Altered directed functional connectivity of the right amygdala in depression: high-density EEG study
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
32157152
PubMed Central
PMC7064485
DOI
10.1038/s41598-020-61264-z
PII: 10.1038/s41598-020-61264-z
Knihovny.cz E-zdroje
- MeSH
- amygdala patofyziologie MeSH
- deprese patofyziologie terapie MeSH
- dospělí MeSH
- elektroencefalografie MeSH
- hluboká mozková stimulace MeSH
- lidé středního věku MeSH
- lidé MeSH
- mapování mozku metody MeSH
- nervové dráhy diagnostické zobrazování patofyziologie MeSH
- počítačové zpracování obrazu MeSH
- studie případů a kontrol MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The cortico-striatal-pallidal-thalamic and limbic circuits are suggested to play a crucial role in the pathophysiology of depression. Stimulation of deep brain targets might improve symptoms in treatment-resistant depression. However, a better understanding of connectivity properties of deep brain structures potentially implicated in deep brain stimulation (DBS) treatment is needed. Using high-density EEG, we explored the directed functional connectivity at rest in 25 healthy subjects and 26 patients with moderate to severe depression within the bipolar affective disorder, depressive episode, and recurrent depressive disorder. We computed the Partial Directed Coherence on the source EEG signals focusing on the amygdala, anterior cingulate, putamen, pallidum, caudate, and thalamus. The global efficiency for the whole brain and the local efficiency, clustering coefficient, outflow, and strength for the selected structures were calculated. In the right amygdala, all the network metrics were significantly higher (p < 0.001) in patients than in controls. The global efficiency was significantly higher (p < 0.05) in patients than in controls, showed no correlation with status of depression, but decreased with increasing medication intake ([Formula: see text]). The amygdala seems to play an important role in neurobiology of depression. Practical treatment studies would be necessary to assess the amygdala as a potential future DBS target for treating depression.
Department of Basic Neurosciences University of Geneva Campus Biotech Geneva Switzerland
Department of Neuroscience University of Padova Padova Italy
Department of Psychiatry Faculty of Medicine Masaryk University Brno Czech Republic
Department of Psychiatry University Hospital Brno Brno Czech Republic
Lemanic Biomedical Imaging Centre Lausanne and Geneva Switzerland
Zobrazit více v PubMed
Andrade L, et al. The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) surveys. Int. J. Methods Psychiatr. Res. 2003;12:3–21. doi: 10.1002/mpr.138. PubMed DOI PMC
Bora E., Harrison B. J., Davey C. G., Yücel M., Pantelis C. Meta-analysis of volumetric abnormalities in cortico-striatal-pallidal-thalamic circuits in major depressive disorder. Psychological Medicine. 2011;42(4):671–681. doi: 10.1017/S0033291711001668. PubMed DOI
Yang J, et al. Amygdala Atrophy and Its Functional Disconnection with the Cortico-Striatal-Pallidal-Thalamic Circuit in Major Depressive Disorder in Females. PLoS One. 2017;12:e0168239. doi: 10.1371/journal.pone.0168239. PubMed DOI PMC
Zhang B, et al. Mapping anhedonia-specific dysfunction in a transdiagnostic approach: an ALE meta-analysis. Brain Imaging Behav. 2016;10:920–939. doi: 10.1007/s11682-015-9457-6. PubMed DOI PMC
Disner SG, Beevers CG, Haigh EAP, Beck AT. Neural mechanisms of the cognitive model of depression. Nat. Rev. Neurosci. 2011;12:467–477. doi: 10.1038/nrn3027. PubMed DOI
Surguladze S, et al. A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biol. Psychiatry. 2005;57:201–209. doi: 10.1016/j.biopsych.2004.10.028. PubMed DOI
Sheline YI, et al. Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol. Psychiatry. 2001;50:651–658. doi: 10.1016/S0006-3223(01)01263-X. PubMed DOI
Siegle GJ, Thompson W, Carter CS, Steinhauer SR, Thase ME. Increased Amygdala and Decreased Dorsolateral Prefrontal BOLD Responses in Unipolar Depression: Related and Independent Features. Biol. Psychiatry. 2007;61:198–209. doi: 10.1016/j.biopsych.2006.05.048. PubMed DOI
Nugent AC, Robinson SE, Coppola R, Furey ML, Zarate CA. Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder. Neuroimage. 2015;118:1–12. doi: 10.1016/j.neuroimage.2015.05.051. PubMed DOI PMC
Knyazev GG, et al. Task-positive and task-negative networks in major depressive disorder: A combined fMRI and EEG study. J. Affect. Disord. 2018;235:211–219. doi: 10.1016/j.jad.2018.04.003. PubMed DOI
Lu Y, et al. The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder. NeuroImage. Clin. 2016;11:658–666. doi: 10.1016/j.nicl.2016.04.008. PubMed DOI PMC
Kim MJ, Hamilton JP, Gotlib IH. Reduced caudate gray matter volume in women with major depressive disorder. Psychiatry Res. Neuroimaging. 2008;164:114–122. doi: 10.1016/j.pscychresns.2007.12.020. PubMed DOI PMC
Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc. Natl. Acad. Sci. 2010;107:11020–11025. doi: 10.1073/pnas.1000446107. PubMed DOI PMC
Kuhn S, Gallinat J. Resting-State Brain Activity in Schizophrenia and Major Depression: A Quantitative Meta-Analysis. Schizophr. Bull. 2013;39:358–365. doi: 10.1093/schbul/sbr151. PubMed DOI PMC
Lorenzetti V, Allen NB, Fornito A, Yücel M. Structural brain abnormalities in major depressive disorder: A selective review of recent MRI studies. J. Affect. Disord. 2009;117:1–17. doi: 10.1016/j.jad.2008.11.021. PubMed DOI
Veer, I. M. Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Front. Syst. Neurosci. 4, 41 (2010). PubMed PMC
Hamilton JP, et al. Functional Neuroimaging of Major Depressive Disorder: A Meta-Analysis and New Integration of Baseline Activation and Neural Response Data. Am. J. Psychiatry. 2012;169:693–703. doi: 10.1176/appi.ajp.2012.11071105. PubMed DOI
Bielau H, et al. Volume deficits of subcortical nuclei in mood disorders. Eur. Arch. Psychiatry Clin. Neurosci. 2005;255:401–412. doi: 10.1007/s00406-005-0581-y. PubMed DOI
Holtzheimer PE, Mayberg HS. Stuck in a rut: rethinking depression and its treatment. Trends Neurosci. 2011;34:1–9. doi: 10.1016/j.tins.2010.10.004. PubMed DOI PMC
Drobisz D, Damborská A. Deep brain stimulation targets for treating depression. Behav. Brain Res. 2019;359:266–273. doi: 10.1016/j.bbr.2018.11.004. PubMed DOI
Holtzheimer PE, et al. Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Unipolar and Bipolar Depression. Arch. Gen. Psychiatry. 2012;69:150. doi: 10.1001/archgenpsychiatry.2011.1456. PubMed DOI PMC
Knight G. Stereotactic Tractotomy in The Surgical Treatment of Mental Illness. J. Neurol. Neurosurg. Psychiatry. 1965;28:304–310. doi: 10.1136/jnnp.28.4.304. PubMed DOI PMC
Dougherty DD, et al. Cerebral metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of major depression. J. Neurosurg. 2003;99:1010–1017. doi: 10.3171/jns.2003.99.6.1010. PubMed DOI
Hamani C, et al. Deep brain stimulation in rats: Different targets induce similar antidepressant-like effects but influence different circuits. Neurobiol. Dis. 2014;71:205–214. doi: 10.1016/j.nbd.2014.08.007. PubMed DOI PMC
Hamani C, Nóbrega JN. Deep brain stimulation in clinical trials and animal models of depression. Eur. J. Neurosci. 2010;32:1109–1117. doi: 10.1111/j.1460-9568.2010.07414.x. PubMed DOI
Hamani C, et al. Antidepressant-Like Effects of Medial Prefrontal Cortex Deep Brain Stimulation in Rats. Biol. Psychiatry. 2010;67:117–124. doi: 10.1016/j.biopsych.2009.08.025. PubMed DOI
Moshe H, et al. Prelimbic Stimulation Ameliorates Depressive-Like Behaviors and Increases Regional BDNF Expression in a Novel Drug-Resistant Animal Model of Depression. Brain Stimul. 2016;9:243–250. doi: 10.1016/j.brs.2015.10.009. PubMed DOI
Thiele S, Furlanetti L, Pfeiffer LM, Coenen VA, Döbrössy MD. The effects of bilateral, continuous, and chronic Deep Brain Stimulation of the medial forebrain bundle in a rodent model of depression. Exp. Neurol. 2018;303:153–161. doi: 10.1016/j.expneurol.2018.02.002. PubMed DOI
Rummel J, et al. Testing different paradigms to optimize antidepressant deep brain stimulation in different rat models of depression. J. Psychiatr. Res. 2016;81:36–45. doi: 10.1016/j.jpsychires.2016.06.016. PubMed DOI
Clemm Von Hohenberg, C. et al. Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression. Transl. Psychiatry8, 68 (2018). PubMed PMC
Baeken C, Duprat R, Wu GR, De Raedt R, van Heeringen K. Subgenual Anterior Cingulate–Medial Orbitofrontal Functional Connectivity in Medication-Resistant Major Depression: A Neurobiological Marker for Accelerated Intermittent Theta Burst Stimulation Treatment? Biol. Psychiatry Cogn. Neurosci. Neuroimaging. 2017;2:556–565. doi: 10.1016/j.bpsc.2017.01.001. PubMed DOI
Johansen-Berg H, et al. Anatomical connectivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression. Cereb. Cortex. 2008;18:1374–1383. doi: 10.1093/cercor/bhm167. PubMed DOI PMC
Greicius MD, et al. Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus. Biol. Psychiatry. 2007;62:429–437. doi: 10.1016/j.biopsych.2006.09.020. PubMed DOI PMC
Riva-Posse P, et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol. Psychiatry. 2014;76:963–969. doi: 10.1016/j.biopsych.2014.03.029. PubMed DOI PMC
Quevedo K, et al. Ventral Striatum Functional Connectivity during Rewards and Losses and Symptomatology in Depressed Patients. Biol. Psychol. 2017;123:62–73. doi: 10.1016/j.biopsycho.2016.11.004. PubMed DOI PMC
Gutman DA, Holtzheimer PE, Behrens TEJ, Johansen-Berg H, Mayberg HS. A Tractography Analysis of Two Deep Brain Stimulation White Matter Targets for Depression. Biol. Psychiatry. 2009;65:276–282. doi: 10.1016/j.biopsych.2008.09.021. PubMed DOI PMC
Bracht T, et al. White matter microstructure alterations of the medial forebrain bundle in melancholic depression. J. Affect. Disord. 2014;155:186–193. doi: 10.1016/j.jad.2013.10.048. PubMed DOI
Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry. 2015;72:603–611. doi: 10.1001/jamapsychiatry.2015.0071. PubMed DOI PMC
Smith SM, et al. Functional connectomics from resting-state fMRI. Trends in Cognitive Sciences. 2013;17:666–682. doi: 10.1016/j.tics.2013.09.016. PubMed DOI PMC
Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience. 2007;8:700–711. doi: 10.1038/nrn2201. PubMed DOI
Hamilton JP, et al. Default-Mode and Task-Positive Network Activity in Major Depressive Disorder: Implications for Adaptive and Maladaptive Rumination. Biol. Psychiatry. 2011;70:327–333. doi: 10.1016/j.biopsych.2011.02.003. PubMed DOI PMC
Lui S, et al. Resting-state functional connectivity in treatment-resistant depression. Am. J. Psychiatry. 2011;168:642–648. doi: 10.1176/appi.ajp.2010.10101419. PubMed DOI
Whitton AE, et al. Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression. Biol. Psychiatry Cogn. Neurosci. Neuroimaging. 2018;3:50–58. doi: 10.1016/j.bpsc.2017.07.001. PubMed DOI PMC
Sikora M, et al. Salience Network Functional Connectivity Predicts Placebo Effects in Major Depression. Biol. Psychiatry Cogn. Neurosci. Neuroimaging. 2016;1:68–76. doi: 10.1016/j.bpsc.2015.10.002. PubMed DOI PMC
Gong JY, et al. Disrupted functional connectivity within the default mode network and salience network in unmedicated bipolar II disorder. Prog. Neuro-Psychopharmacology Biol. Psychiatry. 2019;88:11–18. doi: 10.1016/j.pnpbp.2018.06.012. PubMed DOI
Sacchet MD, et al. Large-scale hypoconnectivity between resting-state functional networks in unmedicated adolescent major depressive disorder. Neuropsychopharmacology. 2016;41:2951–2960. doi: 10.1038/npp.2016.76. PubMed DOI PMC
Williams KA, Mehta NS, Redei EE, Wang L, Procissi D. Aberrant resting-state functional connectivity in a genetic rat model of depression. Psychiatry Res. - Neuroimaging. 2014;222:111–113. doi: 10.1016/j.pscychresns.2014.02.001. PubMed DOI
Kopell BH, Greenberg B, Rezai AR. Deep Brain Stimulation for Psychiatric Disorders. J. Clin. Neurophysiol. 2004;21:51–67. doi: 10.1097/00004691-200401000-00007. PubMed DOI
Sartorius Alexander, Kiening Karl L., Kirsch Peter, von Gall Carl C., Haberkorn Uwe, Unterberg Andreas W., Henn Fritz A., Meyer-Lindenberg Andreas. Remission of Major Depression Under Deep Brain Stimulation of the Lateral Habenula in a Therapy-Refractory Patient. Biological Psychiatry. 2010;67(2):e9–e11. doi: 10.1016/j.biopsych.2009.08.027. PubMed DOI
Kukleta M, Bob P, Brázdil M, Roman R, Rektor I. The level of frontal-temporal beta-2 band EEG synchronization distinguishes anterior cingulate cortex from other frontal regions. Conscious. Cogn. 2010;19:879–886. doi: 10.1016/j.concog.2010.04.007. PubMed DOI
Brázdil M, et al. Directional functional coupling of cerebral rhythms between anterior cingulate and dorsolateral prefrontal areas during rare stimuli: A directed transfer function analysis of human depth EEG signal. Hum. Brain Mapp. 2009;30:138–146. doi: 10.1002/hbm.20491. PubMed DOI PMC
Kibleur A, et al. Stimulation of subgenual cingulate area decreases limbic top-down effect on ventral visual stream: A DBS-EEG pilot study. Neuroimage. 2017;146:544–553. doi: 10.1016/j.neuroimage.2016.10.018. PubMed DOI
Pereda E, Quiroga RQ, Bhattacharya J. Nonlinear multivariate analysis of neurophysiological signals. Prog. Neurobiol. 2005;77:1–37. doi: 10.1016/j.pneurobio.2005.10.003. PubMed DOI
Seth AK, Barrett AB, Barnett L. Granger Causality Analysis in Neuroscience and Neuroimaging. J. Neurosci. 2015;35:3293–3297. doi: 10.1523/JNEUROSCI.4399-14.2015. PubMed DOI PMC
Granger CWJ. Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica. 1969;37:424–438. doi: 10.2307/1912791. DOI
Leistritz L, et al. Connectivity Analysis of Somatosensory Evoked Potentials in Patients with Major Depression. Methods Inf. Med. 2010;49:484–491. doi: 10.3414/ME09-02-0038. PubMed DOI
Sun, Y., Sijung, H., Chambers, J., Yisheng Z. & Tong, S. Graphic patterns of cortical functional connectivity of depressed patients on the basis of EEG measurements. in 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 1419–1422, 10.1109/IEMBS.2011.6090334 (IEEE, 2011). PubMed
Tang Y, et al. The altered cortical connectivity during spatial search for facial expressions in major depressive disorder. Prog. Neuro-Psychopharmacology Biol. Psychiatry. 2011;35:1891–1900. doi: 10.1016/j.pnpbp.2011.08.006. PubMed DOI
Mao, W., Li, Y., Tang, Y., Li, H. & Wang, J. The coherence changes in the depressed patients in response to different facial expressions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)6064 LNCS, 392–399 (2010).
Wang C, et al. The brain network research of poststroke depression based on partial directed coherence (PDC) Chinese J. Biomed. Eng. 2015;34:385–391.
Sun Y, Li Y, Zhu Y, Chen X, Tong S. Electroencephalographic differences between depressed and control subjects: An aspect of interdependence analysis. Brain Res. Bull. 2008;76:559–564. doi: 10.1016/j.brainresbull.2008.05.001. PubMed DOI
Schoffelen J-M, Gross J. Source connectivity analysis with MEG and EEG. Hum. Brain Mapp. 2009;30:1857–1865. doi: 10.1002/hbm.20745. PubMed DOI PMC
He B, et al. Electrophysiological Brain Connectivity: Theory and Implementation. IEEE Trans. Biomed. Eng. 2019;66:2115–2137. doi: 10.1109/TBME.2019.2913928. PubMed DOI PMC
Coito A, Michel CM, van Mierlo P, Vulliemoz S, Plomp G. Directed Functional Brain Connectivity Based on EEG Source Imaging: Methodology and Application to Temporal Lobe Epilepsy. IEEE Trans. Biomed. Eng. 2016;63:2619–2628. doi: 10.1109/TBME.2016.2619665. PubMed DOI
Sperdin, H. F. et al. Early alterations of social brain networks in young children with autism. Elife7, e31670 (2018). PubMed PMC
Coito A, Michel CM, Vulliemoz S, Plomp G. Directed functional connections underlying spontaneous brain activity. Hum. Brain Mapp. 2019;40:879–888. doi: 10.1002/hbm.24418. PubMed DOI PMC
Milde T, et al. A new Kalman filter approach for the estimation of high-dimensional time-variant multivariate AR models and its application in analysis of laser-evoked brain potentials. Neuroimage. 2010;50:960–969. doi: 10.1016/j.neuroimage.2009.12.110. PubMed DOI
Pessoa L, Adolphs R. Emotion processing and the amygdala: from a ‘low road’ to ‘many roads’ of evaluating biological significance. Nat. Rev. Neurosci. 2010;11:773–782. doi: 10.1038/nrn2920. PubMed DOI PMC
Zheng J, et al. Amygdala-hippocampal dynamics during salient information processing. Nat. Commun. 2017;8:14413. doi: 10.1038/ncomms14413. PubMed DOI PMC
Freese, J. L. & Amaral, D. G. Neuroanatomy of the primate amygdala. - PsycNET. (Guilford Press, 2009).
Kober H, et al. Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies. Neuroimage. 2008;42:998–1031. doi: 10.1016/j.neuroimage.2008.03.059. PubMed DOI PMC
Thomas Yeo BT, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 2011;106:1125–1165. doi: 10.1152/jn.00338.2011. PubMed DOI PMC
Price JL, Drevets WC. Neurocircuitry of Mood Disorders. Neuropsychopharmacology. 2010;35:192–216. doi: 10.1038/npp.2009.104. PubMed DOI PMC
Hamilton JP, Chen MC, Gotlib IH. Neural systems approaches to understanding major depressive disorder: An intrinsic functional organization perspective. Neurobiol. Dis. 2013;52:4–11. doi: 10.1016/j.nbd.2012.01.015. PubMed DOI PMC
Ramasubbu, R. et al. Reduced Intrinsic Connectivity of Amygdala in Adults with Major Depressive Disorder. Front. Psychiatry5, 17 (2014). PubMed PMC
Tang S, et al. Abnormal amygdala resting-state functional connectivity in adults and adolescents with major depressive disorder: A comparative meta-analysis. EBioMedicine. 2018;36:436–445. doi: 10.1016/j.ebiom.2018.09.010. PubMed DOI PMC
Tang S, et al. Anomalous functional connectivity of amygdala subregional networks in major depressive disorder. Depress. Anxiety. 2019;36:712–722. doi: 10.1002/da.22901. PubMed DOI
Zhang XF, He X, Wu L, Liu CJ, Wu W. Altered Functional Connectivity of Amygdala with the Fronto-Limbic-Striatal Circuit in Temporal Lobe Lesion as a Proposed Mechanism for Poststroke Depression. Am. J. Phys. Med. Rehabil. 2019;98:303–310. doi: 10.1097/PHM.0000000000001081. PubMed DOI
Ferdek MA, van Rijn CM, Wyczesany M. Depressive rumination and the emotional control circuit: An EEG localization and effective connectivity study. Cogn. Affect. Behav. Neurosci. 2016;16:1099–1113. doi: 10.3758/s13415-016-0456-x. PubMed DOI PMC
van Eijndhoven P, et al. Amygdala Volume Marks the Acute State in the Early Course of Depression. Biol. Psychiatry. 2009;65:812–818. doi: 10.1016/j.biopsych.2008.10.027. PubMed DOI
Sandu A-L, et al. Amygdala and regional volumes in treatment-resistant versus nontreatment-resistant depression patients. Depress. Anxiety. 2017;34:1065–1071. doi: 10.1002/da.22675. PubMed DOI
Bauer IE, et al. Amygdala enlargement in unaffected offspring of bipolar parents. J. Psychiatr. Res. 2014;59:200–205. doi: 10.1016/j.jpsychires.2014.08.023. PubMed DOI PMC
Inman CS, et al. Direct electrical stimulation of the amygdala enhances declarative memory in humans. Proc. Natl. Acad. Sci. 2018;115:98–103. doi: 10.1073/pnas.1714058114. PubMed DOI PMC
Bijanki KR, et al. Case Report: Stimulation of the Right Amygdala Induces Transient Changes in Affective Bias. Brain Stimul. 2014;7:690–693. doi: 10.1016/j.brs.2014.05.005. PubMed DOI PMC
Tyrand R, Seeck M, Pollo C, Boëx C. Effects of amygdala–hippocampal stimulation on synchronization. Epilepsy Res. 2014;108:327–330. doi: 10.1016/j.eplepsyres.2013.11.024. PubMed DOI
Tyrand R, et al. Effects of amygdala–hippocampal stimulation on interictal epileptic discharges. Epilepsy Res. 2012;99:87–93. doi: 10.1016/j.eplepsyres.2011.10.026. PubMed DOI
Langevin J-P, et al. Deep Brain Stimulation of the Basolateral Amygdala: Targeting Technique and Electrodiagnostic Findings. Brain Sci. 2016;6:28. doi: 10.3390/brainsci6030028. PubMed DOI PMC
Koek RJ, et al. Deep brain stimulation of the basolateral amygdala for treatment-refractory combat post-traumatic stress disorder (PTSD): study protocol for a pilot randomized controlled trial with blinded, staggered onset of stimulation. Trials. 2014;15:356. doi: 10.1186/1745-6215-15-356. PubMed DOI PMC
Sturm V, et al. DBS in the basolateral amygdala improves symptoms of autism and related self-injurious behavior: a case report and hypothesis on the pathogenesis of the disorder. Front. Hum. Neurosci. 2013;6:341. doi: 10.3389/fnhum.2012.00341. PubMed DOI PMC
Admon R, et al. Striatal hypersensitivity during stress in remitted individuals with recurrent depression. Biol. Psychiatry. 2015;78:67–76. doi: 10.1016/j.biopsych.2014.09.019. PubMed DOI PMC
Marchand WR, Yurgelun-Todd D. Striatal structure and function in mood disorders: a comprehensive review. Bipolar Disord. 2010;12:764–785. doi: 10.1111/j.1399-5618.2010.00874.x. PubMed DOI
Bluhm R, et al. Resting state default-mode network connectivity in early depression using a seed region-of-interest analysis: Decreased connectivity with caudate nucleus. Psychiatry Clin. Neurosci. 2009;63:754–761. doi: 10.1111/j.1440-1819.2009.02030.x. PubMed DOI
Butters MA, et al. Three-Dimensional Surface Mapping of the Caudate Nucleus in Late-Life Depression. Am. J. Geriatr. Psychiatry. 2009;17:4–12. doi: 10.1097/JGP.0b013e31816ff72b. PubMed DOI PMC
Ma C, et al. Resting-State Functional Connectivity Bias of Middle Temporal Gyrus and Caudate with Altered Gray Matter Volume in Major Depression. PLoS One. 2012;7:e45263. doi: 10.1371/journal.pone.0045263. PubMed DOI PMC
Krishnan KRR. Magnetic Resonance Imaging of the Caudate Nuclei in Depression. Arch. Gen. Psychiatry. 1992;49:553. doi: 10.1001/archpsyc.1992.01820070047007. PubMed DOI
Tymofiyeva O, et al. DTI-based connectome analysis of adolescents with major depressive disorder reveals hypoconnectivity of the right caudate. J. Affect. Disord. 2017;207:18–25. doi: 10.1016/j.jad.2016.09.013. PubMed DOI PMC
Khundakar A, Morris C, Oakley A, Thomas AJ. Morphometric Analysis of Neuronal and Glial Cell Pathology in the Caudate Nucleus in Late-Life Depression. Am. J. Geriatr. Psychiatry. 2011;19:132–141. doi: 10.1097/JGP.0b013e3181df4642. PubMed DOI
Hannestad J, et al. White matter lesion volumes and caudate volumes in late-life depression. Int. J. Geriatr. Psychiatry. 2006;21:1193–1198. doi: 10.1002/gps.1640. PubMed DOI
Pillay S. A quantitative magnetic resonance imaging study of caudate and lenticular nucleus gray matter volume in primary unipolar major depression: relationship to treatment response and clinical severity. Psychiatry Res. Neuroimaging. 1998;84:61–74. doi: 10.1016/S0925-4927(98)00048-1. PubMed DOI
Price JL, Drevets WC. Neural circuits underlying the pathophysiology of mood disorders. Trends Cogn. Sci. 2012;16:61–71. doi: 10.1016/j.tics.2011.12.011. PubMed DOI
Limbic-cortical dysregulation: a proposed model of depression. J. Neuropsychiatry Clin. Neurosci. 9, 471–481 (1997). PubMed
Pizzagalli DA. Frontocingulate Dysfunction in Depression: Toward Biomarkers of Treatment Response. Neuropsychopharmacology. 2011;36:183–206. doi: 10.1038/npp.2010.166. PubMed DOI PMC
Seeber M, et al. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat. Commun. 2019;10:753. doi: 10.1038/s41467-019-08725-w. PubMed DOI PMC
Aouizerate B, et al. Deep brain stimulation of the ventral caudate nucleus in the treatment of obsessive—compulsive disorder and major depression. J. Neurosurg. 2004;101:682–686. doi: 10.3171/jns.2004.101.4.0682. PubMed DOI
Millet B, et al. Limbic versus cognitive target for deep brain stimulation in treatment-resistant depression: Accumbens more promising than caudate. Eur. Neuropsychopharmacol. 2014;24:1229–1239. doi: 10.1016/j.euroneuro.2014.05.006. PubMed DOI
Grin-Yatsenko VA, Baas I, Ponomarev VA, Kropotov JD. EEG Power Spectra at Early Stages of Depressive Disorders. J. Clin. Neurophysiol. 2009;26:401–406. doi: 10.1097/WNP.0b013e3181c298fe. PubMed DOI
Pollock VE, Schneider LS. Topographic Quantitative EEG in Elderly Subjects with Major Depression. Psychophysiology. 1990;27:438–444. doi: 10.1111/j.1469-8986.1990.tb02340.x. PubMed DOI
Roemer RA, Shagass C, Dubin W, Jaffe R, Siegal L. Quantitative EEG in elderly depressives. Brain Topogr. 1992;4:285–290. doi: 10.1007/BF01135566. PubMed DOI
Kwon JS, Youn T, Jung HY. Right hemisphere abnormalities in major depression: Quantitative electroencephalographic findings before and after treatment. J. Affect. Disord. 1996;40:169–173. doi: 10.1016/0165-0327(96)00057-2. PubMed DOI
Jiang H, et al. Predictability of depression severity based on posterior alpha oscillations. Clin. Neurophysiol. 2016;127:2108–2114. doi: 10.1016/j.clinph.2015.12.018. PubMed DOI
Neumann W-J, et al. Different patterns of local field potentials from limbic DBS targets in patients with major depressive and obsessive compulsive disorder. Mol. Psychiatry. 2014;19:1186–1192. doi: 10.1038/mp.2014.2. PubMed DOI PMC
Mégevand P, et al. Electric source imaging of interictal activity accurately localises the seizure onset zone. J. Neurol. Neurosurg. Psychiatry. 2014;85:38–43. doi: 10.1136/jnnp-2013-305515. PubMed DOI
Michel CM, et al. 128-Channel EEG source imaging in epilepsy: Clinical yield and localization precision. J. Clin. Neurophysiol. 2004;21:71–83. doi: 10.1097/00004691-200403000-00001. PubMed DOI
Attal Y, Schwartz D. Assessment of Subcortical Source Localization Using Deep Brain Activity Imaging Model with Minimum Norm Operators: A MEG Study. PLoS One. 2013;8:59856. doi: 10.1371/journal.pone.0059856. PubMed DOI PMC
Krishnaswamy P, et al. Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG. Proc. Natl. Acad. Sci. USA. 2017;114:E10465–E10474. doi: 10.1073/pnas.1705414114. PubMed DOI PMC
Pizzo F, et al. Deep brain activities can be detected with magnetoencephalography. Nat. Commun. 2019;10:971. doi: 10.1038/s41467-019-08665-5. PubMed DOI PMC
Damborská, A. et al. EEG Resting-State Large-Scale Brain Network Dynamics Are Related to Depressive Symptoms. Front. Psychiatry10, 548 (2019). PubMed PMC
Williams JBW, Kobak KA. Development and reliability of a structured interview guide for the Montgomery-Åsberg Depression Rating Scale (SIGMA) Br. J. Psychiatry. 2008;192:52–58. doi: 10.1192/bjp.bp.106.032532. PubMed DOI
Guy, W. ECDEU assessment manual for psychopharmacology. (U.S. Dept. of Health Education and Welfare Public Health Service Alcohol Drug Abuse and Mental Health Administration National Institute of Mental Health Psychopharmacology Research Branch, 1976).
Jung T-P, et al. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clin. Neurophysiol. 2000;111:1745–1758. doi: 10.1016/S1388-2457(00)00386-2. PubMed DOI
Perrin F, Pernier J, Bertrand O, Echallier JF. Spherical splines for scalp potential and current density mapping. Electroencephalogr. Clin. Neurophysiol. 1989;72:184–187. doi: 10.1016/0013-4694(89)90180-6. PubMed DOI
The Cartool Community group. Available: cartoolcommunity.unige.ch.
Grave de Peralta Menendez R, Murray MM, Michel CM, Martuzzi R, Gonzalez Andino SL. Electrical neuroimaging based on biophysical constraints. Neuroimage. 2004;21:527–539. doi: 10.1016/j.neuroimage.2003.09.051. PubMed DOI
Michel CM, Brunet D. EEG Source Imaging: A Practical Review of the Analysis Steps. Front. Neurol. 2019;10:325. doi: 10.3389/fneur.2019.00325. PubMed DOI PMC
Spinelli L, Andino SG, Lantz G, Seeck M, Michel CM. Electromagnetic Inverse Solutions in Anatomically Constrained Spherical Head Models. Brain Topogr. 2000;13:115–125. doi: 10.1023/A:1026607118642. PubMed DOI
Tzourio-Mazoyer N, et al. Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. Neuroimage. 2002;15:273–289. doi: 10.1006/nimg.2001.0978. PubMed DOI
Rubega M., Carboni M., Seeber M., Pascucci D., Tourbier S., Toscano G., Van Mierlo P., Hagmann P., Plomp G., Vulliemoz S., Michel C. M. Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis. Brain Topography. 2018;32(4):704–719. doi: 10.1007/s10548-018-0691-2. PubMed DOI
Rubega M. et al. Time-varying effective EEG source connectivity: The optimization of model parameters. In 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE (2019). PubMed
Takahashi DY, Baccalá LA, Sameshima K. Information theoretic interpretation of frequency domain connectivity measures. Biol. Cybern. 2010;103:463–469. doi: 10.1007/s00422-010-0410-x. PubMed DOI
Sameshima, K., Baccala, L. A. & Baccala, L. A. Methods in Brain Connectivity Inference through Multivariate Time Series Analysis. 20145078, (CRC Press, 2014).
Vettoretti M, Facchinetti A, Sparacino G, Cobelli C. Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments. IEEE Trans. Biomed. Eng. 2018;65:1281–1290. doi: 10.1109/TBME.2017.2746340. PubMed DOI
Man CD, et al. The UVA/PADOVA Type 1 Diabetes Simulator. J. Diabetes Sci. Technol. 2014;8:26–34. doi: 10.1177/1932296813514502. PubMed DOI PMC
Available, http://www.brain-connectivity-toolbox.net.
Bullmore E, Sporns O. The economy of brain network organization. Nat. Rev. Neurosci. 2012;13:336–349. doi: 10.1038/nrn3214. PubMed DOI
Latora V, Marchiori M. Efficient Behavior of Small-World Networks. Phys. Rev. Lett. 2001;87:198701. doi: 10.1103/PhysRevLett.87.198701. PubMed DOI
Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature. 1998;393:440–442. doi: 10.1038/30918. PubMed DOI
Fagiolo G. Clustering in complex directed networks. Phys. Rev. E. 2007;76:026107. doi: 10.1103/PhysRevE.76.026107. PubMed DOI
Babiloni F, et al. Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function. Neuroimage. 2005;24:118–131. doi: 10.1016/j.neuroimage.2004.09.036. PubMed DOI
Bazire, S. Benzodiazepine equivalent doses. Psychotropic Drug Directory. (Lloyd-Reinhold Communications, 2014).