Article tools Author information Need help? | Published in Volume
119, Issue 4 (April 1, 2009) J Clin Invest. 2009;119(4):717–725.
doi:10.1172/JCI38454.
Copyright © 2009, American Society for Clinical
Investigation
Review Series
Targeted electrode-based modulation of neural circuits for
depressionHelen S. Mayberg Department of Psychiatry and Department of Neurology, Emory University
School of Medicine, Atlanta, Georgia, USA. Address correspondence to: Helen Mayberg, Emory University, Department of
Psychiatry, 101 Woodruff Circle, WMB 4313, Atlanta, Georgia 30322, USA. Phone: (404)
727-6740; Fax: (404) 727-6743; E-mail: hmayber@emory.edu. Published April 1, 2009
During the last 20 years of neuroscience research, we have witnessed a fundamental
shift in the conceptualization of psychiatric disorders, with the dominant
psychological and neurochemical theories of the past now complemented by a growing
emphasis on developmental, genetic, molecular, and brain circuit models. Facilitating
this evolving paradigm shift has been the growing contribution of functional
neuroimaging, which provides a versatile platform to characterize brain circuit
dysfunction underlying specific syndromes as well as changes associated with their
successful treatment. Discussed here are converging imaging findings that established
a rationale for testing a targeted neuromodulation strategy, deep brain stimulation,
for treatment-resistant major depression.
Depression affects at least 10% of the world population and is a leading cause of worldwide
disability (1). Major depressive disorder (MDD) is
clinically defined as a multidimensional syndrome, involving disruption of mood, cognition,
sensorimotor functions, and homeostatic/drive functions (including those that control
sleep, appetite, and libido). While depression can be treated in many cases with either
medication or an evidence-based psychotherapy, remission rates in controlled trials using
currently available treatments rarely exceed 30%, and relapse is the rule rather than the
exception (2). For many patients, combinations of
multiple medications and electroconvulsive therapy (ECT) are required. For those who remain
severely depressed despite these aggressive approaches, new strategies are needed (3). This Review describes the development and testing of
a new interventional strategy, deep brain stimulation (DBS), directed at this group of
patients who are otherwise resistant to treatment.
Critical to the development of DBS as a new treatment for intractable MDD has been the
evolving understanding of the brain circuits that mediate normal and abnormal mood states
and the systematic characterization of changes in these circuits that accompany successful
and unsuccessful response to various treatments, measured using functional imaging
(reviewed in refs. 4–8). Based on brain circuit models of depression derived
primarily from PET scan measures of glucose metabolism and blood flow, the first region of
the brain to be targeted with DBS in patients with treatment-resistant depression (TRD) was
the subcallosal cingulate (SCC), the ventral-most segment of the cingulate gyrus (Figure
1). As detailed in the following sections, this
region of the brain was considered a critical node within a putative mood regulatory
circuit, as it showed the most consistent changes in metabolism and blood flow with
clinical recovery, using various well-established antidepressant interventions (9). As such, it was hypothesized that direct stimulation
of the SCC and adjacent white matter would produce modulatory or normalizing changes within
this otherwise unresponsive mood circuit, resulting in antidepressant effects (10). The first clinical results of DBS of the SCC were
encouraging, leading to the initiation of additional clinical studies (11, 12). This
initial clinical success further motivated continued refinement of this depression circuit
model, with goals to optimize surgical targeting, define biomarkers that might effectively
guide patient selection, and increase understanding of DBS mechanisms of action.
Neurological depression circuit model: theoretical frameworkThe development and evolution of a circuit model to explain the many regional brain
abnormalities reported in numerous imaging studies of depressed patients is in keeping
with the classical neurological tradition of symptom localization, using lesion-deficit
correlational analyses. Using this strategy, construction of a depression circuit first
assumes that depression is unlikely to be the result of injury or dysfunction of a
single brain region but rather a system-wide disorder, in which interruption at specific
sites or “nodes” within a defined functional circuit or network
linking many brain regions can result in stereotypic depressive symptoms (9, 13). It is
further hypothesized that a major depressive episode reflects the failure to
appropriately regulate activity in this multi-region circuit, under circumstances of
cognitive, emotional, or somatic stress (6). From
this perspective, a given scan pattern is a readout of both the inciting insult or
provocation and the resulting compensatory processes, influenced by various contributing
factors, including heredity, temperament, early-life experiences, and previous
depressive episodes (14–17). As such, variations in brain scan patterns
among patients would be expected, thus defining distinct depression phenotypes with
potentially predictable responses to different antidepressant treatments (Figure 2). While this premise is purely speculative,
published findings that support this hypothesis are reviewed below, highlighting
disease-, state-, and treatment-specific effects facilitated by pharmacotherapy,
cognitive behavioral therapy (CBT), and DBS.
Defining affected brain regionsStructural imaging studies. Structure-function correlations performed in patients developing a depression
syndrome, in the context of either acquired brain lesions (18, 19) or
neurodegenerative disorders (reviewed in ref. 13), provided an early anatomical perspective, consistently identifying clear
abnormalities in both the frontal cortex and basal ganglia. Studies in individuals
with primary depression, on the other hand, have indicated that structural
abnormalities are more subtle, generally necessitating more advanced image
acquisition and analytic approaches. Such studies have identified volume changes in
the amygdala, hippocampus, and anterior cingulate, ventromedial, and prefrontal
cortices but with considerable variability (8,
20–22) (Figure 1). Postmortem
studies further identify glial cell loss in primary depression but the findings are
also not localized to any one brain region (23–26). Unlike
depression following a selective brain lesion or injury, in which causal inferences
can be reasonably asserted, volume changes reported in MDD appear to be more complex,
particularly since acute lesions of the amygdala, hippocampus, cingulate cortex, and
ventromedial frontal cortex do not precipitate depressive symptoms or syndromes
(18, 19). Furthermore, genetic risk factors and environmental stress may further
contribute to some of these reported structural abnormalities, independent of the
presence of depression (27–29). Nonetheless, comparative cytoarchitectural
and anatomical connectivity studies generally confirm the critical involvement of
these regions, most consistently the frontal cortex, cingulate cortex, basal ganglia,
amygdala, and hippocampus in animal models of depression and associated emotional
behaviors (30–34), supporting the hypothesis that even subtle
disruption of pathways linking these regions in humans can result in disturbances in
emotion regulation typical of MDD, namely negative mood coupled with sustained
changes in motivation, motor performance, cognition, and circadian functions. Studies
of regional brain dysfunction with functional imaging further support this
hypothesis.
Functional imaging studies.There are now a variety of imaging methods (PET, single photon emission computed
tomography, functional MRI [fMRI], magnetic resonance spectroscopy, EEG,
magnetoencephalography, and optical imaging) capable of quantifying a wide range of
physiological parameters relevant to the study of major depression. In this brief
overview, resting-state blood flow and glucose metabolism measures using PET are
highlighted, as they make up the bulk of the published studies. Functional imaging
studies of primary depression (reviewed in refs. 6–8) commonly report
frontal cortex and cingulate abnormalities, a pattern also seen in neurological
depressions (13). Other limbic-paralimbic
(amygdala, anterior temporal, and insula) and subcortical (basal ganglia and thalamus)
abnormalities have also been identified, but the findings are more variable. Across
studies, the most robust and best-replicated finding is that of decreased prefrontal
cortex function, although normal frontal activity and frontal hyperactivity have also
been reported (35, 36). Localization of abnormalities within the frontal lobe includes
regions of the dorsolateral and ventral-lateral prefrontal cortex (specifically Brodmann
area 9 [BA9], BA46, BA10, and BA47) as well as orbital frontal and ventromedial frontal
cortices (specifically BA11, BA32, and BA10). Findings are generally bilateral, although
asymmetries have been described. Cingulate cortex changes (increases or decreases in
activity) are also commonly seen and consistently involve anterior sectors (in
particular, BA24 and BA25).
Potential sources of scan variabilityWhile there are clearly a highly reproducible set of functional and structural findings
across studies, not all patients show the same pattern. Differences among patient
subgroups (e.g., among those with familial, bipolar, unipolar, neurological, or early
trauma depression) as well as heterogeneous expression of clinical symptoms, such as
illness severity, cognitive impairment, anxiety, anhedonia, mood reactivity, and
psychomotor slowing, are thought to contribute to the described variance, but there is
not yet a consensus. The best-replicated behavioral correlate of a resting-state
abnormality in depression is that of an inverse relationship between the activity of the
prefrontal cortex and the severity of depression. Low prefrontal cortex activity has
also been correlated with slowed reaction times and impairment in cognitive functions
such as attention and working memory; low parietal and parahippocampus activity has been
associated with anxiety; medial frontal and cingulate hypoactivity has been associated
with impairments in performance in error detection and set-shifting tasks; ventral
striatum/nucleus accumbens hypoactivity has been associated with anhedonia; and amygdala
hyperactivity has been associated with cortisol status (37–43). A more complex
ventral-dorsal segregation of frontal lobe functions has also been described, with
anxiety/tension positively correlated with ventral prefrontal cortex activity and
psychomotor and cognitive slowing negatively correlated with dorsolateral prefrontal
cortex activity (40). The prefrontal cortex and
amygdala hyperactivity seen in patients with a more ruminative/anxious clinical
presentation is also consistent with findings described in individuals with primary
anxiety and obsessional disorders (39),
memory-evoked anxiety and fear in healthy subjects and response to the testing
environment due to novelty or state anxiety as well as gene-mediated variability in
emotional reactivity (44). Even with these
considerations, the presence of clinical symptom variability within a given patient
cohort does not appear to fully explain the consistent inconsistencies
in the published imaging literature (6, 17).
One can alternatively consider variable patterns from a systems perspective, as outlined
in Figure 2, in which dysregulated circuit activity
identified in the baseline depressed state is seen to reflect both foci of primary
dysfunction as well as sites of attempted (or failed) adaptation. Such a model would
theoretically accommodate the reported variability among published depression cohorts,
the recognized heterogeneity of depressive symptoms, and purported etiologic risk
factors (15, 16) and is also in keeping with conceptual models of sustained allostatic load
(45). Hypothetically, in the setting of
sustained overactivity of the regulatory circuit (whatever the cause), an exaggerated or
hypersensitive compensatory response may result in an agitated, mood-reactive,
ruminative depressive state in one patient, whereas failure to initiate or maintain an
adequate compensatory response may lead to anergy, psychomotor retardation, apathy, and
mood nonreactivity in a second patient with equally severe depression. In this context,
net circuit activity resulting in a sustained but only partially compensated state would
probably respond equally well to either pharmacological or psychological treatments,
consistent with empirical clinical experience as well as randomized controlled studies
(46). On the other hand, more extreme states
of adaptive changes in the circuit (either overactive or underactive) would require more
specific treatments (i.e., CBT or interpersonal psychotherapy when overactive [ref.
47] and medication augmentation or ECT, vagus
nerve stimulation, or repetitive transcranial magnetic stimulation when underactive
[refs. 2, 48–51]), with failure of
the circuit to initiate an adaptive response defining patients with TRD and a need for
more aggressive interventions such as DBS (11,
12, 52–54). Such hypotheses lay the foundation for a related goal, namely
to define a specific brain circuit signature that could eventually provide a therapeutic
road map for optimal treatment selection in individual depressed patients —
if baseline variability and associated change patterns with different treatment
interventions can be fully characterized (6).
While important insights have been made using group-based analyses, as described in the
following sections, practically speaking, fMRI may prove a more agile technology to
achieve this goal, since circuit patterns, commonly termed “functional
connectivity”, are testable in individual subjects. Such strategies
emphasize not merely the absolute state of regional activity, but rather, the way in
which activities in different locales influence one another as indexed using
region-region correlations or covariances (55–57).
Scan variability as a biomarker of response likelihoodIn an attempt to define a neural signature that could indicate the treatment most likely
to be effective in a given patient, several groups have already identified pretreatment
scan patterns that differentiate response-specific subtypes to various treatments (58–67). Retrospective analyses of resting-state PET studies and, more recently,
fMRI studies using behavioral tasks have consistently reported that increased
pretreatment activity in the pregenual anterior cingulate cortex (pACC; BA24)
distinguishes responders to several different antidepressant interventions from
nonresponders (58, 59, 63, 67). However, prospective testing has not been done to indicate
whether this pattern differentially predicts response to a specific treatment class.
Using similar methods, SCC (specifically BA25) hyperactivity has been shown to predict
response to sleep deprivation (64) and
cingulotomy (66) in patients who had previously
not responded to medication treatment, identifying a potential marker of treatment
resistance (11, 62, 68). Systematic characterization
of these potential predictive patterns alone or in combination with genetic markers
(69) has important therapeutic implications in
light of increasing evidence that the presence of residual symptoms places patients at
increased risk for future relapse or recurrence (48).
Brain targets of antidepressant treatmentsAs seen in studies of the baseline depressed state, PET measures of regional cerebral
glucose metabolism and blood flow, and, more recently, resting-state and task fMRI have
also proven to be sensitive indices of changing brain function following various
treatments. Changes in cortical, limbic-paralimbic, and subcortical regions have been
described following treatments as diverse as medication, psychotherapy, sleep
deprivation, ECT, repetitive transcranial magnetic stimulation, vagus nerve stimulation,
ablative surgery, and DBS (6, 7, 10–12, 62, 70–78). While
normalization of frontal abnormalities is the best-replicated finding, other regional
effects are reported with variable patterns with different treatments. The nature of the
specific imaging strategy and the behavior provocation or task used to test the effect
of treatment contribute to variability. Despite this caveat, modality-specific effects
are consistent with the hypothesis that different interventions modulate specific
regional targets, resulting in a variety of complementary, adaptive chemical, and
molecular changes sufficient to reestablish a euthymic, remitted state.
Medication. Across studies of chronic antidepressant treatment using commonly prescribed
medications, prefrontal cortical changes are the most consistently reported, with
normalization of frontal cortex overactivity and underactivity both described (62, 70–72). Additionally,
changes are also seen in limbic and subcortical regions, including the subgenual
cingulate, amygdala, hippocampus, posterior cingulate cortex, and insula, with
decreased activity most commonly observed (70,
71, 74–77). The time course
of these medication effects and differences between responders and nonresponders have
provided additional localizing clues as to critical brain changes
mediating depression remission. In one such experiment (70), responders and nonresponders to the selective serotonin
reuptake inhibitor (SSRI) fluoxetine were differentiated by their pattern of glucose
metabolism observed six weeks after the initiation of therapy, with clinical
improvement associated with limbic-paralimbic and striatal decreases and dorsal
cortical increase in glucose metabolism. Failed response was associated with
persistence of the pattern of glucose metabolism observed one week after the
initiation of therapy (when the same pattern was seen in both groups) and absence of
either SCC (specifically BA25) or prefrontal cortex changes. This combination of
reciprocal dorsal cortical and ventral limbic changes appears to be a common pattern
in individuals that respond to treatment with SSRIs (72), placebo medication (79), and
combination serotonin-norepinephrine reuptake inhibitors (SNRIs) (62). The change in the glucose metabolism pattern
in only those patients who showed clinical improvement suggests a process of neural
plasticity or adaptation in specific brain regions with chronic treatment. These
responder-nonresponder differences are also consistent with the time course and
location of changes identified in animal studies of antidepressant medications, which
emphasize early brainstem and hippocampal changes and late cortical effects,
involving presynaptic autoregulatory desensitization, up- and downregulation of
multiple postsynaptic receptor sites, and receptor-mediated second messenger and
neurotrophic intracellular signaling effects (80, 81).
Psychotherapy.In contrast to pharmacological treatments, CBT is thought to retrain brain activity by
modifying attention and memory functions involved in the mediation of
depression-relevant explicit cognitions, affective bias, and maladaptive information
processing, all of which are putatively localized to orbital, medial frontal,
prefrontal, and anterior cingulate regions of the cortex (82, 83). Imaging studies
examining brain changes following interpersonal psychotherapy and CBT report substantial
regional effects — most prominently decreased glucose metabolism and blood
flow in the prefrontal cortex (62, 71, 84, 85), but with differential non–frontal
cortex changes depending on the specific therapeutic intervention employed. For example,
using CBT, remission was associated with not only prefrontal cortex changes but also
decreased metabolism in posterior cingulate, dorsomedial frontal, and orbital frontal
cortices as well as increased metabolism in anterior mid-cingulate cortex and
parahippocampal regions (71). This CBT-specific
change pattern was generally replicated in a follow-up, randomized study comparing
treatment with CBT and the SNRI venlafaxine (62).
Interestingly, this second study identified both a common decrease in dorsomedial
frontal cortical activity with both treatments as well as reciprocal changes in
subgenual cingulate cortex activity (increased with CBT, decreased, as seen previously,
with medication), further suggesting a critical role for this region in mediating
remission from depression across treatments.
Critical role for the SCCAmong the series of treatment studies surveyed, the involvement of the SCC is especially
prominent (Figure 3, A–E). Not only do
changes in this region appear critical for antidepressant response to active and placebo
pharmacotherapy, ECT, and CBT (62, 70, 73, 79), but functional hyperactivity of this region
best characterizes more treatment-resistant patients (Figure 3, F–I) (11, 62, 65, 66, 68).
Furthermore, anatomical changes on structural MRI scans as well as postmortem
identification of glial cell abnormalities (21,
23) are reported in depressed patient samples.
In addition, structural and functional variability in this region has been linked to a
normal polymorphism in the serotonin transporter, an emerging risk factor for depression
(28). These converging anatomical findings
complement a large functional imaging literature, linking the SCC to the regulation of
negative emotional states, as illustrated by increased activity in this region with the
provocation of sad mood, using either autobiographical memory (Figure 3J) (10) or a
pharmacological challenge, such as tryptophan depletion (86), as well as passive exposure to sad, negative, or unpleasant pictures and
words (61, 87).
The foundation for a more specific role of the SCC in the autonomic and circadian
aspects of emotion regulation, as occurs with both stress and depression, including
alterations in sleep, appetite, libido, and endocrine functioning, is also suggested by
the predominant afferent and efferent connections of the SCC to the insula, brainstem,
and hypothalamus (34, 88–91).
Reciprocal pathways linking SCC BA25 to orbitofrontal, medial frontal, and dorsal
prefrontal cortices, the anterior and posterior cingulate cortices, and to the amygdala,
hippocampus, and nucleus accumbens further identify plausible pathways by which
interceptive and homeostatic processes might influence aspects of learning, memory,
reward, and reinforcement (34, 91–94), which are core behaviors impaired in depressed patients. Interestingly,
these various connections show considerable overlap with the pattern of regional changes
seen with both CBT and pharmacotherapy treatment described above, providing strong
evidence to pursue strategies that might effectively alter SCC
connectivity in individuals with TRD, rather than focusing on merely
correcting absolute activity in SCC in isolation.
Testing the model: targeting the SCC with DBSThe repeated observations of increased activity in the SCC in studies of acute negative
affective states (sadness), cellular abnormalities in this region in depressed patients
postmortem, and predictable decreases in activity with a variety of pharmacological and
somatic antidepressant treatments provided the critical foundation to test the use of
direct modulation of SCC (BA25), using high frequency DBS as a novel treatment strategy
for individuals with otherwise treatment-resistant MDD. Based on the well-established
evidence in Parkinson disease (PD), demonstrating that chronic, high frequency DBS in
pathologically overactive motor circuits produces profound clinical benefits (95), it was hypothesized that focal stimulation of
the SCC and adjacent white matter would not only reduce chronically elevated SCC
activity but would also normalize aberrant activity throughout the depression circuit,
with resulting clinical benefit.
In a proof-of-principle study, six patients with refractory MDD who had failed to
respond to multiple medications as well as psychotherapy and ECT were implanted with two
DBS electrodes (one in each hemisphere) under local anesthesia, using MRI guidance and
stereotaxic surgical procedures routinely used in the treatment of PD. A protocol
similar to that used in evaluating stimulation thresholds for efficacy and adverse
effects for PD was also adopted for use in the patients with TRD, with stimulation
settings programmed via an implanted pulse generator inserted in the subcutaneous chest
wall. Chronic bilateral stimulation (pulse width = 90 μs; frequency = 130
Hz; voltage ≅ 4 V) of the white matter tracts adjacent
to the SCC produced a sustained remission of depressive symptoms in four of the six
patients in the pilot study (11). Consistent with
the circuit hypothesis stated above, clinical antidepressant effects were associated
with a marked reduction in SCC blood flow as well as changes in downstream limbic and
cortical sites (decreased activity in the hypothalamus, ventral striatum, and orbital
and medial frontal cortices and increased activity in the dorsolateral prefrontal,
parietal, mid-cingulate, and posterior cingulate cortices) measured using PET (Figure
4). While it is not yet clear which of these
remote changes is most critical to the sustained antidepressant effects, the clinical
and imaging findings have now been replicated in an additional 14 patients, with an
overall six-month response rate of 60% and with sustained response exceeding one year
(12). Placebo-controlled trials extending
these first studies are now underway, examining both clinical efficacy and mechanisms as
well as potential clinical or imaging biomarkers that might identify the patients with
TRD most likely to benefit from this intervention.
Emergent questionsIn addition to the apparent sustained rate of clinical recovery in the first
experimental group treated with DBS was the intriguing observation that the precise
target of stimulation was extremely critical, with variable clinical effects seen with
stimulation of adjacent contacts separated by mere millimeters along the same electrode
(Figure 4, left panel). Similarly, with patients
awake in the operating room, immediate behavioral effects were often seen with acute
stimulation of some but not all the individual contacts. Such acute effects often
predicted future sustained antidepressant response with chronic stimulation at the same
contact. Among spontaneous patient reports, “a lifting of the
void” or resolution of dread were most common, with heightened interest and
a sense of “connectedness” as well as increased motor speed,
increased volume and rate of spontaneous speech, and improved prosody also observed
(11). These provocative findings have not been
systematically characterized either clinically or with appropriate imaging strategies
but are the focus of current experiments. New studies have also implemented diffusion
imaging and probabilistic tractography analyses and are now examining the specific white
matter tracts affected by focal stimulation of adjacent individual contacts to further
delineate which pathways mediate these potentially critical acute stimulation effects
(96, 97). Such studies combined with real-time electrophysiological recordings in
animals will provide new models that inform on system-level dynamics, mediating the
transition from acute to sustained antidepressant effects at the cellular, local
circuit, and network level.
Unifying depression circuit modelTo help summarize converging findings and facilitate future experiments, an expanded
version of a previously proposed and evolving multi-node circuit model of depression
(6, 9)
has been constructed from the various studies discussed in the previous sections (Figure
5). Regions within this model are clustered into
four main functional compartments, based on reproducible patterns across various
experiments, and informed by comparative anatomical, electrophysiological, and
tract-tracing experiments in nonhuman primates and rodents (34, 88–94, 98). Such
compartmental groupings aim to accommodate the major defining symptoms of MDD (sustained
mood, motor, cognitive, and circadian dysfunction) and changes in these behaviors
accompanying treatment and recovery. The model further attempts to capture basic
cognitive (exteroceptive) and visceral-motor (interoceptive) processes mediating normal
responses to novel overt and covert emotional stimuli (34, 38, 44, 99–108), recognizing that the complexities and nuances
of brain mechanisms mediating these behaviors are grossly oversimplified by this model.
With this caveat, consistent functional interactions and region-region correlations are
emphasized in the assignment of a particular region to a specific compartment, with
explicit anatomical connections linking individual regions both within and across
compartments critical to the core model construct.
While earlier versions of this model implicated a more limited set of brain regions
(9, 13),
what has remained consistent across models are the reciprocal interactions between
ventral limbic (interoceptive) regions and dorsal cortical (exteroceptive) regions as a
hallmark of a negative mood state (increased limbic activity and decreased cortical
activity), occurring either transiently — such as with an acute emotional
provocation — or when sustained, as seen during a major depressive episode.
Similarly, reversal of this pattern (decreased limbic activity and increased cortical
activity) characterizes mood improvement, with depression remission (10, 11).
Medial frontal cortical regions have been assigned a distinct compartment in the model,
as these regions appear most critical to active cognitive control and overt regulation
of emotional and affective state (37, 103–106, 109). Similarly, a set of
subcortical regions, including the amygdala, basal ganglia, and thalamus, which have
been consistently implicated in primary and often covert processing of novel emotional
and nonemotional stimuli (37), have been grouped
together to emphasize their more general role in evaluating salience (107) and in mediating reinforcement, learning, and
habit (38, 44, 108, 110–112).
Ventral (subcallosal SCC BA25), rostral (pACC BA24), and dorsal (supragenual or
mid-cingulate cortex BA24) subregions of the anterior cingulate cortex (also shown in
Figure 1) have been similarly segregated, in
keeping with their differential anatomical connections within and between compartments
(34, 88, 94, 98). Within this framework, synchronized changes within and across
compartments are considered critical for illness remission, regardless of treatment
modality, accommodating the described pharmacotherapy as well as cognitive and surgical
interventions. That said, it is not yet clear if the specific balance between regions or
compartments is differentially sensitive to a particular treatment, as postulated in
Figure 2, but this remains an important focus of
ongoing studies.
Future directionsMulticenter, randomized, placebo-controlled trials are ultimately necessary to determine
the clinical efficacy of DBS for TRD, using modulation of the SCC as described here
(11, 12) or modulation of other brain regions currently being testing, including the
anterior limb of the internal capsule, the nucleus accumbens, and the inferior thalamic
peduncle (52–54). That said, complementary research studies in patients
undergoing these procedures offer unique opportunities to examine both disease and
treatment mechanisms from new perspectives. Such studies will optimally benefit from a
flexible research infrastructure that can take best advantage of ongoing advances in
multimodal imaging and computational modeling of complex circuits (109, 113–116) as well as new animal models (30–32, 117–119). As has proven to be the case with DBS for the
treatment of PD (120–124), such platforms facilitate the necessary
translational studies needed to fully characterize DBS effects at the cellular,
molecular, and network levels. It is further expected that continued refinement of
brain-based circuit models for depression and other neuropsychiatric disorders will have
a growing role not only in the development of novel therapies but in defining a new
depression nosology, a critical step toward the eventual use of evidence-based brain
biomarkers to optimize treatment selection in individual patients.
Acknowledgments I thank my many colleagues who contributed to these many studies, including Robert
Robinson, Sergio Starkstein, Stephen Brannan, Mario Liotti, Sidney Kennedy, Zindel
Segal, Andres Lozano, Paul Holtzheimer, and Cameron Craddock. Past and current work is
supported by grants from the National Institute of Mental Health (NIMH), Canadian
Institute for Health Research (CIHR), National Alliance for Research on Schizophrenia
and Depression (NARSAD), Dana Foundation, Stanley Medical Research Institute, and the
Woodruff Foundation.
FootnotesConflict of interest: The author consults with Advanced Neuromodulation
Systems (ANS, a division of St. Jude Medical [SJM]) and has intellectual property
rights on a deep brain stimulation technology for treating depression that has been
licensed to ANS/SJM. Nonstandard abbreviations used: BA, Brodmann area; CBT, cognitive
behavioral therapy; DBS, deep brain stimulation; ECT, electroconvulsive therapy;
fMRI, functional MRI; MDD, major depressive disorder; PD, Parkinson disease; SCC,
subcallosal cingulate; TRD, treatment-resistant depression. Citation for this article:
J. Clin. Invest.
119:717–725 (2009). doi:10.1172/JCI38454
References-
McKenna, M.T., Michaud, C.M., Murray, C.J., Marks, J.S. 2005. Assessing the burden of disease in the United States using
disability-adjusted life years. Am. J. Prev. Med. 28:415-423.
-
Warden, D., Rush, A.J., Trivedi, M.H., Fava, M., Wisniewski, S.R. 2007. The STAR*D Project results: a comprehensive review of findings. Curr. Psychiatry Rep. 9:449-459.
-
Holtzheimer, P.E., Nemeroff, C.B. 2008. Novel targets for antidepressant therapies. Curr. Psychiatry Rep. 10:465-473.
-
Davidson, R.J., Pizzagalli, D., Nitschke, J.B., Putnam, K. 2002. Depression: perspectives from affective neuroscience. Annu. Rev. Psychol. 53:545-574.
-
Phillips, M.L., Drevets, W.C., Rauch, S.L., Lane, R. 2003. Neurobiology of emotion perception II: Implications for major
psychiatric disorders. Biol. Psychiatry. 54:515-528.
-
Mayberg, H.S. 2003. Modulating dysfunctional limbic-cortical circuits in depression:
towards development of brain-based algorithms for diagnosis and optimised
treatment. Br. Med. Bull. 65:193-207.
-
Fitzgerald, P.B., Laird, A.R., Maller, J., Daskalakis, Z.J. 2008. A meta-analytic study of changes in brain activation in depression. Hum. Brain Mapp. 29:683-695.
-
Drevets, W.C., Price, J.L., Furey, M.L. 2008. Brain structural and functional abnormalities in mood disorders:
implications for neurocircuitry models of depression. Brain Struct. Funct. 213:93-118.
-
Mayberg, H.S. 1997. Limbic-cortical dysregulation: a proposed model of depression. J. Neuropsychiatry Clin. Neurosci. 9:471-481.
-
Mayberg, H.S., et al. 1999. Reciprocal limbic-cortical function and negative mood: converging PET
findings in depression and normal sadness. Am. J. Psychiatry. 156:675-682.
-
Mayberg, H.S., et al. 2005. Deep brain stimulation for treatment-resistant depression. Neuron. 45:651-660.
-
Lozano, A.M., et al. 2008. Subcallosal cingulate gyrus deep brain stimulation for
treatment-resistant depression. Biol. Psychiatry. 64:461-467.
-
Mayberg, H.S. 1994. Frontal lobe dysfunction in secondary depression. J. Neuropsychiatry Clin. Neurosci. 6:428-442.
-
McEwen, B.S., Seeman, T. 1999. Protective and damaging effects of mediators of stress. Elaborating
and testing the concepts of allostasis and allostatic load. Ann. N. Y. Acad. Sci. 896:30-47.
-
Kendler, K.S., Thornton, L.M., Gardner, C.O. 2001. Genetic risk, number of previous depressive episodes, and stressful
life events in predicting onset of major depression. Am. J. Psychiatry. 158:582-586.
-
Caspi, A., et al. 2003. Influence of life stress on depression: moderation by a polymorphism
in the 5-HTT gene. Science. 301:386-389.
-
Hasler, G., Drevets, W.C., Manji, H.K., Charney, D.S. 2004. Discovering endophenotypes for major depression. Neuropsychopharmacology. 29:1765-1781.
-
Robinson, R.G., Kubos, K.L., Starr, L.B., Rao, K., Price, T.R. 1984. Mood disorders in stroke patients. Importance of location of lesion. Brain. 107:81-93.
-
Koenigs, M., et al. 2008. Distinct regions of prefrontal cortex mediate resistance and
vulnerability to depression. J. Neurosci. 28:12341-12348.
-
Sheline, Y.I. 2003. Neuroimaging studies of mood disorder effects on the brain. Biol. Psychiatry. 54:338-352.
-
Drevets, W.C., et al. 1997. Subgenual prefrontal cortex abnormalities in mood disorders. Nature. 386:824-827.
-
Pizzagalli D.A., et al. 2004;Functional but not structural subgenual prefrontal cortex
abnormalities in melancholia.. Mol. Psychiatry. 9:325. , 395–405
-
Ongur, D., Drevets, W.C., Price, J.L. 1998. Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. U. S. A. 95:13290-13295.
-
Bowley, M.P., Drevets, W.C., Ongur, D., Price, J.L. 2002. Low glial numbers in the amygdala in major depressive disorder. Biol. Psychiatry. 52:404-412.
-
Harrison, P.J. 2002. The neuropathology of primary mood disorder. Brain. 125:1428-1449.
-
Rajkowska, G., Miguel-Hidalgo, J.J. 2007. Gliogenesis and glial pathology in depression. CNS Neurol. Disord. Drug Targets. 6:219-233.
-
McEwen, B.S., Magarinos, A.M. 1997. Stress effects on morphology and function of the hippocampus. Ann. N. Y. Acad. Sci. 821:271-284.
-
Pezawas, L., et al. 2005. 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a
genetic susceptibility mechanism for depression. Nat. Neurosci. 8:828-834.
-
Radley, J.J., et al. 2008. Repeated stress alters dendritic spine morphology in the rat medial
prefrontal cortex. J. Comp. Neurol. 507:1141-1150.
-
Banasr, M., Duman, R.S. 2007. Regulation of neurogenesis and gliogenesis by stress and
antidepressant treatment. CNS Neurol. Disord. Drug Targets. 6:311-320.
-
Krishnan, V., Nestler, E.J. 2008. The molecular neurobiology of depression. Nature. 455:894-902.
-
Airan, R.D., et al. 2007. High-speed imaging reveals neurophysiological links to behavior in an
animal model of depression. Science. 317:819-823.
-
Diorio, D., Viau, V., Meaney, M.J. 1993. The role of the medial prefrontal cortex (cingulate gyrus) in the
regulation of hypothalamic-pituitary-adrenal responses to stress. J. Neurosci. 13:3839-3847.
-
Barbas, H., Saha, S., Rempel-Clower, N., Ghashghaei, T. 2003. Serial pathways from primate prefrontal cortex to autonomic areas may
influence emotional expression. BMC Neurosci. 4:25.
-
Baxter (Jr.), L.R., et al. 1985. Cerebral metabolic rates for glucose in mood disorders. Studies with
positron emission tomography and fluorodeoxyglucose F 18. Arch. Gen. Psychiatry. 42:441-447.
-
Drevets, W.C., et al. 1992. A functional anatomical study of unipolar depression. J. Neurosci. 12:3628-3641.
-
Wang, L., et al. 2008. Prefrontal mechanisms for executive control over emotional distraction
are altered in major depression. Psychiatry Res. 163:143-155.
-
Tremblay, L.K., et al. 2005. Functional neuroanatomical substrates of altered reward processing in
major depressive disorder revealed by a dopaminergic probe. Arch. Gen. Psychiatry. 62:1228-1236.
-
Osuch, E.A., et al. 2000. Regional cerebral metabolism associated with anxiety symptoms in
affective disorder patients. Biol. Psychiatry. 48:1020-1023.
-
Brody, A.L., et al. 2001. Brain metabolic changes associated with symptom factor improvement in
major depressive disorder. Biol. Psychiatry. 50:171-178.
-
Dunn, R.T., et al. 2002. Principal components of the Beck Depression Inventory and regional
cerebral metabolism in unipolar and bipolar depression. Biol. Psychiatry. 51:387-399.
-
Drevets, W.C., et al. 2002. Glucose metabolism in the amygdala in depression: relationship to
diagnostic subtype and plasma cortisol levels. Pharmacol. Biochem. Behav. 71:431-447.
-
Videbech, P., et al. 2002. The Danish PET/depression project: clinical symptoms and cerebral
blood flow. A regions-of-interest analysis. Acta. Psychiatr. Scand. 106:35-44.
-
Hariri, A.R., et al. 2005. A susceptibility gene for affective disorders and the response of the
human amygdala. Arch. Gen. Psychiatry. 62:146-152.
-
McEwen, B.S. 1998. Protective and damaging effects of stress mediators. N. Engl. J. Med. 338:171-179.
-
DeRubeis, R.J., et al. 2005. Cognitive therapy vs medications in the treatment of moderate to
severe depression. Arch. Gen. Psychiatry. 62:409-416.
-
Nemeroff, C.B., et al. 2003. Differential responses to psychotherapy versus pharmacotherapy in
patients with chronic forms of major depression and childhood trauma. Proc. Natl. Acad. Sci. U. S. A. 100:14293-14296.
-
Rush, A.J., et al. 2006. Acute and longer-term outcomes in depressed outpatients requiring one
or several treatment steps: a STAR*D report. Am. J. Psychiatry. 163:1905-1917.
-
Kellner, C.H., et al. 2006. Continuation electroconvulsive therapy vs pharmacotherapy for relapse
prevention in major depression: a multisite study from the Consortium for Research
in Electroconvulsive Therapy (CORE). Arch. Gen. Psychiatry. 63:1337-1344.
-
Lam, R.W., Chan, P., Wilkins-Ho, M., Yatham, L.N. 2008. Repetitive transcranial magnetic stimulation for treatment-resistant
depression: a systematic review and metaanalysis. Can. J. Psychiatry. 53:621-631.
-
Nierenberg, A.A., Alpert, J.E., Gardner-Schuster, E.E., Seay, S., Mischoulon, D. 2008. Vagus nerve stimulation: 2-year outcomes for bipolar versus unipolar
treatment-resistant depression. Biol. Psychiatry. 64:455-460.
-
Schlaepfer, T.E., et al. 2008. Deep brain stimulation to reward circuitry alleviates anhedonia in
refractory major depression. Neuropsychopharmacology. 33:368-377.
-
Malone (Jr.), D.A., et al. 2008. Deep brain stimulation of the ventral capsule/ventral striatum for
treatment-resistant depression. Biol. Psychiatry. 65:267-275.
-
Jimenez, F., et al. 2005. A patient with a resistant major depression disorder treated with deep
brain stimulation in the inferior thalamic peduncle. Neurosurgery. 57:585-593; discussion 585–593.
-
Friston, K., Phillips, J., Chawla, D., Buchel, C. 1999. Revealing interactions among brain systems with nonlinear PCA. Hum. Brain Mapp. 8:92-97.
-
Horwitz, B. 2004. Relating fMRI and PET signals to neural activity by means of
large-scale neural models. Neuroinformatics. 2:251-266.
-
Margulies, D.S., et al. 2007. Mapping the functional connectivity of anterior cingulate cortex. Neuroimage. 37:579-588.
-
Mayberg, H.S., et al. 1997. Cingulate function in depression: a potential predictor of treatment
response. Neuroreport. 8:1057-1061.
-
Pizzagalli, D., et al. 2001. Anterior cingulate activity as a predictor of degree of treatment
response in major depression: evidence from brain electrical tomography analysis. Am. J. Psychiatry. 158:405-415.
-
Little, J.T., et al. 1996. Venlafaxine or bupropion responders but not nonresponders show
baseline prefrontal and paralimbic hypometabolism compared with controls. Psychopharmacol. Bull. 32:629-635.
-
Siegle, G.J., Carter, C.S., Thase, M.E. 2006. Use of FMRI to predict recovery from unipolar depression with
cognitive behavior therapy. Am. J. Psychiatry. 163:735-738.
-
Kennedy, S.H., et al. 2007. Differences in brain glucose metabolism between responders to CBT and
venlafaxine in a 16-week randomized controlled trial. Am. J. Psychiatry. 164:778-788.
-
Chen, C.H., et al. 2007. Brain imaging correlates of depressive symptom severity and predictors
of symptom improvement after antidepressant treatment. Biol. Psychiatry. 62:407-414.
-
Wu, J., et al. 1999. Prediction of antidepressant effects of sleep deprivation by metabolic
rates in the ventral anterior cingulate and medial prefrontal cortex. Am. J. Psychiatry. 156:1149-1158.
-
Seminowicz, D.A., et al. 2004. Limbic-frontal circuitry in major depression: a path modeling
metanalysis. Neuroimage. 22:409-418.
-
Dougherty, D.D., et al. 2003. Cerebral metabolic correlates as potential predictors of response to
anterior cingulotomy for treatment of major depression. J. Neurosurg. 99:1010-1017.
-
Salvadore, G., et al. 2009. Increased anterior cingulate cortical activity in response to fearful
faces: a neurophysiological biomarker that predicts rapid antidepressant response
to ketamine. Biol. Psychiatry. 65:289-295.
-
Greicius, M.D., et al. 2007. Resting-state functional connectivity in major depression: abnormally
increased contributions from subgenual cingulate cortex and thalamus. Biol. Psychiatry. 62:429-437.
-
Eichelbaum, M., Ingelman-Sundberg, M., Evans, W.E. 2006. Pharmacogenomics and individualized drug therapy. Annu. Rev. Med. 57:119-137.
-
Mayberg, H.S., et al. 2000. Regional metabolic effects of fluoxetine in major depression: serial
changes and relationship to clinical response. Biol. Psychiatry. 48:830-843.
-
Goldapple, K., et al. 2004. Modulation of cortical-limbic pathways in major depression:
treatment-specific effects of cognitive behavior therapy. Arch. Gen. Psychiatry. 61:34-41.
-
Kennedy, S.H., et al. 2001. Changes in regional brain glucose metabolism measured with positron
emission tomography after paroxetine treatment of major depression. Am. J. Psychiatry. 158:899-905.
-
Nobler, M.S., et al. 2001. Decreased regional brain metabolism after ECT. Am. J. Psychiatry. 158:305-308.
-
Pardo, J.V., et al. 2008. Chronic vagus nerve stimulation for treatment-resistant depression
decreases resting ventromedial prefrontal glucose metabolism. Neuroimage. 42:879-889.
-
Sheline, Y.I., et al. 2001. Increased amygdala response to masked emotional faces in depressed
subjects resolves with antidepressant treatment: an fMRI study. Biol. Psychiatry. 50:651-658.
-
Fu, C.H., et al. 2004. Attenuation of the neural response to sad faces in major depression by
antidepressant treatment: a prospective, event-related functional magnetic
resonance imaging study. Arch. Gen. Psychiatry. 61:877-889.
-
Anand, A., et al. 2005. Antidepressant effect on connectivity of the mood-regulating circuit:
an FMRI study. Neuropsychopharmacology. 30:1334-1344.
-
Luborzewski, A., et al. 2007. Metabolic alternations in the dorsolateral prefrontal cortex after
treatment with high-frequency repetitive transcranial magnetic stimulation in
patients with unipolar depression. J. Psychiatr. Res. 41:606-615.
-
Mayberg, H.S., et al. 2002. The functional neuroanatomy of the placebo effect. Am. J. Psychiatry. 159:728-737.
-
Freo, U., Ori, C., Dam, M., Merico, A., Pizzolato, G. 2000. Effects of acute and chronic treatment with fluoxetine on regional
glucose cerebral metabolism in rats: implications for clinical therapies. Brain Res. 854:35-41.
-
Frechilla, D., Otano, A., Del Rio, J. 1998. Effect of chronic antidepressant treatment on transcription factor
binding activity in rat hippocampus and frontal cortex. Prog. Neuropsychopharmacol. Biol. Psychiatry. 22:787-802.
-
Watkins, E., Teasdale, J.D. 2004. Adaptive and maladaptive self-focus in depression. J. Affect. Disord. 82:1-8.
-
Rush, A.J., Kovacs, M., Beck, A.T., Weissenburger, J., Hollon, S.D. 1981. Differential effects of cognitive therapy and pharmacotherapy on
depressive symptoms. J. Affect. Disord. 3:221-229.
-
Brody, A.L., et al. 2001. Regional brain metabolic changes in patients with major depression
treated with either paroxetine or interpersonal therapy: preliminary findings. Arch. Gen. Psychiatry. 58:631-640.
-
Martin, S.D., Martin, E., Rai, S.S., Richardson, M.A., Royall, R. 2001. Brain blood flow changes in depressed patients treated with
interpersonal psychotherapy or venlafaxine hydrochloride: preliminary findings. Arch. Gen. Psychiatry. 58:641-648.
-
Talbot, P.S., Cooper, S.J. 2006. Anterior cingulate and subgenual prefrontal blood flow changes
following tryptophan depletion in healthy males. Neuropsychopharmacology. 31:1757-1767.
-
Zald, D.H., Mattson, D.L., Pardo, J.V. 2002. Brain activity in ventromedial prefrontal cortex correlates with
individual differences in negative affect. Proc. Natl. Acad. Sci. U. S. A. 99:2450-2454.
-
Ghashghaei, H.T., Hilgetag, C.C., Barbas, H. 2007. Sequence of information processing for emotions based on the anatomic
dialogue between prefrontal cortex and amygdala. Neuroimage. 34:905-923.
-
Hsu, D.T., Price, J.L. 2007. Midline and intralaminar thalamic connections with the orbital and
medial prefrontal networks in macaque monkeys. J. Comp. Neurol. 504:89-111.
-
Freedman, L.J., Insel, T.R., Smith, Y. 2000. Subcortical projections of area 25 (subgenual cortex) of the macaque
monkey. J. Comp. Neurol. 421:172-188.
-
Vertes, R.P. 2004. Differential projections of the infralimbic and prelimbic cortex in
the rat. Synapse. 51:32-58.
-
Haber, S.N., Kim, K.S., Mailly, P., Calzavara, R. 2006. Reward-related cortical inputs define a large striatal region in
primates that interface with associative cortical connections, providing a
substrate for incentive-based learning. J. Neurosci. 26:8368-8376.
-
Ongur, D., Price, J.L. 2000. The organization of networks within the orbital and medial prefrontal
cortex of rats, monkeys and humans. Cereb. Cortex. 10:206-219.
-
Petrides, M., Pandya, D.N. 2007. Efferent association pathways from the rostral prefrontal cortex in
the macaque monkey. J. Neurosci. 27:11573-11586.
-
Benabid, A.L. 2003. Deep brain stimulation for Parkinson’s disease. Curr. Opin. Neurobiol. 13:696-706.
-
Johansen-Berg, H., et al. 2008. Anatomical connectivity of the subgenual cingulate region targeted
with DBS for treatment-resistant depression. Cereb. Cortex. 18:1374-1383.
-
Gutman, D.A., Holtzheimer, P.E., Behrens, T.E., Johansen-Berg, H., Mayberg, H.S. 2008. A tractography analysis of two deep brain stimulation white matter
targets for depression. Biol. Psychiatry. 65:276-282.
-
Vogt, B.A., Nimchinsky, E.A., Vogt, L.J., Hof, P.R. 1995. Human cingulate cortex: surface features, flat maps, and
cytoarchitecture. J. Comp. Neurol. 359:490-506.
-
Craig, A.D. 2002. How do you feel? Interoception: the sense of the physiological
condition of the body. Nat. Rev. Neurosci. 3:655-666.
-
Northoff, G., et al. 2006. Self-referential processing in our brain--a meta-analysis of imaging
studies on the self. Neuroimage. 31:440-457.
-
Phan, K.L., Wager, T., Taylor, S.F., Liberzon, I. 2002. Functional neuroanatomy of emotion: a meta-analysis of emotion
activation studies in PET and fMRI. Neuroimage. 16:331-348.
-
Harvey, P.O., et al. 2005. Cognitive control and brain resources in major depression: an fMRI
study using the n-back task. Neuroimage. 26:860-869.
-
Etkin, A., Egner, T., Peraza, D.M., Kandel, E.R., Hirsch, J. 2006. Resolving emotional conflict: a role for the rostral anterior
cingulate cortex in modulating activity in the amygdala. Neuron. 51:871-882.
-
Fossati, P., et al. 2003. In search of the emotional self: an FMRI study using positive and
negative emotional words. Am. J. Psychiatry. 160:1938-1945.
-
Yoshimura, S., et al. 2009. Self-referential processing of negative stimuli within the ventral
anterior cingulate gyrus and right amygdala. Brain Cogn. 69:218-225.
-
Ochsner, K.N., et al. 2004. For better or for worse: neural systems supporting the cognitive down-
and up-regulation of negative emotion. Neuroimage. 23:483-499.
-
Zink, C.F., Pagnoni, G., Martin, M.E., Dhamala, M., Berns, G.S. 2003. Human striatal response to salient nonrewarding stimuli. J. Neurosci. 23:8092-8097.
-
Siegle, G.J., Steinhauer, S.R., Thase, M.E., Stenger, V.A., Carter, C.S. 2002. Can’t shake that feeling: event-related fMRI assessment of
sustained amygdala activity in response to emotional information in depressed
individuals. Biol. Psychiatry. 51:693-707.
-
Koechlin, E., Ody, C., Kouneiher, F. 2003. The architecture of cognitive control in the human prefrontal cortex. Science. 302:1181-1185.
-
Knutson, B., Greer, S.M. 2008. Anticipatory affect: neural correlates and consequences for choice. Philos. Trans. R Soc. Lond. B Biol. Sci. 363:3771-3786.
-
Myers, K.M., Davis, M. 2007. Mechanisms of fear extinction. Mol. Psychiatry. 12:120-150.
-
Santini, E., Quirk, G.J., Porter, J.T. 2008. Fear conditioning and extinction differentially modify the intrinsic
excitability of infralimbic neurons. J. Neurosci. 28:4028-4036.
-
Izhikevich, E.M., Edelman, G.M. 2008. Large-scale model of mammalian thalamocortical systems. Proc. Natl. Acad. Sci. U. S. A. 105:3593-3598.
-
Palomero-Gallagher, N., Vogt, B.A., Schleicher, A., Mayberg, H.S., Zilles, K. 2008. Receptor architecture of human cingulate cortex: evaluation of the
four-region neurobiological model. Hum. Brain Mapp.Online publication ahead of print. doi:
-
Pape, H.C., Narayanan, R.T., Smid, J., Stork, O., Seidenbecher, T. 2005. Theta activity in neurons and networks of the amygdala related to
long-term fear memory. Hippocampus. 15:874-880.
-
Fried, I., et al. 1999. Cerebral microdialysis combined with single-neuron and
electroencephalographic recording in neurosurgical patients. Technical note. J. Neurosurg. 91:697-705.
-
McCracken, C.B., Grace, A.A. 2007. High-frequency deep brain stimulation of the nucleus accumbens region
suppresses neuronal activity and selectively modulates afferent drive in rat
orbitofrontal cortex in vivo. J. Neurosci. 27:12601-12610.
-
Belujon, P., Grace, A.A. 2008. Critical role of the prefrontal cortex in the regulation of
hippocampus-accumbens information flow. J. Neurosci. 28:9797-9805.
-
Zhang, F., Aravanis, A.M., Adamantidis, A., de Lecea, L., Deisseroth, K. 2007. Circuit-breakers: optical technologies for probing neural signals and
systems. Nat. Rev. Neurosci. 8:577-581.
-
Benabid, A.L., Pollak, P., Louveau, A., Henry, S., de Rougemont, J. 1987. Combined (thalamotomy and stimulation) stereotactic surgery of the VIM
thalamic nucleus for bilateral Parkinson disease. Appl. Neurophysiol. 50:344-346.
-
DeLong, M.R., Wichmann, T. 2007. Circuits and circuit disorders of the basal ganglia. Arch. Neurol. 64:20-24.
-
Li, S., Arbuthnott, G.W., Jutras, M.J., Goldberg, J.A., Jaeger, D. 2007. Resonant antidromic cortical circuit activation as a consequence of
high-frequency subthalamic deep-brain stimulation. J. Neurophysiol. 98:3525-3537.
-
Trost, M., et al. 2006. Network modulation by the subthalamic nucleus in the treatment of
Parkinson’s disease. Neuroimage. 31:301-307.
-
Poston, K.L., Eidelberg, D. 2008. Network biomarkers for the diagnosis and treatment of movement
disorders. Neurobiol. Dis.Online publication ahead of print. doi:
|