Defining Critical White Matter Pathways Mediating
Successful Subcallosal Cingulate Deep Brain
Stimulation for Treatment-Resistant Depression
Patricio Riva-Posse, Ki Sueng Choi, Paul E. Holtzheimer, Cameron C. McIntyre, Robert E. Gross,
Ashutosh Chaturvedi, Andrea L. Crowell, Steven J. Garlow, Justin K. Rajendra, and
Helen S. Mayberg
Background: Subcallosal cingulate white matter (SCC) deep brain stimulation (DBS) is an evolving investigational treatment for
depression. Mechanisms of action are hypothesized to involve modulation of activity within a structurally defined network of brain
regions involved in mood regulation. Diffusion tensor imaging was used to model white matter connections within this network to
identify those critical for successful antidepressant response.
Methods: Preoperative high-resolution magnetic resonance imaging data, including diffusion tensor imaging, were acquired in 16
patients with treatment-resistant depression, who then received SCC DBS. Computerized tomography was used postoperatively to locate
DBS contacts. The activation volume around the contacts used for chronic stimulation was modeled for each patient retrospectively.
Probabilistic tractography was used to delineate the white matter tracts traveling through each activation volume. Patient-specific tract
maps were calculated using whole-brain analysis. Clinical evaluations of therapeutic outcome from SCC DBS were defined at 6 months
and 2 years.
Results: Whole-brain activation volume tractography demonstrated that all DBS responders at 6 months (n ¼ 6) and 2 years (n ¼ 12)
shared bilateral pathways from their activation volumes to 1) medial frontal cortex via forceps minor and uncinate fasciculus; 2) rostral
and dorsal cingulate cortex via the cingulum bundle; and 3) subcortical nuclei. Nonresponders did not consistently show these
connections. Specific anatomical coordinates of the active contacts did not discriminate responders from nonresponders.
Conclusions: Patient-specific activation volume tractography modeling may identify critical tracts that mediate SCC DBS antidepressant
response. This suggests a novel method for patient-specific target and stimulation parameter selection.
Key Words: Antidepressant response, bipolar disorder, deep brain
stimulation, diffusion tensor imaging, major depressive disorder,
subcallosal cingulate, subgenual cingulate, tractography, treatment-
been investigated, including the subcallosal cingulate (SCC) white
matter, the ventral capsule/ventral striatum, the nucleus accum-
bens, the lateral habenula, the inferior thalamic peduncle, and the
medial forebrain bundle (1–6). Six-month response rates across
eep brain stimulation (DBS) is an emerging experimental
therapy for treatment-resistant depression (TRD). In the
past decade, a number of different stimulation sites have
studies range from 41% to 66% with sustained and increased
response over time. Of the various targets for treating TRD, SCC
white matter has been the most studied with published data
available for 77 patients implanted at eight separate centers.
Within some cohorts, outcome data for patients receiving more
than 6 years of chronic SCC DBS suggest significant and lasting
antidepressant efficacy (7–14).
The initial rationale for targeting the SCC white matter was
based on converging imaging data demonstrating changes in SCC
white matter activity with antidepressant response to a variety of
standard treatments (15–19). Selection of this target was further
supported by an extensive literature demonstrating monosynaptic
connections between the subcallosal cingulate and specific frontal,
limbic, subcortical, and brainstem sites involved in mood regu-
lation, depression, and the antidepressant response (20–26).
Placement of the DBS electrodes was guided by local anatomical
landmarks with approximate coordinates derived from positron
emission tomography imaging studies localizing the subcallosal
cingulate region (Brodmann area [BA] 25) and adjacent white
matter and use of standard neurosurgical atlases (21,27).
Although SCC DBS is associated with notable antidepressant
effects in patients with TRD, the magnitude of the response varies.
Initial efforts to define differences in outcome focused on the
anatomical location of the active contacts used for chronic
stimulation, but these studies did not differentiate responders
and nonresponders (28). There was no difference in anatomical
distribution of the active contacts between responders and non-
responders in a second cohort of patients using comparable
localization methods (8). Additional positron emission tomography
studies suggested that activity changes in brain regions remote
Authors PR-P and KSC contributed equally to this work.
Address correspondence to Patricio Riva-Posse, M.D., Emory University
School of Medicine, Department of Psychiatry and Behavioral Sciences,
101 Woodruff Circle NE, Suite 4309, Atlanta, GA 30322; E-mail:
Received Oct 2, 2013; revised Mar 18, 2014; accepted Mar 19, 2014.
From the Department of Psychiatry and Behavioral Sciences (PR-P, KSC,
PEH, ALC, SJG, JKR, HSM), Emory University; and The Wallace H. Coulter
Department of Biomedical Engineering (KSC, REG), and Biomedical
Imaging Technology Center (KSC), Georgia Institute of Technology and
Emory University, Atlanta, Georgia; Departments of Psychiatry and
Surgery (PEH), Geisel School of Medicine at Dartmouth, Hanover, New
Hampshire; Departments of Neurology (REG, HSM) and Neurosurgery
(REG), Emory University, Atlanta, Georgia; and Department of Biome-
dical Engineering (CCM, AC), Case Western Reserve University, Cleve-
BIOL PSYCHIATRY 2014;76:963–969
& 2014 Society of Biological Psychiatry
from the site of stimulation, such as the dorsal cingulate and
frontal cortex, were potentially as important to the antidepressant
response as activity changes in the vicinity of the SCC DBS target
(1). Axonal elements directly modulated by DBS (afferents and
efferents projecting to and from the SCC, as well as fibers of
passage) may be especially important to the effects of the
stimulation (29–32). Characterizing these white matter pathways
is therefore seen as a logical next step for optimizing the clinical
procedure as well as better delineating mechanisms of action of
Fiber tractography techniques have been used in healthy
subjects to map the connections of the SCC, identifying midline
frontal, cingulate, mesial temporal, striatal, thalamic, hypothala-
mic, and brainstem pathways (33–35). The same pattern of
connections had been previously characterized in nonhuman
primates (22,25,36). Detailed computational models of the
DBS activation volume have additionally been developed and
successfully applied to the study of DBS in Parkinson’s dis-
ease with newest methods incorporating the location of white
matter fibers (37–40). This study used individual activation
volumes and probabilistic tractography in patients enrolled in a
clinical trial of SCC DBS for TRD to define the combination and
location of specific white matter tracts mediating clinical
Methods and Materials
Participants and Clinical Protocol
Seventeen chronically depressed, treatment-resistant patients
gave written consent to participate in a research protocol at
Emory University testing safety and efficacy of SCC DBS in
treatment-resistant depression (9) (ClinicalTrials.gov NCT00367003).
The protocol was approved by Emory University Institutional
Review Board and the US Food and Drug Administration under
an Investigational Device Exemption (G060028 held by H.S.M.)
and was monitored by the Emory University Department of
Psychiatry and Behavioral Sciences Data and Safety Monitoring
Patients underwent implantation of bilateral electrodes in the
SCC area as previously described by Holtzheimer et al. (9). After a
4-week, single-blind, sham stimulation phase, a 24-week open-
label active stimulation phase was conducted. As described in the
initial report, after this period, during which psychopharmaco-
logic treatment remained unchanged, patients entered a natural-
istic long-term follow-up phase. Response was defined here as in
the original report of the clinical trial: 50% decrease in the 17-item
Hamilton Depression Rating Scale (41). After 6 months of chronic
stimulation, there were 7 responders and 10 nonresponders
(41%). There were no significant differences in demographics or
clinical characteristics between responders and nonresponders
[data available in (9)]. At 2 years of DBS, there were 13 responders
and 2 nonresponders. Two subjects were explanted before they
reached the 2-year time point. Unfortunately, one of the res-
ponders (at 6 months and 2 years) was excluded from analysis
due to inadequate quality of the presurgical diffusion tensor
imaging (DTI) data. Therefore, the imaging analyses were per-
formed in 6 responders and 10 nonresponders at 6 months and
12 responders and 2 nonresponders at 2 years.
Magnetic Resonance and Computed Tomography Imaging
Multi-sequence structural and diffusion magnetic resonance
imaging (MRI) were acquired in a single session 1 week before
surgery. T1-weighted and DTI data were acquired on a 3T Tim Trio
MRI scanner with a 12-channel head array coil (Siemens Medical
Solutions, Malvern, Pennsylvania) that permits maximum gradient
amplitudes of 40 mT/m. Single-shot spin-echo echo-planar imag-
ing sequence was used for DTI with generalized autocalibrating
parallel acquisition with twofold acceleration (R ¼ 2) (42).
Diffusion tensor imaging parameters were field of view ¼ 256 ?
256; b value ¼ 1000 seconds/mm2; voxel resolution ¼ 2 ? 2 ?
2 mm; number of slices ¼ 64; matrix ¼ 128 ? 128; 2 averages; 64
noncollinear directions with one nondiffusion weighted image
(b ¼ 0); repetition time/echo time ¼ 11300/90 msec. High-resolution
T1 weighted images were collected using a three-dimensional
magnetization prepared rapid acquisition gradient-echo sequence
with the following parameters: repetition time/inversion time/echo
time ¼ 2600/900/3.02 msec; a flip angle of 8°, voxel resolution ¼ 1 ?
1 ? 1 mm; number of slices ¼ 176; matrix ¼ 224 ? 256.
Postsurgical high-resolution computed tomography (CT) data
were acquired on a LightSpeed16 (GE Medical System, Milwau-
kee, Wisconsin) with resolution of .46 ? .46 ? .65 mm3. These
data were used to identify the location of DBS contacts.
DBS Activation Volumes
The DBS contact locations were first identified in native T1
space based on electrode and contact location in a high-
resolution CT image that was transferred to native T1 space using
the Functional Magnetic Resonance Imaging of the Brain (FMRIB)
Linear Image Registration Tool (FLIRT; Oxford University, Oxford,
United Kingdom). The patient-specific DBS activation volumes
were then created by electrical DBS field model based on
identified contact location in native T1 space (see below). For
the group-shared fiber tract map, individual activation volume in
native T1 space was then transferred to Montreal Neurological
Institute (MNI) space to perform probabilistic tractography.
Figure 1. Identification of contact location. (A) Postsurgical computed tomography image superimposed on the presurgical T1 image for one subject.
Contacts are numbered inferior to superior, 1 to 4. (B) Activation volume using contact 1 and typical parameters for a sample subject (6 mA, 130 Hz, 90
microseconds). (C) Probabilistic tractography connections from the calculated activation volume for one subject.
BIOL PSYCHIATRY 2014;76:963–969
P. Riva-Posse et al.
Figure 1 presents an example of the four contacts visible on one
subject’s T1 image with overlapped CT image. There are four
individual contacts on each DBS lead. Each contact is 1.4 mm in
diameter. The contact at the tip of the array is longer than the
other three (3 mm vs. 1.5 mm, respectively), with each separated
by a 1.5 mm nonconductive gap (Libra system, St. Jude Medical,
Calculation of the DBS activation volumes required some
special considerations given the St. Jude Medical DBS system
and the gray/white matter transitions of the SCC region. Therefore,
custom activation volumes were created for this study. The
detailed methodology for DBS activation volume prediction,
described in Chaturvedi et al. (38), relies on artificial neural
networks (ANNs) to characterize the spatial extent of directly
activated axons as a function of the stimulation parameter
settings. These ANNs are trained on the results of thousands of
simulations that directly couple DBS electric field models with
multi-compartment cable models of axons. In addition, the ANNs
used in this study have several unique features: 1) explicit
representation of the St. Jude Medical DBS electrode design;
2) use of current-controlled stimulation; and 3) separate ANNs for
representing DBS in gray matter or white matter. Gray matter was
represented in the DBS electric field model as an isotropic bulk
tissue domain, while white matter was represented as an
anisotropic bulk tissue domain with the axon models oriented
parallel to the orientation of high electrical conductivity (38,39,43).
Activation Volume Tractography
Preprocessing. Tools from the FMRIB Software Library (FSL)
(http://www.fmrib.ox.ac.uk/fsl) were used for all image regis-
tration and tractography processing (44,45). First, T1 and DTI
data were skull stripped to remove nonbrain regions. Diffusion
data underwent eddy current correction and local DTI fitting
using the FMRIB Diffusion Toolbox (33,46). T1 data were
segmented into gray matter/white matter/cerebrospinal fluid
(CSF) using the FMRIB Automated Segmentation Tool, and CSF
mask was later used for stop mask to reduce artificial
connection errors caused by probabilistic tractography. T1
data and CSF mask were normalized to MNI152 template by
combination of linear (FLIRT) and nonlinear transformation
(FMRIB Nonlinear Image Registration Tool [FNIRT]). Computed
tomography and diffusion images were co-registered to T1
image by linear transform and then normalized to MNI152
template by applying nonlinear transformation information
previously calculated by FNIRT in the nonlinear registration
from T1 to the MNI152 template.
Whole-brain activation volume probabilistic tractography was
performed using FMRIB Diffusion Toolbox (33). Right and left
hemisphere tract maps were generated using individually defined
activation volumes for each patient using the specific electrode
contact and stimulation parameters utilized at the 6-month and
2-year evaluation time points. Five thousand random samples per
voxel were sent out from each individual’s bilateral activation
volumes to whole brain. The whole-brain probabilistic tractog-
raphy map was divided by total number of streamlines sent out
to compensate seed size difference and was then binarized
(.001% was used in the present results, but a series of other
thresholds were also tested) (47). Each binary map was added to
create the common population map of the structural connections
for responder and nonresponder groups (e.g., all subjects in each
group share all voxels).
Anatomical Active Stimulation Coordinate
Given past attempts using lower resolution MRI data to
evaluate anatomical variation in active contact locations in
responders and nonresponders to SCC DBS (28,34), a final analysis
of the activation volume location in standard stereotaxic space
using the high-resolution presurgical T1 images was performed.
This analysis would show if structural anatomy alone could
explain response to DBS. The activation volume for each subject
was transferred to MNI space using a combination of linear and
nonlinear transformations (FLIRT and FNIRT, see above); the
center of mass of the activation volume (x-, y-, z-, and
Euclidean-distance from MNI center coordinate) was statistically
Probabilistic Whole-Brain Tractography Analysis
Responder Groups. Three bilateral white matter pathways
were common to all DBS responders: 1) bilateral forceps minor
and medial aspect of the uncinate fasciculus connecting the
activation volume to the medial frontal cortex (BA 10); 2) the
cingulate bundle connecting the activation volume to the rostral
and dorsal anterior and midcingulate cortex; and 3) short
descending midline fibers connecting the activation volume to
subcortical nuclei, including the nucleus accumbens, caudate,
putamen, and anterior thalamus. This particular connectivity
pattern was present in the six subjects who were responders at
6 months; a near identical pattern was seen in the expanded
group of responders at 2 years (n = 12) (Figure 2).
Six-Month Nonresponder Group. This group (n ¼ 10) lacked
the connections mentioned above, with shared tracts failing to
reach the frontal poles and body of the cingulum bundle and
with fewer connections to subcortical areas (Figure 2).
Six-Month Nonresponders Converted to Responders at 2
Years. Of the 10 subjects in the nonresponder group at 6 months,
6 became responders at 2 years, 2 were explanted, and 2
remained nonresponders (Figure 3). All subjects had changes in
their stimulation location or stimulation parameters, thus changing
their individual activation volumes. Confirming the involvement of
bilateral forceps minor, cingulum bundle, and short subcortical
fibers to response, the 6 nonresponders at 6 months who
converted to responders at 2 years gained connectivity to these
regions. None of the 2-year nonresponders (including those
explanted) showed this pattern (Figure S1 in Supplement 1).
Anatomical Stimulation Volume Coordinates
Anatomical location of the active contacts did not discriminate
the subgroups. There were no significant differences between
responders and nonresponders when analyzing either the coor-
dinates of active electrode contacts (activation volumes) or the
Euclidean distance from MNI center (Mann-Whitney U test
uncorrected, left x: p ¼ .32, y: p ¼ .51, z: p ¼ .38, Euclidean
distance: p ¼ .58; right x: p ¼ .36, y: p ¼ .63, z: p ¼ .42, Euclidean
distance: p ¼ .87) (Figure 4, Table 1). In addition, there was no
lateralized difference in the location of the active contacts in the
right and left hemisphere, based on the coordinates of the
This study demonstrates that clinical response to SCC DBS is
mediated by direct impact on a combination of three distinct
P. Riva-Posse et al.
BIOL PSYCHIATRY 2014;76:963–969
fiber bundles passing through the SCC white matter target. These
fiber bundles include: 1) bilateral forceps minor of the anterior
corpus callosum connecting the right and left medial frontal
cortices; 2) the bilateral cingulum bundles connecting ipsilateral
subcallosal cingulate to rostral, dorsal anterior, and midcingulate
cortices; and 3) medial branch of the uncinate fasciculus bilat-
erally connecting subcallosal cingulate and medial frontal cortex
rostrally and subcallosal cingulate to the nucleus accumbens,
anterior thalamus, and other subcortical regions caudally (36).
Given the threshold requiring a given voxel in the tractography
map to be shared by all responders at any time point, the nearly
identical pattern seen in the 6-month (n ¼ 6) and 2-year (n ¼ 12)
responder suggests specificity of the combination of these three
bundles for clinically effective SCC DBS. Notably, the 2-year
nonresponder group consistently failed to include medial frontal
pathways, and if present, they generally did not reach the frontal
pole. Critically, contact changes that resulted in the inclusion of all
three bundles were associated with conversion of nonresponders
to responders (Figure 3). However, confirmation of these findings
will require prospective testing.
These results also reconcile the failure of previous simple
measurements of the anatomical location of the active contacts
to discriminate responders and nonresponders (28), a finding also
confirmed in this cohort (Figure 4, Table 1). The comparability in
the structural location of the active electrode contacts across
groups confirms that gray matter variability is not the source of
variance; rather, it is the variability in the hub location where
these three fiber bundles intersect. The similarity in the spatial
location of the active contacts in responders and nonresponders
demonstrates that while the surgeon may implant consistently
across subjects, the proposed anatomical location does not
necessarily coincide with the hub location of the three critical
white matter bundles for each individual. Overall, the use of
patient-specific activation volume tractography modeling pro-
vides a new strategy for optimizing surgical targeting and
stimulation parameter selection for SCC DBS, as well as founda-
tion for evaluating mechanisms mediating DBS effects.
An acknowledged limitation of this study is that the compar-
ison used a qualitative assessment of individual, binarized tract
maps. To date, there is no gold standard methodology to reliably
quantify the strength of connectivity across subjects, an approach
that, if available, would allow a more nuanced assessment of the
nature of the nonresponders. Additionally, alternative diffusion
methods (48) may allow detection of more subtle, but equally
critical, pathways mediating response to SCC DBS. For example,
pathways to the brainstem or medial branches of the uncinate
fasciculus, which sits lateral to forceps minor at this axial plane,
may also be important to the clinical response (36). While
Figure 3. Change in tract maps in individuals that were nonresponders at
6 months and who converted to responders by 2 years (n ¼ 6). Green: 6-
month shared tract map. Blue: 2-year shared tract map. Structural
connection differences are seen in both forceps minor and descending
subcortical connections. ACC, anterior cingulate cortex; L, left; mF, medial
frontal; P, putamen; R, right; Th, thalamus; vSt, ventral striatum.
Figure 2. Whole-brain probabilistic tractography of shared fiber tract maps of subcallosal cingulate deep brain stimulation target. Left: 6-month
responders (resp.) (n ¼ 6); middle: 6-month nonresponders (non-resp.) (n ¼ 10); right: 2-year responders (n ¼ 12). Responders (6-month and 2-year): blue.
Nonresponders (6-month): green. Based on individual activation volume tract maps, all 6-month responders share bilateral pathways via forceps minor
and uncinate fasciculus to medial frontal cortex (Brodmann area 10); via the cingulum bundle to subgenual, rostral, and dorsal anterior and midcingulate;
and descending subcortical fibers to ventral striatum (nucleus accumbens, ventral pallidum), putamen, hypothalamus, and anterior thalamus. Six-month
nonresponders, while similar in some regions, lack connections to both medial frontal and subcortical regions seen in the responder group. All 2-year
responders show a pattern that is nearly identical to the 6-month responder tract map. ACC, anterior cingulate cortex; L, left; mF, medial frontal; P,
putamen; R, right; Th, thalamus; vSt, ventral striatum.
BIOL PSYCHIATRY 2014;76:963–969
P. Riva-Posse et al.
identifying the necessary tracts, these methods do not define the
sufficient tracts for response to SCC DBS. Resolution of the
diffusion data utilized here does not allow such a level of detail.
That said, the method used for this analysis has proven adequate
to identify a consistent and specific pattern of tracts and may
provide a starting point for refining surgical planning for SCC DBS
Based on the findings described, it could be postulated that
targeting bilateral SCC-BA 10 (medial frontal cortex) connections
alone could be sufficient to generate the optimal antidepressant
effect, as these tracts were most consistently missed in the 6-
month nonresponders. We have no example of any responder at
either time point where medial frontal tracts were impacted in
the absence of one or both of the other two bundles; so, this
hypothesis cannot be tested with the current dataset. The
consistent inclusion of the cingulum in both 6-month responders
and nonresponders further suggests that this bundle is also
necessary but definitely not sufficient for response (see pattern in
the two long-term nonresponders; Figure S1 in Supplement 1).
Future studies using electrodes with the capability for selective
steering to each of these individual bundles would allow direct
testing of the necessary and sufficient hypothesis (49). Such
technological advances would also allow disambiguation of
stimulation of the direct SCC-BA 10 connections from transhemi-
spheric connections through forceps minor and even passing
fibers from medial frontal (BA 10) to subcortical regions. Given the
available data, the most conservative conclusion is that the
combination of all three pathways is required for reliable clinical
response using these methods and devices.
The primary finding from this study is that the antidepressant
effect of chronic high-frequency DBS likely involves modulation of
a distributed, multi-region network in addition to local changes in
SCC gray matter. Based on the available evidence, the mecha-
nisms of DBS most likely involve a combination of local effects on
neurons and glia that may be directly stimulated by the applied
electric field, as well as orthodromic and antidromic effects on
fibers of passage (50,51). Full characterization of the fiber and cell
types, as well as chronic electrophysiological recordings in multi-
ple brain regions, will be required to fully model DBS mechanisms
of action, especially considering the complex transsynaptic effects
that result from the stimulation.
From a practical point of view, this network analysis provides a
potential new algorithm for target selection for SCC DBS. Instead of
a purely anatomical or coordinate-based approach targeting a single
region, these findings support a target selection strategy based on
network connectivity, i.e., choosing a target to ensure a stimulation
field that impacts the critical local regions and the distributed white
matter tracts linking the target to other key regions within the
network (Figure 5). Prospective testing of presurgical mapping of an
individual patient’s network structure using probabilistic tractogra-
phy with lead placement and contact selection targeting the SCC
hub will be necessary to test this hypothesis.
Management of nonresponse to SCC DBS in this context is an
important next consideration. While identification of a robust
Figure 4. Anatomical locations in Montreal Neurological Institute space of the deep brain stimulation activation volumes for responders (blue) and
nonresponders (red) at 6 months. No statistical difference in anatomical location between the responder and nonresponder groups was identified. L, left;
Table 1. Coordinates of Activation Volumes in Montreal Neurological Institute Space
Left Hemisphere Right Hemisphere
xyz EDxyz ED
Responder (n ¼ 6)
Nonresponder (n ¼ 10)
ED, Euclidean distance from Montreal Neurological Institute center coordinate; Stat., statistical analysis (Mann-Whitney U test); p, p value.
P. Riva-Posse et al.
BIOL PSYCHIATRY 2014;76:963–969
responder pattern was the focus of the analyses in this study,
contributors to nonresponse can include factors beyond ideal
electrode placement: unrecognized psychiatric comorbid condi-
tions that affect rating scales, personality characteristics, and
psychological or environmental factors that become evident after
the implantation. As such, the lack of a full DBS response may be
independent of appropriate modulation of the requisite neural
pathways. Therefore, we propose that contacts should not be
changed prematurely if the individual activation volume con-
nectivity map shows that the tracts match the desired response
fingerprint. This also will require prospective testing and reassess-
ment with a larger patient cohort.
In conclusion, the tractography maps of unambiguous
response to chronic SCC DBS define a fiber bundle template
involving bilateral forceps minor, cingulum, and medial frontal-
striatal/subcortical fibers. These pathways can be characterized in
individual patients before surgery using DBS models coupled with
probabilistic tractography. Such an approach provides a new
strategy for optimizing electrode implantation and stimulation
parameter selection for SCC DBS.
We thank J. Luis Luján and Angela Noecker for assistance with
the deep brain stimulation activation volume calculations and David
Gutman and Mary Kelley for discussions regarding tractography
Paul E. Holtzheimer has received consulting fees from St. Jude
Medical Neuromodulation and research funding from Cervel Neuro-
tech and Otsuka. Cameron C. McIntyre received consulting fees from
Boston Scientific Neuromodulation; authored intellectual property
now owned by Boston Scientific Neuromodulation; has equity
interest in Surgical Information Sciences Inc., Autonomic Technolo-
gies Inc., and Neuros Medical Inc.; and received funding from
National Institutes of Health R01 NS059736. Robert E. Gross has
received consulting fees from Boston Scientific Neuromodulation, St.
Jude Medical Neuromodulation, and Medtronic/Lilly. Helen S. Mayberg
has received consulting fees from St. Jude Medical Neuromodulation
and Eli Lilly; reports intellectual property from St. Jude Medical
Neuromodulation; and has received funding from Dana Foundation,
Woodruff Fund, Stanley Medical Research Institute, and the Hope for
Depression Foundation. All other authors report no biomedical
financial interests or potential conflicts of interest.
Supplementary material cited in this article is available online at
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