Bio

Academic Appointments


  • Clinical Assistant Professor, Psychiatry and Behavioral Sciences

Honors & Awards


  • Merit Based Travel Award, American College of Neuropsychopharmacology (2017)
  • Merit based Travel Fellowship Award, Society of Biological Psychiatry (2017)
  • Seed Grant Recipient, Center for Neurobiological Imaging (CNI) (2017)
  • NRSA F32 Title: Neuroimaging and Machine Learning to Redefine Anxiety and Depression, NIMH (2016-2019)
  • Merit Based Professional Development Travel Award, Society for Neuroscience (2016)
  • Clinical Loan Repayment Award, National Institute of Health (2015-2016)
  • Seed Grant Recipient, Center for Neurobiological Imaging (CNI) (2015)
  • Merit Based Trainee Travel Award, Sleep Research Society (2012)
  • NRSA F31 Title: Sleep Loss, Trait Anxiety and Emotional Brain Reactivity, NIMH (2011-2014)
  • Honorable Mention, NSF Graduate Research Fellowship (2009)
  • Graduated Summa Cum Laude, University of California, San Diego (2006)

Professional Education


  • PhD, University of California Berkeley, Neuroscience/Psychology (2014)
  • BS, University of California San Diego, Cognitive Science (2006)
  • BS, University of California San Diego, Psychology (2006)

Publications

All Publications


  • Sex, Sleep Deprivation, and the Anxious Brain JOURNAL OF COGNITIVE NEUROSCIENCE Goldstein-Piekarski, A. N., Greer, S. M., Saletin, J. M., Harvey, A. G., Williams, L. M., Walker, M. P. 2018; 30 (4): 565–78

    Abstract

    Insufficient sleep is a known trigger of anxiety. Nevertheless, not everyone experiences these effects to the same extent. One determining factor is sex, wherein women experience a greater anxiogenic impact in response to sleep loss than men. However, the underlying brain mechanism(s) governing this sleep-loss-induced anxiety increase, including the markedly different reaction in women and men, is unclear. Here, we tested the hypothesis that structural brain morphology in a discrete network of emotion-relevant regions represents one such explanatory factor. Healthy participants were assessed across sleep-rested and sleep-deprived conditions, with brain structure quantified using gray matter volume measures. Sleep loss triggered greater levels of anxiety in women compared with men. Reduced gray matter volume in the anterior insula and lateral orbitofrontal cortex predicted the anxiogenic impact of sleep loss in women, yet predicted resilience in men, and did so with high discrimination accuracy. In contrast, gray matter volume in ventromedial prefrontal cortex predicted the anxiogenic impact of sleep loss in both men and women. Structural human brain morphology therefore appears to represent one mechanistic pathway (and possible biomarker) determining anxiety vulnerability to sleep loss-a discovery that may help explain the higher prevalence of sleep disruption and anxiety in women.

    View details for PubMedID 29244642

  • Intrinsic functional connectivity predicts remission on antidepressants: a randomized controlled trial to identify clinically applicable imaging biomarkers TRANSLATIONAL PSYCHIATRY Goldstein-Piekarski, A. N., Staveland, B. R., Ball, T. M., Yesavage, J., Korgaonkar, M. S., Williams, L. M. 2018; 8: 57

    Abstract

    Default mode network (DMN) dysfunction (particularly within the anterior cingulate cortex (ACC) and medial prefrontal cortex (mPFC)) has been implicated in major depressive disorder (MDD); however, its contribution to treatment outcome has not been clearly established. Here we tested the role of DMN functional connectivity as a general and differential biomarker for predicting treatment outcomes in a large, unmedicated adult sample with MDD. Seventy-five MDD outpatients completed fMRI scans before and 8 weeks after randomization to escitalopram, sertraline, or venlafaxine-XR. A whole-brain voxel-wise t-test identified profiles of pretreatment intrinsic functional connectivity that distinguished patients who were subsequently classified as remitters or non-remitters at follow-up. Connectivity was seeded in the PCC, an important node of the DMN. We further characterized differences between remitters, non-remitters, and 31 healthy controls and characterized changes pretreatment to posttreatment. Remitters were distinguished from non-remitters by relatively intact connectivity between the PCC and ACC/mPFC, not distinguishable from healthy controls, while non-remitters showed relative hypo-connectivity. In validation analyses, we demonstrate that PCC-ACC/mPFC connectivity predicts remission status with >80% cross-validated accuracy. In analyses testing whether intrinsic connectivity differentially relates to outcomes for a specific type of antidepressant, interaction models did not survive the corrected threshold. Our findings demonstrate that the overall capacity to remit on commonly used antidepressants may depend on intact organization of intrinsic functional connectivity between PCC and ACC/mPFC prior to treatment. The findings highlight the potential utility of functional scans for advancing a more precise approach to tailoring antidepressant treatment choices.

    View details for PubMedID 29507282

  • Transdiagnostic Symptom Clusters and Associations With Brain, Behavior, and Daily Function in Mood, Anxiety, and Trauma Disorders Grisanzio, K. A., Goldstein-Piekarski, A. N., Wang, M., Ahmed, A., Samara, Z., Williams, L. M. AMER MEDICAL ASSOC. 2018: 201–9

    Abstract

    The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices.To propose and demonstrate 1 approach for identifying subtypes within a transdiagnostic sample.This cross-sectional study analyzed data from the Brain Research and Integrative Neuroscience Network Foundation Database that had been collected at the University of Sydney and University of Adelaide between 2006 and 2010 and replicated at Stanford University between 2013 and 2017. The study included 420 individuals with a primary diagnosis of major depressive disorder (n = 100), panic disorder (n = 53), posttraumatic stress disorder (n = 47), or no disorder (healthy control participants) (n = 220). Data were analyzed between October 2016 and October 2017.We followed a data-driven approach to achieve the primary study outcome of identifying transdiagnostic subtypes. First, machine learning with a hierarchical clustering algorithm was implemented to classify participants based on self-reported negative mood, anxiety, and stress symptoms. Second, the robustness and generalizability of the subtypes were tested in an independent sample. Third, we assessed whether symptom subtypes were expressed at behavioral and physiological levels of functioning. Fourth, we evaluated the clinically meaningful differences in functional capacity of the subtypes. Findings were interpreted relative to a complementary diagnostic frame of reference.Four hundred twenty participants with a mean (SD) age of 39.8 (14.1) years were included in the final analysis; 256 (61.0%) were female. We identified 6 distinct subtypes characterized by tension (n=81; 19%), anxious arousal (n=55; 13%), general anxiety (n=38; 9%), anhedonia (n=29; 7%), melancholia (n=37; 9%), and normative mood (n=180; 43%), and these subtypes were replicated in an independent sample. Subtypes were expressed through differences in cognitive control (F5,383 = 5.13, P < .001, ηp2 = 0.063), working memory (F5,401 = 3.29, P = .006, ηp2 = 0.039), electroencephalography-recorded β power in a resting paradigm (F5,357 = 3.84, P = .002, ηp2 = 0.051), electroencephalography-recorded β power in an emotional paradigm (F5,365 = 3.56, P = .004, ηp2 = 0.047), social functional capacity (F5,414 = 21.33, P < .001, ηp2 = 0.205), and emotional resilience (F5,376 = 15.10, P < .001, ηp2 = 0.171).These findings offer a data-driven framework for identifying robust subtypes that signify specific, coherent, meaningful associations between symptoms, behavior, brain function, and observable real-world function, and that cut across DSM-IV-defined diagnoses of major depressive disorder, panic disorder, and posttraumatic stress disorder.

    View details for PubMedID 29197929

    View details for PubMedCentralID PMC5838569

  • The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model. Behaviour research and therapy Williams, L. M., Pines, A., Goldstein-Piekarski, A. N., Rosas, L. G., Kullar, M., Sacchet, M. D., Gevaert, O., Bailenson, J., Lavori, P. W., Dagum, P., Wandell, B., Correa, C., Greenleaf, W., Suppes, T., Perry, L. M., Smyth, J. M., Lewis, M. A., Venditti, E. M., Snowden, M., Simmons, J. M., Ma, J. 2018; 101: 58–70

    Abstract

    Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top contributors to the global burden of disease and disability. To optimize treatments and address these burdens, behavior change and self-regulation must be better understood in relation to their neurobiological underpinnings. Here, we present the conceptual framework and protocol for a novel study, "Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE)". The ENGAGE study integrates neuroscience with behavioral science to better understand the self-regulation related mechanisms of behavior change for improving mood and weight outcomes among adults with comorbid depression and obesity. We collect assays of three self-regulation targets (emotion, cognition, and self-reflection) in multiple settings: neuroimaging and behavioral lab-based measures, virtual reality, and passive smartphone sampling. By connecting human neuroscience and behavioral science in this manner within the ENGAGE study, we develop a prototype for elucidating the underlying self-regulation mechanisms of behavior change outcomes and their application in optimizing intervention strategies for multiple chronic diseases.

    View details for PubMedID 29074231

  • Antidepressant Outcomes Predicted by Genetic Variation in Corticotropin-Releasing Hormone Binding Protein. The American journal of psychiatry O'Connell, C. P., Goldstein-Piekarski, A. N., Nemeroff, C. B., Schatzberg, A. F., Debattista, C., Carrillo-Roa, T., Binder, E. B., Dunlop, B. W., Craighead, W. E., Mayberg, H. S., Williams, L. M. 2018; 175 (3): 251–61

    Abstract

    Genetic variation within the hypothalamic-pituitary-adrenal (HPA) axis has been linked to risk for depression and antidepressant response. However, these associations have yet to produce clinical gains that inform treatment decisions. The authors investigated whether variation within HPA axis genes predicts antidepressant outcomes within two large clinical trials.The test sample comprised 636 patients from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) who completed baseline and 8-week follow-up visits and for whom complete genotyping data were available. The authors tested the relationship between genotype at 16 candidate HPA axis single-nucleotide polymorphisms (SNPs) and treatment outcomes for three commonly used antidepressants (escitalopram, sertraline, and extended-release venlafaxine), using multivariable linear and logistic regression with Bonferroni correction. Response and remission were defined using the Hamilton Depression Rating Scale. Findings were then validated using the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study of outcome predictors in treatment-naive patients with major depression.The authors found that the rs28365143 variant within the corticotropin-releasing hormone binding protein (CRHBP) gene predicted antidepressant outcomes for remission, response, and symptom change. Patients homozygous for the G allele of rs28365143 had greater remission rates, response rates, and symptom reductions. These effects were specific to drug class. Patients homozygous for the G allele responded significantly better to the selective serotonin reuptake inhibitors escitalopram and sertraline than did A allele carriers. In contrast, rs28365143 genotype was not associated with treatment outcomes for the serotonin norepinephrine reuptake inhibitor venlafaxine. When patients were stratified by race, the overall effect of genotype on treatment response remained. In the validation sample, the GG genotype was again associated with favorable antidepressant outcomes, with comparable effect sizes.These findings suggest that a specific CRHBP SNP, rs28365143, may have a role in predicting which patients will improve with antidepressants and which type of antidepressant may be most effective. The results add to the foundational knowledge needed to advance a precision approach to personalized antidepressant choices.

    View details for PubMedID 29241359

    View details for PubMedCentralID PMC5832545

  • Clustering Identifies Symptom-Brain-Behavior Subtypes That cut Across Mood, Anxiety, and Trauma Disorders Grisanzio, K. A., Goldstein-Piekarski, A. N., Wang, M., Ahmed, A., Samara, Z., Williams, L. NATURE PUBLISHING GROUP. 2017: S371–S372
  • Sex Differences Modulating Serotonergic Polymorphisms Implicated in the Mechanistic Pathways of Risk for Depression and Related Disorders JOURNAL OF NEUROSCIENCE RESEARCH Perry, L. M., Goldstein-Piekarski, A. N., Williams, L. M. 2017; 95 (1-2): 737-762

    Abstract

    Despite consistent observations of sex differences in depression and related emotional disorders, we do not yet know how these sex differences modulate the effects of genetic polymorphisms implicated in risk for these disorders. This Mini-Review focuses on genetic polymorphisms of the serotonergic system to illustrate how sex differences might modulate the neurobiological pathways involved in the development of depression. We consider the interacting role of environmental factors such as early-life stress. Given limited current knowledge about this topic, we highlight methodological considerations, challenges, and guidelines for future research. © 2016 Wiley Periodicals, Inc.

    View details for DOI 10.1002/jnr.23877

    View details for Web of Science ID 000388443900071

    View details for PubMedID 27870440

    View details for PubMedCentralID PMC5119468

  • Human amygdala engagement moderated by early life stress exposure is a biobehavioral target for predicting recovery on antidepressants PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Goldstein-Piekarski, A. N., Korgaonkar, M. S., Green, E., Suppes, T., Schatzberg, A. F., Hastie, T., Nemeroff, C. B., Williams, L. M. 2016; 113 (42): 11955-11960

    Abstract

    Amygdala circuitry and early life stress (ELS) are both strongly and independently implicated in the neurobiology of depression. Importantly, animal models have revealed that the contribution of ELS to the development and maintenance of depression is likely a consequence of structural and physiological changes in amygdala circuitry in response to stress hormones. Despite these mechanistic foundations, amygdala engagement and ELS have not been investigated as biobehavioral targets for predicting functional remission in translational human studies of depression. Addressing this question, we integrated human neuroimaging and measurement of ELS within a controlled trial of antidepressant outcomes. Here we demonstrate that the interaction between amygdala activation engaged by emotional stimuli and ELS predicts functional remission on antidepressants with a greater than 80% cross-validated accuracy. Our model suggests that in depressed people with high ELS, the likelihood of remission is highest with greater amygdala reactivity to socially rewarding stimuli, whereas for those with low-ELS exposure, remission is associated with lower amygdala reactivity to both rewarding and threat-related stimuli. This full model predicted functional remission over and above the contribution of demographics, symptom severity, ELS, and amygdala reactivity alone. These findings identify a human target for elucidating the mechanisms of antidepressant functional remission and offer a target for developing novel therapeutics. The results also offer a proof-of-concept for using neuroimaging as a target for guiding neuroscience-informed intervention decisions at the level of the individual person.

    View details for DOI 10.1073/pnas.1606671113

    View details for PubMedID 27791054

  • A Genetic Polymorphism of the Human Dopamine Transporter Determines the Impact of Sleep Deprivation on Brain Responses to Rewards and Punishments JOURNAL OF COGNITIVE NEUROSCIENCE Greer, S. M., Goldstein, A. N., Knutson, B., Walker, M. P. 2016; 28 (6): 803-810

    Abstract

    Despite an emerging link between alterations in motivated behavior and a lack of sleep, the impact of sleep deprivation on human brain mechanisms of reward and punishment remain largely unknown, as does the role of trait dopamine activity in modulating such effects in the mesolimbic system. Combining fMRI with an established incentive paradigm and individual genotyping, here, we test the hypothesis that trait differences in the human dopamine transporter (DAT) gene-associated with altered synaptic dopamine signalling-govern the impact of sleep deprivation on neural sensitivity to impending monetary gains and losses. Consistent with this framework, markedly different striatal reward responses were observed following sleep loss depending on the DAT functional polymorphisms. Only participants carrying a copy of the nine-repeat DAT allele-linked to higher phasic dopamine activity-expressed amplified striatal response during anticipation of monetary gain following sleep deprivation. Moreover, participants homozygous for the ten-repeat DAT allele-linked to lower phasic dopamine activity-selectively demonstrated an increase in sensitivity to monetary loss within anterior insula following sleep loss. Together, these data reveal a mechanistic dependency on human of trait dopaminergic function in determining the interaction between sleep deprivation and neural processing of rewards and punishments. Such findings have clinical implications in disorders where the DAT genetic polymorphism presents a known risk factor with comorbid sleep disruption, including attention hyperactive deficit disorder and substance abuse.

    View details for DOI 10.1162/jocn_a_00939

    View details for Web of Science ID 000375780300003

    View details for PubMedID 26918589

  • Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression ("RAD") project BMC PSYCHIATRY Williams, L. M., Goldstein-Piekarski, A. N., Chowdhry, N., Grisanzio, K. A., Haug, N. A., Samara, Z., Etkin, A., O'Hara, R., Schatzberg, A. F., Suppes, T., Yesavage, J. 2016; 16

    Abstract

    Understanding how brain circuit dysfunctions relate to specific symptoms offers promise for developing a brain-based taxonomy for classifying psychopathology, identifying targets for mechanistic studies and ultimately for guiding treatment choice. The goal of the Research Domain Criteria (RDoC) initiative of the National Institute of Mental Health is to accelerate the development of such neurobiological models of mental disorder independent of traditional diagnostic criteria. In our RDoC Anxiety and Depression ("RAD") project we focus trans-diagnostically on the spectrum of depression and anxiety psychopathology. Our aims are a) to use brain imaging to define cohesive dimensions defined by dysfunction of circuits involved in reactivity to and regulation of negatively valenced emotional stimulation and in cognitive control, b) to assess the relationships between these dimension and specific symptoms, behavioral performance and the real world capacity to function socially and at work and c) to assess the stability of brain-symptom-behavior-function relationships over time.Here we present the protocol for the "RAD" project, one of the first RDoC studies to use brain circuit functioning to define new dimensions of psychopathology. The RAD project follows baseline-follow up design. In line with RDoC principles we use a strategy for recruiting all clients who "walk through the door" of a large community mental health clinic as well as the surrounding community. The clinic attends to a broad spectrum of anxiety and mood-related symptoms. Participants are unmedicated and studied at baseline using a standardized battery of functional brain imaging, structural brain imaging and behavioral probes that assay constructs of threat reactivity, threat regulation and cognitive control. The battery also includes self-report measures of anxiety and mood symptoms, and social and occupational functioning. After baseline assessments, therapists in the clinic apply treatment planning as usual. Follow-up assessments are undertaken at 3 months, to establish the reliability of brain-based subgroups over time and to assess whether these subgroups predict real-world functional capacity over time. First enrollment was August 2013, and is ongoing.This project is designed to advance knowledge toward a neural circuit taxonomy for mental disorder. Data will be shared via the RDoC database for dissemination to the scientific community. The clinical translational neuroscience goals of the project are to develop brain-behavior profile reports for each individual participant and to refine these reports with therapist feedback. Reporting of results is expected from December 2016 onward.ClinicalTrials.gov Identifier: NCT02220309 . Registered: August 13, 2014.

    View details for DOI 10.1186/s12888-016-0771-3

    View details for Web of Science ID 000372738400001

    View details for PubMedCentralID PMC4793523

  • Human Hippocampal Structure: A Novel Biomarker Predicting Mnemonic Vulnerability to, and Recovery from, Sleep Deprivation JOURNAL OF NEUROSCIENCE Saletin, J. M., Goldstein-Piekarski, A. N., Greer, S. M., Stark, S., Stark, C. E., Walker, M. P. 2016; 36 (8): 2355-2363

    Abstract

    Sleep deprivation impairs the formation of new memories. However, marked interindividual variability exists in the degree to which sleep loss compromises learning, the mechanistic reasons for which are unclear. Furthermore, which physiological sleep processes restore learning ability following sleep deprivation are similarly unknown. Here, we demonstrate that the structural morphology of human hippocampal subfields represents one factor determining vulnerability (and conversely, resilience) to the impact of sleep deprivation on memory formation. Moreover, this same measure of brain morphology was further associated with the quality of nonrapid eye movement slow wave oscillations during recovery sleep, and by way of such activity, determined the success of memory restoration. Such findings provide a novel human biomarker of cognitive susceptibility to, and recovery from, sleep deprivation. Moreover, this metric may be of special predictive utility for professions in which memory function is paramount yet insufficient sleep is pervasive (e.g., aviation, military, and medicine).

    View details for DOI 10.1523/JNEUROSCI.3466-15.2016

    View details for Web of Science ID 000370819400005

    View details for PubMedID 26911684

    View details for PubMedCentralID PMC4764658

  • Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression ("RAD") project. BMC psychiatry Williams, L. M., Goldstein-Piekarski, A. N., Chowdhry, N., Grisanzio, K. A., Haug, N. A., Samara, Z., Etkin, A., O'Hara, R., Schatzberg, A. F., Suppes, T., Yesavage, J. 2016; 16 (1): 68-?

    Abstract

    Understanding how brain circuit dysfunctions relate to specific symptoms offers promise for developing a brain-based taxonomy for classifying psychopathology, identifying targets for mechanistic studies and ultimately for guiding treatment choice. The goal of the Research Domain Criteria (RDoC) initiative of the National Institute of Mental Health is to accelerate the development of such neurobiological models of mental disorder independent of traditional diagnostic criteria. In our RDoC Anxiety and Depression ("RAD") project we focus trans-diagnostically on the spectrum of depression and anxiety psychopathology. Our aims are a) to use brain imaging to define cohesive dimensions defined by dysfunction of circuits involved in reactivity to and regulation of negatively valenced emotional stimulation and in cognitive control, b) to assess the relationships between these dimension and specific symptoms, behavioral performance and the real world capacity to function socially and at work and c) to assess the stability of brain-symptom-behavior-function relationships over time.Here we present the protocol for the "RAD" project, one of the first RDoC studies to use brain circuit functioning to define new dimensions of psychopathology. The RAD project follows baseline-follow up design. In line with RDoC principles we use a strategy for recruiting all clients who "walk through the door" of a large community mental health clinic as well as the surrounding community. The clinic attends to a broad spectrum of anxiety and mood-related symptoms. Participants are unmedicated and studied at baseline using a standardized battery of functional brain imaging, structural brain imaging and behavioral probes that assay constructs of threat reactivity, threat regulation and cognitive control. The battery also includes self-report measures of anxiety and mood symptoms, and social and occupational functioning. After baseline assessments, therapists in the clinic apply treatment planning as usual. Follow-up assessments are undertaken at 3 months, to establish the reliability of brain-based subgroups over time and to assess whether these subgroups predict real-world functional capacity over time. First enrollment was August 2013, and is ongoing.This project is designed to advance knowledge toward a neural circuit taxonomy for mental disorder. Data will be shared via the RDoC database for dissemination to the scientific community. The clinical translational neuroscience goals of the project are to develop brain-behavior profile reports for each individual participant and to refine these reports with therapist feedback. Reporting of results is expected from December 2016 onward.ClinicalTrials.gov Identifier: NCT02220309 . Registered: August 13, 2014.

    View details for DOI 10.1186/s12888-016-0771-3

    View details for PubMedID 26980207

  • A trans-diagnostic review of anxiety disorder comorbidity and the impact of multiple exclusion criteria on studying clinical outcomes in anxiety disorders. Translational psychiatry Goldstein-Piekarski, A. N., Williams, L. M., Humphreys, K. 2016; 6 (6)

    Abstract

    Anxiety disorders are highly comorbid with each other and with other serious mental disorders. As our field progresses, we have the opportunity to pursue treatment study designs that consider these comorbidities. In this perspective review, we first characterized the prevalence of multiple anxiety disorder comorbidity by reanalyzing national survey data, then conducted an English-language PubMed search of studies analyzing the impact of exclusion criteria on treatment outcome data. In the prevalence data, 60% of people with an anxiety disorder had one or more additional anxiety or depression diagnosis. Because our commonly applied exclusion criteria focus on a single diagnosis and do not consider a multiple comorbidity profile, the impact of the criteria may be to exclude up to 92% of anxiety disorder treatment seekers. Moreover, the findings do not suggest a consistent relationship between the number of exclusion criteria and the effect size of treatment outcomes. Thus, future studies might consider a more trans-diagnostic rationale for determining exclusion criteria, one that is generalizable to real-world settings in which multiple diagnoses commonly co-occur. The findings also encourage a more systematic reporting of rationales for the choice of-and the implications of-each exclusion criterion.

    View details for DOI 10.1038/tp.2016.108

    View details for PubMedID 27351601

    View details for PubMedCentralID PMC4931606

  • Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial NEUROPSYCHOPHARMACOLOGY Williams, L. M., Korgaonkar, M. S., Song, Y. C., Paton, R., Eagles, S., Goldstein-Piekarski, A., Grieve, S. M., Harris, A. W., Usherwood, T., Etkin, A. 2015; 40 (10): 2398-2408

    Abstract

    Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test-retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin-norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen's d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward 'normalization' post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen's d effect size 1.5; classification accuracy, 81%). Non-responders to venlafaxine-XR showed pre-treatment hyper-reactivity, which progressed to hypo-reactivity rather than normalization post-treatment, and hypo-reactivity post-treatment was abnormal compared to controls. Impaired amygdala activation has not previously been highlighted in the general vs differential prediction of antidepressant outcomes. Amygdala hypo-reactivity to emotions signaling reward and threat predicts the general capacity to respond to antidepressants. Amygdala hyper-reactivity to sad emotion is involved in a specific non-response to a serotonin-norepinephrine reuptake inhibitor. The findings suggest amygdala probes may help inform the personal selection of antidepressant treatments.Neuropsychopharmacology advance online publication, 29 April 2015; doi:10.1038/npp.2015.89.

    View details for DOI 10.1038/npp.2015.89

    View details for Web of Science ID 000359493700012

    View details for PubMedID 25824424

  • Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat. journal of neuroscience Goldstein-Piekarski, A. N., Greer, S. M., Saletin, J. M., Walker, M. P. 2015; 35 (28): 10135-10145

    Abstract

    Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the "embodied" reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive.

    View details for DOI 10.1523/JNEUROSCI.5254-14.2015

    View details for PubMedID 26180190

  • The International Study to Predict Optimized Treatment in Depression (iSPOT-D): Outcomes from the acute phase of antidepressant treatment. Journal of psychiatric research Saveanu, R., Etkin, A., Duchemin, A., Goldstein-Piekarski, A., Gyurak, A., DeBattista, C., Schatzberg, A. F., Sood, S., Day, C. V., Palmer, D. M., Rekshan, W. R., Gordon, E., Rush, A. J., Williams, L. M. 2015; 61: 1-12

    Abstract

    We aimed to characterize a large international cohort of outpatients with MDD within a practical trial design, in order to identify clinically useful predictors of outcomes with three common antidepressant medications in acute-phase treatment of major depressive disorder (MDD). The international Study to Predict Optimized Treatment in Depression has presently enrolled 1008 treatment-seeking outpatients (18-65 years old) at 17 sites (five countries). At pre-treatment, we characterized participants by symptoms, clinical history, functional status and comorbidity. Participants were randomized to receive escitalopram, sertraline or venlafaxine-extended release and managed by their physician following usual treatment practices. Symptoms, function, quality of life, and side-effect outcomes were assessed 8 weeks later. The relationship of anxiety to response and remission was assessed by comorbid Axis I diagnosis, presence/absence of anxiety symptoms, and dimensionally by anxiety symptom severity. The sample had moderate-to-severe symptoms, but substantial comorbidity and functional impairment. Of completers at week 8, 62.2% responded and 45.4% reached remission on the 17-item Hamilton Rating Scale for Depression; 53.3% and 37.6%, respectively on the 16-item Quick Inventory of Depressive Symptoms. Functional improvements were seen across all domains. Most participants had side effects that occurred with a frequency of 25% or less and were reported as being in the "none" to minimal/mild range for intensity and burden. Outcomes did not differ across medication groups. More severe anxiety symptoms at pre-treatment were associated with lower remission rates across all medications, independent of depressive severity, diagnostic comorbidity or side effects. Across medications, we found consistent and similar improvements in symptoms and function, and a dimensional prognostic effect of comorbid anxiety symptoms. These equivalent outcomes across treatments lay the foundation for identifying potential neurobiological and genetic predictors of treatment outcome in this sample.

    View details for DOI 10.1016/j.jpsychires.2014.12.018

    View details for PubMedID 25586212

  • The Role of Sleep in Emotional Brain Function ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 10 Goldstein, A. N., Walker, M. P. 2014; 10: 679-708

    Abstract

    Rapidly emerging evidence continues to describe an intimate and causal relationship between sleep and emotional brain function. These findings are mirrored by long-standing clinical observations demonstrating that nearly all mood and anxiety disorders co-occur with one or more sleep abnormalities. This review aims to (a) provide a synthesis of recent findings describing the emotional brain and behavioral benefits triggered by sleep, and conversely, the detrimental impairments following a lack of sleep; (b) outline a proposed framework in which sleep, and specifically rapid-eye movement (REM) sleep, supports a process of affective brain homeostasis, optimally preparing the organism for next-day social and emotional functioning; and (c) describe how this hypothesized framework can explain the prevalent relationships between sleep and psychiatric disorders, with a particular focus on posttraumatic stress disorder and major depression.

    View details for DOI 10.1146/annurev-clinpsy-032813-153716

    View details for Web of Science ID 000336428200026

    View details for PubMedID 24499013

  • The impact of sleep deprivation on food desire in the human brain NATURE COMMUNICATIONS Greer, S. M., Goldstein, A. N., Walker, M. P. 2013; 4

    Abstract

    Epidemiological evidence supports a link between sleep loss and obesity. However, the detrimental impact of sleep deprivation on central brain mechanisms governing appetitive food desire remains unknown. Here we report that sleep deprivation significantly decreases activity in appetitive evaluation regions within the human frontal cortex and insular cortex during food desirability choices, combined with a converse amplification of activity within the amygdala. Moreover, this bi-directional change in the profile of brain activity is further associated with a significant increase in the desire for weight-gain promoting high-calorie foods following sleep deprivation, the extent of which is predicted by the subjective severity of sleep loss across participants. These findings provide an explanatory brain mechanism by which insufficient sleep may lead to the development/maintenance of obesity through diminished activity in higher-order cortical evaluation regions, combined with excess subcortical limbic responsivity, resulting in the selection of foods most capable of triggering weight-gain.

    View details for DOI 10.1038/ncomms3259

    View details for Web of Science ID 000323751100010

    View details for PubMedID 23922121

  • Tired and Apprehensive: Anxiety Amplifies the Impact of Sleep Loss on Aversive Brain Anticipation JOURNAL OF NEUROSCIENCE Goldstein, A. N., Greer, S. M., Saletin, J. M., Harvey, A. G., Nitschke, J. B., Walker, M. P. 2013; 33 (26): 10607-10615

    Abstract

    Anticipation is an adaptive process, aiding preparatory responses to potentially threatening events. However, excessive anticipatory responding and associated hyper-reactivity in the amygdala and insula are integral to anxiety disorders. Despite the co-occurrence of sleep disruption and anxiety disorders, the impact of sleep loss on affective anticipatory brain mechanisms, and the interaction with anxiety, remains unknown. Here, we demonstrate that sleep loss amplifies preemptive responding in the amygdala and anterior insula during affective anticipation in humans, especially for cues with high predictive certainty. Furthermore, trait anxiety significantly determined the degree of such neural vulnerability to sleep loss: individuals with highest trait anxiety showed the greatest increase in anticipatory insula activity when sleep deprived. Together, these data support a neuropathological model in which sleep disruption may contribute to the maintenance and/or exacerbation of anxiety through its impact on anticipatory brain function. They further raise the therapeutic possibility that targeted sleep restoration in anxiety may ameliorate excessive anticipatory responding and associated clinical symptomatology.

    View details for DOI 10.1523/JNEUROSCI.5578-12.2013

    View details for Web of Science ID 000320928900006

    View details for PubMedID 23804084

  • The Role of Sleep in Directed Forgetting and Remembering of Human Memories CEREBRAL CORTEX Saletin, J. M., Goldstein, A. N., Walker, M. P. 2011; 21 (11): 2534-2541

    Abstract

    Ample evidence supports a role for sleep in the offline consolidation of memory. However, circumstances exist where forgetting can be as critical as remembering, both in daily life and clinically. Using a directed forgetting paradigm, here, we investigate the impact of explicit cue instruction during learning, prior to sleep, on subsequent remembering and forgetting of memory, after sleep. We demonstrate that sleep, relative to time awake, can selectively ignore the facilitation of items previously cued to be forgotten, yet preferentially enhance recall for items cued to be remembered; indicative of specificity based on prior waking instruction. Moreover, the success of this differential remember/forget effect is strongly correlated with fast sleep spindles over the left superior parietal cortex. Furthermore, electroencephalography source analysis of these spindles revealed a repeating loop of current density between selective memory-related regions of the superior parietal, medial temporal, and right prefrontal cortices. These findings move beyond the classical notion of sleep universally strengthening information. Instead, they suggest a model in which sleep may be more ecologically attuned to instructions present during learning while awake, supporting both remembering and targeted forgetting of human memories.

    View details for DOI 10.1093/cercor/bhr034

    View details for Web of Science ID 000295413200011

    View details for PubMedID 21459838

  • Photoperiod and Testosterone Interact to Drive Seasonal Changes in Kisspeptin Expression in Siberian Hamsters (Phodopus sungorus) JOURNAL OF NEUROENDOCRINOLOGY Greives, T. J., Humber, S. A., GOLDSTEIN, A. N., Scotti, M. L., Demas, G. E., Kriegsfeld, L. J. 2008; 20 (12): 1339-1347

    Abstract

    Kisspeptin, a neuropeptide product of the KiSS-1 gene, has recently been implicated in the regulation of seasonal breeding in a number of species, including Siberian hamsters. In this species, kisspeptin expression is reduced in the anteroventral periventricular nucleus (AVPV) following exposure to inhibitory day lengths, and exogenous kisspeptin activates the reproductive neuroendocrine axis of reproductively quiescent animals. Because sex steroids can impact kisspeptin expression, it is unclear whether changes in kisspeptin occur in direct response to photoperiodic cues or secondarily in response to changes in sex steroid concentrations resulting from the transition to reproductive quiescence. The present study aimed to assess the relative contributions of photoperiod and testosterone in regulating kisspeptin expression in Siberian hamsters. Animals housed in long or short day lengths for 8 weeks were either castrated or received sham surgeries. Half of the hamsters in each photoperiod were given testosterone to mimic long-day sex steroid concentrations. The results obtained indicate that kisspeptin neurones in the AVPV and arcuate nuclei were influenced by both photoperiod and testosterone. In the AVPV, removal of testosterone or exposure to inhibitory day lengths led to a marked reduction in kisspeptin-immunoreactive cells, and testosterone treatment increased cell numbers across conditions. Importantly, long-day castrates exhibited significantly more kisspeptin cells than short-day castrates or intact short-day animals with empty capsules, suggesting the influences of photoperiod, independent of gonadal steroids. In general, the opposite pattern emerged for the arcuate nuclei. Collectively, these data suggest a role for both gonadal-dependent and independent (i.e. photoperiodic) mechanisms regulating seasonal changes in kisspeptin expression in Siberian hamsters.

    View details for DOI 10.1111/j.1365-2826.2008.01790.x

    View details for Web of Science ID 000261115700005

    View details for PubMedID 19094081