The neuroscience and context of adolescent depression
2016; 105 (4): 358-365
Adolescent depression is a growing public health concern with an increased risk of negative health outcomes, including suicide. The use of antidepressants and psychotherapy has not halted its increasing prevalence, and there is a critical need for effective prevention and treatment. We reviewed the neuroscience of adolescent depression, with a focus on the neurocircuitry of sustained threat and summarised contextual factors that have an impact on brain development and the pathophysiology of depression. We also reviewed novel treatment models.Attention to the relevant neurocircuitry and contextual factors implicated in adolescent depression is necessary to advance prevention and treatment development.
View details for DOI 10.1111/apa.13299
View details for Web of Science ID 000371892200016
View details for PubMedID 26663379
- Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder PSYCHIATRY RESEARCH-NEUROIMAGING 2016; 249: 91-96
Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder.
2016; 249: 91-96
Neural models of major depressive disorder (MDD) posit that over-response of components of the brain's salience network (SN) to negative stimuli plays a crucial role in the pathophysiology of MDD. In the present proof-of-concept study, we tested this formulation directly by examining the affective consequences of training depressed persons to down-regulate response of SN nodes to negative material. Ten participants in the real neurofeedback group saw, and attempted to learn to down-regulate, activity from an empirically identified node of the SN. Ten other participants engaged in an equivalent procedure with the exception that they saw SN-node neurofeedback indices from participants in the real neurofeedback group. Before and after scanning, all participants completed tasks assessing emotional responses to negative scenes and to negative and positive self-descriptive adjectives. Compared to participants in the sham-neurofeedback group, from pre- to post-training, participants in the real-neurofeedback group showed a greater decrease in SN-node response to negative stimuli, a greater decrease in self-reported emotional response to negative scenes, and a greater decrease in self-reported emotional response to negative self-descriptive adjectives. Our findings provide support for a neural formulation in which the SN plays a primary role in contributing to negative cognitive biases in MDD.
View details for DOI 10.1016/j.pscychresns.2016.01.016
View details for PubMedID 26862057
- Fusiform Gyrus Dysfunction is Associated with Perceptual Processing Efficiency to Emotional Faces in Adolescent Depression: A Model-Based Approach FRONTIERS IN PSYCHOLOGY 2016; 7
Cortical thickness predicts the first onset of major depression in adolescence
INTERNATIONAL JOURNAL OF DEVELOPMENTAL NEUROSCIENCE
2015; 46: 125-131
Given the increasing prevalence of Major Depressive Disorder and recent advances in preventative treatments for this disorder, an important challenge in pediatric neuroimaging is the early identification of individuals at risk for depression. We examined whether machine learning can be used to predict the onset of depression at the individual level. Thirty-three never-disordered adolescents (10-15 years old) underwent structural MRI. Participants were followed for 5 years to monitor the emergence of clinically significant depressive symptoms. We used support vector machines (SVMs) to test whether baseline cortical thickness could reliably distinguish adolescents who develop depression from adolescents who remained free of any Axis I disorder. Accuracies from subsampled cross-validated classification were used to assess classifier performance. Baseline cortical thickness correctly predicted the future onset of depression with an overall accuracy of 70% (69% sensitivity, 70% specificity; p=0.021). Examination of SVM feature weights indicated that the right medial orbitofrontal, right precentral, left anterior cingulate, and bilateral insular cortex contributed most strongly to this classification. These findings indicate that cortical gray matter structure can predict the subsequent onset of depression. An important direction for future research is to elucidate mechanisms by which these anomalies in gray matter structure increase risk for developing this disorder.
View details for DOI 10.1016/j.ijdevneu.2015.07.007
View details for Web of Science ID 000362139500018
View details for PubMedID 26315399
Meta-analysis of Functional Neuroimaging of Major Depressive Disorder in Youth
2015; 72 (10): 1045-1053
Despite its high prevalence and morbidity, the underlying neural basis of major depressive disorder (MDD) in youth is not well understood.To identify in youth diagnosed as having MDD the most reliable neural abnormalities reported in existing functional neuroimaging studies and characterize their relations with specific psychological dysfunctions.Searches were conducted in PubMed and Web of Science to identify relevant studies published from November 2006 through February 2015. The current analysis took place from August 21, 2014, to March 28, 2015.We retained articles that conducted a comparison of youth aged 4 to 24 years diagnosed as having MDD and age-matched healthy controls using task-based functional magnetic resonance imaging and a voxelwise whole-brain approach.We extracted coordinates of brain regions exhibiting differential activity in youth with MDD compared with healthy control participants. Multilevel kernel density analysis was used to examine voxelwise between-group differences throughout the whole brain. Correction for multiple comparisons was performed by computing null hypothesis distributions from 10 000 Monte Carlo simulations and calculating the cluster size necessary to obtain the familywise error rate control at P < .05.Abnormal levels of activation in youth diagnosed as having MDD compared with control participants during a variety of affective processing and executive functioning tasks.Compared with age-matched healthy control participants (n = 274), youth with MDD (n = 246) showed reliable patterns of abnormal activation, including the following task-general and task-specific effects: hyperactivation in subgenual anterior cingulate cortex (P < .05) and ventrolateral prefrontal cortex (P < .05) and hypoactivation in caudate (P < .01) across aggregated tasks; hyperactivation in thalamus (P < .03) and parahippocampal gyrus (P < .003) during affective processing tasks; hypoactivation in cuneus (P < .001), dorsal cingulate cortex (P < .05), and dorsal anterior insula (P < .05) during executive functioning tasks; hypoactivity in posterior insula (P < .005) during positive valence tasks; and hyperactivity in dorsolateral prefrontal cortex (P < .001) and superior temporal cortex (P < .003) during negative valence tasks.Altered activations in several distributed brain networks may help explain the following seemingly disparate symptoms of MDD in youth: hypervigilance toward emotional stimuli from the overactivation of central hubs in the subgenual anterior cingulate cortex and thalamus that lead to a cascade of other symptoms; ineffective emotion regulation despite increased activation of the dorsolateral prefrontal cortex and ventrolateral prefrontal cortex during affective processing, which may reverse across development or the clinical course; maladaptive rumination and poor executive control from difficulties shifting from default mode network activity to task-positive network activity during cognitively demanding tasks; and anhedonia from hypoactivation of the cuneus and posterior insula during reward processing.
View details for DOI 10.1001/jamapsychiatry.2015.1376
View details for Web of Science ID 000362972000017
View details for PubMedID 26332700
Subcortical volumes differentiate Major Depressive Disorder, Bipolar Disorder, and remitted Major Depressive Disorder
JOURNAL OF PSYCHIATRIC RESEARCH
2015; 68: 91-98
Subcortical gray matter regions have been implicated in mood disorders, including Major Depressive Disorder (MDD) and Bipolar Disorder (BD). It is unclear, however, whether or how these regions differ among mood disorders and whether such abnormalities are state- or trait-like. In this study, we examined differences in subcortical gray matter volumes among euthymic BD, MDD, remitted MDD (RMD), and healthy (CTL) individuals. Using automated gray matter segmentation of T1-weighted MRI images, we estimated volumes of 16 major subcortical gray matter structures in 40 BD, 57 MDD, 35 RMD, and 61 CTL individuals. We used multivariate analysis of variance to examine group differences in these structures, and support vector machines (SVMs) to assess individual-by-individual classification. Analyses yielded significant group differences for caudate (p = 0.029) and ventral diencephalon (VD) volumes (p = 0.003). For the caudate, both the BD (p = 0.004) and the MDD (p = 0.037) participants had smaller volumes than did the CTL participants. For the VD, the MDD participants had larger volumes than did the BD and CTL participants (ps < 0.005). SVM distinguished MDD from BD with 59.5% accuracy. These findings indicate that mood disorders are characterized by anomalies in subcortical gray matter volumes and that the caudate and VD contribute uniquely to differential affective pathology. Identifying abnormalities in subcortical gray matter may prove useful for the prevention, diagnosis, and treatment of mood disorders.
View details for DOI 10.1016/j.jpsychires.2015.06.002
View details for Web of Science ID 000359956100015
Common and distinct neural correlates of personal and vicarious reward: A quantitative meta-analysis
2015; 112: 244-253
Individuals experience reward not only when directly receiving positive outcomes (e.g., food or money), but also when observing others receive such outcomes. This latter phenomenon, known as vicarious reward, is a perennial topic of interest among psychologists and economists. More recently, neuroscientists have begun exploring the neuroanatomy underlying vicarious reward. Here we present a quantitative whole-brain meta-analysis of this emerging literature. We identified 25 functional neuroimaging studies that included contrasts between vicarious reward and a neutral control, and subjected these contrasts to an activation likelihood estimate (ALE) meta-analysis. This analysis revealed a consistent pattern of activation across studies, spanning structures typically associated with the computation of value (especially ventromedial prefrontal cortex) and mentalizing (including dorsomedial prefrontal cortex and superior temporal sulcus). We further quantitatively compared this activation pattern to activation foci from a previous meta-analysis of personal reward. Conjunction analyses yielded overlapping VMPFC activity in response to personal and vicarious reward. Contrast analyses identified preferential engagement of the nucleus accumbens in response to personal as compared to vicarious reward, and in mentalizing-related structures in response to vicarious as compared to personal reward. These data shed light on the common and unique components of the reward that individuals experience directly and through their social connections.
View details for DOI 10.1016/j.neuroimage.2014.12.056
View details for Web of Science ID 000353203400025
Identification of a direct GABAergic pallidocortical pathway in rodents
EUROPEAN JOURNAL OF NEUROSCIENCE
2015; 41 (6): 748-759
Interaction between the basal ganglia and the cortex plays a critical role in a range of behaviors. Output from the basal ganglia to the cortex is thought to be relayed through the thalamus, but an intriguing alternative is that the basal ganglia may directly project to and communicate with the cortex. We explored an efferent projection from the globus pallidus externa (GPe), a key hub in the basal ganglia system, to the cortex of rats and mice. Anterograde and retrograde tracing revealed projections to the frontal premotor cortex, especially the deep projecting layers, originating from GPe neurons that receive axonal inputs from the dorsal striatum. Cre-dependent anterograde tracing in Vgat-ires-cre mice confirmed that the pallidocortical projection is GABAergic, and in vitro optogenetic stimulation in the cortex of these projections produced a fast inhibitory postsynaptic current in targeted cells that was abolished by bicuculline. The pallidocortical projections targeted GABAergic interneurons and, to a lesser extent, pyramidal neurons. This GABAergic pallidocortical pathway directly links the basal ganglia and cortex, and may play a key role in behavior and cognition in normal and disease states.
View details for DOI 10.1111/ejn.12822
View details for Web of Science ID 000351439000002
Attention Drives Synchronization of Alpha and Beta Rhythms between Right Inferior Frontal and Primary Sensory Neocortex
JOURNAL OF NEUROSCIENCE
2015; 35 (5): 2074-2082
The right inferior frontal cortex (rIFC) is specifically associated with attentional control via the inhibition of behaviorally irrelevant stimuli and motor responses. Similarly, recent evidence has shown that alpha (7-14 Hz) and beta (15-29 Hz) oscillations in primary sensory neocortical areas are enhanced in the representation of non-attended stimuli, leading to the hypothesis that allocation of these rhythms plays an active role in optimal inattention. Here, we tested the hypothesis that selective synchronization between rIFC and primary sensory neocortex occurs in these frequency bands during inattention. We used magnetoencephalography to investigate phase synchrony between primary somatosensory (SI) and rIFC regions during a cued-attention tactile detection task that required suppression of response to uncertain distractor stimuli. Attentional modulation of synchrony between SI and rIFC was found in both the alpha and beta frequency bands. This synchrony manifested as an increase in the alpha-band early after cue between non-attended SI representations and rIFC, and as a subsequent increase in beta-band synchrony closer to stimulus processing. Differences in phase synchrony were not found in several proximal control regions. These results are the first to reveal distinct interactions between primary sensory cortex and rIFC in humans and suggest that synchrony between rIFC and primary sensory representations plays a role in the inhibition of irrelevant sensory stimuli and motor responses.
View details for DOI 10.1523/JNEUROSCI.1292-14.2015
View details for Web of Science ID 000349671100022
Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory.
Frontiers in psychiatry
2015; 6: 21-?
Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on "support vector machines" to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities.
View details for DOI 10.3389/fpsyt.2015.00021
View details for PubMedID 25762941
Activation of the medial prefrontal and posterior cingulate cortex during encoding of negative material predicts symptom worsening in major depression
2014; 25 (5): 324-329
Considerable research indicates that depressed individuals have better memory for negative material than do nondepressed individuals, and that this bias is associated with differential patterns of neural activation. It is not known, however, whether these aberrant activation patterns predict illness course. Using functional neuroimaging, we examined whether change in depressive symptoms is predicted by baseline patterns of neural activation that underlie negative memory biases in major depressive disorder. Depressed participants viewed negative and neutral pictures during functional MRI at baseline and completed an incidental memory task for these pictures 1 week later. Depression severity was assessed by administering the Beck Depression Inventory both at baseline (Time 1) and at Time 2, an average of 18 months later. Contrast maps of activation for subsequently remembered negative versus subsequently remembered neutral pictures were regressed against change in Beck Depression Inventory scores between Time 1 and Time 2, controlling for initial symptom severity. Results from this analysis revealed no associations between memory sensitivity for negative stimuli and symptom change. In contrast, whole brain analyses revealed significant positive associations between within-subject changes in depressive symptoms and baseline neural activation to successfully recalled negative pictures in the posterior cingulate cortex and medial prefrontal cortex. These findings indicate that neural activation in cortical midline regions is a better predictor of long-term symptomatic outcome than is memory sensitivity for negative material.
View details for DOI 10.1097/WNR.0000000000000095
View details for Web of Science ID 000332601600009
Structural abnormality of the corticospinal tract in major depressive disorder.
Biology of mood & anxiety disorders
2014; 4: 8-?
Scientists are beginning to document abnormalities in white matter connectivity in major depressive disorder (MDD). Recent developments in diffusion-weighted image analyses, including tractography clustering methods, may yield improved characterization of these white matter abnormalities in MDD. In this study, we acquired diffusion-weighted imaging data from MDD participants and matched healthy controls. We analyzed these data using two tractography clustering methods: automated fiber quantification (AFQ) and the maximum density path (MDP) procedure. We used AFQ to compare fractional anisotropy (FA; an index of water diffusion) in these two groups across major white matter tracts. Subsequently, we used the MDP procedure to compare FA differences in fiber paths related to the abnormalities in major fiber tracts that were identified using AFQ.FA was higher in the bilateral corticospinal tracts (CSTs) in MDD (p's < 0.002). Secondary analyses using the MDP procedure detected primarily increases in FA in the CST-related fiber paths of the bilateral posterior limbs of the internal capsule, right superior corona radiata, and the left external capsule.This is the first study to implicate the CST and several related fiber pathways in MDD. These findings suggest important new hypotheses regarding the role of CST abnormalities in MDD, including in relation to explicating CST-related abnormalities to depressive symptoms and RDoC domains and constructs.
View details for DOI 10.1186/2045-5380-4-8
View details for PubMedID 25295159
Major depression duration reduces appetitive word use: An elaborated verbal recall of emotional photographs
JOURNAL OF PSYCHIATRIC RESEARCH
2013; 47 (6): 809-815
Major depressive disorder (MDD) is characterized by cognitive biases in attention, memory and language use. Language use biases often parallel depression symptoms, and contain over-representations of both negative emotive and death words as well as low levels of positive emotive words. This study further explores cognitive biases in depression by comparing the effect of current depression status to cumulative depression history on an elaborated verbal recall of emotional photographs.Following a negative mood induction, fifty-two individuals (42 women) with partially-remitted depression viewed - then recalled and verbally described - slides from the International Affective Picture System (IAPS). Descriptions were transcribed and frequency of depression-related word use (positive emotion, negative emotion, sex, ingestion and death) was analyzed using the Linguistic Inquiry and Word Count program (LIWC).Contrary to expectations and previous findings, current depression status did not affect word use in any categories of interest. However, individuals with more than 5 years of previous depression used fewer words related to positive emotion (t(50) = 2.10, p = .04, (d = 0.57)), and sex (t(48) = 2.50, p = .013 (d = 0.81)), and there was also a trend for these individuals to use fewer ingestion words (t(50) = 1.95, p = .057 (d = 0.58)), suggesting a deficit in appetitive processing.Our findings suggest that depression duration affects appetitive information processing and that appetitive word use may be a behavioral marker for duration related brain changes which may be used to inform treatment.
View details for DOI 10.1016/j.jpsychires.2013.01.022
View details for Web of Science ID 000318328700016
View details for PubMedID 23510497
Mindfulness starts with the body: somatosensory attention and top-down modulation of cortical alpha rhythms in mindfulness meditation
FRONTIERS IN HUMAN NEUROSCIENCE
Using a common set of mindfulness exercises, mindfulness based stress reduction (MBSR) and mindfulness based cognitive therapy (MBCT) have been shown to reduce distress in chronic pain and decrease risk of depression relapse. These standardized mindfulness (ST-Mindfulness) practices predominantly require attending to breath and body sensations. Here, we offer a novel view of ST-Mindfulness's somatic focus as a form of training for optimizing attentional modulation of 7-14 Hz alpha rhythms that play a key role in filtering inputs to primary sensory neocortex and organizing the flow of sensory information in the brain. In support of the framework, we describe our previous finding that ST-Mindfulness enhanced attentional regulation of alpha in primary somatosensory cortex (SI). The framework allows us to make several predictions. In chronic pain, we predict somatic attention in ST-Mindfulness "de-biases" alpha in SI, freeing up pain-focused attentional resources. In depression relapse, we predict ST-Mindfulness's somatic attention competes with internally focused rumination, as internally focused cognitive processes (including working memory) rely on alpha filtering of sensory input. Our computational model predicts ST-Mindfulness enhances top-down modulation of alpha by facilitating precise alterations in timing and efficacy of SI thalamocortical inputs. We conclude by considering how the framework aligns with Buddhist teachings that mindfulness starts with "mindfulness of the body." Translating this theory into neurophysiology, we hypothesize that with its somatic focus, mindfulness' top-down alpha rhythm modulation in SI enhances gain control which, in turn, sensitizes practitioners to better detect and regulate when the mind wanders from its somatic focus. This enhanced regulation of somatic mind-wandering may be an important early stage of mindfulness training that leads to enhanced cognitive regulation and metacognition.
View details for DOI 10.3389/fnhum.2013.00012
View details for Web of Science ID 000315343200001
View details for PubMedID 23408771
- Spatial smoothing systematically biases the localization of reward-related brain activity NEUROIMAGE 2013; 66: 270-277
Mindfulness training alters emotional memory recall compared to active controls: support for an emotional information processing model of mindfulness
FRONTIERS IN HUMAN NEUROSCIENCE
Objectives: While mindfulness-based interventions have received widespread application in both clinical and non-clinical populations, the mechanism by which mindfulness meditation improves well-being remains elusive. One possibility is that mindfulness training alters the processing of emotional information, similar to prevailing cognitive models of depression and anxiety. The aim of this study was to investigate the effects of mindfulness training on emotional information processing (i.e., memory) biases in relation to both clinical symptomatology and well-being in comparison to active control conditions. Methods: Fifty-eight university students (28 female, age?=?20.1?±?2.7?years) participated in either a 12-week course containing a "meditation laboratory" or an active control course with similar content or experiential practice laboratory format (music). Participants completed an emotional word recall task and self-report questionnaires of well-being and clinical symptoms before and after the 12-week course. Results: Meditators showed greater increases in positive word recall compared to controls [F(1, 56)?=?6.6, p?=?0.02]. The meditation group increased significantly more on measures of well-being [F(1, 56)?=?6.6, p?=?0.01], with a marginal decrease in depression and anxiety [F(1, 56)?=?3.0, p?=?0.09] compared to controls. Increased positive word recall was associated with increased psychological well-being (r?=?0.31, p?=?0.02) and decreased clinical symptoms (r?=?-0.29, p?=?0.03). Conclusion: Mindfulness training was associated with greater improvements in processing efficiency for positively valenced stimuli than active control conditions. This change in emotional information processing was associated with improvements in psychological well-being and less depression and anxiety. These data suggest that mindfulness training may improve well-being via changes in emotional information processing. Future research with a fully randomized design will be needed to clarify the possible influence of self-selection.
View details for DOI 10.3389/fnhum.2012.00015
View details for Web of Science ID 000302181400001
View details for PubMedID 22347856
Toward an affective neuroscience account of financial risk taking.
Frontiers in neuroscience
2012; 6: 159-?
To explain human financial risk taking, economic, and finance theories typically refer to the mathematical properties of financial options, whereas psychological theories have emphasized the influence of emotion and cognition on choice. From a neuroscience perspective, choice emanates from a dynamic multicomponential process. Recent technological advances in neuroimaging have made it possible for researchers to separately visualize perceptual input, intermediate processing, and motor output. An affective neuroscience account of financial risk taking thus might illuminate affective mediators that bridge the gap between statistical input and choice output. To test this hypothesis, we conducted a quantitative meta-analysis (via activation likelihood estimate or ALE) of functional magnetic resonance imaging experiments that focused on neural responses to financial options with varying statistical moments (i.e., mean, variance, skewness). Results suggested that different statistical moments elicit both common and distinct patterns of neural activity. Across studies, high versus low mean had the highest probability of increasing ventral striatal activity, but high versus low variance had the highest probability of increasing anterior insula activity. Further, high versus low skewness had the highest probability of increasing ventral striatal activity. Since ventral striatal activity has been associated with positive aroused affect (e.g., excitement), whereas anterior insular activity has been associated with negative aroused affect (e.g., anxiety) or general arousal, these findings are consistent with the notion that statistical input influences choice output by eliciting anticipatory affect. The findings also imply that neural activity can be used to predict financial risk taking - both when it conforms to and violates traditional models of choice.
View details for DOI 10.3389/fnins.2012.00159
View details for PubMedID 23129993
Volitional control of neuromagnetic coherence.
Frontiers in neuroscience
2012; 6: 189-?
Coherence of neural activity between circumscribed brain regions has been implicated as an indicator of intracerebral communication in various cognitive processes. While neural activity can be volitionally controlled with neurofeedback, the volitional control of coherence has not yet been explored. Learned volitional control of coherence could elucidate mechanisms of associations between cortical areas and its cognitive correlates and may have clinical implications. Neural coherence may also provide a signal for brain-computer interfaces (BCI). In the present study we used the Weighted Overlapping Segment Averaging method to assess coherence between bilateral magnetoencephalograph sensors during voluntary digit movement as a basis for BCI control. Participants controlled an onscreen cursor, with a success rate of 124 of 180 (68.9%, sign-test p?0.001) and 84 out of 100 (84%, sign-test p?0.001). The present findings suggest that neural coherence may be volitionally controlled and may have specific behavioral correlates.
View details for DOI 10.3389/fnins.2012.00189
View details for PubMedID 23271991
- Toward an affective neuroscience account of financial risk taking FRONTIERS IN NEUROSCIENCE 2012; 6
- Volitional control of neuromagnetic coherence FRONTIERS IN NEUROSCIENCE 2012; 6