Frontostriatal salience network expansion in individuals in depression.

Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset1. Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals2-4, but this approach has not been applied in depression. Here, using precision functional mapping and several samples of deeply sampled individuals, we found that the frontostriatal salience network is expanded nearly twofold in the cortex of most individuals with depression. This effect was replicable in several samples and caused primarily by network border shifts, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was stable over time, unaffected by mood state and detectable in children before the onset of depression later in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific symptoms and predicted future anhedonia symptoms. Together, these findings identify a trait-like brain network topology that may confer risk for depression and mood-state-dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.

Brain-based mechanisms of late-life depression: Implications for novel interventions.

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Modifiable predictors of nonresponse to psychotherapies for late-life depression with executive dysfunction: a machine learning approach.

The study aimed to: (1) Identify distinct trajectories of change in depressive symptoms by mid-treatment during psychotherapy for late-life depression with executive dysfunction; (2) examine if nonresponse by mid-treatment predicted poor response at treatment end; and (3) identify baseline characteristics predicting an early nonresponse trajectory by mid-treatment. A sample of 221 adults 60 years and older with major depression and executive dysfunction were randomized to 12 weeks of either problem-solving therapy or supportive therapy. We used Latent Growth Mixture Models (LGMM) to detect subgroups with distinct trajectories of change in depression by mid-treatment (6th week). We conducted regression analyses with LGMM subgroups as predictors of response at treatment end. We used random forest machine learning algorithms to identify baseline predictors of LGMM trajectories. We found that ~77.5% of participants had a declining trajectory of depression in weeks 0-6, while the remaining 22.5% had a persisting depression trajectory, with no treatment differences. The LGMM trajectories predicted remission and response at treatment end. A random forests model with high prediction accuracy (80%) showed that the strongest modifiable predictors of the persisting depression trajectory were low perceived social support, followed by high neuroticism, low treatment expectancy, and low perception of the therapist as accepting. Our results suggest that modifiable risk factors of early nonresponse to psychotherapy can be identified at the outset of treatment and addressed with targeted personalized interventions. Therapists may focus on increasing meaningful social interactions, addressing concerns related to treatment benefits, and creating a positive working relationship.

Estimated Regional White Matter Hyperintensity Burden, Resting State Functional Connectivity, and Cognitive Functions in Older Adults.

OBJECTIVE: White matter hyperintensities (WMH) are linked to deficits in cognitive functioning, including cognitive control and memory; however, the structural, and functional mechanisms are largely unknown. We investigated the relationship between estimated regional disruptions to white matter fiber tracts from WMH, resting state functional connectivity (RSFC), and cognitive functions in older adults. DESIGN: Cross-sectional study. SETTING: Community. PARTICIPANTS: Fifty-eight cognitively-healthy older adults. MEASUREMENTS: Tasks of cognitive control and memory, structural MRI, and resting state fMRI. We estimated the disruption to white matter fiber tracts from WMH and its impact on gray matter regions in the cortical and subcortical frontoparietal network, default mode network, and ventral attention network by overlaying each subject's WMH mask on a normative tractogram dataset. We calculated RSFC between nodes in those same networks. We evaluated the interaction of regional WMH burden and RSFC in predicting cognitive control and memory. RESULTS: The interaction of estimated regional WMH burden and RSFC in cortico-striatal regions of the default mode network and frontoparietal network was associated with delayed recall. Models predicting working memory, cognitive inhibition, and set-shifting were not significant. CONCLUSION: Findings highlight the role of network-level structural and functional alterations in resting state networks that are related to WMH and impact memory in older adults.

The Structural and Functional Neuroanatomy of Post-Stroke Depression and Executive Dysfunction: A Review of Neuroimaging Findings and Implications for Treatment.

Post-stroke depression and executive dysfunction co-occur and are highly debilitating. Few treatments alleviate both depression and executive dysfunction after stroke. Understanding the brain network changes underlying post-stroke depression with executive dysfunction can inform the development of targeted and efficacious treatment. In this review, we synthesize neuroimaging findings in post-stroke depression and post-stroke executive dysfunction and highlight the network commonalities that may underlie this comorbidity. Structural and functional alterations in the cognitive control network, salience network, and default mode network are associated with depression and executive dysfunction after stroke. Specifically, post-stroke depression and executive dysfunction are both linked to changes in intrinsic functional connectivity within resting state networks, functional over-connectivity between the default mode and salience/cognitive control networks, and reduced cross-hemispheric frontoparietal functional connectivity. Cognitive training and noninvasive brain stimulation targeted at these brain network abnormalities and specific clinical phenotypes may help advance treatment for post-stroke depression with executive dysfunction.

Strategies to Promote Cognitive Health in Aging: Recent Evidence and Innovations.

PURPOSE OF REVIEW: We review recent work on applications of non-pharmacologic strategies to promote cognitive health in older adulthood and discuss potential network mechanisms, limitations, and considerations for improving intervention uptake and efficacy. RECENT FINDINGS: In healthy older adults and patients with mild cognitive impairment, cognitive training produces global and domain-specific cognitive gains, though effect sizes tend to be modest and transfer is variable. Non-invasive brain stimulation has shown moderate success in enhancing cognitive function, though the optimum approach, parameters, and cortical targets require further investigation. Physical activity improves cognitive functions in late life, with emerging trials highlighting key intervention components that may maximize treatment outcomes. Multimodal interventions may be superior to single-component interventions in conferring cognitive gains, although interpretation is limited by modest sample sizes and variability in training components and parameters. Across modalities, individual differences in patient characteristics predict therapeutic response. These interventions may advance cognitive health by modulating functional networks that support core cognitive abilities including the default mode, executive control, and salience networks. Effectiveness of cognitive enhancement strategies may be increased with clinician-led coaching, booster sessions, gamification, integration of multiple intervention modalities, and concrete applications to everyday functioning. Future trials involving rigorous comparisons of training components, parameters, and delivery formats will be essential in establishing the precise approaches needed to maximize cognitive outcomes. Novel studies using patient-level clinical and neuroimaging features to predict individual differences in training gains may inform the development of personalized intervention prescriptions to optimize cognitive health in late life.

Cortical Thickness of the Salience Network and Change in Apathy Following Antidepressant Treatment for Late-Life Depression.

OBJECTIVE: Apathy is common in late-life depression and is associated with poor response to antidepressant drugs. In depressed older adults, apathy may be characterized by neuroanatomical abnormalities of the salience network. The current study examined whether cortical thickness of select salience network structures predicted change in apathy following a 12-week treatment with escitalopram. METHODS: A sample of 46 older adults with major depressive disorder received 12 weeks of escitalopram treatment at a daily target dose of 20 mg. All participants underwent a structural brain MRI scan at baseline, and cortical thickness was estimated in key cortical nodes of the salience network: the caudal anterior cingulate cortex and the insula. We measured baseline and post-treatment symptoms using the Apathy Evaluation Scale and the Hamilton Depression Rating Scale. RESULTS: A thicker insula at baseline predicted reduction in apathy symptoms following 12 weeks of treatment with escitalopram, even when controlling for age, baseline depression severity and change in depressive symptoms. CONCLUSION: Reduced insular thickness predicted residual apathetic symptoms following escitalopram treatment. These results converge with our previous findings of abnormal functional connectivity of the insular cortex in older depressed individuals with apathy. Older depressed adults with apathy may benefit from alternative treatment approaches or augmentative interventions that target abnormalities of the salience network.

Targeting Cognitive Control Deficits With Neuroplasticity-Based Computerized Cognitive Remediation in Patients With Geriatric Major Depression: A Randomized, Double-Blind, Controlled Trial.

Late life major depression (LLD) is often accompanied by cognitive deficits. When patients have specific deficits in cognitive control functions (CCD), they are not only distressing and debilitating, they often predict poor clinical outcomes such as reduced response to SSRI/SNRI antidepressants, increased disability, suicide and all-cause mortality. We recently reported that in an open label trial, our treatment designed to target these specific CCD with neuroplasticity-based computerized cognitive remediation (nCCR) improved depression and CCD in patients who failed to remit with conventional antidepressant treatment. This study tested the hypothesis that in patients with LLD who have failed at least one trial of an SSRI/SNRI antidepressant at an adequate dose for at least 8 weeks, nCCR will improve both depressive symptoms and the CCD associated with poor antidepressant response (i.e. semantic strategy, inhibition of prepotent responses) more than an active control group. Participants were randomized (1:1) to receive either 30 hours/ 4 weeks of neuroplasticity based computerized cognitive remediation (nCCR) designed to target CCD, or the active control condition matched for duration, engagement, reward, computer presentation, and contact with study staff. All participants and raters were blinded. Mixed effects model analysis the time effect (week) (F(1,71.22)=25.2, p<0.0001) and treatment group X time interaction (F(1,61.8)=11.37, p=.002) reached significance indicating that the slope of decline in MADRS was steeper in the nCCR-GD group. Further, the nCCR group improved their semantic clustering strategy(t(28)=9.5; p=.006), as well as performance on the Stroop interference condition, and cognitive flexibility (Trails B). Further, results transferred to memory performance, which was not a function trained by nCCR. clinicaltrials.gov.

Resting State Functional Connectivity and Outcomes of Psychotherapies for Late-Life Depression.

BACKGROUND: Problem solving therapy (PST) and "Engage," a reward-exposure" based therapy, are important treatment options for late-life depression, given modest efficacy of antidepressants in this disorder. Abnormal function of the reward and default mode networks has been observed during depressive episodes. This study examined whether resting state functional connectivity (rsFC) of reward and DMN circuitries is associated with treatment outcomes. METHODS: Thirty-two older adults with major depression (mean age = 72.7) were randomized to 9-weeks of either PST or "Engage." We assessed rsFC at baseline and week 6. We placed seeds in three a priori regions of interest: subgenual anterior cingulate cortex (sgACC), dorsal anterior cingulate cortex (dACC), and nucleus accumbens (NAcc). Outcome measures included the Hamilton Depression Rating Scale (HAMD) and the Behavioral Activation for Depression Scale (BADS). RESULTS: In both PST and "Engage," higher rsFC between the sgACC and middle temporal gyrus at baseline was associated with greater improvement in depression severity (HAMD). Preliminary findings suggested that in "Engage" treated participants, lower rsFC between the dACC and dorsomedial prefrontal cortex at baseline was associated with HAMD improvement. Finally, in Engage only, increased rsFC from baseline to week 6 between NAcc and Superior Parietal Cortex was associated with increased BADS scores. CONCLUSION: The results suggest that patients who present with higher rsFC between the sgACC and a structure within the DMN may benefit from behavioral psychotherapies for late life depression. "Engage" may lead to increased rsFC within the reward system reflecting a reconditioning of the reward systems by reward exposure.

Neuroanatomical Abnormalities in Older Depressed Adults With Apathy: A Systematic Review.

OBJECTIVE: Apathy is a common phenomenon in late-life depression and is associated with poor outcomes. Apathy is often unrecognized in older depressed adults, and efficacious treatment options are lacking. This review provides a systematic review of the neuroanatomical abnormalities associated with apathy in late-life depression. In addition, the review summarizes the neuroimaging findings from studies of neurodegenerative and focal brain injury conditions that frequently present with apathy. The goal is to elucidate cerebral network abnormalities that give rise to apathy in older adults with mood disturbances and to inform future treatment targets. METHOD: Systematic literature review. RESULTS: The few studies that have directly examined the neuroanatomical abnormalities of apathy in late-life depression suggest disturbances in the anterior cingulate cortex, insula, orbital and dorsal prefrontal cortex, striatum, and limbic structures (ie, amygdala, thalamus, and hippocampus). Studies examining the neuroanatomical correlates of apathy in other aging populations are consistent with the pattern observed in late-life depression. CONCLUSIONS: Apathy in late-life depression appears to be accompanied by neuroanatomical abnormalities in the salience and reward networks. These network findings are consistent with that observed in individuals presenting with apathy in other aging-related conditions. These findings may inform future treatments that target apathy.

Subgroups Defined by the Montreal Cognitive Assessment Differ in Functional Gain During Acute Inpatient Stroke Rehabilitation.

OBJECTIVE: To validate subgroups of cognitive impairment on the Montreal Cognitive Assessment (MoCA)-defined as normal (score of 25-30), mildly impaired (score of 20-24), and moderately impaired (score less than 19)-by determining whether they differ in rehabilitation gain during inpatient stroke rehabilitation. DESIGN: Observational study. Linear regression models were conducted and predictors included MoCA subgroups and relevant baseline demographic and clinical covariates. Separate models included the cognitive subscale of the FIM instrument as a predictor. SETTING: Inpatient rehabilitation facility of an urban, academic medical center. PARTICIPANTS: Inpatients (N=334) with mild-moderate strokes who were administered the MoCA on admission. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The mean relative functional gain (mRFG) and mean relative functional efficiency (mRFE, which adjusts for length of stay) on the FIM total. RESULTS: MoCA subgroups significantly predicted mRFG and mRFE after accounting for age, sex, education, stroke severity, and recurrent vs first stroke. The normal group exhibited greater mRFG and mRFE than the mildly impaired group, while the moderately impaired group had significantly worse mRFG and mRFE than the mildly impaired group. The moderately impaired group had a significantly smaller proportion of individuals who made a clinically meaningful change on the total-FIM than the mildly impaired and normal groups. MoCA subgroups better accounted for mRFG and mRFE than a standard-of-care cognitive assessment (cognitive-FIM). CONCLUSIONS: Use of MoCA-defined subgroups can assist providers in predicting functional gain in survivors of stroke being treated in inpatient rehabilitation.

Omission of temporal nuisance regressors from dual regression can improve accuracy of fMRI functional connectivity maps.

Functional connectivity (FC) maps from brain fMRI data can be derived with dual regression, a proposed alternative to traditional seed-based FC (SFC) methods that detect temporal correlation between a predefined region (seed) and other regions in the brain. As with SFC, incorporating nuisance regressors (NR) into the dual regression must be done carefully, to prevent potential bias and insensitivity of FC estimates. Here, we explore the potentially untoward effects on dual regression that may occur when NR correlate highly with the signal of interest, using both synthetic and real fMRI data to elucidate mechanisms responsible for loss of accuracy in FC maps. Our tests suggest significantly improved accuracy in FC maps derived with dual regression when highly correlated temporal NR were omitted. Single-map dual regression, a simplified form of dual regression that uses neither spatial nor temporal NR, offers a viable alternative whose FC maps may be more easily interpreted, and in some cases be more accurate than those derived with standard dual regression.

Training the Next Generation of Geriatric-Focused Clinical Neuroscientists.

It remains challenging to integrate clinical neuroscience into clinical practice. Hindrances at the training level (e.g., lack of qualified faculty and curriculum) contribute to this impasse. To help address this, we present a model of training in clinical neuroscience. We expand on a growing literature on incorporating neuroscience into psychiatry training by emphasizing two points. That is, 1) we propose a training model designed for the geriatric-minded clinician; and 2) that extends across several phases of education and career development. Considering the relevance of dementia to our population of interest, and the potential impact expertise in clinical neuroscience can have in elders with cognitive impairment, we provide relevant curriculum examples at various training stages. Clinical research, both as a practitioner and consumer, figures prominently into our training model. We discuss two mentoring programs, T32 fellowships and Research Career Institute in the Mental Health of Aging, as ways to engage geriatric psychiatrists early in their training and transition them successfully to post-residency clinical investigator positions. Although there is increasing opportunity for geriatric psychiatrists and other clinicians to become leaders in the field of neuroscience, this remains a work in progress; ours and others' training programs continue to evolve based on input from trainers and trainees alike, as well as from the increasing literature on this important topic.

Engagement in Socially and Interpersonally Rewarding Activities as a Predictor of Outcome in "Engage" Behavioral Activation Therapy for Late-Life Depression.

OBJECTIVE: Loneliness and social isolation are associated with depressive symptoms, cognitive and physical disabilities, and increased risk of mortality among older adults. Socially rewarding activities reduce loneliness, and neurobiological evidence suggests that these activities may activate neural reward systems in older adults to a greater extent than other rewarding experiences. The current study was designed to investigate whether engagement in social and interpersonal activities (i.e., exposure to social rewards) predicts subsequent increase in behavioral activation and reduction in depressive symptoms in reward exposure treatment for late-life depression. METHODS: Forty-eight older adults without cognitive impairment and with major depression received nine sessions of "Engage" psychotherapy. Behavioral activation and depression severity were assessed by trained raters at baseline and weeks 6 and 9. Patients' weekly behavioral plans were categorized into three groups: 1) solitary activities; 2) social-group activities (attending a social gathering or a social setting such as church or a senior center); and 3) interpersonal-individual activities (engaging in an interpersonal interaction with a specific friend or family member). RESULTS: Mixed-effects models showed reduction in depression severity and increase in behavioral activation over time. In linear regression models, a higher percentage of interpersonal-individual activities (but not solitary or social-group activities) predicted subsequent increase in behavioral activation and improvement of depression. CONCLUSION: These findings highlight the importance of understanding the effects of engagement in specific types of rewarding activities in behavioral activation treatments for late-life depression. Exposure to socially rewarding interpersonal interactions could contribute to the efficacy of psychotherapy for late-life depression.

The diagnostic accuracy of the Montreal Cognitive Assessment in inpatient stroke rehabilitation.

The Montreal Cognitive Assessment (MoCA) is a commonly used screening measure for cognitive impairment; however, the diagnostic accuracy and optimal cutoff points in inpatients with mild stroke severity is unknown. We examined the diagnostic accuracy of the MoCA in an acute inpatient stroke rehabilitation unit (N = 95). The criterion neuropsychological assessment was the 30-minute National Institute of Neurological Disorders and Stroke-Canadian Stroke Network battery, modified to include the Symbol-Digit Modalities Test and Trail Making Test A & B. The MoCA had moderately strong diagnostic accuracy in receiver operating curve analyses, with areas under the curve ranging from .80 to .89 depending on the threshold for defining cognitive impairment. Sensitivity ranged from .72 to .87, and was generally greater than specificity, which ranged from .60 to .81. The optimal cutoff on the MoCA for detecting mild or greater cognitive impairment was <25/30. The optimal cutoff using more conservative definitions of cognitive impairment ranged from <23-24/30. Exploratory analyses of MoCA subgroups ("normal," "mildly impaired," and "functionally impaired") differed in the frequency and magnitude of impairment on the criterion neuropsychological assessment. These findings inform the clinical use of the MoCA in individuals with mild stroke in an inpatient rehabilitation setting.

Age-Related Repetitive Transcranial Magnetic Stimulation Effects on Executive Function in Depression: A Systematic Review.

OBJECTIVE: The aims of the current review were to: 1) examine whether the rTMS effects on executive function increase as age advances; 2) to examine the potential of rTMS to remediate executive function in older depressed patients; and 3) to assess the relationship between the executive function and mood benefits from rTMS in depression. METHODS: Randomized or matched-groups, blind, sham-controlled studies (12 studies, 347 participants) on excitatory rTMS applied to left DLPFC in depression were reviewed. RESULTS: A series of meta-regressions found no evidence of greater rTMS effects on executive functions as age advances. Similarly, meta-analyses showed no significant rTMS effects on executive functions in older depressed individuals. However, meta-regression analyses showed that the size of the executive function benefits from rTMS in depression are positively related to the effect size of mood symptom reduction. Despite its correlational nature, this finding is consistent with the idea that improvement in executive function may play a critical role in depression recovery. CONCLUSIONS: The authors consider these findings preliminary because of the modest number of available studies. Based on a qualitative review, the authors describe methodologic modifications that may increase rTMS efficacy for both executive functions and mood in late-life depression.

Reward learning impairment and avoidance and rumination responses at the end of Engage therapy of late-life depression.

OBJECTIVES: This study examined the association between reward processing, as measured by performance on the probabilistic reversal learning (PRL) task and avoidance/rumination in depressed older adults treated with Engage, a psychotherapy that uses "reward exposure" to increase behavioral activation. METHODS: Thirty older adults with major depression received 9 weeks of Engage treatment. At baseline and treatment end, the 24-item Hamilton Depression Rating Scale (HAM-D) was used to assess depression severity and the Behavioral Activation for Depression Scale (BADS) to assess behavioral activation and avoidance/rumination. Participants completed the PRL task at baseline and at treatment end. The PRL requires participants to learn stimulus-reward contingencies through trial and error, and switch strategies when the contingencies unexpectedly change. RESULTS: At the end of Engage treatment, the severity of depression was lower (HAM-D: t(19) = -7.67, P < .001) and behavioral activation was higher (BADS: t(19) = 2.23, P = .02) compared to baseline. Response time following all switches (r(19) = -0.63, P = .003) and error switches (r(19) = -0.57, P = .01) at baseline was negatively associated with the BADS avoidance/rumination subscale score at the end of Engage treatment. CONCLUSIONS: Impaired reward learning, evidenced by slower response following all switches and error switches, contributes to avoidant, ruminative behavior at the end of Engage therapy even when depression improves. Understanding reward processing abnormalities of avoidance and rumination may improve the timing and targeting of interventions for these symptoms, whose persistence compromises quality of life and increases the risk of depression relapse.

Improving late life depression and cognitive control through the use of therapeutic video game technology: A proof-of-concept randomized trial.

BACKGROUND: Existing treatments for depression are known to have only modest effects, are insufficiently targeted, and are inconsistently utilized, particularly in older adults. Indeed, older adults with impaired cognitive control networks tend to demonstrate poor response to a majority of existing depression interventions. Cognitive control interventions delivered using entertainment software have the potential to not only target the underlying cerebral dysfunction associated with depression, but to do so in a manner that is engaging and engenders adherence to treatment protocol. METHODS: In this proof-of-concept trial (Clinicaltrials.gov #: NCT02229188), individuals with late life depression (LLD) (22; 60+ years old) were randomized to either problem solving therapy (PST, n = 10) or a neurobiologically inspired digital platform designed to enhance cognitive control faculties (Project: EVO™, n = 12). Given the overlapping functional neuroanatomy of mood disturbances and executive dysfunction, we explored the impact of an intervention targeting cognitive control abilities, functional disability, and mood in older adults suffering from LLD, and how those outcomes compare to a therapeutic gold standard. RESULTS: EVO participants demonstrated similar improvements in mood and self-reported function after 4 weeks of treatment to PST participants. The EVO participants also showed generalization to untrained measures of working memory and attention, as well as negativity bias, a finding not evident in the PST condition. Individuals assigned to EVO demonstrated 100% adherence. CONCLUSIONS: This study provides preliminary findings that this therapeutic video game targeting cognitive control deficits may be an efficacious LLD intervention. Future research is needed to confirm these findings.

Effects of Transcranial Magnetic Stimulation on the Cognitive Control of Emotion: Potential Antidepressant Mechanisms.

Depression negatively impacts quality of life and is associated with high mortality rates. Recent research has demonstrated that improvement in depression symptoms with transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (DLPFC) may involve changes in the cognitive control network, a regulatory system modulating the function of cognitive and emotional systems, composed of the DLPFC, dorsal anterior cingulate, and posterior parietal cortices. Transcranial magnetic stimulation to the DLPFC node of the cognitive control network may have antidepressant efficacy via direct effects on cognitive control processes involved in emotion regulation. This review provides a review of the impact of TMS on cognitive control processes, especially those related to emotion regulation, and posits that these effects are critical to the mechanism of action of TMS for depression. Treatment implications and future directions for study are discussed.