An integrated brain-behavior model for working memory.

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network

Dissociable auditory mismatch response and connectivity patterns in adolescents with schizophrenia and adolescents with bipolar disorder with psychosis: A magnetoencephalography study

BACKGROUND: There is overlap between schizophrenia and bipolar disorder regarding genetic risk as well as neuropsychological and structural brain deficits. Finding common and distinct event-response potential (ERP) responses and connectivity patterns may offer potential biomarkers to distinguish the disorders. OBJECTIVE: To examine the neuronal auditory response elicited by a roving mismatch negativity (MMN) paradigm using magnetoencephalography (MEG). PARTICIPANTS: 15 Adolescents with schizophrenia (ASZ), 16 adolescents with bipolar disorder with psychosis (ABP), and 14 typically developing individuals (TD) METHODS: The data were analysed using time-series techniques and dynamic causal modelling (DCM). OUTCOME MEASURES: MEG difference wave (deviant - standard) at primary auditory (~90ms), MMN (~180ms) and long latency (~300ms). RESULTS: The amplitude of difference wave showed specific patterns at all latencies. Most notably, it was significantly reduced ABP compared to both controls and ASZ at early latencies. In contrast, the amplitude was significantly reduced in ASZ compared to both controls and ABP. The DCM analysis showed differential connectivity patterns in all three groups. Most notably, inter-hemispheric connections were strongly dominated by the right side in ASZ only. CONCLUSIONS: Dissociable patterns of the primary auditory response and MMN response indicate possible developmentally sensitive, but separate biomarkers for schizophrenia and bipolar disorder

Distribution of mesozooplankton resting eggs in seabottom sediments of Thermaikos gulf (NW Aegean Sea, Greece) and possible effects of sediment resuspension.

The distribution of mesozooplankton resting eggs was studied in the bottom sediments of Thermaikos Gulf (Aegean Sea, Greece), to study possible effects of sediment resuspension on egg assemblages, due to physical forcing (storm events) and/or anthropogenic activity (trawling). The total abundance of eggs in sediments was higher at stations located close to the rivers’ mouths, with muddy sediments, and with the water column richer of zooplankton, than at stations located at greater depths and with muddy-sand bed sediments. At the former stations the vertical distribution of eggs has revealed a trend of homogenization within the sediment column, from September to February. This is related probably to the sediment re-suspension. At the latter stations, no clear temporal variability in the vertical distribution was detected. The eggs found in the bottom sediments of Thermaikos Gulf were assigned to 16 morpho-types. Amongst these, those assigned to Paracartia latisetosa and Labidocera wollastoni (as well as one type called Calanoida 3), were found to be dominant at all the stations and during all the sampling periods, both as full and empty eggs

Neuroticism and conscientiousness respectively constrain and facilitate short-term plasticity within the working memory neural network

Individual differences in cognitive efficiency, particularly in relation to working memory (WM), have been associated both with personality dimensions that reflect enduring regularities in brain configuration, and with short-term neural plasticity, that reflects task-related changes in brain connectivity. To elucidate the relationship of these two divergent mechanisms, we tested the hypothesis that personality dimensions, which reflect enduring aspects of brain configuration, inform about the neurobiological framework within which short-term, task-related plasticity, as measured by effective connectivity, can be facilitated or constrained. As WM consistently engages the dorsolateral prefrontal (DLPFC), parietal (PAR), and anterior cingulate cortex (ACC), we specified a WM network model with bidirectional, ipsilateral, and contralateral connections between these regions from a functional magnetic resonance imaging dataset obtained from 40 healthy adults while performing the 3-back WM task. Task-related effective connectivity changes within this network were estimated using Dynamic Causal Modelling. Personality was evaluated along the major dimensions of Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Only two dimensions were relevant to task-dependent effective connectivity. Neuroticism and Conscientiousness respectively constrained and facilitated neuroplastic responses within the WM network. These results suggest individual differences in cognitive efficiency arise from the interplay between enduring and short-term plasticity in brain configuration

Independent modulation of engagement and connectivity of the facial network during affect processing by CACNA1C and ANK3 risk genes for bipolar disorder

IMPORTANCE: Genome-wide association studies (GWASs) indicate that single-nucleotide polymorphisms in the CACNA1C and ANK3 genes increase the risk for bipolar disorder (BD). The genes influence neuronal firing by modulating calcium and sodium channel functions, respectively. Both genes modulate γ-aminobutyric acid-transmitting interneuron function and can thus affect brain regional activation and interregional connectivity. OBJECTIVE: To determine whether the genetic risk for BD associated with 2 GWAS-supported risk single-nucleotide polymorphisms at CACNA1C rs1006737 and ANK3 rs10994336 is mediated through changes in regional activation and interregional connectivity of the facial affect-processing network. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional functional magnetic resonance imaging study at a research institute of 41 euthymic patients with BD and 46 healthy participants, all of British white descent. MAIN OUTCOMES AND MEASURES: Blood oxygen level-dependent signal and effective connectivity measures during the facial affect-processing task. RESULTS: In healthy carriers, both genetic risk variants were independently associated with increased regional engagement throughout the facial affect-processing network and increased effective connectivity between the visual and ventral prefrontal cortical regions. In contrast, BD carriers of either genetic risk variant exhibited pronounced reduction in ventral prefrontal cortical activation and visual-prefrontal effective connectivity. CONCLUSIONS AND RELEVANCE: Our data demonstrate that the effect of CACNA1C rs1006737 and ANK3 rs10994336 (or genetic variants in linkage disequilibrium) on the brain converges on the neural circuitry involved in affect processing and provides a mechanism linking BD to genome-wide genetic risk variants

Cortical thickness across the lifespan: data from 17,075 healthy individuals aged 3–90 years

Pathways through Adolescenc

Cortical Thickness and Subcortical Volume Trajectories Across the Lifespan: Data From 14,600 Healthy Individuals Aged 6-90 Years

Background: Age is a critical determinant of brain morphometry. We formed the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis(ENIGMA) Consortium to perform a large-scale analysis of cortical thickness data across more than 79 samples and14,600 healthy individuals aged 6-90 years. Methods: We used fractional polynomial (FP) regression to characterize age-related trajectories in brain morphometry. Normalized growth centiles were constructed using the para-metric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was analyzed using meta-analysis and one-way analysis of variance. Results: The volume of subcortical regions followed an inverted U-shaped trajectory while cortical thickness in almost all regions decreased during the first two to three decades of life and showed an attenuated or plateaued slope afterwards. Exceptions were the entorhinal, anterior cingulate and temporopolar cortices that followed attenuated age-related U-shaped trajectories. Age and its FP combinations explained up to 48% variance in morphometry. Sample, strength of the MRI scanner magnetic field and FreeSurfer version jointly accounted for a median of 17% of the variance. Conclusions: Our results could shed light on the uncertainties about age-related developmental trajectories of cortical thickness. The estimated centile values will provide scientists and clinicians with more efficient tools to detect brain morphological deviations and their association with behavioral, cognitive and clinical outcome

Practicalities in running early-phase trials using the time-to-event continual reassessment method (TiTE-CRM) for interventions with long toxicity periods using two radiotherapy oncology trials as examples

BACKGROUND: Awareness of model-based designs for dose-finding studies such as the Continual Reassessment Method (CRM) is now becoming more commonplace amongst clinicians, statisticians and trial management staff. In some settings toxicities can occur a long time after treatment has finished, resulting in extremely long, interrupted, CRM design trials. The Time-to-Event CRM (TiTE-CRM), a modification to the original CRM, accounts for the timing of late-onset toxicities and results in shorter trial duration. In this article, we discuss how to design and deliver a trial using this method, from the grant application stage through to dissemination, using two radiotherapy trials as examples. METHODS: The TiTE-CRM encapsulates the dose-toxicity relationship with a statistical model. The model incorporates observed toxicities and uses a weight to account for the proportion of completed follow-up of participants without toxicity. This model uses all available data to determine the next participant's dose and subsequently declare the maximum tolerated dose. We focus on two trials designed by the authors to illustrate practical issues when designing, setting up, and running such studies. RESULTS: In setting up a TiTE-CRM trial, model parameters need to be defined and the time element involved might cause complications, therefore looking at operating characteristics through simulations is essential. At the grant application stage, we suggest resources to fund statisticians' time before funding is awarded and make recommendations for the level of detail to include in funding applications. While running the trial, close contact of all involved staff is required as a dose decision is made each time a participant is recruited. We suggest ways of capturing data in a timely manner and give example code in R for design and delivery of the trial. Finally, we touch upon dissemination issues while the trial is running and upon completion. CONCLUSION: Model-based designs can be complex. We hope this paper will help clinical trial teams to demystify the conduct of TiTE-CRM trials and be a starting point for using this methodology in practice

Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia

BACKGROUND: Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms. METHODS: Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T(1)-weighted structural neuroimaging data from 84 patients (aged 16–35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16–37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters. RESULTS: HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE. DISCUSSION: Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted

Personalized Estimates of Brain Structural Variability in Individuals With Early Psychosis

Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples.; Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55). Regional brain variability in cortical thickness (CT), surface area (SA), and subcortical volume (SV) was assessed with the coefficient of variation (CV). Furthermore, the person-based similarity index (PBSI) was employed to quantify the similarity of CT, SA, and SV profile of each individual to others within the same diagnostic group. Normative modeling of the PBSI-CT, PBSI-SA, and PBSI-SV was used to identify CHR and FEP individuals whose scores deviated markedly from those of the healthy individuals.; There was no effect of diagnosis on the CV for any regional measure (P > .38). CHR and FEP individuals differed significantly from the HC group in terms of PBSI-CT (P < .0001), PBSI-SA (P < .0001), and PBSI-SV (P = .01). In the clinical groups, normative modeling identified 32 (22%) individuals with deviant PBSI-CT, 12 (8.4%) with deviant PBSI-SA, and 21 (15%) with deviant PBSI-SV; differences of small effect size indicated that individuals with deviant PBSI scores had lower IQ and higher psychopathology.; Examination of brain structural variability in early psychosis indicated heterogeneity at the level of individual profiles and encourages further large-scale examination to identify individuals that deviate markedly from normative reference data