeutic approaches. The central concept is the identification of common pathways across the spectrum of these disorders (which include Alzheimer ’s and related diseases) that are relevant for both mechanistic insights and therapy. These include both ‘toxic’ processes that can be targeted to prevent neuronal death, and regenerative processes that can be harnessed for repair. I will discuss our data in mouse models targeting both of these aspects to prevent neurodegeneration and their relevance for human disease. I will focus on modulating the Unfolded Protein Response pharmacolog- ically and the recent discovery of repurposed drugs ready for clinical trials. I will also discuss the strategy of harnessing pathways that drive synapse regeneration, as occurs in hibernation, for the therapy of neurodegeneration.

© 2018 Elsevier Ltd The central cholinergic system and the amygdala are important for motivation and mnemonic processes. Different cholinergic populations innervate the amygdala, but it is unclear how these projections impact amygdala processes. Using optogenetic circuit-mapping strategies in choline acetyltransferase (ChAT)-cre mice, we demonstrate that amygdala-projecting basal forebrain and brainstem ChAT-containing neurons can differentially affect amygdala circuits and behavior. Photo-activating ChAT terminals in vitro revealed the underlying synaptic impact of brainstem inputs to the central lateral division to be excitatory, mediated via the synergistic glutamatergic activation of AMPA and NMDA receptors. In contrast, stimulating basal forebrain inputs to the basal nucleus resulted in endogenous acetylcholine (ACh) release, resulting in biphasic inhibition-excitation responses onto principal neurons. Such response profiles are physiological hallmarks of neural oscillations and could thus form the basis of ACh-mediated rhythmicity in amygdala networks. Consistent with this, in vivo basal forebrain ChAT+ activation strengthened amygdala basal nucleus theta and gamma frequency rhythmicity, both of which continued for seconds after stimulation and were dependent on local muscarinic and nicotinic receptor activation, respectively. Activation of brainstem ChAT-containing neurons, however, resulted in a transient increase in central lateral amygdala activity that was independent of cholinergic receptors. In addition, driving these respective inputs in behaving animals induced opposing appetitive and defensive learning-related behavioral changes. Because learning and memory are supported by both cellular and network-level processes in central cholinergic and amygdala networks, these results provide a route by which distinct cholinergic inputs can convey salient information to the amygdala and promote associative biophysical changes that underlie emotional memories. Aitta-aho et al. show that different cholinergic neuronal populations projecting to distinct amygdala nuclei coordinate local circuits and can reinforce approach and avoidance behavior. These results reveal separate mechanisms by which ACh populations can engage processes for inducing biophysical changes that underlie emotional memories.

Communication among neurons is the most promising technique for biocompatible nanonetworks. This necessitates the thorough communication theoretical analysis of information transmission among neurons. The information flow in neuro-spike communication channel is regulated by the ability of neurons to change their synaptic strengths over time, i.e. synaptic plasticity. Thus, the performance evaluation of the nervous nanonetwork is incomplete without considering the influence of synaptic plasticity. Hence, in this paper, we provide a comprehensive model for multiple-input single-output (MISO) neuro-spike communication by integrating the spike timing dependent plasticity (STDP) into existing channel model. We simulate this model for a realistic scenario with correlated inputs and varying spiking threshold. We show that plasticity is strengthening the correlated input synapses at the expense of weakening the synapses with uncorrelated inputs. Moreover, a nonlinear behavior in signal transmission is observed with changing spiking threshold.

© 2017 There is an unprecedented opportunity for psychologists and behavioral scientists to merge prior theory and research with big data to develop profound insights into the way people use and are affected by music. There are now streaming services that store data from millions of people on their day-to-day musical listening habits; song-level data that tags sonic and emotion attributes for millions of songs; wearable devices (e.g. watches and earbuds) that capture physiological metrics including heartrate and galvanic skin response; mobile technologies that track a person's moment-to-moment activity, location, mood, and sociability; and survey instruments and digital footprints that capture personality and other biopsychosocial metrics in just under a minute. We propose that merging these technologies can create a new age in music psychology that exponentially expands the present knowledge and scope of the field. The new data will advance general areas of music psychology, but will also provide an important opportunity to establish new knowledge about health and well-being that can have a direct impact on the public. By scientifically mapping how music changes behavior and health in the short-term and long-term, Big Music Data can lead to future health initiatives including the development of new evidence-based treatment modalities to be utilized by medical physicians and mental health practitioners. Importantly, industry and streaming services can use these new insights to optimize their technologies and develop music-based health and wellness platforms aimed at improving the well-being of its users, ultimately impacting the way music is used by millions of people globally.

Neuromodulation is mediated by neurotransmitters that typically act on G-protein-coupled receptors. It can confer behavioural flexibility by modifying the functional properties of anatomically hard-wired neural circuits. Single neuromodulators generally have divergent cellular and synaptic effects (Harris-Warrick and Johnson, 2010), and different modulators, of which there are many in even simpler systems, can interact by converging onto the same effectors. These interactions can generate synergistic, antagonistic, or novel effects (see Harris-Warrick and Johnson, 2010). Further modulator complexity is offered by the potential for concentration, time, and state-dependent influences (see Parker, 2015 and references therein). All of these effects can make neuromodulation highly flexible, making it difficult to predict or explain the functional effects resulting from the targeting of even a single modulatory system. As many clinically used drugs target G-protein-coupled receptors, being able to explain and predict these effects is important.

Academic research on whether social networks influence financial outcomes is still undeveloped. The literature has typically focused on three major questions — whether social networks affect investor behavior, firm behavior, or intermediary behavior. Because the theoretical framework in finance is organized around an accepted set of paradigms, and because data on intermediaries and firms have been publicly available for a long time, the financial economics area has just started using big data in its analysis. This note describes the extant research in this area and outlines how the field is likely to evolve.

Human behavior is the focus of many studies in the social, health, and behavioral sciences. Yet, few studies use behavioral observation methods to collect objective measures of behavior as it occurs in daily life, out in the real world — presumably the context of ultimate interest. Here, we provide a review of recent studies focused on measuring human behavior using smartphones and their embedded mobile sensors. To draw attention to current advances in the field of smartphone sensing, we describe the daily behaviors captured using these methods, which include movement behaviors (physical activity, mobility patterns), social behaviors (face-to-face encounters, computer-mediated communications), and other daily activities (non-mediated and mediated activities). We conclude by pointing to promising areas of future research for studies using Smartphone Sensing Methods (SSMs) in the behavioral sciences.