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Figure 1.
Example of Deep Brain Stimulation Lead Location and Patient-Specific Volume of Tissue Activated (VTA) Used for Tractography Maps
Example of Deep Brain Stimulation Lead Location and Patient-Specific Volume of Tissue Activated (VTA) Used for Tractography Maps

The VTA seed (red ball) is shown in situ on a registered postoperative computed tomographic image. The anatomical location of the VTA is also seen on the superimposed high-resolution, T1-weighted magnetic resonance image. The size of the VTA seed is generated using the patient-specific stimulation settings shown (frequency, 130 Hz; pulse width, 90 microseconds; and stimulation amplitude, 6 mA). Contact numbers are designated C1 through C4.

Figure 2.
Whole-Brain Probabilistic Tractography of a Shared Fiber Tract Map of Contacts With Best Intraoperative Responses
Whole-Brain Probabilistic Tractography of a Shared Fiber Tract Map of Contacts With Best Intraoperative Responses

The following 3 common white matter bundles were affected by stimulation of the 9 left-sided contacts to mediate a best response: the uncinate fasciculus (UF) connecting to the ipsilateral ventromedial frontal cortex (A and C), the forceps minor (FM) connecting to the bilateral ventromedial frontal cortices (C and D), and the left cingulum bundle (CB) connecting to the ipsilateral anterior cingulate cortex (A, B, and D). Best response is described in the Intraoperative Behavior Response Assessments subsection of the Methods section. Blue labels indicate white matter bundles; black labels, cortical regions. ACC indicates anterior cingulate cortex; L, left side; MCC, midcingulate cortex; R, right side; SCC, subcallosal cingulate cortex; and vmF, ventromedial frontal cortex.

Figure 3.
Whole-Brain Probabilistic Tractography of a Shared Fiber Tract Map of Contacts With Salient Intraoperative Responses
Whole-Brain Probabilistic Tractography of a Shared Fiber Tract Map of Contacts With Salient Intraoperative Responses

The common white matter bundle consists of the cingulum bundle (CB) connecting to ipsilateral anterior cingulate cortex. The images show the left (A and B) and right (C and D) hemisphere contacts with salient intraoperative response. Salient response is described in the Intraoperative Behavior Response Assessments subsection of the Methods section. Red labels indicate white matter bundles; black labels, cortical regions. ACC indicates anterior cingulate cortex; L, left side; R, right side; and SCC, subcallosal cingulate cortex.

Table 1.  
Demographic and Clinical Characteristics of Patients With Treatment-Resistant Depression
Demographic and Clinical Characteristics of Patients With Treatment-Resistant Depression
Table 2.  
Narrative Descriptions Recorded by Participants
Narrative Descriptions Recorded by Participants
1.
Rezai  AR, Kopell  BH, Gross  RE,  et al.  Deep brain stimulation for Parkinson’s disease: surgical issues. Mov Disord. 2006;21(suppl 14):S197-S218.
PubMedArticle
2.
Bishop  MP, Elder  ST, Heath  RG.  Intracranial self-stimulation in man. Science. 1963;140(3565):394-396.
PubMedArticle
3.
Nuttin  BJ, Gabriëls  LA, Cosyns  PR,  et al.  Long-term electrical capsular stimulation in patients with obsessive-compulsive disorder. Neurosurgery. 2003;52(6):1263-1272.
PubMedArticle
4.
Okun  MS, Bowers  D, Springer  U,  et al.  What’s in a “smile?” Intra-operative observations of contralateral smiles induced by deep brain stimulation. Neurocase. 2004;10(4):271-279.
PubMedArticle
5.
Krack  P, Vercueil  L.  Review of the functional surgical treatment of dystonia. Eur J Neurol. 2001;8(5):389-399.
PubMedArticle
6.
Bejjani  BP, Damier  P, Arnulf  I,  et al.  Transient acute depression induced by high-frequency deep-brain stimulation. N Engl J Med. 1999;340(19):1476-1480.
PubMedArticle
7.
Bejjani  BP, Houeto  JL, Hariz  M,  et al.  Aggressive behavior induced by intraoperative stimulation in the triangle of Sano. Neurology. 2002;59(9):1425-1427.
PubMedArticle
8.
Rasche  D, Rinaldi  PC, Young  RF, Tronnier  VM.  Deep brain stimulation for the treatment of various chronic pain syndromes. Neurosurg Focus. 2006;21(6):1-8.
PubMedArticle
9.
Shapira  NA, Okun  MS, Wint  D,  et al.  Panic and fear induced by deep brain stimulation. J Neurol Neurosurg Psychiatry. 2006;77(3):410-412.
PubMedArticle
10.
Hamani  C, McAndrews  MP, Cohn  M,  et al.  Memory enhancement induced by hypothalamic/fornix deep brain stimulation. Ann Neurol. 2008;63(1):119-123.
PubMedArticle
11.
Mayberg  HS, Lozano  AM, Voon  V,  et al.  Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45(5):651-660.
PubMedArticle
12.
Lozano  AM, Mayberg  HS, Giacobbe  P, Hamani  C, Craddock  RC, Kennedy  SH.  Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2008;64(6):461-467.
PubMedArticle
13.
Lozano  AM, Giacobbe  P, Hamani  C,  et al.  A multicenter pilot study of subcallosal cingulate area deep brain stimulation for treatment-resistant depression. J Neurosurg. 2012;116(2):315-322.
PubMedArticle
14.
Holtzheimer  PE, Kelley  ME, Gross  RE,  et al.  Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression. Arch Gen Psychiatry. 2012;69(2):150-158.
PubMedArticle
15.
Puigdemont  D, Pérez-Egea  R, Portella  MJ,  et al.  Deep brain stimulation of the subcallosal cingulate gyrus: further evidence in treatment-resistant major depression. Int J Neuropsychopharmacol. 2012;15(1):121-133.
PubMedArticle
16.
Kennedy  SH, Giacobbe  P, Rizvi  SJ,  et al.  Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years. Am J Psychiatry. 2011;168(5):502-510.
PubMedArticle
17.
Merkl  A, Schneider  GH, Schönecker  T,  et al.  Antidepressant effects after short-term and chronic stimulation of the subgenual cingulate gyrus in treatment-resistant depression. Exp Neurol. 2013;249:160-168.
PubMedArticle
18.
Ramasubbu  R, Anderson  S, Haffenden  A, Chavda  S, Kiss  ZH.  Double-blind optimization of subcallosal cingulate deep brain stimulation for treatment-resistant depression: a pilot study. J Psychiatry Neurosci. 2013;38(5):325-332.
PubMedArticle
19.
Guinjoan  SM, Mayberg  HS, Costanzo  EY,  et al.  Asymmetrical contribution of brain structures to treatment-resistant depression as illustrated by effects of right subgenual cingulum stimulation. J Neuropsychiatry Clin Neurosci. 2010;22(3):265-277.
PubMedArticle
20.
Schlaepfer  TE, Cohen  MX, Frick  C,  et al.  Deep brain stimulation to reward circuitry alleviates anhedonia in refractory major depression. Neuropsychopharmacology. 2008;33(2):368-377.
PubMedArticle
21.
Schlaepfer  TE, Bewernick  BH, Kayser  S, Mädler  B, Coenen  VA.  Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73(12):1204-1212.
PubMedArticle
22.
Bewernick  BH, Hurlemann  R, Matusch  A,  et al.  Nucleus accumbens deep brain stimulation decreases ratings of depression and anxiety in treatment-resistant depression. Biol Psychiatry. 2010;67(2):110-116.
PubMedArticle
23.
Bewernick  BH, Kayser  S, Sturm  V, Schlaepfer  TE.  Long-term effects of nucleus accumbens deep brain stimulation in treatment-resistant depression: evidence for sustained efficacy. Neuropsychopharmacology. 2012;37(9):1975-1985.
PubMedArticle
24.
Stefurak  T, Mikulis  D, Mayberg  H,  et al.  Deep brain stimulation for Parkinson’s disease dissociates mood and motor circuits: a functional MRI case study. Mov Disord. 2003;18(12):1508-1516.
PubMedArticle
25.
Riva-Posse  P.  Identification of critical white matter pathways involved in efficacious subcallosal cingulate deep brain stimulation: implications for prospective target selection [abstract]. Biol Psychiatry. 2014;7S(9):S15.
26.
ClinicalTrials.gov. Deep Brain Stimulation for Treatment Resistant Depression. NCT00367003. https://clinicaltrials.gov/ct2/show/NCT00367003. Accessed May 1, 2015.
27.
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMedArticle
28.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text revision. Washington, DC: American Psychiatric Association; 2000.
29.
Riva-Posse  P, Choi  KS, Holtzheimer  PE,  et al.  Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2014;76(12):963-969.
PubMedArticle
30.
Griswold  MA, Jakob  PM, Heidemann  RM,  et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47(6):1202-1210.
PubMedArticle
31.
Smith  SM, Jenkinson  M, Woolrich  MW,  et al.  Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23(suppl 1):S208-S219.
PubMedArticle
32.
Jenkinson  M, Beckmann  CF, Behrens  TE, Woolrich  MW, Smith  SM.  FSL. Neuroimage. 2012;62(2):782-790.
PubMedArticle
33.
Smith  SM.  Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143-155.
PubMedArticle
34.
Behrens  TE, Woolrich  MW, Jenkinson  M,  et al.  Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50(5):1077-1088.
PubMedArticle
35.
Greve  DN, Fischl  B.  Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48(1):63-72.
PubMedArticle
36.
Chaturvedi  A, Luján  JL, McIntyre  CC.  Artificial neural network based characterization of the volume of tissue activated during deep brain stimulation. J Neural Eng. 2013;10(5):056023. doi:10.1088/1741-2560/10/5/056023.
PubMedArticle
37.
Lujan  JL, Chaturvedi  A, Malone  DA, Rezai  AR, Machado  AG, McIntyre  CC.  Axonal pathways linked to therapeutic and nontherapeutic outcomes during psychiatric deep brain stimulation. Hum Brain Mapp. 2012;33(4):958-968.
PubMedArticle
38.
McIntyre  CC, Miocinovic  S, Butson  CR.  Computational analysis of deep brain stimulation. Expert Rev Med Devices. 2007;4(5):615-622.
PubMedArticle
39.
Hagmann  P, Cammoun  L, Gigandet  X,  et al.  Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6(7):e159. doi:10.1371/journal.pbio.0060159.
PubMedArticle
40.
Li  L, Rilling  JK, Preuss  TM, Glasser  MF, Hu  X.  The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography. Hum Brain Mapp. 2012;33(8):1894-1913.
PubMedArticle
41.
Wakana  S, Caprihan  A, Panzenboeck  MM,  et al.  Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage. 2007;36(3):630-644.
PubMedArticle
42.
Hua  K, Zhang  J, Wakana  S,  et al.  Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage. 2008;39(1):336-347.
PubMedArticle
43.
Wiens  S.  Interoception in emotional experience. Curr Opin Neurol. 2005;18(4):442-447.
PubMedArticle
44.
Craig  AD.  How do you feel? interoception: the sense of the physiological condition of the body. Nat Rev Neurosci. 2002;3(8):655-666.
PubMedArticle
45.
Craig  AD.  Interoception: the sense of the physiological condition of the body. Curr Opin Neurobiol. 2003;13(4):500-505.
PubMedArticle
46.
Critchley  HD, Elliott  R, Mathias  CJ, Dolan  RJ.  Neural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J Neurosci. 2000;20(8):3033-3040.
PubMed
47.
Critchley  HD, Mathias  CJ, Josephs  O,  et al.  Human cingulate cortex and autonomic control: converging neuroimaging and clinical evidence. Brain. 2003;126(pt 10):2139-2152.
PubMedArticle
48.
Critchley  HD, Wiens  S, Rotshtein  P, Ohman  A, Dolan  RJ.  Neural systems supporting interoceptive awareness. Nat Neurosci. 2004;7(2):189-195.
PubMedArticle
49.
Critchley  HD.  Neural mechanisms of autonomic, affective, and cognitive integration. J Comp Neurol. 2005;493(1):154-166.
PubMedArticle
50.
Critchley  HD, Eccles  J, Garfinkel  SN.  Interaction between cognition, emotion, and the autonomic nervous system. Handb Clin Neurol. 2013;117:59-77.
PubMed
51.
Critchley  HD, Harrison  NA.  Visceral influences on brain and behavior. Neuron. 2013;77(4):624-638.
PubMedArticle
52.
Fredrickson  BL.  What good are positive emotions? Rev Gen Psychol. 1998;2(3):300-319.
PubMedArticle
53.
Pereira  EA, Wang  S, Paterson  DJ, Stein  JF, Aziz  TZ, Green  AL.  Sustained reduction of hypertension by deep brain stimulation. J Clin Neurosci. 2010;17(1):124-127.
PubMedArticle
54.
Pollatos  O, Kirsch  W, Schandry  R.  Brain structures involved in interoceptive awareness and cardioafferent signal processing: a dipole source localization study. Hum Brain Mapp. 2005;26(1):54-64.
PubMedArticle
55.
Barrett  LF, Simmons  WK.  Interoceptive predictions in the brain. Nat Rev Neurosci. 2015;16(7):419-429.
PubMedArticle
56.
Lane  RD, Fink  GR, Chau  PM, Dolan  RJ.  Neural activation during selective attention to subjective emotional responses. Neuroreport. 1997;8(18):3969-3972.
PubMedArticle
57.
Vogt  BA, Pandya  DN.  Cingulate cortex of the rhesus monkey, II: cortical afferents. J Comp Neurol. 1987;262(2):271-289.
PubMedArticle
58.
Vogt  BA, Sikes  RW.  The medial pain system, cingulate cortex, and parallel processing of nociceptive information. Prog Brain Res. 2000;122:223-235.
PubMed
59.
Vogt  BA.  Pain and emotion interactions in subregions of the cingulate gyrus. Nat Rev Neurosci. 2005;6(7):533-544.
PubMedArticle
60.
Vogt  BA.  Submodalities of emotion in the context of cingulate subregions. Cortex. 2014;59:197-202.
PubMedArticle
61.
Wager  TD, van Ast  VA, Hughes  BL, Davidson  ML, Lindquist  MA, Ochsner  KN.  Brain mediators of cardiovascular responses to social threat, part II: prefrontal-subcortical pathways and relationship with anxiety. Neuroimage. 2009;47(3):836-851.
PubMedArticle
62.
Mayer  EA.  Gut feelings: the emerging biology of gut-brain communication. Nat Rev Neurosci. 2011;12(8):453-466.
PubMedArticle
63.
Mayer  EA, Gupta  A, Kilpatrick  LA, Hong  JY.  Imaging brain mechanisms in chronic visceral pain. Pain. 2015;156(suppl 1):S50-S63.
PubMedArticle
64.
Greicius  M.  Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol. 2008;21(4):424-430.
PubMedArticle
65.
Seeley  WW, Menon  V, Schatzberg  AF,  et al.  Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27(9):2349-2356.
PubMedArticle
66.
Sridharan  D, Levitin  DJ, Menon  V.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci U S A. 2008;105(34):12569-12574.
PubMedArticle
67.
Mayberg  HS.  Targeted electrode-based modulation of neural circuits for depression. J Clin Invest. 2009;119(4):717-725.
PubMedArticle
68.
Mayberg  HS, Liotti  M, Brannan  SK,  et al.  Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am J Psychiatry. 1999;156(5):675-682.
PubMed
69.
Liotti  M, Mayberg  HS, Brannan  SK, McGinnis  S, Jerabek  P, Fox  PT.  Differential limbic-cortical correlates of sadness and anxiety in healthy subjects: implications for affective disorders. Biol Psychiatry. 2000;48(1):30-42.
PubMedArticle
70.
Jones  CL, Minati  L, Nagai  Y,  et al.  Neuroanatomical substrates for the volitional regulation of heart rate. Front Psychol. 2015;6:300. doi:10.3389/fpsyg.2015.00300.
PubMed
71.
Damasio  AR.  The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philos Trans R Soc Lond B Biol Sci. 1996;351(1346):1413-1420.
PubMedArticle
72.
Amodio  DM, Frith  CD.  Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci. 2006;7(4):268-277.
PubMedArticle
73.
Fossati  P.  Neural correlates of emotion processing: from emotional to social brain. Eur Neuropsychopharmacol. 2012;22(suppl 3):S487-S491.
PubMedArticle
74.
Smith  R, Braden  BB, Chen  K, Ponce  FA, Lane  RD, Baxter  LC.  The neural basis of attaining conscious awareness of sad mood [published online September 19, 2014]. Brain Imaging Behav. doi:10.1007/s11682-014-9318-8.
PubMed
75.
Simpson  JR  Jr, Snyder  AZ, Gusnard  DA, Raichle  ME.  Emotion-induced changes in human medial prefrontal cortex, I: during cognitive task performance. Proc Natl Acad Sci U S A. 2001;98(2):683-687.
PubMedArticle
76.
Reiman  EM, Lane  RD, Ahern  GL,  et al.  Neuroanatomical correlates of externally and internally generated human emotion. Am J Psychiatry. 1997;154(7):918-925.
PubMedArticle
77.
Nyberg  L, Kim  AS, Habib  R, Levine  B, Tulving  E.  Consciousness of subjective time in the brain. Proc Natl Acad Sci U S A. 2010;107(51):22356-22359.
PubMedArticle
78.
Addis  DR, Pan  L, Vu  MA, Laiser  N, Schacter  DL.  Constructive episodic simulation of the future and the past: distinct subsystems of a core brain network mediate imagining and remembering. Neuropsychologia. 2009;47(11):2222-2238.
PubMedArticle
79.
Koechlin  E, Hyafil  A.  Anterior prefrontal function and the limits of human decision-making. Science. 2007;318(5850):594-598.
PubMedArticle
80.
Liotti  M, Mayberg  HS.  The role of functional neuroimaging in the neuropsychology of depression. J Clin Exp Neuropsychol. 2001;23(1):121-136.
PubMedArticle
81.
Krüger  S, Seminowicz  D, Goldapple  K, Kennedy  SH, Mayberg  HS.  State and trait influences on mood regulation in bipolar disorder: blood flow differences with an acute mood challenge. Biol Psychiatry. 2003;54(11):1274-1283.
PubMedArticle
82.
Greicius  MD, Flores  BH, Menon  V,  et al.  Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007;62(5):429-437.
PubMedArticle
Original Investigation
Circuits and Circuit Disorders
November 2015

Mapping the “Depression Switch” During Intraoperative Testing of Subcallosal Cingulate Deep Brain Stimulation

Author Affiliations
  • 1Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
  • 2Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia
  • 3Department of Neurology, Emory University School of Medicine, Atlanta, Georgia
JAMA Neurol. 2015;72(11):1252-1260. doi:10.1001/jamaneurol.2015.2564
Abstract

Importance  The clinical utility of monitoring behavioral changes during intraoperative testing of subcallosal cingulate deep brain stimulation is unknown.

Objective  To characterize the structural connectivity correlates of deep brain stimulation–evoked behavioral effects using probabilistic tractography in depression.

Design, Setting, and Participants  Categorization of acute behavioral effects was conducted in 9 adults undergoing deep brain stimulation implantation surgery for chronic treatment-resistant depression in a randomized and blinded testing session at Emory University. Patients were studied from September 1, 2011, through June 30, 2013. Post hoc analyses of the structural tractography patterns mediating distinct categories of evoked behavioral effects were defined, including the best response overall. Data analyses were performed from May 1 through July 1, 2015.

Main Outcomes and Measures  Categorization of stimulation-induced transient behavioral effects and delineation of the shared white matter tracts mediating response subtypes.

Results  Among the 9 patients, 72 active and 36 sham trials were recorded. The following stereotypical behavior patterns were identified: changes in interoceptive (noted changes in body state in 30 of 72 active and 4 of 36 sham trials) and in exteroceptive (shift in attention from patient to others in 9 of 72 active and 0 sham trials) awareness. The best response was a combination of exteroceptive and interoceptive changes at a single left contact for all 9 patients. Structural connectivity showed that the best response contacts had a pattern of connections to the bilateral ventromedial frontal cortex (via forceps minor and left uncinate fasciculus) and to the cingulate cortex (via left cingulum bundle), whereas behaviorally salient but nonbest contacts had only cingulate involvement. The involvement of the 3 white matter bundles during stimulation of the best contacts suggests a mechanism for the observed transient “depression switch.”

Conclusions and Relevance  This analysis of transient behavior changes during intraoperative deep brain stimulation of the subcallosal cingulate and the subsequent identification of unique connectivity patterns may provide a biomarker of a rapid-onset depression switch to guide surgical implantation and to refine and optimize algorithms for the selection of contacts in long-term stimulation for treatment-resistant depression.

Introduction

Intraoperative testing during deep brain stimulation (DBS) implantation surgery offers a unique window on localized brain function beyond its critical role in determining optimal targeting and stimulation settings. Intraoperative effects with transient stimulation have a well-recognized role during surgery for movement disorders, when such testing commonly is used to optimize clinically desirable changes in tremor, rigidity, or bradykinesia and to avoid adverse effects, such as diplopia and paresthesias.1 Although this strategy has been used most systematically for contemporary DBS techniques, behavioral and emotional responses to acute stimulation were first described during the early studies of intracranial self-stimulation conducted in the 1960s.2 With the development and testing of new clinical indications for DBS, these nonmotor acute behavioral phenomena have been increasingly observed with stimulation at various brain targets across multiple neuropsychiatric disorders, such as euphoria, involuntary smiles, and laughter within the nucleus accumbens35; despair,6 apathy, hypomania, and aggressive behavior7 in and around the subthalamic nucleus; panic8,9 in the posterior hypothalamus; and episodic memory recollections in the fornix.10

Deep brain stimulation of the subcallosal cingulate (SCC) white matter is an emerging strategy for treatment-resistant depression.1119 In addition to growing evidence of the efficacy of long-term stimulation, transient changes in mood, attention, and social connectedness have been reported during intraoperative testing. These observations are not exclusive to the SCC target; such effects have also been described with stimulation in other putative depression targets, including the medial forebrain bundle and nucleus accumbens.2023

To date, the experience of patients during SCC testing has been notable for certain stereotypical features. Patients commonly describe “a sudden calmness or lightness,” disappearance of a “void,” a sense of “connectedness,” increased interest, and even sudden brightening of the room.11 These responses occur with stimulation in either hemisphere, are specific to contacts and the delivered current dose, and most important, occur with stimulation at some but not all contacts along the DBS lead. These behavioral effects quickly and consistently fade with discontinuation of the stimulation. When present, the effects are unequivocal and reproducible for each patient; however, owing to the idiosyncratic nature of self-reports, quantification has yet to be standardized. These acute SCC stimulation effects are rarely duplicated outside the operating room and, if present, are considerably more subtle. As with acute stimulation effects seen with other DBS targets, whether these SCC stimulation effects reflect changes in local SCC or more widespread network function remains unclear.6,24 Also unknown is whether these effects predict a sustained antidepressant response to long-term DBS.

Structural connectivity analyses using diffusion magnetic resonance imaging and patient-specific tractography maps to define the extent of the white matter network affected by long-term SCC DBS have demonstrated that clinically effective SCC stimulation requires inclusion of the following 4 white matter bundles in each hemisphere: the forceps minor of the anterior corpus callosum connecting the 2 ventromedial frontal cortices, the cingulum bundle connecting the ipsilateral SCC to the rostral and dorsal anterior cingulate cortices, the uncinate fasciculus connecting the SCC to the ventromedial frontal cortex, and the frontal-subcortical fibers connecting the SCC to the basal ganglia, thalamus, and brainstem.24 Identification of these white matter bundles in advance of DBS lead implantation is now being tested prospectively to determine whether targeting and stimulation at this white matter hub improves clinical outcomes compared with standard methods.25 With this foundation, we examined similarly derived structural connectivity patterns of SCC stimulation mediating acute intraoperative behavior responses with the goal of identifying an intraoperative biomarker of optimal SCC lead placement.

Methods
Participants

From September 1, 2011, through June 30, 2013, 9 consecutive patients with severe, chronic, treatment-resistant major depressive disorder were enrolled in a research protocol at Emory University to test the safety and efficacy of SCC DBS.26 The protocol was approved by the institutional review board at Emory University and by the US Food and Drug Administration under Investigational Device Exemption G060028 sponsored by one of us (H.S.M.) and is monitored by the Data and Safety Monitoring Board of the Department of Psychiatry and Behavioral Sciences, Emory University. All participants signed an informed consent to participate; all patients continue in the ongoing longitudinal study. The last follow-up for data presented herein is December 2013.

The study inclusion and exclusion criteria were identical to those previously published by Holtzheimer et al.14 In brief, patients were required to have been depressed for at least 12 months of the current depressive episode, with a minimum Hamilton Depression Rating Scale severity score of 20 (range, 0-50, with higher scores indicating increased severity)27; to have used at least 4 antidepressant treatments (including electroconvulsive therapy) without improvement; to have no significant psychiatric or medical comorbidities; and to be functionally disabled with a Global Assessment of Function score of less than 50 (range, 1-100, with higher scores indicating better function)28 (Table 1).

DBS Implantation Surgery

The surgical procedure for DBS lead and pulse generator implantation followed published methods.11,12,14 We extended a previously described frame-based, stereotaxic, anatomical localization protocol whereby the gray-white matter junction at the middle SCC region is identified on high-resolution T1-weighted magnetic resonance structural images.11,14 Target selection for this patient cohort also used an individualized preoperative deterministic tractography map to identify the location of the intersection of 4 white matter bundles recently shown to be necessary for effective antidepressant effects.29 The combined tractography and anatomical images guided standard localization of the DBS lead tip and trajectory using a surgical planning workstation (Stealth Station; Medtronic, Inc). Bilateral DBS leads (Libra system; St Jude Medical), each with 4 contacts (1.5-mm intercontact spacing), were placed and secured. Testing was then initiated with the patient awake and alert.

Intraoperative Behavior Response Assessments

The stimulation protocol consisted of 12 trials (1 at each of the 8 available contacts [4 left and 4 right sides] and 4 sham trials) with 3 minutes of stimulation on followed by 3 minutes of stimulation off using standard settings for long-term SCC stimulation (monopolar stimulation; frequency, 130 Hz; pulse width, 90 microseconds; and current, 6 mA). The order of active or sham trials was randomized, with the patient and the clinician rater blinded to the condition. The design of 3 minutes on and 3 minutes off maximized the likelihood of adequate time to capture acute (within the first minute) and sustained (maintained throughout the stimulation epoch) behavioral changes and to ensure that a new baseline was reestablished before the next trial. The procedure was videotaped to review, verify, and catalog patient comments outside the operating room. Patients were instructed to monitor themselves during each trial for any changes in sensation, feelings, mood, or thought and to describe any changes when queried. Self-reports were recorded at fixed points within each trial (1 minute after initiation of stimulation and again 1 minute after discontinuation of stimulation). At the conclusion of the protocol, responses for each of the 12 trials were reviewed and designated as present or absent. In trials with the response present, features of the response were further classified into 2 categorical types based on the salience, quality, and magnitude of the self-report. Response type 1 was defined by the presence solely of a perceived change in body state (ie, interoceptive awareness) or specific physical sensations. Response type 2 was characterized by a more complex set of evoked thoughts and feelings commonly indicated by a shift in attention from self to others (ie, exteroceptive awareness). The numbers of type 1 or type 2 responses were summed for each hemisphere, and a “best” contact was then selected reflecting the most robust combination of interoceptive awareness (type 1) and complex behavioral phenomena (type 2) overall. Once rankings were completed, the trials were unblinded and the contacts (left side, 1-4; right side, 1-4) were matched to the trial and response types. These classifications were subsequently used for structural connectivity analyses to define white matter tracts mediating the best vs any salient responses (type 1 or type 2 alone) and differences between the right and left hemisphere stimulation effects.

Imaging Acquisition Protocol

One week before surgery, magnetic resonance imaging was performed (3.0-T Tim-Trio scanner; Siemens Medical Solutions) at the Biomedical Imaging Technology Center of Emory University. A high-resolution, T1-weighted structural image was collected for each patient using a 3-dimensional, magnetization-prepared, rapid gradient-echo sequence with the following settings: repetition time, 2600 milliseconds; inversion time, 900 milliseconds; echo time, 3.02 milliseconds; flip angle, 8°; voxel resolution, 1 × 1 × 1 mm; number of sections, 176; and matrix, 224 × 256. Sixty noncollinear diffusion-weighted images were obtained using single-shot, spin-echo echo-planar imaging with the following settings: generalized autocalibrating parallel acquisition30 reduction factor, 2; field of view, 256 × 256; b value, 1000 s/mm2; voxel resolution, 2 × 2 × 2 mm; number of sections, 64; matrix, 128 × 128; repetition time, 11 300 milliseconds; echo time, 104 milliseconds; 4 nondiffusion-weighted images (b value, 0); and 2 different phase-encoding directions (anterior to posterior and posterior to anterior) to compensate for susceptibility-induced distortion. Three weeks after surgery, a high-resolution computed tomographic image was collected (LightSpeed 16; GE Medical System) (voxel size, 0.46 × 0.46 × 0.65 mm3) to identify a lead and contact location.

Image Processing

All image processing and analyses were performed using tools from the FMRIB Software Library (FSL) (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/).31,32 First, T1-weighted images were normalized into a Montreal Neurological Institute (MNI)–152 template using a combination of linear and nonlinear registration methods (FLIRT and FNIRT, respectively, in FSL). Second, diffusion tensor imaging data underwent simultaneous Eddy current and movement correction (FSL), skull stripping (Brain Extraction Tool in FSL),33 and local tensor fitting (FMRIB Diffusion Toolbox in FSL).34 Then, diffusion tensor imaging data were coregistered to T1-weighted images using the Boundary-Based Registration35 method and normalized to the MNI-152 template using a previously calculated, nonlinear warping field from the T1-weighted normalization step.

Lead Localization and Modeling of Volume of Tissue Activated

The location of each of the 8 contacts was identified using a postoperative computed tomographic image for each patient (Figure 1). First, the computed tomographic image was transferred to T1 space by linear transformation, and each contact location was identified in T1 native space. Second, a patient-specific volume of tissue activated (VTA) was generated for each contact in T1 native space using DBS activation volume prediction modeling methods3638 and the following stimulation settings: frequency, 130 Hz; pulse width, 90 microseconds; stimulation amplitude, 6 mA; and individual impedance measures. Last, the patient-specific VTAs were transformed to the MNI-152 template for use as seeds for the probabilistic tractography analyses.

Connectivity Analysis of Acute Intraoperative Behavior

Whole-brain probabilistic fiber tractography was generated from each of the patient-specific VTA seeds to construct a structural connectivity map (FMRIB Diffusion Toolbox in FSL).34 Eight different structural connectivity maps from patient-specific VTA seeds (4 contacts in each hemisphere) were generated for each patient. Five thousand streamlines were sent out from each voxel within the VTA with masking of the cerebrospinal fluid to reduce false-positive connections. A streamline density map was generated by the number of connected streamlines divided by the total number of streamlines sent out.39 Next, the streamline density map was binarized (ie, streamline was present or absent within given voxel) at a threshold value of 0.2% after optimization procedures that tested various threshold values (0.01% to approximately 1%).40 Last, the binarized maps were summed and divided by the total number of each specific response type to calculate the overlap map. To identify the specific white matter bundles mediating the defined response types, a common shared map (80% shared voxels) was generated for (1) the best contacts (regardless of hemisphere), (2) those contacts that were not best but nonetheless salient (left and right hemisphere contacts grouped separately), and (3) those contacts with no response. All data analysis was performed from May 1 through July 1, 2015.

Results
Intraoperative Behavior Response Characteristics

Among the 9 patients, a total of 108 individual stimulation trials were recorded (72 active [36 per hemisphere] and 36 sham). Thirty of the 72 active contacts generated a type 1 interoceptive response (17 in the left hemisphere and 13 in the right hemisphere) and 9 contacts generated a type 2 exteroceptive response (all in the left hemisphere), whereas 42 contacts evoked no response. Of the 36 sham trials, only 4 generated a mild type 1 response and none generated a type 2 response. As previously observed, a behavioral switch was apparent to patients within the first minute of the initiation of the stimulation, and effects were sustained while stimulation remained on. Patients generally noted a clear fading of any effects within the first minute after discontinuation and a return to their pretrial baseline after about 2 minutes.

The best contact for each of the 9 patients was always in the left hemisphere. Self-reports from these best contacts showed robust types 1 and 2 responses, including “lightening of mood”; “feeling warm”; “lighter”; “feeling more connected”; “I can get outside of myself to pay attention to you”; noticing objects, people, and activities ongoing in the operating room; and interest and perceived capacity to engage in various personally relevant activities if they were home (eg, taking a shower, washing the dishes, and walking the dog). Salient (positive but not best) responses occurred with equal frequency with stimulation of contacts in either hemisphere. Self-reported statements included “lifting,” “less heaviness,” “less tension,” “increased air and ability to breathe,” and “a feeling of relief.” These physical sensations were commonly accompanied by changes in facial expression observed by the rater (eg, eyes widening, softening of corrugator muscle contractions) and increases in verbal fluency and speech output. Overall, the salient responses primarily involved changes in interoceptive awareness (type 1 responses). In contrast, the best responses were consistently characterized by a combination of interoceptive changes (type 1) and exteroceptive attention and engagement (type 2). Samples of spontaneous statements and clinical observations from the 9 patients are listed in Table 2.

Behavioral Connectivity Analyses

The following 3 common white matter bundles were affected by stimulation of the 9 left-sided contacts mediating a best response: the uncinate fasciculus connecting to the ipsilateral ventromedial frontal cortex, the forceps minor connecting to the bilateral ventromedial frontal cortices, and the left cingulum bundle connecting to the ipsilateral anterior cingulate cortex (Figure 2).41,42 White matter bundles mediating the salient responses were limited to the ipsilateral cingulate bundle with a mirror pattern for right- and left-sided contacts (Figure 3). In contrast to the best and salient contacts, the no-behavior contacts shared no common pathways regardless of hemisphere.

Discussion

This study characterizes the tractography patterns mediating the transient, stereotypical behavioral changes evoked by acute high-frequency SCC stimulation performed during DBS lead implantation surgery in patients with treatment-resistant depression. Double-blinded evaluations during the acute stimulation test of each contact revealed 2 behavioral response patterns. Type 1, a change in the interoceptive state, was reported with stimulation at more than 1 contact in the right or the left hemisphere for most patients. Type 2 responses were more multifaceted, with complex shifts in attentional focus, social connectedness, and interest occurring only with stimulation of left hemisphere contacts. Contacts eliciting a robust type 2 response also showed a type 1 response immediately preceding the self-referential and action-oriented declarations. These 2-part responses were consistently the contact categorized as best for every patient. Structural connectivity analyses further demonstrated that these distinct response types were mediated by a differential effect on the ventromedial frontal cortex and cingulate with bilateral frontal white matter tracts distinguishing best from merely salient contacts where only the cingulate was involved. The responses were described mostly as a relief and lessening of a negative state rather than the sudden appearance of a positive mood as described in other DBS targets, such as the nucleus accumbens, the medial forebrain bundle, or the ventral capsule.

Interoceptive awareness has been defined operationally as a perception of physiological changes in body states,4345 with quantitative measures of autonomic reactivity often used as a physiological surrogate. The role of the ventral, anterior, and midcingulate in these behaviors is well established. Functional imaging studies have demonstrated activity changes in the SCC and the midcingulate to correlate with the blood pressure, heart rate, and skin conductance changes during a variety of mental and emotional tasks.4657 Activation of these regions has been similarly reported in studies of provoked visceral, somatic, and emotional pain.5863 These regions have been further classified as key components in the resting-state salience network64,65 that mediates shifts between personally relevant internal and external stimuli.66 Changes in the SCC and in the dorsal anterior and dorsal midcingulate activity are reported across antidepressant treatment trials using various interventions, including SCC DBS.67 Similar changes in these regions are among the most robust with acute sad mood induction.68,69 Across studies, left- and right-sided activity changes have been reported, which is consistent with the lack of lateralized effects seen herein with acute stimulation. Although other regions, including the anterior insula and frontal cortex, are clearly critical to a full interoceptive experience and a complete recovery from depression,70 the common involvement of the cingulate in the type 1 salient and type 2 best responses is nonetheless consistent with this principal role of the cingulate in interoceptive processing.

Exteroceptive awareness, in contrast, is defined as the perception of external stimuli and the shifting of attention away from the self toward the environment.71 Imaging studies have repeatedly demonstrated a role of the ventromedial frontal cortex in activities using exteroceptive engagement, such as mentalizing, self-knowledge, and outcome monitoring.72 Ventromedial frontal cortex activity has been demonstrated during self-referential processing of emotional words and pictures,7375 in generating external vs internal emotional states,76 and in recognizing and imagining the experience of others.77,78 With particular relevance to depression, the medial frontal cortex has an important role in protecting the execution of long-term mental plans from immediate environmental or internal demands.79 Patients with depression commonly show hypoactivity of these regions and inappropriate deactivation during negative mood challenge.80,81 Not surprisingly, the medial frontal cortex has a critical role in the resting-state default mode network and has shown hyperconnectivity to the SCC in treatment-resistant depression.82 Failure of this system to shift toward external stimuli and instead remain stuck inside one’s self is the very definition of the treatment-resistant depressive state. The common involvement of bilateral medial frontal fibers linking directly to the SCC and passing fibers connecting the medial frontal cortex to the amygdala via the uncinate fasciculus during stimulation of the best contacts suggests a mechanism for the observed transient depression switch from a pervasive state stuck at negative to sensing a sudden capacity to get outside of one’s self.

The significant overlap of the tract patterns seen with the best contacts with those mediating long-term antidepressant response29 further suggests that these transient behavioral effects may provide a behavioral biomarker of the optimal site for long-term DBS, particularly at the left hemisphere contact. In support of this hypothesis, 7 of the 9 patients using the type 2 best left hemisphere contact had a response to treatment at 6 months.

This study has a number of limitations. Intraoperative testing is a strenuous task for patients, and some important responses may have been missed owing to the patient’s pain or fatigue. Therefore, the lack of response to a particular contact does not mean that a particular contact is not the desired target or affects a certain circuit. Clinical ratings, although performed in a double-blinded fashion, can still misinterpret some observations that are unique to individuals; furthermore, not all salient responses are of the same intensity. Continuous measures, such as heart rate, skin conductance, or facial or speech recognition technology, may be preferable for the capture of more nuanced phenomena than the categorical metrics used herein. Additional studies are focused on concurrent or antecedent changes in autonomic reactivity, facial expression, and speech output and electrophysiological changes in the SCC and frontal cortex. In regard to the tractography technique, resolution limits are set by the acquisition protocol and analytic methods. Therefore, other shared bundles, particularly small or more variable subcortical tracts, may have been missed.

At present, whether left-sided stimulation alone would be adequate to achieve a full antidepressant response remains untested because only bilateral stimulation has been evaluated. However, recent tractography studies of effective bilateral stimulation25 demonstrate that bilateral cingulum and uncinate fasciculus are needed in addition to crossing fibers within the forceps minor. Explicit comparisons of right- and left-sided unilateral stimulation await future investigation.

Conclusions

In treatment-resistant depression, pervasive negative mood and mental anguish, disinterest, social disengagement, and paucity of thought and action are prominent clinical features. We posit that acute stimulation in the requisite combination of fibers affecting the bilateral ventral frontal cortex, the anterior cingulate, and the midcingulate has immediate but transient effects on these core depression features and represents the first stage of depression network engagement required for long-term antidepressant effects of SCC DBS.

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Article Information

Corresponding Author: Ki Sueng Choi, PhD, Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 101 Woodruff Cir NE, Woodruff Memorial Research Bldg, Ste 4303, Atlanta, GA 30322 (kchoi8@emory.edu).

Accepted for Publication: July 29, 2015.

Published Online: September 26, 2015. doi:10.1001/jamaneurol.2015.2564.

Author Contributions: Drs Choi and Riva-Posse contributed equally to this work. Dr Choi had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Choi, Riva-Posse, Mayberg.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Choi.

Obtained funding: Mayberg.

Administrative, technical, or material support: Choi, Gross, Mayberg.

Study supervision: Gross, Mayberg.

Conflict of Interest Disclosures: Dr Gross reports serving as a paid consultant to Medtronic, Inc, and St Jude Medical Corp. Medtronic and St Jude Medical Corp develop products related to the research described in this article. Dr Mayberg reports consulting agreement with St Jude Medical Neuromodulation, which has licensed her intellectual property to develop SCC DBS for the treatment of severe depression (US 2005/0033379A1). The terms of these arrangements for Drs Mayberg and Gross have been reviewed and approved by Emory University in accordance with their conflict of interest policies. No other disclosures were reported.

Funding/Support: This study was supported by the Dana Foundation, by the Hope for Depression Research Foundation, and by grant R01 NS059736 from the National Institutes of Health. The study device was donated by St Jude Medical, Inc.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Psychiatrists Steve Garlow, MD, PhD, and Andrea Crowell, MD, Department of Psychiatry and Behavioral Science, Emory University School of Medicine, screened, enrolled, and managed ongoing deep brain stimulation treatment of the course of the study. Justin Rajendra, BA, Department of Psychiatry and Behavioral Science, Emory University School of Medicine, provided image and data analysis; and Sinead Quinn, BA, Department of Psychiatry and Behavioral Science, Emory University School of Medicine, coordinated research. All contributors listed are coinvestigators or staff on the grants that supported this study.

References
1.
Rezai  AR, Kopell  BH, Gross  RE,  et al.  Deep brain stimulation for Parkinson’s disease: surgical issues. Mov Disord. 2006;21(suppl 14):S197-S218.
PubMedArticle
2.
Bishop  MP, Elder  ST, Heath  RG.  Intracranial self-stimulation in man. Science. 1963;140(3565):394-396.
PubMedArticle
3.
Nuttin  BJ, Gabriëls  LA, Cosyns  PR,  et al.  Long-term electrical capsular stimulation in patients with obsessive-compulsive disorder. Neurosurgery. 2003;52(6):1263-1272.
PubMedArticle
4.
Okun  MS, Bowers  D, Springer  U,  et al.  What’s in a “smile?” Intra-operative observations of contralateral smiles induced by deep brain stimulation. Neurocase. 2004;10(4):271-279.
PubMedArticle
5.
Krack  P, Vercueil  L.  Review of the functional surgical treatment of dystonia. Eur J Neurol. 2001;8(5):389-399.
PubMedArticle
6.
Bejjani  BP, Damier  P, Arnulf  I,  et al.  Transient acute depression induced by high-frequency deep-brain stimulation. N Engl J Med. 1999;340(19):1476-1480.
PubMedArticle
7.
Bejjani  BP, Houeto  JL, Hariz  M,  et al.  Aggressive behavior induced by intraoperative stimulation in the triangle of Sano. Neurology. 2002;59(9):1425-1427.
PubMedArticle
8.
Rasche  D, Rinaldi  PC, Young  RF, Tronnier  VM.  Deep brain stimulation for the treatment of various chronic pain syndromes. Neurosurg Focus. 2006;21(6):1-8.
PubMedArticle
9.
Shapira  NA, Okun  MS, Wint  D,  et al.  Panic and fear induced by deep brain stimulation. J Neurol Neurosurg Psychiatry. 2006;77(3):410-412.
PubMedArticle
10.
Hamani  C, McAndrews  MP, Cohn  M,  et al.  Memory enhancement induced by hypothalamic/fornix deep brain stimulation. Ann Neurol. 2008;63(1):119-123.
PubMedArticle
11.
Mayberg  HS, Lozano  AM, Voon  V,  et al.  Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45(5):651-660.
PubMedArticle
12.
Lozano  AM, Mayberg  HS, Giacobbe  P, Hamani  C, Craddock  RC, Kennedy  SH.  Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2008;64(6):461-467.
PubMedArticle
13.
Lozano  AM, Giacobbe  P, Hamani  C,  et al.  A multicenter pilot study of subcallosal cingulate area deep brain stimulation for treatment-resistant depression. J Neurosurg. 2012;116(2):315-322.
PubMedArticle
14.
Holtzheimer  PE, Kelley  ME, Gross  RE,  et al.  Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression. Arch Gen Psychiatry. 2012;69(2):150-158.
PubMedArticle
15.
Puigdemont  D, Pérez-Egea  R, Portella  MJ,  et al.  Deep brain stimulation of the subcallosal cingulate gyrus: further evidence in treatment-resistant major depression. Int J Neuropsychopharmacol. 2012;15(1):121-133.
PubMedArticle
16.
Kennedy  SH, Giacobbe  P, Rizvi  SJ,  et al.  Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years. Am J Psychiatry. 2011;168(5):502-510.
PubMedArticle
17.
Merkl  A, Schneider  GH, Schönecker  T,  et al.  Antidepressant effects after short-term and chronic stimulation of the subgenual cingulate gyrus in treatment-resistant depression. Exp Neurol. 2013;249:160-168.
PubMedArticle
18.
Ramasubbu  R, Anderson  S, Haffenden  A, Chavda  S, Kiss  ZH.  Double-blind optimization of subcallosal cingulate deep brain stimulation for treatment-resistant depression: a pilot study. J Psychiatry Neurosci. 2013;38(5):325-332.
PubMedArticle
19.
Guinjoan  SM, Mayberg  HS, Costanzo  EY,  et al.  Asymmetrical contribution of brain structures to treatment-resistant depression as illustrated by effects of right subgenual cingulum stimulation. J Neuropsychiatry Clin Neurosci. 2010;22(3):265-277.
PubMedArticle
20.
Schlaepfer  TE, Cohen  MX, Frick  C,  et al.  Deep brain stimulation to reward circuitry alleviates anhedonia in refractory major depression. Neuropsychopharmacology. 2008;33(2):368-377.
PubMedArticle
21.
Schlaepfer  TE, Bewernick  BH, Kayser  S, Mädler  B, Coenen  VA.  Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73(12):1204-1212.
PubMedArticle
22.
Bewernick  BH, Hurlemann  R, Matusch  A,  et al.  Nucleus accumbens deep brain stimulation decreases ratings of depression and anxiety in treatment-resistant depression. Biol Psychiatry. 2010;67(2):110-116.
PubMedArticle
23.
Bewernick  BH, Kayser  S, Sturm  V, Schlaepfer  TE.  Long-term effects of nucleus accumbens deep brain stimulation in treatment-resistant depression: evidence for sustained efficacy. Neuropsychopharmacology. 2012;37(9):1975-1985.
PubMedArticle
24.
Stefurak  T, Mikulis  D, Mayberg  H,  et al.  Deep brain stimulation for Parkinson’s disease dissociates mood and motor circuits: a functional MRI case study. Mov Disord. 2003;18(12):1508-1516.
PubMedArticle
25.
Riva-Posse  P.  Identification of critical white matter pathways involved in efficacious subcallosal cingulate deep brain stimulation: implications for prospective target selection [abstract]. Biol Psychiatry. 2014;7S(9):S15.
26.
ClinicalTrials.gov. Deep Brain Stimulation for Treatment Resistant Depression. NCT00367003. https://clinicaltrials.gov/ct2/show/NCT00367003. Accessed May 1, 2015.
27.
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMedArticle
28.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text revision. Washington, DC: American Psychiatric Association; 2000.
29.
Riva-Posse  P, Choi  KS, Holtzheimer  PE,  et al.  Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2014;76(12):963-969.
PubMedArticle
30.
Griswold  MA, Jakob  PM, Heidemann  RM,  et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47(6):1202-1210.
PubMedArticle
31.
Smith  SM, Jenkinson  M, Woolrich  MW,  et al.  Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23(suppl 1):S208-S219.
PubMedArticle
32.
Jenkinson  M, Beckmann  CF, Behrens  TE, Woolrich  MW, Smith  SM.  FSL. Neuroimage. 2012;62(2):782-790.
PubMedArticle
33.
Smith  SM.  Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143-155.
PubMedArticle
34.
Behrens  TE, Woolrich  MW, Jenkinson  M,  et al.  Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50(5):1077-1088.
PubMedArticle
35.
Greve  DN, Fischl  B.  Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48(1):63-72.
PubMedArticle
36.
Chaturvedi  A, Luján  JL, McIntyre  CC.  Artificial neural network based characterization of the volume of tissue activated during deep brain stimulation. J Neural Eng. 2013;10(5):056023. doi:10.1088/1741-2560/10/5/056023.
PubMedArticle
37.
Lujan  JL, Chaturvedi  A, Malone  DA, Rezai  AR, Machado  AG, McIntyre  CC.  Axonal pathways linked to therapeutic and nontherapeutic outcomes during psychiatric deep brain stimulation. Hum Brain Mapp. 2012;33(4):958-968.
PubMedArticle
38.
McIntyre  CC, Miocinovic  S, Butson  CR.  Computational analysis of deep brain stimulation. Expert Rev Med Devices. 2007;4(5):615-622.
PubMedArticle
39.
Hagmann  P, Cammoun  L, Gigandet  X,  et al.  Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6(7):e159. doi:10.1371/journal.pbio.0060159.
PubMedArticle
40.
Li  L, Rilling  JK, Preuss  TM, Glasser  MF, Hu  X.  The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography. Hum Brain Mapp. 2012;33(8):1894-1913.
PubMedArticle
41.
Wakana  S, Caprihan  A, Panzenboeck  MM,  et al.  Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage. 2007;36(3):630-644.
PubMedArticle
42.
Hua  K, Zhang  J, Wakana  S,  et al.  Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage. 2008;39(1):336-347.
PubMedArticle
43.
Wiens  S.  Interoception in emotional experience. Curr Opin Neurol. 2005;18(4):442-447.
PubMedArticle
44.
Craig  AD.  How do you feel? interoception: the sense of the physiological condition of the body. Nat Rev Neurosci. 2002;3(8):655-666.
PubMedArticle
45.
Craig  AD.  Interoception: the sense of the physiological condition of the body. Curr Opin Neurobiol. 2003;13(4):500-505.
PubMedArticle
46.
Critchley  HD, Elliott  R, Mathias  CJ, Dolan  RJ.  Neural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J Neurosci. 2000;20(8):3033-3040.
PubMed
47.
Critchley  HD, Mathias  CJ, Josephs  O,  et al.  Human cingulate cortex and autonomic control: converging neuroimaging and clinical evidence. Brain. 2003;126(pt 10):2139-2152.
PubMedArticle
48.
Critchley  HD, Wiens  S, Rotshtein  P, Ohman  A, Dolan  RJ.  Neural systems supporting interoceptive awareness. Nat Neurosci. 2004;7(2):189-195.
PubMedArticle
49.
Critchley  HD.  Neural mechanisms of autonomic, affective, and cognitive integration. J Comp Neurol. 2005;493(1):154-166.
PubMedArticle
50.
Critchley  HD, Eccles  J, Garfinkel  SN.  Interaction between cognition, emotion, and the autonomic nervous system. Handb Clin Neurol. 2013;117:59-77.
PubMed
51.
Critchley  HD, Harrison  NA.  Visceral influences on brain and behavior. Neuron. 2013;77(4):624-638.
PubMedArticle
52.
Fredrickson  BL.  What good are positive emotions? Rev Gen Psychol. 1998;2(3):300-319.
PubMedArticle
53.
Pereira  EA, Wang  S, Paterson  DJ, Stein  JF, Aziz  TZ, Green  AL.  Sustained reduction of hypertension by deep brain stimulation. J Clin Neurosci. 2010;17(1):124-127.
PubMedArticle
54.
Pollatos  O, Kirsch  W, Schandry  R.  Brain structures involved in interoceptive awareness and cardioafferent signal processing: a dipole source localization study. Hum Brain Mapp. 2005;26(1):54-64.
PubMedArticle
55.
Barrett  LF, Simmons  WK.  Interoceptive predictions in the brain. Nat Rev Neurosci. 2015;16(7):419-429.
PubMedArticle
56.
Lane  RD, Fink  GR, Chau  PM, Dolan  RJ.  Neural activation during selective attention to subjective emotional responses. Neuroreport. 1997;8(18):3969-3972.
PubMedArticle
57.
Vogt  BA, Pandya  DN.  Cingulate cortex of the rhesus monkey, II: cortical afferents. J Comp Neurol. 1987;262(2):271-289.
PubMedArticle
58.
Vogt  BA, Sikes  RW.  The medial pain system, cingulate cortex, and parallel processing of nociceptive information. Prog Brain Res. 2000;122:223-235.
PubMed
59.
Vogt  BA.  Pain and emotion interactions in subregions of the cingulate gyrus. Nat Rev Neurosci. 2005;6(7):533-544.
PubMedArticle
60.
Vogt  BA.  Submodalities of emotion in the context of cingulate subregions. Cortex. 2014;59:197-202.
PubMedArticle
61.
Wager  TD, van Ast  VA, Hughes  BL, Davidson  ML, Lindquist  MA, Ochsner  KN.  Brain mediators of cardiovascular responses to social threat, part II: prefrontal-subcortical pathways and relationship with anxiety. Neuroimage. 2009;47(3):836-851.
PubMedArticle
62.
Mayer  EA.  Gut feelings: the emerging biology of gut-brain communication. Nat Rev Neurosci. 2011;12(8):453-466.
PubMedArticle
63.
Mayer  EA, Gupta  A, Kilpatrick  LA, Hong  JY.  Imaging brain mechanisms in chronic visceral pain. Pain. 2015;156(suppl 1):S50-S63.
PubMedArticle
64.
Greicius  M.  Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol. 2008;21(4):424-430.
PubMedArticle
65.
Seeley  WW, Menon  V, Schatzberg  AF,  et al.  Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27(9):2349-2356.
PubMedArticle
66.
Sridharan  D, Levitin  DJ, Menon  V.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci U S A. 2008;105(34):12569-12574.
PubMedArticle
67.
Mayberg  HS.  Targeted electrode-based modulation of neural circuits for depression. J Clin Invest. 2009;119(4):717-725.
PubMedArticle
68.
Mayberg  HS, Liotti  M, Brannan  SK,  et al.  Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am J Psychiatry. 1999;156(5):675-682.
PubMed
69.
Liotti  M, Mayberg  HS, Brannan  SK, McGinnis  S, Jerabek  P, Fox  PT.  Differential limbic-cortical correlates of sadness and anxiety in healthy subjects: implications for affective disorders. Biol Psychiatry. 2000;48(1):30-42.
PubMedArticle
70.
Jones  CL, Minati  L, Nagai  Y,  et al.  Neuroanatomical substrates for the volitional regulation of heart rate. Front Psychol. 2015;6:300. doi:10.3389/fpsyg.2015.00300.
PubMed
71.
Damasio  AR.  The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philos Trans R Soc Lond B Biol Sci. 1996;351(1346):1413-1420.
PubMedArticle
72.
Amodio  DM, Frith  CD.  Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci. 2006;7(4):268-277.
PubMedArticle
73.
Fossati  P.  Neural correlates of emotion processing: from emotional to social brain. Eur Neuropsychopharmacol. 2012;22(suppl 3):S487-S491.
PubMedArticle
74.
Smith  R, Braden  BB, Chen  K, Ponce  FA, Lane  RD, Baxter  LC.  The neural basis of attaining conscious awareness of sad mood [published online September 19, 2014]. Brain Imaging Behav. doi:10.1007/s11682-014-9318-8.
PubMed
75.
Simpson  JR  Jr, Snyder  AZ, Gusnard  DA, Raichle  ME.  Emotion-induced changes in human medial prefrontal cortex, I: during cognitive task performance. Proc Natl Acad Sci U S A. 2001;98(2):683-687.
PubMedArticle
76.
Reiman  EM, Lane  RD, Ahern  GL,  et al.  Neuroanatomical correlates of externally and internally generated human emotion. Am J Psychiatry. 1997;154(7):918-925.
PubMedArticle
77.
Nyberg  L, Kim  AS, Habib  R, Levine  B, Tulving  E.  Consciousness of subjective time in the brain. Proc Natl Acad Sci U S A. 2010;107(51):22356-22359.
PubMedArticle
78.
Addis  DR, Pan  L, Vu  MA, Laiser  N, Schacter  DL.  Constructive episodic simulation of the future and the past: distinct subsystems of a core brain network mediate imagining and remembering. Neuropsychologia. 2009;47(11):2222-2238.
PubMedArticle
79.
Koechlin  E, Hyafil  A.  Anterior prefrontal function and the limits of human decision-making. Science. 2007;318(5850):594-598.
PubMedArticle
80.
Liotti  M, Mayberg  HS.  The role of functional neuroimaging in the neuropsychology of depression. J Clin Exp Neuropsychol. 2001;23(1):121-136.
PubMedArticle
81.
Krüger  S, Seminowicz  D, Goldapple  K, Kennedy  SH, Mayberg  HS.  State and trait influences on mood regulation in bipolar disorder: blood flow differences with an acute mood challenge. Biol Psychiatry. 2003;54(11):1274-1283.
PubMedArticle
82.
Greicius  MD, Flores  BH, Menon  V,  et al.  Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007;62(5):429-437.
PubMedArticle
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