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\"This book presents recent advancements in positive psychology, specifically its application across broad areas of current interest. Chapters include submissions from various international authors in the field and cover discussion and presentation of relevant research, theories, and applications. The volume covers topics such as CBT, Psychotherapy, Coaching, Workplaces, Aging, Education, Leadership, Emotion, Interventions, Measurement, Technology, Design, Health, Relationships, Experiences, Communities. With the growing interest in the applications of positive psychology across diverse fields within psychology and beyond, this book will make a worthwhile contribution to the field. It will also fill the current need for a volume that highlights specifically the various recent advancements in positive psychology into diverse fields and as such will be of benefit to a wide range of professionals, including psychologists, educators, clinicians, therapists, and many others.\" -- Publisher's website.

A central challenge in the fMRI based study of functional connectivity is distinguishing neuronally related signal fluctuations from the effects of motion, physiology, and other nuisance sources. Conventional techniques for removing nuisance effects include modeling of noise time courses based on external measurements followed by temporal filtering. These techniques have limited effectiveness. Previous studies have shown using multi-echo fMRI that neuronally related fluctuations are Blood Oxygen Level Dependent (BOLD) signals that can be characterized in terms of changes in R2* and initial signal intensity (S0) based on the analysis of echo-time (TE) dependence. We hypothesized that if TE-dependence could be used to differentiate BOLD and non-BOLD signals, non-BOLD signal could be removed to denoise data without conventional noise modeling. To test this hypothesis, whole brain multi-echo data were acquired at 3 TEs and decomposed with Independent Components Analysis (ICA) after spatially concatenating data across space and TE. Components were analyzed for the degree to which their signal changes fit models for R2* and S0 change, and summary scores were developed to characterize each component as BOLD-like or not BOLD-like. These scores clearly differentiated BOLD-like “functional network” components from non BOLD-like components related to motion, pulsatility, and other nuisance effects. Using non BOLD-like component time courses as noise regressors dramatically improved seed-based correlation mapping by reducing the effects of high and low frequency non-BOLD fluctuations. A comparison with seed-based correlation mapping using conventional noise regressors demonstrated the superiority of the proposed technique for both individual and group level seed-based connectivity analysis, especially in mapping subcortical–cortical connectivity. The differentiation of BOLD and non-BOLD components based on TE-dependence was highly robust, which allowed for the identification of BOLD-like components and the removal of non BOLD-like components to be implemented as a fully automated procedure. [Display omitted] ► ICA components were analyzed for TE-dependence. ► Component-level TE-dependence scores identified BOLD components. ► BOLD networks were identified without spatial templates or frequency thresholds. ► Removing non-BOLD components dramatically denoised data. ► Robust subcortical-cortical connectivity was revealed after denoising.

Major depressive disorder (MDD) is associated with altered global brain connectivity (GBC), as assessed via resting-state functional magnetic resonance imaging (rsfMRI). Previous studies found that antidepressant treatment with ketamine normalized aberrant GBC changes in the prefrontal and cingulate cortices, warranting further investigations of GBC as a putative imaging marker. These results were obtained via global signal regression (GSR). This study is an independent replication of that analysis using a separate dataset. GBC was analyzed in 28 individuals with MDD and 22 healthy controls (HCs) at baseline, post-placebo, and post-ketamine. To investigate the effects of preprocessing, three distinct pipelines were used: (1) regression of white matter (WM)/cerebrospinal fluid (CSF) signals only (BASE); (2) WM/CSF + GSR (GSR); and (3) WM/CSF + physiological parameter regression (PHYSIO). Reduced GBC was observed in individuals with MDD only at baseline in the anterior and medial cingulate cortices, as well as in the prefrontal cortex only after regressing the global signal. Ketamine had no effect compared to baseline or placebo in either group in any pipeline. PHYSIO did not resemble GBC preprocessed with GSR. These results concur with several studies that used GSR to study GBC. Further investigations are warranted into disease-specific components of global fMRI signals that may drive these results and of GBCr as a potential imaging marker in MDD.

The hippocampus and amygdala have been implicated in the pathophysiology and treatment of major depressive disorder (MDD). Preclinical models suggest that stress-related changes in these regions can be reversed by antidepressants, including ketamine. Clinical studies have identified reduced volumes in MDD that are thought to be potentiated by early life stress and worsened by repeated depressive episodes. This study used 3T and 7T structural magnetic resonance imaging data to examine longitudinal changes in hippocampal and amygdalar subfield volumes associated with ketamine treatment. Data were drawn from a previous double-blind, placebo-controlled, crossover trial of healthy volunteers (HVs) unmedicated individuals with treatment-resistant depression (TRD) (3T: 18 HV, 26 TRD, 7T: 17 HV, 30 TRD) who were scanned at baseline and twice following either a 40 min IV ketamine (0.5 mg/kg) or saline infusion (acute: 1–2 days, interim: 9–10 days post infusion). No baseline differences were noted between the two groups. At 10 days post-infusion, a slight increase was observed between ketamine and placebo scans in whole left amygdalar volume in individuals with TRD. No other differences were found between individuals with TRD and HVs at either field strength. These findings shed light on the timing of ketamine’s effects on cortical structures.

Activity changes within the anterior cingulate cortex (ACC) are implicated in the antidepressant effects of ketamine, but the ACC is cytoarchitectonically and functionally heterogeneous and ketamine’s effects may be subregion specific. In the context of a double-blind randomized placebo-controlled crossover trial investigating the clinical and resting-state fMRI effects of intravenous ketamine vs. placebo in patients with treatment resistant depression (TRD) vs. healthy volunteers (HV), we used seed-based resting-state functional connectivity (rsFC) analyses to determine differential changes in subgenual ACC (sgACC), perigenual ACC (pgACC) and dorsal ACC (dACC) rsFC two days post-infusion. Across cingulate subregions, ketamine differentially modulated rsFC to the right insula and anterior ventromedial prefrontal cortex, compared to placebo, in TRD vs. HV; changes to pgACC-insula connectivity correlated with improvements in depression scores. Post-hoc analysis of each cingulate subregion separately revealed differential modulation of sgACC-hippocampal, sgACC-vmPFC, pgACC-posterior cingulate, and dACC-supramarginal gyrus connectivity. By comparing rsFC changes following ketamine vs. placebo in the TRD group alone, we found that sgACC rsFC was most substantially modulated by ketamine vs. placebo. Changes to sgACC-pgACC, sgACC-ventral striatal, and sgACC-dACC connectivity correlated with improvements in anhedonia symptoms. This preliminary evidence suggests that accurate segmentation of the ACC is needed to understand the precise effects of ketamine’s antidepressant and anti-anhedonic action.

Objectives This study explored the potential of non‐parametric and complexity analysis metrics to detect changes in activity post‐ketamine and their association with depressive symptomatology. Methods Individuals with treatment‐resistant depression (TRD: n = 27, 16F, 35.9 ± 10.8 years) and healthy volunteers (HVs: n = 9, 4F, 36.4 ± 9.59 years) had their activity monitored during an inpatient, double‐blind, crossover study where they received an infusion of ketamine or saline placebo. All participants were 18–65 years old, medication‐free, and had a MADRS score ≥20. Non‐parametric metrics averaged over each study day, metrics derived from complexity analysis, and traditionally calculated non‐parametric metrics averaged over two weeks were calculated from the actigraphy time series. A separate analysis was conducted for a subsample (n = 17) to assess the utility of these metrics in a hospital setting. Results In HVs, lower intradaily variability was observed within daily rest/activity patterns post‐ketamine versus post‐placebo (F = 5.16(1,15), p = 0.04). No other significant effects of drug or drug‐by‐time or correlations between depressive symptomatology and activity were detected. Conclusions Weak associations between non‐parametric variables and ketamine were found but were not consistent across actigraphy measures. Clinical Trial registration ClinicalTrials.gov, NCT00088699.

The present study investigated age-related differences in the amygdala and other nodes of face-processing networks in response to facial expression and familiarity. fMRI data were analyzed from 31 children (3.5–8.5 years) and 14 young adults (18–33 years) who viewed pictures of familiar (mothers) and unfamiliar emotional faces. Results showed that amygdala activation for faces over a scrambled image baseline increased with age. Children, but not adults, showed greater amygdala activation to happy than angry faces; in addition, amygdala activation for angry faces increased with age. In keeping with growing evidence of a positivity bias in young children, our data suggest that children find happy faces to be more salient or meaningful than angry faces. Both children and adults showed preferential activation to mothers’ over strangers’ faces in a region of rostral anterior cingulate cortex associated with self-evaluation, suggesting that some nodes in frontal evaluative networks are active early in development. This study presents novel data on neural correlates of face processing in childhood and indicates that preferential amygdala activation for emotional expressions changes with age.

Ketamine improves motivation-related symptoms in depression but simultaneously elicits similar symptoms in healthy individuals, suggesting that it might have different effects in health and disease. This study examined whether ketamine affects the brain’s fronto-striatal system, which is known to drive motivational behavior. The study also assessed whether inflammatory mechanisms—which are known to influence neural and behavioral motivational processes—might underlie some of these changes. These questions were explored in the context of a double-blind, placebo-controlled, crossover trial of ketamine in 33 individuals with treatment-resistant major depressive disorder (TRD) and 25 healthy volunteers (HVs). Resting-state functional magnetic resonance imaging (rsfMRI) was acquired 2 days post-ketamine (final sample: TRD n = 27, HV n = 19) and post-placebo (final sample: TRD n = 25, HV n = 18) infusions and was used to probe fronto-striatal circuitry with striatal seed-based functional connectivity. Ketamine increased fronto-striatal functional connectivity in TRD participants toward levels observed in HVs while shifting the connectivity profile in HVs toward a state similar to TRD participants under placebo. Preliminary findings suggest that these effects were largely observed in the absence of inflammatory (C-reactive protein) changes and were associated with both acute and sustained improvements in symptoms in the TRD group. Ketamine thus normalized fronto-striatal connectivity in TRD participants but disrupted it in HVs independently of inflammatory processes. These findings highlight the potential importance of reward circuitry in ketamine’s mechanism of action, which may be particularly relevant for understanding ketamine-induced shifts in motivational symptoms.

The functional magnetic resonance (fMRI) baseline is known to drift over the course of an experiment and is often attributed to hardware instability. These ultraslow fMRI fluctuations are inseparable from blood oxygenation level dependent (BOLD) changes in standard single echo fMRI and they are therefore typically removed before further analysis in both resting-state and task paradigms. However, some part of these fluctuations may be of neuronal origin, as neural activity can indeed fluctuate at the scale of several minutes or even longer, such as after the administration of drugs or during the ultradian rhythms. Here, we show that it is possible to separate the slow BOLD and non-BOLD drifts automatically using multi-echo fMRI and multi-echo independent components analysis (ME-ICA) denoising by demonstrating the detection of a visual signal evoked from a flickering checkerboard with slowly changing contrast. •Successful separation of slow task signal from slow non-BOLD baseline drifts using ME-ICA•ME-ICA resolves tasks responses more faithfully than standard preprocessing.•ME-ICA enables the study of low-frequency BOLD activity and the use of slower task paradigms.

Abstract Background Ketamine has rapid-acting antidepressant effects but is associated with psychotomimetic and other adverse effects. A 7-chlorokynurenic acid is a potent and specific glycine site N-methyl-d-aspartate receptor antagonist but crosses the blood-brain barrier inefficiently. Its prodrug, L-4-chlorokynurenine (4-Cl-KYN), exerts acute and sustained antidepressant-like effects in rodents and has no reported psychotomimetic effects in either rodents or healthy volunteers. This study examined whether 4-Cl-KYN has rapid antidepressant effects in individuals with treatment-resistant depression. Methods After a 2-week drug-free period, 19 participants with treatment-resistant depression were randomized to receive daily oral doses of 4-Cl-KYN monotherapy (1080 mg/d for 7 days, then 1440 mg/d for 7 days) or placebo for 14 days in a randomized, placebo-controlled, double-blind, crossover manner. The primary outcome measure was the Hamilton Depression Rating Scale score, assessed at several time points over a 2-week period; secondary outcome measures included additional rating scale scores. Pharmacokinetic measures of 7-chlorokynurenic acid and 4-Cl-KYN and pharmacodynamic assessments were obtained longitudinally and included 1H-magnetic resonance spectroscopy brain glutamate levels, resting-state functional magnetic resonance imaging, and plasma and cerebrospinal fluid measures of kynurenine metabolites and neurotrophic factors. Results Linear mixed models detected no treatment effects, as assessed by primary and secondary outcome measures. No difference was observed for any of the peripheral or central biological indices or for adverse effects at any time between groups. A 4-Cl-KYN was safe and well-tolerated, with generally minimal associated adverse events. Conclusions In this small crossover trial, 4-Cl-KYN monotherapy exerted no antidepressant effects at the doses and treatment duration studied. ClinicalTrials.gov identifier: NCT02484456.