Detection of emotions in Parkinson's disease using higher order spectral features from brain's electrical activity

Non-motor symptoms in Parkinson's disease (PD) involving cognition and emotion have been progressively receiving more attention in recent times. Electroencephalogram (EEG) signals, being an activity of central nervous system, can reflect the underlying true emotional state of a person. This paper presents a computational framework for classifying PD patients compared to healthy controls (HC) using emotional information from the brain's electrical activity

The Impact of Worry on Attention to Threat

Prior research has often linked anxiety to attentional vigilance for threat using the dot probe task, which presents probes in spatial locations that were or were not preceded by a putative threat stimulus. The present study investigated the impact of worry on threat vigilance by administering this task during a worry condition and during a mental arithmetic control condition to 56 undergraduate students scoring in the low normal range on a measure of chronic worry. The worry induction was associated with faster responses than arithmetic to probes in the attended location following threat words, indicating the combined influence of worry and threat in facilitating attention. Within the worry condition, responses to probes in the attended location were faster for trials containing threat words than for trials with only neutral words, whereas the converse pattern was observed for responses to probes in the unattended location. This connection between worry states and attentional capture by threat may be central to understanding the impact of hypervigilance on information processing in anxiety and its disorders

Childhood Trauma History Is Linked To Abnormal Brain Connectivity In Major Depression

Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset ( n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: ( i ) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], ( ii ) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and ( iii ) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker

Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder.

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.PEV was supported by the Medical Research Council (grant no. MR/K020706/1) and is a Fellow of MQ: Transforming Mental Health (MQF17_24)

Accounting for Viscous Effects in Nonlinear Analyses of Strain Softening Clays

The results of static and dynamic nonlinear analyses of earthen structures are dependent on the implemented numerical methods including the constitutive models, the solution scheme, and the modeling software. Recent significant static failures (e.g., Feijão Dam 1) and past dynamic failures (e.g., 4th Ave. landslide in Anchorage, Alaska) have occurred due to yielding of the plastic soils. These failures were influenced by the strain-softening tendencies of the plastic soils, which highlights the need for continued development of numerical tools to model plastic soils in nonlinear analyses. This dissertation presents the development of a new constitutive model, a relationship that connects element level viscous behavior to field scale analyses, and system level analyses with new solution schemes that incorporate viscous effects and strain- softening in nonlinear analyses. First, a viscoplastic constitutive model for representing plastic silts and clays in geotechnical static slope stability applications is presented. The PM4SiltR model builds on the stress ratio-controlled, critical state-based, bounding surface plasticity model PM4Silt and is coded as a dynamic link library for use in the finite difference program FLAC 8.1. PM4SiltR incorporates strain rate-dependent shear strength, stress relaxation, and creep using a consistency approach combined with an internal strain rate and auto-decay process. Six parameters are introduced to control the viscous response of PM4SiltR while the parameters controlling the nonviscous portion of the response are the same as for PM4Silt. Single element simulations are presented to illustrate the influence of viscoplasticity on the constitutive response in direct simple shear loading and undrained creep. Single element responses are shown to be consistent with observed experimental results. Simulations of a hypothetical tailings dam of upstream construction are performed to illustrate use of PM4SiltR at the field scale. Results of field scale simulations show PM4SiltR can model undrained creep and progressive failure leading to delayed slope instability after relatively minor changes in loading conditions at.A numerical study is then presented that shows the effect that viscoplasticity can have on the localization process in sensitive, saturated clays and plastic silts. Numerical simulations of laboratory specimens of sensitive, viscoplastic soil subjected to monotonic, undrained, direct simple shear loading were performed using the PM4SiltR constitutive model. Parametric analyses evaluated the effects of soil sensitivity, post-peak strain-softening rate, and strain rate-dependency, as well as specimen size, mesh discretization, and loading rate. The numerical results showed that the global strain at which a localization forms primarily depends on the strain rate-dependency of the soil's shearing resistance relative to its rate of post-peak strain-softening. A regression model is subsequently presented that relates the global strain at the onset of localization to the soil's strain rate-dependency and post-peak strain-softening rate. The results indicate that the inclusion of reasonable levels of viscoplasticity significantly increases the strain that can develop before a localization develops in clays and plastic silts with modest strain-softening rates. The consistency of the numerical results with available laboratory observations is discussed. Implications for practice and future research needs are discussed.Next, two-dimensional viscoplastic nonlinear analyses of the 2019 Feijão Dam 1 failure in Brazil are performed using the finite difference program FLAC 8.1 with the user-defined constitutive models PM4SiltR and PM4Sand. A brief history of Feijão Dam 1, its failure, and the conflicting findings from two previous independent failure investigations are summarized. The present study uses the site characterization from those prior studies to develop the dam cross section, define material index properties, and establish groundwater conditions, but uses alternative techniques for characterizing undrained shear strengths. Simulations show that the dam was marginally stable against long-term consolidated, undrained conditions and that modest loading changes were sufficient to trigger failure with deformation patterns consistent with the observed failure. Simulations further show that collapse could have been triggered by a modest wetting event causing an increase in water content and loss of suction above the phreatic surface, by ongoing drilling activities causing a localized loss of shear strength in the tailings, or a combination of both mechanisms. Sensitivity of the results to choices in the calibration process and the numerical solution scheme are discussed. The implications of these results on the interpretation of the Feijão Dam 1 failure and long-term slope stability assessment procedures in practice are discussed.Finally, two investigations look at the influence of sensitivity and strain-softening on the seismic deformations of a set-back levee. First, nonlinear dynamic analyses are used to investigate how seismic deformations of a 6-m tall levee founded on a deposit of normally consolidated clay may vary with the sensitivity of the clay. The analysis results showed that strain-softening and associated strength loss in the clay layer increased with increasing clay sensitivity, but it did not result in increased levee deformations for the conditions examined. Instead, the results showed that increasing clay sensitivity slightly reduced the levee deformations, which was attributed to the strength loss in the clay also causing a reduction in the accelerations that developed in the levee. Second, the results of nonlinear dynamic analyses (NDAs) of an idealized levee founded on a sensitive clay are compared with simplified procedures that combine limit equilibrium (LE) and Newmark sliding block methods. The tendency for simplified procedures to underestimate or overestimate seismic deformations compared with NDA results is shown to depend on the specific conditions (e.g., soil sensitivity and brittleness, ground motion intensity, margin of safety against instability) and how potential strength loss is accounted for in the simplified methods. Limitations of these findings for practice are discussed.Overall, the outcomes from this dissertation contribute to an increased understanding on how to account for viscous effects and strain-softening in static and dynamic nonlinear analyses

Influence of strain-rate on localization and strain-softening in normally consolidated clays with varying strength profiles

The performance of geotechnical structures founded on normally consolidated (NC) clays under static or dynamic loading is dependent on the soil's strain-softening tendency and the potential for localizations to develop. Prior studies of the localization phenomenon have demonstrated that the addition of viscous (or strain-rate dependent) shearing resistance suppresses the onset of localization and provides a measure of regularization for the numerical simulation of the localization process. The onset of localization is delayed when the reduction in strength due to strain softening is counteracted by the increase in strength due to the increased strain rate that develops within a potential localization zone. Understanding localization tendencies is further complicated by spatial variability in clay properties. This paper presents a numerical study that investigates the combined effects of strain-rate, sensitivity, rate of strain softening, and varying strength profiles on the localization tendencies and the global stress-strain behavior of NC clays. The analyses were performed using the finite difference program FLAC 8.0 with the user-defined constitutive model PM4Silt modified to incorporate strain-rate effects. Parametric analyses examine the influence of strain rate, strength profile variations, local soil brittleness, and mesh size on the global post-peak stress-strain behavior of clays

Elevating the field for applying neuroimaging to individual patients in psychiatry

Abstract Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate