Mapping the Neural Substrates of Behavior.

Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.

Perception of social inclusion/exclusion and response inhibition in adolescents with past suicide attempt: a multidomain task-based fMRI study.

The occurrence of suicidal behaviors increases during adolescence. Hypersensitivity to negative social signals and deficits in cognitive control are putative mechanisms of suicidal behaviors, which necessitate confirmation in youths. Multidomain functional neuroimaging could enhance the identification of patients at suicidal risk beyond standard clinical measures. Three groups of adolescents (N = 96; 78% females, age = 11.6-18.1) were included: patients with depressive disorders and previous suicide attempts (SA, n = 29); patient controls with depressive disorders but without any suicide attempt history (PC, n = 35); and healthy controls (HC, n = 32). We scanned participants with 3T-MRI during social inclusion/exclusion (Cyberball Game) and response inhibition (Go-NoGo) tasks. Neural activation was indexed by the blood-oxygenation-level dependent (BOLD) of the hemodynamic response during three conditions in the Cyberball Game ("Control condition", "Social Inclusion", and "Social Exclusion"), and two conditions in Go-NoGo task ("Go" and "NoGo" blocks). ANCOVA-style analysis identified group effects across three whole-brain contrasts: 1) NoGo vs. Go, 2) Social inclusion vs. control condition, 3) Social exclusion vs. control condition. We found that SA had lower activation in the left insula during social inclusion vs. control condition compared to PC and HC. Moreover, SA compared to PC had higher activity in the right middle prefrontal gyrus during social exclusion vs. control condition, and in bilateral precentral gyri during NoGo vs. Go conditions. Task-related behavioral and self-report measures (Self-reported emotional reactivity in the Cyberball Game, response times and number of errors in the Go-NoGo Task) did not discriminate groups. In conclusion, adolescent suicidal behaviors are likely associated with neural alterations related to the processing of social perception and response inhibition. Further research, involving prospective designs and diverse cohorts of patients, is necessary to explore the potential of neuroimaging as a tool in understanding the emergence and progression of suicidal behaviors.

Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: a large-scale meta-analysis of functional neuroimaging studies.

BACKGROUND: Over the past few decades, neuroimaging research in Bipolar Disorder (BD) has identified neural differences underlying cognitive and emotional processing. However, substantial clinical and methodological heterogeneity present across neuroimaging experiments potentially hinders the identification of consistent neural biomarkers of BD. This meta-analysis aims to comprehensively reassess brain activation and connectivity in BD in order to identify replicable differences that converge across and within resting-state, cognitive, and emotional neuroimaging experiments. METHODS: Neuroimaging experiments (using fMRI, PET, or arterial spin labeling) reporting whole-brain results in adults with BD and controls published from December 1999-June 18, 2019 were identified via PubMed search. Coordinates showing significant activation and/or connectivity differences between BD participants and controls during resting-state, emotional, or cognitive tasks were extracted. Four parallel, independent meta-analyses were calculated using the revised activation likelihood estimation algorithm: all experiment types, all resting-state experiments, all cognitive experiments, and all emotional experiments. To confirm reliability of identified clusters, two different meta-analytic significance tests were employed. RESULTS: 205 published studies yielding 506 individual neuroimaging experiments (150 resting-state, 134 cognitive, 222 emotional) comprising 5745 BD and 8023 control participants were included. Five regions survived both significance tests. Individuals with BD showed functional differences in the right posterior cingulate cortex during resting-state experiments, the left amygdala during emotional experiments, including those using a mixed (positive/negative) valence manipulation, and the left superior and right inferior parietal lobules during cognitive experiments, while hyperactivating the left medial orbitofrontal cortex during cognitive experiments. Across all experiments, there was convergence in the right caudate extending to the ventral striatum, surviving only one significance test. CONCLUSIONS: Our findings indicate reproducible localization of prefrontal, parietal, and limbic differences distinguishing BD from control participants that are condition-dependent, despite heterogeneity, and point towards a framework for identifying reproducible differences in BD that may guide diagnosis and treatment.

Altered patterns of central executive, default mode and salience network activity and connectivity are associated with current and future depression risk in two independent young adult samples.

Neural markers of pathophysiological processes underlying the dimension of subsyndromal-syndromal-level depression severity can provide objective, biologically informed targets for novel interventions to help prevent the onset of depressive and other affective disorders in individuals with subsyndromal symptoms, and prevent worsening symptom severity in those with these disorders. Greater functional connectivity (FC) among the central executive network (CEN), supporting emotional regulation (ER) subcomponent processes such as working memory (WM), the default mode network (DMN), supporting self-related information processing, and the salience network (SN), is thought to interfere with cognitive functioning and predispose to depressive disorders. We examined in young adults (1) relationships among activity and FC in these networks and current depression severity, using a paradigm designed to examine WM and ER capacity in n = 90, age = 21.7 (2.0); (2) the extent to which these relationships were specific to depression versus mania/hypomania; (3) whether findings in a first, "discovery" sample could be replicated in a second, independent, "test" sample of young adults n = 96, age = 21.6 (2.1); and (4) whether such relationships also predicted depression at up to 12 months post scan and/or mania/hypomania severity in (n = 61, including participants from both samples, age = 21.6 (2.1)). We also examined the extent to which there were common depression- and anxiety-related findings, given that depression and anxiety are highly comorbid. In the discovery sample, current depression severity was robustly predicted by greater activity and greater positive functional connectivity among the CEN, DMN, and SN during working memory and emotional regulation tasks (all ps < 0.05 qFDR). These findings were specific to depression, replicated in the independent sample, and predicted future depression severity. Similar neural marker-anxiety relationships were shown, with robust DMN-SN FC relationships. These data help provide objective, neural marker targets to better guide and monitor early interventions in young adults at risk for, or those with established, depressive and other affective disorders.

Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis.

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

A specific neural substrate predicting current and future impulsivity in young adults.

Impulsivity (rash action with deleterious outcomes) is common to many psychiatric disorders. While some studies indicate altered amygdala and prefrontal cortical (PFC) activity associated with impulsivity, it remains unclear whether these patterns of neural activity are specific to impulsivity or common to a range of affective and anxiety symptoms. To elucidate neural markers specific to impulsivity, we aimed to differentiate patterns of amygdala-PFC activity and functional connectivity associated with impulsivity from those associated with affective and anxiety symptoms, and identify measures of this circuitry predicting future worsening of impulsivity. Using a face emotion processing task that reliably activates amygdala-PFC circuitry, neural activity and connectivity were assessed in a transdiagnostically-recruited sample of young adults, including healthy (N = 47) and treatment-seeking individuals (N = 67). Relationships were examined between neural measures and impulsivity, anhedonia, and affective and anxiety symptoms at baseline (N = 114), and at 6 months post scan (N = 30). Impulsivity, particularly negative urgency and lack of perseverance, was related to greater amygdala activity (beta = 0.82, p = 0.003; beta = 0.68, p = 0.004; respectively) and lower amygdala-medial PFC functional connectivity (voxels = 60, tpeak = 4.45, pFWE = 0.017; voxels = 335, tpeak = 5.26, pFWE = 0.001; respectively) to facial fear. Left vlPFC, but not amygdala, activity to facial anger was inversely associated with mania/hypomania (beta = -2.08, p = 0.018). Impulsivity 6 months later was predicted by amygdala activity to facial sadness (beta = 0.50, p = 0.017). There were no other significant relationships between neural activity and 6-month anhedonia, affective, and anxiety symptoms. Our findings are the first to associate amygdala-PFC activity and functional connectivity with impulsivity in a large, transdiagnostic sample, providing neural targets for future interventions to reduce predisposition to impulsivity and related future mental health problems in young adults.

Distinguishing between depression in bipolar disorder and unipolar depression using magnetic resonance imaging: a systematic review.

OBJECTIVES: Magnetic resonance imaging (MRI) studies comparing bipolar and unipolar depression characterize pathophysiological differences between these conditions. However, it is difficult to interpret the current literature due to differences in MRI modalities, analysis methods, and study designs. METHODS: We conducted a systematic review of publications using MRI to compare individuals with bipolar and unipolar depression. We grouped studies according to MRI modality and task design. Within the discussion, we critically evaluated and summarized the functional MRI research and then further complemented these findings by reviewing the structural MRI literature. RESULTS: We identified 88 MRI publications comparing participants with bipolar depression and unipolar depressive disorder. Compared to individuals with unipolar depression, participants with bipolar disorder exhibited heightened function, increased within network connectivity, and reduced grey matter volume in salience and central executive network brain regions. Group differences in default mode network function were less consistent but more closely associated with depressive symptoms in participants with unipolar depression but distractibility in bipolar depression. CONCLUSIONS: When comparing mood disorder groups, the neuroimaging evidence suggests that individuals with bipolar disorder are more influenced by emotional and sensory processing when responding to their environment. In contrast, depressive symptoms and neurofunctional response to emotional stimuli were more closely associated with reduced central executive function and less adaptive cognitive control of emotionally oriented brain regions in unipolar depression. Researchers now need to replicate and refine network-level trends in these heterogeneous mood disorders and further characterize MRI markers associated with early disease onset, progression, and recovery.

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.

Reduced frontostriatal response to expected value and reward prediction error in remitted monozygotic twins with mood disorders and their unaffected high-risk co-twins.

BACKGROUND: Depressive episodes experienced in unipolar (UD) and bipolar (BD) disorders are characterized by anhedonia and have been associated with abnormalities in reward processes related to reward valuation and error prediction. It remains however unclear whether these deficits are associated with familial vulnerability to mood disorders. METHODS: In a functional magnetic resonance imaging study, we evaluated differences in the expected value (EV) and reward prediction error (RPE) signals in ventral striatum (VS) and prefrontal cortex between three groups of monozygotic twins: affected twins in remission for either UD or BD (n = 53), their high-risk unaffected co-twins (n = 34), and low-risk twins with no family history of mood disorders (n = 25). RESULTS: Compared to low-risk twins, affected twins showed lower EV signal bilaterally in the frontal poles and lower RPE signal bilaterally in the VS, left frontal pole and superior frontal gyrus. The high-risk group did not show a significant change in the EV or RPE signals in frontostriatal regions, yet both reward signals were consistently lower compared with low-risk twins in all regions where the affected twins showed significant reductions. CONCLUSION: Our findings strengthen the notion that reduced valuation of expected rewards and reduced error-dependent reward learning may underpin core symptom of depression such as loss of interest in rewarding activities. The trend reduction in reward-related signals in unaffected co-twins warrants further investigation of this effect in larger samples and prospective follow-up to confirm possible association with increased familial vulnerability to mood disorders.

Lithium prevents grey matter atrophy in patients with bipolar disorder: an international multicenter study.

BACKGROUND: Lithium (Li) is the gold standard treatment for bipolar disorder (BD). However, its mechanisms of action remain unknown but include neurotrophic effects. We here investigated the influence of Li on cortical and local grey matter (GM) volumes in a large international sample of patients with BD and healthy controls (HC). METHODS: We analyzed high-resolution T1-weighted structural magnetic resonance imaging scans of 271 patients with BD type I (120 undergoing Li) and 316 HC. Cortical and local GM volumes were compared using voxel-wise approaches with voxel-based morphometry and SIENAX using FSL. We used multiple linear regression models to test the influence of Li on cortical and local GM volumes, taking into account potential confounding factors such as a history of alcohol misuse. RESULTS: Patients taking Li had greater cortical GM volume than patients without. Patients undergoing Li had greater regional GM volumes in the right middle frontal gyrus, the right anterior cingulate gyrus, and the left fusiform gyrus in comparison with patients not taking Li. CONCLUSIONS: Our results in a large multicentric sample support the hypothesis that Li could exert neurotrophic and neuroprotective effects limiting pathological GM atrophy in key brain regions associated with BD.

Transcranial direct current stimulation: a roadmap for research, from mechanism of action to clinical implementation.

Transcranial direct current stimulation (tDCS) is a promising method for altering the function of neural systems, cognition, and behavior. Evidence is emerging that it can also influence psychiatric symptomatology, including major depression and schizophrenia. However, there are many open questions regarding how the method might have such an effect, and uncertainties surrounding its influence on neural activity, and human cognition and functioning. In the present critical review, we identify key priorities for future research into major depression and schizophrenia, including studies of the mechanism(s) of action of tDCS at the neuronal and systems levels, the establishment of the cognitive impact of tDCS, as well as investigations of the potential clinical efficacy of tDCS. We highlight areas of progress in each of these domains, including data that appear to favor an effect of tDCS on neural oscillations rather than spiking, and findings that tDCS administration to the prefrontal cortex during task training may be an effective way to enhance behavioral performance. Finally, we provide suggestions for further empirical study that will elucidate the impact of tDCS on brain and behavior, and may pave the way for efficacious clinical treatments for psychiatric disorders.

Discovery and replication of cerebral blood flow differences in major depressive disorder.

Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.

Reward related ventral striatal activity and differential response to sertraline versus placebo in depressed individuals.

Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. A total of 222 unmedicated adults with MDD randomized to receive sertraline (n = 110) or placebo (n = 112) in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study completed demographic and clinical assessments, and pretreatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression (HSRD) over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on week-8 depression levels (Fs ≥ 9.67, ps ≤ 0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pretreatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pretreatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment.

Functional differentiation in the human ventromedial frontal lobe: A data-driven parcellation.

Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.

Clinical, cortical thickness and neural activity predictors of future affective lability in youth at risk for bipolar disorder: initial discovery and independent sample replication.

We aimed to identify markers of future affective lability in youth at bipolar disorder risk from the Pittsburgh Bipolar Offspring Study (BIOS) (n = 41, age = 14, SD = 2.30), and validate these predictors in an independent sample from the Longitudinal Assessment of Manic Symptoms study (LAMS) (n = 55, age = 13.7, SD = 1.9). We included factors of mixed/mania, irritability, and anxiety/depression (29 months post MRI scan) in regularized regression models. Clinical and demographic variables, along with neural activity during reward and emotion processing and gray matter structure in all cortical regions at baseline, were used to predict future affective lability factor scores, using regularized regression. Future affective lability factor scores were predicted in both samples by unique combinations of baseline neural structure, function, and clinical characteristics. Lower bilateral parietal cortical thickness, greater left ventrolateral prefrontal cortex thickness, lower right transverse temporal cortex thickness, greater self-reported depression, mania severity, and age at scan predicted greater future mixed/mania factor score. Lower bilateral parietal cortical thickness, greater right entorhinal cortical thickness, greater right fusiform gyral activity during emotional face processing, diagnosis of major depressive disorder, and greater self-reported depression severity predicted greater irritability factor score. Greater self-reported depression severity predicted greater anxiety/depression factor score. Elucidating unique clinical and neural predictors of future-specific affective lability factors is a step toward identifying objective markers of bipolar disorder risk, to provide neural targets to better guide and monitor early interventions in bipolar disorder at-risk youth.

Klotho deficiency affects the spine morphology and network synchronization of neurons.

Klotho-deficient mice rapidly develop cognitive impairment and show some evidence of the onset of neurodegeneration. However, it is impossible to investigate the long-term consequences on the brain because of the dramatic shortening of lifespan caused by systemic klotho deficiency. As klotho expression is downregulated with advancing organismal age, understanding the mechanisms of klotho action is important for developing novel strategies to support healthy brain aging. Previously, we reported that klotho-deficient mice show enhanced long-term potentiation prior to the onset of cognitive impairment. To inform this unusual phenotype, herein, we examined neuronal structure and in vitro synaptic function. Our results indicate that klotho deficiency causes the population of dendritic spines to shift towards increased head diameter and decreased length consistent with mature, mushroom type spines. Multi-electrode array recordings from klotho-deficient neurons show increased synchronous firing and activity changes reflective of increased neuronal network activity. Supplementation of the neuronal growth media with recombinant shed klotho corrected some but not all of the activity changes caused by klotho deficiency. Last, in vivo we found that klotho-deficient mice have a decreased latency to induced seizure activity. Together these data show that klotho-deficient memory impairments are underpinned by structural and functional changes that may preclude ongoing normal cognition.

Functional Segmentation of the Anterior Limb of the Internal Capsule: Linking White Matter Abnormalities to Specific Connections.

The anterior limb of the internal capsule (ALIC) carries thalamic and brainstem fibers from prefrontal cortical regions that are associated with different aspects of emotion, motivation, cognition processing, and decision-making. This large fiber bundle is abnormal in several psychiatric illnesses and a major target for deep brain stimulation. Yet, we have very little information about where specific prefrontal fibers travel within the bundle. Using a combination of tracing studies and diffusion MRI in male nonhuman primates, as well as diffusion MRI in male and female human subjects, we segmented the human ALIC into five regions based on the positions of axons from different cortical regions within the capsule. Fractional anisotropy (FA) abnormalities in patients with bipolar disorder were detected when FA was averaged in the ALIC segment that carries ventrolateral prefrontal cortical connections. Together, the results set the stage for linking abnormalities within the ALIC to specific connections and demonstrate the utility of applying connectivity profiles of large white matter bundles based on animal anatomic studies to human connections and associating disease abnormalities in those pathways with specific connections. The ability to functionally segment large white matter bundles into their components begins a new era of refining how we think about white matter organization and use that information in understanding abnormalities.SIGNIFICANCE STATEMENT The anterior limb of the internal capsule (ALIC) connects prefrontal cortex with the thalamus and brainstem and is abnormal in psychiatric illnesses. However, we know little about the location of specific prefrontal fibers within the bundle. Using a combination of animal tracing studies and diffusion MRI in animals and human subjects, we segmented the human ALIC into five regions based on the positions of axons from different cortical regions. We then demonstrated that differences in FA values between bipolar disorder patients and healthy control subjects were specific to a given segment. Together, the results set the stage for linking abnormalities within the ALIC to specific connections and for refining how we think about white matter organization in general.

Longitudinal changes in brain activation during anticipation of monetary loss in bipolar disorder.

BACKGROUND: Individuals with bipolar disorder (BD) show aberrant brain activation patterns during reward and loss anticipation. We examined for the first time longitudinal changes in brain activation during win and loss anticipation to identify trait markers of aberrant anticipatory processing in BD. METHODS: Thirty-four euthymic and depressed individuals with BD-I and 17 healthy controls (HC) were scanned using functional magnetic resonance imaging twice 6 months apart during a reward task. RESULTS: HC, but not individuals with BD, showed longitudinal reductions in the right lateral occipital cortex (RLOC) activation during processing of cues predicting possible money loss (p-corrected <0.05). This result was not affected by psychotropic medication, mood state or the changes in depression/mania severity between the two scans in BD. Elevated symptoms of subthreshold hypo/mania at baseline predicted more aberrant longitudinal patterns of RLOC activation explaining 12.5% of variance in individuals with BD. CONCLUSIONS: Increased activation in occipital cortex during negative outcome anticipation may be related to elevated negative emotional arousal during anticipatory cue processing. One interpretation is that, unlike HC, individuals with BD were not able to learn at baseline that monetary losses were smaller than monetary gains and were not able to reduce emotional arousal for negative cues 6 months later. Future research in BD should examine how modulating occipital cortical activation affects learning from experience in individuals with BD.

Trauma-associated anterior cingulate connectivity during reward learning predicts affective and anxiety states in young adults.

BACKGROUND: Trauma exposure is associated with development of depression and anxiety; yet, some individuals are resilient to these trauma-associated effects. Differentiating mechanisms underlying development of negative affect and resilience following trauma is critical for developing effective interventions. One pathway through which trauma could exert its effects on negative affect is reward-learning networks. In this study, we examined relationships among lifetime trauma, reward-learning network function, and emotional states in young adults. METHODS: One hundred eleven young adults self-reported trauma and emotional states and underwent functional magnetic resonance imaging during a monetary reward task. Trauma-associated neural activation and functional connectivity were analyzed during reward prediction error (RPE). Relationships between trauma-associated neural functioning and affective and anxiety symptoms were examined. RESULTS: Number of traumatic events was associated with greater ventral anterior cingulate cortex (vACC) activation, and lower vACC connectivity with the right insula, frontopolar, inferior parietal, and temporoparietal regions, during RPE. Lower trauma-associated vACC connectivity with frontoparietal regions implicated in regulatory and decision-making processes was associated with heightened affective and anxiety symptoms; lower vACC connectivity with insular regions implicated in interoception was associated with lower affective and anxiety symptoms. CONCLUSIONS: In a young adult sample, two pathways linked the impact of trauma on reward-learning networks with higher v. lower negative affective and anxiety symptoms. The disconnection between vACC and regions implicated in decision-making and self-referential processes may reflect aberrant regulatory but appropriate self-focused mechanisms, respectively, conferring risk for v. resilience against negative affective and anxiety symptoms.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.