Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Functional connectivity of the amygdala subnuclei in various mood states of bipolar disorder

Molecular Psychiatry (2024)Cite this article

Subjects

Abstract

Amygdala functional dysconnectivity lies at the heart of the pathophysiology of bipolar disorder (BD). Recent preclinical studies suggest that the amygdala is a heterogeneous group of nuclei, whose specific connectivity could drive positive or negative emotional valence. We investigated functional connectivity (FC) changes within these circuits emerging from each amygdala’s subdivision in 127 patients with BD in different mood states and 131 healthy controls (HC), who underwent resting-state functional MRI. FC was evaluated between lateral and medial nuclei of amygdalae, and key subcortical regions of the emotion processing network: anterior and posterior parts of the hippocampus, and core and shell parts of the nucleus accumbens. FC was compared across groups, and subgroups of patients depending on their mood states, using linear mixed models. We also tested correlations between FC and depression (MADRS) and mania (YMRS) scores. We found no difference between the whole sample of BD patients vs. HC but a significant correlation between MADRS and right lateral amygdala /right anterior hippocampus, right lateral amygdala/right posterior hippocampus and right lateral amygdala/left anterior hippocampus FC (r = −0.44, r = −0.32, r = −0.27, respectively, all pFDR<0.05). Subgroup analysis revealed decreased right lateral amygdala/right anterior hippocampus and right lateral amygdala/right posterior hippocampus FC in depressed vs. non-depressed patients and increased left medial amygdala/shell part of the left nucleus accumbens FC in manic vs non-manic patients. These results demonstrate that acute mood states in BD concur with FC changes in individual nuclei of the amygdala implicated in distinct emotional valence processing. Overall, our data highlight the importance to consider the amygdala subnuclei separately when studying its FC patterns including patients in distinct homogeneous mood states.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Illustration of the ROIs extracted from the Tian et al. (2020) atlas of subcortical regions, projected on sagittal, coronal, and axial T1-weighted images.
Fig. 2: Scatterplots of the significant correlations between the MADRS scores and the functional connectivity between the lateral amygdala and the hippocampus subdivisions.
Fig. 3: Illustration of the subgroups results.

Similar content being viewed by others

Code availability

All codes written in support of this publication are publicly available at https://github.com/eniluap/Krystal_et_al_2024.

References

  1. Pignatelli M, Beyeler A. Valence coding in amygdala circuits. Curr Opin Behav Sci. Avr. 2019;26:97–106. https://doi.org/10.1016/j.cobeha.2018.10.010.

    Article  Google Scholar 

  2. O’Neill PK, Gore F, Salzman CD. Basolateral amygdala circuitry in positive and negative valence. Curr Opin Neurobiol. 2018;49:175–83. https://doi.org/10.1016/j.conb.2018.02.012.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Beyeler A, Namburi P, Glober GF, Simonnet C, Calhoon GG, Conyers GF, et al. Divergent Routing of Positive and Negative Information from the Amygdala during Memory Retrieval. Neuron. 2016;90:348–61. https://doi.org/10.1016/j.neuron.2016.03.004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Paton JJ, Belova MA, Morrison SE, Salzman CD. The primate amygdala represents the positive and negative value of visual stimuli during learning. Nature. 2006;439:865–70. https://doi.org/10.1038/nature04490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Shabel SJ, Janak PH. Substantial similarity in amygdala neuronal activity during conditioned appetitive and aversive emotional arousal. Proc Natl Acad Sci USA. 2009;106:15031–6. https://doi.org/10.1073/pnas.0905580106.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Gore F, Schwartz EC, Brangers BC, Aladi S, Stujenske JM, Likhtik E, et al. Neural Representations of Unconditioned Stimuli in Basolateral Amygdala Mediate Innate and Learned Responses. Cell. 2015;162:134–45. https://doi.org/10.1016/j.cell.2015.06.027.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Namburi P, Beyeler A, Yorozu S, Calhoon GG, Halbert SA, Wichmann R, et al. A circuit mechanism for differentiating positive and negative associations. Nature. 2015;520:675–8. https://doi.org/10.1038/nature14366.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhang W, Schneider DM, Belova MA, Morrison SE, Paton JJ, Salzman CD. Functional circuits and anatomical distribution of response properties in the primate amygdala. J Neurosci Off J Soc Neurosci. 2013;33:722–33. https://doi.org/10.1523/JNEUROSCI.2970-12.2013.

    Article  CAS  Google Scholar 

  9. Kim J, Pignatelli M, Xu S, Itohara S, Tonegawa S. Antagonistic negative and positive neurons of the basolateral amygdala. Nat Neurosci. 2016;19:1636–46. https://doi.org/10.1038/nn.4414.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Beyeler A, Chang CJ, Silvestre M, Lévêque C, Namburi P, Wildes CP, et al. Organization of Valence-Encoding and Projection-Defined Neurons in the Basolateral Amygdala. Cell Rep. 2018;22:905–18. https://doi.org/10.1016/j.celrep.2017.12.097.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Felix-Ortiz AC, Beyeler A, Seo C, Leppla CA, Wildes CP, Tye KM. BLA to vHPC inputs modulate anxiety-related behaviors. Neuron. 2013;79:658–64. https://doi.org/10.1016/j.neuron.2013.06.016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Li H, Namburi P, Olson JM, Borio M, Lemieux ME, Beyeler A, et al. Neurotensin orchestrates valence assignment in the amygdala. Nature. 2022;608:586–92. https://doi.org/10.1038/s41586-022-04964-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shen CJ, Zheng D, Li KX, Yang JM, Pan HQ, Yu XD, et al. Cannabinoid CB1 receptors in the amygdalar cholecystokinin glutamatergic afferents to nucleus accumbens modulate depressive-like behavior. Nat Med. 2019;25:337–49. https://doi.org/10.1038/s41591-018-0299-9. FebErratum in: Nat Med. 2019 Jan 30: PMID: 30643290.

    Article  CAS  PubMed  Google Scholar 

  14. Zhou K, Xu H, Lu S, Jiang S, Hou G, Deng X, et al. Reward and aversion processing by input-defined parallel nucleus accumbens circuits in mice. Nat Commun. 2022;13:6244 https://doi.org/10.1038/s41467-022-33843-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bigot M, Alonso M, Houenou J, Sarrazin S, Dargél AA, Lledo PM, et al. An emotional-response model of bipolar disorders integrating recent findings on amygdala circuits. Neurosci Biobehav Rev. 2020;118:358–66. https://doi.org/10.1016/j.neubiorev.2020.07.037.

    Article  PubMed  Google Scholar 

  16. Phillips ML, Ladouceur CD, Drevets WC. A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Mol Psychiatry. 2008;13:833–57. https://doi.org/10.1038/mp.2008.65.

    Article  Google Scholar 

  17. Strakowski SM, Adler CM, Almeida J, Altshuler LL, Blumberg HP, Chang KD, et al. The functional neuroanatomy of bipolar disorder: a consensus model. Bipolar Disord. 2012;14:313–25. https://doi.org/10.1111/j.1399-5618.2012.01022.x.

    Article  PubMed  Google Scholar 

  18. Lawrence NS, Williams AM, Surguladze S, Giampietro V, Brammer MJ, Andrew C, et al. Subcortical and ventral prefrontal cortical neural responses to facial expressions distinguish patients with bipolar disorder and major depression. Biol Psychiatry. 2004;55:578–87. https://doi.org/10.1016/j.biopsych.2003.11.017.

    Article  PubMed  Google Scholar 

  19. Blumberg HP, Fredericks C, Wang F, Kalmar JH, Spencer L, Papademetris X, et al. Preliminary evidence for persistent abnormalities in amygdala volumes in adolescents and young adults with bipolar disorder. Bipolar Disord. 2005;7:570–6. https://doi.org/10.1111/j.1399-5618.2005.00264.x.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Anand A, Li Y, Wang Y, Lowe MJ, Dzemidzic M. Resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder and unipolar depression. Psychiatry Res. 2009;171:189–98. https://doi.org/10.1016/j.pscychresns.2008.03.012.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Chepenik LG, Raffo M, Hampson M, Lacadie C, Wang F, Jones MM, et al. Functional connectivity between ventral prefrontal cortex and amygdala at low frequency in the resting state in bipolar disorder. Psychiatry Res. 2010;182:207–10. https://doi.org/10.1016/j.pscychresns.2010.04.002.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Dickstein DP, Gorrostieta C, Ombao H, Goldberg LD, Brazel AC, Gable CJ, et al. Fronto-Temporal Spontaneous Resting State Functional Connectivity in Pediatric Bipolar Disorder. Biol Psychiatry. 2010;68:839–46. https://doi.org/10.1016/j.biopsych.2010.06.029.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Anticevic A, Brumbaugh MS, Winkler AM, Lombardo LE, Barrett J, Corlett PR, et al. Global prefrontal and fronto-amygdala dysconnectivity in bipolar I disorder with psychosis history. Biol Psychiatry. 2013;73:565–73. https://doi.org/10.1016/j.biopsych.2012.07.031.

    Article  PubMed  Google Scholar 

  24. Torrisi S, Moody TD, Vizueta N, Thomason ME, Monti MM, Townsend JD, et al. Differences in resting corticolimbic functional connectivity in bipolar I euthymia. Bipolar Disord. 2013;15:156–66. https://doi.org/10.1111/bdi.12047.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Favre P, Baciu M, Pichat C, Bougerol T, Polosan M. fMRI evidence for abnormal resting-state functional connectivity in euthymic bipolar patients. J Affect Disord. 2014;165:182–9. https://doi.org/10.1016/j.jad.2014.04.054.

    Article  PubMed  Google Scholar 

  26. Brady RO, Masters GA, Mathew IT, Margolis A, Cohen BM, Öngür D, et al. State dependent cortico-amygdala circuit dysfunction in bipolar disorder. J Affect Disord. 2016;201:79–87. https://doi.org/10.1016/j.jad.2016.04.052.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Altinay M, Karne H, Anand A. Lithium monotherapy associated clinical improvement effects on amygdala-ventromedial prefrontal cortex resting state connectivity in bipolar disorder. J Affect Disord. 2018;225:4–12. https://doi.org/10.1016/j.jad.2017.06.047.

    Article  CAS  PubMed  Google Scholar 

  28. Tang Y, Ma Y, Chen X, Fan X, Jiang X, Zhou Y, et al. Age-specific effects of structural and functional connectivity in prefrontal-amygdala circuitry in women with bipolar disorder. BMC Psychiatry. 2018;18:177 https://doi.org/10.1186/s12888-018-1732-9.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lee I, Nielsen K, Nawaz U, Hall MH, Öngür D, Keshavan M, et al. Diverse pathophysiological processes converge on network disruption in mania. J Affect Disord. 2019;244:115–23. https://doi.org/10.1016/j.jad.2018.10.087.

    Article  PubMed  Google Scholar 

  30. Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry J Ment Sci. 1978;133:429–35. https://doi.org/10.1192/bjp.133.5.429.

    Article  CAS  Google Scholar 

  31. Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry J Ment Sci. 1979;134:382–9. https://doi.org/10.1192/bjp.134.4.382.

    Article  CAS  Google Scholar 

  32. Weiner L, Ossola P, Causin JB, Desseilles M, Keizer I, Metzger JY, et al. Racing thoughts revisited: A key dimension of activation in bipolar disorder. J Affect Disord. 2019;255:69–76. https://doi.org/10.1016/j.jad.2019.05.033.

    Article  PubMed  Google Scholar 

  33. Herrmann N, Black SE, Lawrence J, Szekely C, Szalai JP. The Sunnybrook Stroke Study: a prospective study of depressive symptoms and functional outcome. Stroke. 1998;29:618–24. https://doi.org/10.1161/01.str.29.3.618.

    Article  CAS  PubMed  Google Scholar 

  34. Duarte-Guerra LS, Gorenstein C, Paiva-Medeiros PF, Santo MA, Lotufo Neto F, Wang YP. Clinical utility of the Montgomery-Åsberg Depression Rating Scale for the detection of depression among bariatric surgery candidates. BMC Psychiatry. 2016;16:119 https://doi.org/10.1186/s12888-016-0823-8.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Esteban O, Markiewicz CJ, Blair RW, Moodie CA, Isik AI, Erramuzpe A, et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods. 2019;16:111–6. https://doi.org/10.1038/s41592-018-0235-4.

    Article  CAS  PubMed  Google Scholar 

  36. Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R. Movement-related effects in fMRI time-series. Magn Reson Med. 1996;35:346–55. https://doi.org/10.1002/mrm.1910350312.

    Article  CAS  PubMed  Google Scholar 

  37. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA. 2005;102:9673–8. https://doi.org/10.1073/pnas.0504136102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? NeuroImage. 2009;44:893–905. https://doi.org/10.1016/j.neuroimage.2008.09.036.

    Article  PubMed  Google Scholar 

  39. Yang GJ, Murray JD, Repovs G, Cole MW, Savic A, Glasser MF, et al. Altered global brain signal in schizophrenia. Proc Natl Acad Sci USA. 2014;111:7438–43. https://doi.org/10.1073/pnas.1405289111.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Abraham A, Pedregosa F, Eickenberg M, Gervais P, Mueller A, Kossaifi J, et al. Machine learning for neuroimaging with scikit-learn. Front Neuroinform. 2014;8:14 https://doi.org/10.3389/fninf.2014.00014.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage. 2012;59:2142–54. https://doi.org/10.1016/j.neuroimage.2011.10.018.

    Article  PubMed  Google Scholar 

  42. Ciric R, Nomi JS, Uddin LQ, Satpute AB. Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks. Sci Rep. 2017;7:6537 https://doi.org/10.1038/s41598-017-06866-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Parkes L, Fulcher B, Yücel M, Fornito A. An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage. 2018;171:415–36. https://doi.org/10.1016/j.neuroimage.2017.12.073.

    Article  PubMed  Google Scholar 

  44. Fan Z, Yang J, Zeng C, Xi C, Wu G, Guo S, et al. Bipolar Mood State Reflected in Functional Connectivity of the Hate Circuit: A Resting-State Functional Magnetic Resonance Imaging Study. Front Psychiatry. 2020;11:556126 https://doi.org/10.3389/fpsyt.2020.556126.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Tian Y, Margulies DS, Breakspear M, Zalesky A. Topographic organization of the human subcortex unveiled with functional connectivity gradients. Nat Neurosci. 2020;23:1421–32. https://doi.org/10.1038/s41593-020-00711-6.

    Article  CAS  PubMed  Google Scholar 

  46. Bates D, Mächler M, Bolker B, Walker S. “Fitting Linear Mixed-Effects Models Using lme4”. J Stat Softw. 2015;67:1–48. https://doi.org/10.18637/jss.v067.i01.

    Article  Google Scholar 

  47. Saunders RC, Rosene DL, Van Hoesen GW. Comparison of the efferents of the amygdala and the hippocampal formation in the rhesus monkey: II. Reciprocal and non-reciprocal connections. J Comp Neurol. 1988;271:185–207. https://doi.org/10.1002/cne.902710203.

    Article  CAS  PubMed  Google Scholar 

  48. Nieuwenhuys R, Voogd J, van Huijzen C, editors. Telencephalon: Hippocampus and Related Structures. In: The Human Central Nervous System [Internet]. Berlin, Heidelberg: Springer [cited 2022 Nov 27]. 361–400. https://doi.org/10.1007/978-3-540-34686-9_12 (2008).

  49. Paré D, Collins DR, Pelletier JG. Amygdala oscillations and the consolidation of emotional memories. Trends Cogn Sci. 2002;6:306–14. https://doi.org/10.1016/s1364-6613(02)01924-1.

    Article  PubMed  Google Scholar 

  50. Ritchey M, Dolcos F, Cabeza R. Role of amygdala connectivity in the persistence of emotional memories over time: an event-related FMRI investigation. Cereb Cortex N Y N 1991. 2008;18:2494–504. https://doi.org/10.1093/cercor/bhm262.

    Article  Google Scholar 

  51. McGaugh JL. Memory consolidation and the amygdala: a systems perspective. Trends Neurosci. 2002;25:456 https://doi.org/10.1016/s0166-2236(02)02211-7.

    Article  CAS  PubMed  Google Scholar 

  52. Phelps EA. Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr Opin Neurobiol. 2004;14:198–202. https://doi.org/10.1016/j.conb.2004.03.015.

    Article  CAS  PubMed  Google Scholar 

  53. Fastenrath M, Coynel D, Spalek K, Milnik A, Gschwind L, Roozendaal B, et al. Dynamic modulation of amygdala-hippocampal connectivity by emotional arousal. J Neurosci Off J Soc Neurosci. 2014;34:13935–47. https://doi.org/10.1523/JNEUROSCI.0786-14.2014.

    Article  CAS  Google Scholar 

  54. Dolcos F, LaBar KS, Cabeza R. Remembering one year later: role of the amygdala and the medial temporal lobe memory system in retrieving emotional memories. Proc Natl Acad Sci USA. 2005;102:2626–31. https://doi.org/10.1073/pnas.0409848102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Greenberg DL, Rice HJ, Cooper JJ, Cabeza R, Rubin DC, Labar KS. Co-activation of the amygdala, hippocampus and inferior frontal gyrus during autobiographical memory retrieval. Neuropsychologia. 2005;43:659–74. https://doi.org/10.1016/j.neuropsychologia.2004.09.002.

    Article  PubMed  Google Scholar 

  56. Smith APR, Stephan KE, Rugg MD, Dolan RJ. Task and content modulate amygdala-hippocampal connectivity in emotional retrieval. Neuron. 2006;49:631–8. https://doi.org/10.1016/j.neuron.2005.12.025.

    Article  CAS  PubMed  Google Scholar 

  57. Zhu Y, Gao H, Tong L, Li Z, Wang L, Zhang C, et al. Emotion Regulation of Hippocampus Using Real-Time fMRI Neurofeedback in Healthy Human. Front Hum Neurosci. 2019;13:242 https://doi.org/10.3389/fnhum.2019.00242.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Li M, Huang C, Deng W, Ma X, Han Y, Wang Q, et al. Contrasting and convergent patterns of amygdala connectivity in mania and depression: a resting-state study. J Affect Disord. 2015;173:53–8. https://doi.org/10.1016/j.jad.2014.10.044.

    Article  PubMed  Google Scholar 

  59. Singh MK, Kelley RG, Chang KD, Gotlib IH. Intrinsic Amygdala Functional Connectivity in Youth With Bipolar I Disorder. J Am Acad Child Adolesc Psychiatry. 2015;54:763–70. https://doi.org/10.1016/j.jaac.2015.06.016.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Luking KR, Repovs G, Belden AC, Gaffrey MS, Botteron KN, Luby JL, et al. Functional connectivity of the amygdala in early-childhood-onset depression. J Am Acad Child Adolesc Psychiatry. 2011;50:1027–41.e3. https://doi.org/10.1016/j.jaac.2011.07.019.

    Article  PubMed  PubMed Central  Google Scholar 

  61. van der Werff SJA, Pannekoek JN, Veer IM, van Tol MJ, Aleman A, Veltman DJ, et al. Resting-state functional connectivity in adults with childhood emotional maltreatment. Psychol Med. 2013;43:1825–36. https://doi.org/10.1017/S0033291712002942.

    Article  PubMed  Google Scholar 

  62. Cullen KR, Westlund MK, Klimes-Dougan B, Mueller BA, Houri A, Eberly LE, et al. Abnormal amygdala resting-state functional connectivity in adolescent depression. JAMA Psychiatry. 2014;71:1138–47. https://doi.org/10.1001/jamapsychiatry.2014.1087.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Zeng LL, Shen H, Liu L, Wang L, Li B, Fang P, et al. Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain J Neurol. 2012;135:1498–507. https://doi.org/10.1093/brain/aws059.

    Article  Google Scholar 

  64. Ambrosi E, Arciniegas DB, Madan A, Curtis KN, Patriquin MA, Jorge RE, et al. Insula and amygdala resting-state functional connectivity differentiate bipolar from unipolar depression. Acta Psychiatr Scand. 2017;136:129–39. https://doi.org/10.1111/acps.12724.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Hamilton JP, Gotlib IH. Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biol Psychiatry. 2008;63:1155–62. https://doi.org/10.1016/j.biopsych.2007.12.015.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Magioncalda P, Martino M, Conio B, Escelsior A, Piaggio N, Presta A, et al. Functional connectivity and neuronal variability of resting state activity in bipolar disorder-reduction and decoupling in anterior cortical midline structures. Hum Brain Mapp. 2015;36:666–82. https://doi.org/10.1002/hbm.22655.

    Article  PubMed  Google Scholar 

  67. Liu C, Pu W, Wu G, Zhao J, Xue Z. Abnormal resting-state cerebral-limbic functional connectivity in bipolar depression and unipolar depression. BMC Neurosci. 2019;20:30 https://doi.org/10.1186/s12868-019-0508-6.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Gong J, Chen G, Jia Y, Zhong S, Zhao L, Luo X, et al. Disrupted functional connectivity within the default mode network and salience network in unmedicated bipolar II disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2019;88:11–18. https://doi.org/10.1016/j.pnpbp.2018.06.012.

    Article  PubMed  Google Scholar 

  69. Wang J, Wang Y, Wu X, Huang H, Jia Y, Zhong S, et al. Shared and specific functional connectivity alterations in unmedicated bipolar and major depressive disorders based on the triple-network model. Brain Imaging Behav. 2020;14:186–99. https://doi.org/10.1007/s11682-018-9978-x.

    Article  CAS  PubMed  Google Scholar 

  70. Marchand WR, Lee JN, Johnson S, Gale P, Thatcher J. Abnormal functional connectivity of the medial cortex in euthymic bipolar II disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2014;51:28–33. https://doi.org/10.1016/j.pnpbp.2014.01.004.

    Article  PubMed  Google Scholar 

  71. Rodríguez-Cano E, Alonso-Lana S, Sarró S, Fernández-Corcuera P, Goikolea JM, Vieta E, et al. Differential failure to deactivate the default mode network in unipolar and bipolar depression. Bipolar Disord. 2017;19:386–95. https://doi.org/10.1111/bdi.12517.

    Article  CAS  PubMed  Google Scholar 

  72. Brandt CL, Eichele T, Melle I, Sundet K, Server A, Agartz I, et al. Working memory networks and activation patterns in schizophrenia and bipolar disorder: comparison with healthy controls. Br J Psychiatry. 2014;204:290–8. https://doi.org/10.1192/bjp.bp.113.129254.

    Article  PubMed  Google Scholar 

  73. Rey G, Piguet C, Benders A, Favre S, Eickhoff SB, Aubry JM, et al. Resting-state functional connectivity of emotion regulation networks in euthymic and non-euthymic bipolar disorder patients. Eur Psychiatry. 2016;34:56–63. https://doi.org/10.1016/j.eurpsy.2015.12.005.

    Article  CAS  PubMed  Google Scholar 

  74. Yoon S, Kim TD, Kim J, Lyoo IK. Altered functional activity in bipolar disorder: A comprehensive review from a large-scale network perspective. Brain Behav. 2021;11:e01953 https://doi.org/10.1002/brb3.1953.

    Article  PubMed  Google Scholar 

  75. Pi G, Gao D, Wu D, Wang Y, Lei H, Zeng W, et al. Posterior basolateral amygdala to ventral hippocampal CA1 drives approach behaviour to exert an anxiolytic effect. Nat Commun. 2020;11:183 https://doi.org/10.1038/s41467-019-13919-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Janak PH, Tye KM. From circuits to behaviour in the amygdala. Nature. 2015;517:284–92. https://doi.org/10.1038/nature14188.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Hall J, Parkinson JA, Connor TM, Dickinson A, Everitt BJ. Involvement of the central nucleus of the amygdala and nucleus accumbens core in mediating Pavlovian influences on instrumental behaviour. Eur J Neurosci. 2001;13:1984–92. https://doi.org/10.1046/j.0953-816x.2001.01577.x.

    Article  CAS  PubMed  Google Scholar 

  78. Wang Y, Liu Z, Cai L, Guo R, Dong Y, Huang YH. A Critical Role of Basolateral Amygdala-to-Nucleus Accumbens Projection in Sleep Regulation of Reward Seeking. Biol Psychiatry. 2020;87:954–66. https://doi.org/10.1016/j.biopsych.2019.10.027.

    Article  CAS  PubMed  Google Scholar 

  79. Heller AS, Cohen AO, Dreyfuss MFW, Casey BJ. Changes in cortico-subcortical and subcortico-subcortical connectivity impact cognitive control to emotional cues across development. Soc Cogn Affect Neurosci. 2016;11:1910–8. https://doi.org/10.1093/scan/nsw097.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Almeida JRC, Versace A, Hassel S, Kupfer DJ, Phillips ML. Elevated amygdala activity to sad facial expressions: a state marker of bipolar but not unipolar depression. Biol Psychiatry. 2010;67:414–21. https://doi.org/10.1016/j.biopsych.2009.09.027.

    Article  PubMed  Google Scholar 

  81. Eickhoff SB, Yeo BTT, Genon S. Imaging-based parcellations of the human brain. Nat Rev Neurosci. 2018;19:672–86. https://doi.org/10.1038/s41583-018-0071-7.

    Article  CAS  PubMed  Google Scholar 

  82. Saygin ZM, Kliemann D, Iglesias JE, van der Kouwe AJW, Boyd E, Reuter M, et al. High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas. NeuroImage. 2017;155:370–82. https://doi.org/10.1016/j.neuroimage.2017.04.046.

    Article  CAS  PubMed  Google Scholar 

  83. Šimić G, Tkalčić M, Vukić V, Mulc D, Španić E, Šagud M, et al. Understanding Emotions: Origins and Roles of the Amygdala. Biomolecules. 2021;11:823 https://doi.org/10.3390/biom11060823.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Lydersen S Balanced or imbalanced samples? Tidsskr Nor Laegeforen. Sep 17;138. English, Norwegian. https://doi.org/10.4045/tidsskr.18.0539 (2018).

  85. Hafeman DM, Chang KD, Garrett AS, Sanders EM, Phillips ML. Effects of medication on neuroimaging findings in bipolar disorder: an updated review. Bipolar Disord. 2012;14:375–410. https://doi.org/10.1111/j.1399-5618.2012.01023.x.

    Article  PubMed  Google Scholar 

  86. Boissoneault J, Stennett B, Robinson ME. Acute alcohol intake alters resting state functional connectivity of nucleus accumbens with pain-related corticolimbic structures. Drug Alcohol Depend. 2020;207:107811 https://doi.org/10.1016/j.drugalcdep.2019.107811.

    Article  PubMed  Google Scholar 

  87. Scofield MD, Heinsbroek JA, Gipson CD, Kupchik YM, Spencer S, Smith AC, et al. The Nucleus Accumbens: Mechanisms of Addiction across Drug Classes Reflect the Importance of Glutamate Homeostasis. Pharmacol Rev. 2016;68:816–71. https://doi.org/10.1124/pr.116.012484.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Shin LM, Liberzon I. The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology. 2010;35:169–91. https://doi.org/10.1038/npp.2009.83.

    Article  PubMed  Google Scholar 

  89. Power JD, Mitra A, Laumann TO, Snyder AZ, Schlaggar BL, Petersen SE. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage. 2014;84:320–41. https://doi.org/10.1016/j.neuroimage.2013.08.048.

    Article  PubMed  Google Scholar 

  90. Sripada C, Rutherford S, Angstadt M, Thompson WK, Luciana M, Weigard A, et al. Prediction of neurocognition in youth from resting state fMRI. Mol Psychiatry. 2020;25:3413–21. https://doi.org/10.1038/s41380-019-0481-6.

    Article  PubMed  Google Scholar 

  91. Saleem A, Harmata G, Jain S, Voss MW, Fiedorowicz JG, Williams A, et al. Functional Connectivity of the Cerebellar Vermis in Bipolar Disorder and Associations with Mood. Frontiers in Psychiatry. 2023;14:1147540 https://doi.org/10.1101/2023.02.02.526878.

  92. Midway S, Robertson M, Flinn S, Kaller M. Comparing multiple comparisons: practical guidance for choosing the best multiple comparisons test. PeerJ. 2020;8:e10387 https://doi.org/10.7717/peerj.10387.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Allen M, Poggiali D, Whitaker K, Marshall TR, Kievit R. Raincloud plots: a multi-platform tool for robust data visualization. Wellcome Open Research, 2019 Psychiatry. 2014;71:1138–47. https://doi.org/10.12688/wellcomeopenres.15191.2.

    Article  Google Scholar 

Download references

Acknowledgements

The study was supported by research grants from the Grenoble University Hospital, the French University Institute, the Grenoble Cognition Center, and the Health and Society Research Network of the Pierre Mendès-France University (Grenoble). The Grenoble MRI facility IRMaGe/ Neurophysiology was partly funded by the French program “Investissement d’Avenir” run by the “Agence Nationale pour la Recherche”. SK was partially funded by a grant “Société Française de Radiologie – Alain Rahmouni”. The Paris site was funded by a grant “Infrastructure d’avenir en Biologie Santé”—ANR-11-INBS-0006” and the Agence Nationale pour la Recherche (ANR-11-IDEX-0004 Labex BioPsy, ANR-10-COHO-10-01 psyCOH), Fondation pour la Recherche Médicale (Bioinformatique pour la biologie 2014) and the Fondation de l’Avenir (Recherche Médicale Appliquée 2014). This work was also supported by the Swiss National Center of Competence in Research; “Synapsy: the Synaptic Basis of Mental Diseases” financed by the Swiss National Science Foundation [Grant Number 51NF40-158776], as well as a grant of the Swiss National Science Foundation [Grant Number 32003B_156914].

Author information

Authors and Affiliations

  1. Neurospin, UNIACT lab, PsyBrain team, CEA Paris-Saclay, Gif-sur-Yvette, France

    Sidney Krystal, Josselin Houenou & Pauline Favre

  2. Hôpital Fondation Adolphe de Rothschild, Radiology Department, Paris, France

    Sidney Krystal, Laure Gracia & Julien Savatovsky

  3. CHU Lille, Neuroradiology Department, Lille, France

    Sidney Krystal

  4. Translational Neuropsychiatry team, Université Paris-Est Créteil, INSERM U955, Créteil, France

    Sidney Krystal, Josselin Houenou & Pauline Favre

  5. Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland

    Camille Piguet

  6. Université Paris Cité, Paris, France

    Chantal Henry

  7. GHU psychiatrie & neurosciences, Paris, France

    Chantal Henry

  8. Institut Pasteur, Université Paris Cité, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 3571, Perception and Memory Unit, F-75015, Paris, France

    Chantal Henry & Mariana Alonso

  9. CHU Grenoble Alpes, Univ. Grenoble Alpes, 38000, Grenoble, France

    Mircea Polosan

  10. Grenoble Institut Neurosciences, INSERM U1216, 38000, Grenoble, France

    Mircea Polosan

  11. Fondation FondaMental, Créteil, France

    Mircea Polosan, Josselin Houenou & Pauline Favre

  12. DMU IMPACT de Psychiatrie et d’Addictologie, Faculté de Médecine de Créteil, APHP, Hôp Universitaires Mondor, Créteil, France

    Josselin Houenou

Authors
  1. Sidney Krystal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laure Gracia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Camille Piguet
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chantal Henry
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mariana Alonso
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mircea Polosan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Julien Savatovsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Josselin Houenou
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Pauline Favre
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

P.F., J.H., C.H. and M.A. formulated the research question. S.K., J.H. and P.F. conceptualized the project, and designed the study and methods. C.P., M.P., J.H. and P.F. collected the neuroimaging data, and performed the clinical assessment of participants. J.S. provided institutional support. S.K. and L.G. analyzed the data under the supervision of P.F., S.K. wrote the first draft of the manuscript. All the authors reviewed the manuscript and provided critical input.

Corresponding author

Correspondence to Pauline Favre.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krystal, S., Gracia, L., Piguet, C. et al. Functional connectivity of the amygdala subnuclei in various mood states of bipolar disorder. Mol Psychiatry (2024). https://doi.org/10.1038/s41380-024-02580-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41380-024-02580-y

Search

Advanced search

Quick links