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Gender and task type effects on the neural network of emotional prosody processing
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  • Published: 02 February 2026

Gender and task type effects on the neural network of emotional prosody processing

  • Pinyuan Hu1,
  • Xiaochen Sun2,
  • Xingyu Ouyang2,
  • Xinyu Zhang2,
  • Shaoling Peng  ORCID: orcid.org/0000-0003-3725-68113,4,
  • Yuwei Su  ORCID: orcid.org/0000-0002-4412-094X1,
  • Min Lan1,
  • Wenjiang Zhang1 &
  • …
  • Suyu Zhong  ORCID: orcid.org/0000-0003-0252-39161,5 

Communications Biology , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Language
  • Neuroscience

Abstract

Emotional prosody (EP) processing is vital for social communication. Seed-based functional connectivity has been widely used to probe its neural basis, yet most studies rely on part of predefined regions, introducing uncertainty and bias. Furthermore, although gender and task type modulate its activation pattern, their network-level impact remains unclear. Using activation network mapping (a network-level analogue of meta-analysis), we identified a unified EP network and delineated its modulation by gender and task types (explicit or implicit). Results showed broader activation networks in females compared to males, regardless of the task type. Moreover, explicit tasks recruited additional frontal and sensorimotor regions beyond implicit tasks, supporting hierarchical processing. We also identified associations with specific receptors and diseases like autism and Alzheimer’s. These findings underscore the importance of considering gender and task type effects on emotional processing research and provide a network-level neural mechanism underlying emotional prosody.

Data availability

All data are available in the main text or the supplementary materials.

Code availability

The ANM algorithm is open - source and can be freely accessed at (https://github.com/sailingpeng/2021_ActivationNetworkMapping.git). The custom code is available in website https://github.com/PinyuanHu/Emotional-prosody-ANM.

References

  1. Eddy, C. M. & Cook, J. L. Emotions in action: the relationship between motor function and social cognition across multiple clinical populations. Prog. Neuro Psychopharmacol. Biol. Psychiatry 86, 229–244 (2018).

    Google Scholar 

  2. Blonder, L. X., Gur, R. E. & Gur, R. C. The effects of right and left hemiparkinsonism on prosody. Brain Lang. 36, 193–207 (1989).

    Google Scholar 

  3. Shamay-Tsoory, S. G., Tomer, R., Goldsher, D., Berger, B. D. & Aharon-Peretz, J. Impairment in cognitive and affective empathy in patients with brain lesions: anatomical and cognitive correlates. J. Clin. Exp. Neuropsyc 26, 1113–1127 (2004).

    Google Scholar 

  4. Van Lancker, D. & Sidtis, J. J. The identification of affective-prosodic stimuli by left- and right-hemisphere-damaged subjects: all errors are not created equal. J. Speech Hear Res. 35, 963–970 (1992).

    Google Scholar 

  5. Grandjean, D., Bänziger, T. & Scherer, K. R. Intonation as an interface between language and affect. In Progress in Brain Research Vol. 156, 235–247 (Elsevier, 2006).

  6. Pell, M. D. Judging emotion and attitudes from prosody following brain damage. In Progress in Brain Research, Vol. 156, 303–317 (Elsevier, 2006).

  7. Mitchell, R. L. C. & Ross, E. D. Attitudinal prosody: what we know and directions for future study. Neurosci. Biobehav. R. 37, 471–479 (2013).

    Google Scholar 

  8. Ethofer, T. et al. Cerebral pathways in processing of affective prosody: a dynamic causal modeling study. NeuroImage 30, 580–587 (2006).

    Google Scholar 

  9. Leitman. “It’s not what you say, but how you say it”: a reciprocal temporo-frontal network for affective prosody. Front. Hum. Neurosci. https://doi.org/10.3389/fnhum.2010.00019 (2010).

  10. Ethofer, T. et al. Emotional voice areas: anatomic location, functional properties, and structural connections revealed by combined fMRI/DTI. Cereb. Cortex 22, 191–200 (2012).

    Google Scholar 

  11. Pichon, S. & Kell, C. A. Affective and sensorimotor components of emotional prosody generation. J. Neurosci. 33, 1640–1650 (2013).

    Google Scholar 

  12. Péron, J., Frühholz, S., Ceravolo, L. & Grandjean, D. Structural and functional connectivity of the subthalamic nucleus during vocal emotion decoding. Soc. Cogn. Affect Neurosci. 11, 349–356 (2016).

    Google Scholar 

  13. Correia, A. I. et al. Resting-state connectivity reveals a role for sensorimotor systems in vocal emotional processing in children. NeuroImage 201, 116052 (2019).

    Google Scholar 

  14. Ceravolo, L., Frühholz, S., Pierce, J., Grandjean, D. & Péron, J. Basal ganglia and cerebellum contributions to vocal emotion processing as revealed by high-resolution fMRI. Sci. Rep. 11, 10645 (2021).

    Google Scholar 

  15. Leipold, S., Abrams, D. A., Karraker, S., Phillips, J. M. & Menon, V. Aberrant emotional prosody circuitry predicts social communication impairments in children with autism. Biol. Psychiatry 8, 531–541 (2023).

    Google Scholar 

  16. Li, M.-T. et al. The effect of seed location on functional connectivity: evidence from an image-based meta-analysis. Front. Neurosci. 17, 1120741 (2023).

    Google Scholar 

  17. Kotz, S. A., Meyer, M. & Paulmann, S. Lateralization of emotional prosody in the brain: an overview and synopsis on the impact of study design. In Progress in Brain Research, Vol. 156 (eds Anders, S., Ende, G., Junghofer, M., Kissler, J. & Wildgruber, D.) 285–294 (Elsevier, 2006).

  18. Elizalde Acevedo, B. et al. Brain mapping of emotional prosody in patients with drug-resistant temporal epilepsy: an indicator of plasticity. Cortex 153, 97–109 (2022).

    Google Scholar 

  19. Peng, S., Xu, P., Jiang, Y. & Gong, G. Activation network mapping for integration of heterogeneous fMRI findings. Nat. Hum. Behav. 6, 1417–1429 (2022).

    Google Scholar 

  20. Schirmer, A., Zysset, S., Kotz, S. A. & Yves Von Cramon, D. Gender differences in the activation of inferior frontal cortex during emotional speech perception. NeuroImage 21, 1114–1123 (2004).

    Google Scholar 

  21. Beaucousin, V. et al. Sex-dependent modulation of activity in the neural networks engaged during emotional speech comprehension. Brain Res. 1390, 108–117 (2011).

    Google Scholar 

  22. Frühholz, S., Ceravolo, L. & Grandjean, D. Specific brain networks during explicit and implicit decoding of emotional prosody. Cereb. Cortex 22, 1107–1117 (2012).

    Google Scholar 

  23. Wildgruber, D., Pihan, H., Ackermann, H., Erb, M. & Grodd, W. Dynamic brain activation during processing of emotional intonation: influence of acoustic parameters, emotional valence, and sex. NeuroImage 15, 856–869 (2002).

    Google Scholar 

  24. Imaizumi, S., Homma, M., Ozawa, Y., Maruishi, M. & Muranaka, H. Gender differences in the functional organization of the brain for emotional prosody processing. In Speech Prosody 2004 605–608 (ISCA, 2004). https://doi.org/10.21437/SpeechProsody.2004-139.

  25. Eagly, A. H. & Wood, W. The origins of sex differences in human behavior: evolved dispositions versus social roles. Am. Psychol. 54, 408–423 (1999).

    Google Scholar 

  26. Kret, M. E. & De Gelder, B. A review on sex differences in processing emotional signals. Neuropsychologia 50, 1211–1221 (2012).

    Google Scholar 

  27. Malezieux, M., Klein, A. S. & Gogolla, N. Neural circuits for emotion. Annu. Rev. Neurosci. 46, 211–231 (2023).

    Google Scholar 

  28. Taylor, S. E. et al. Biobehavioral responses to stress in females: tend-and-befriend, not fight-or-flight. Psychol. Rev. 107, 411–429 (2000).

    Google Scholar 

  29. Cosgrove, K. P., Mazure, C. M. & Staley, J. K. Evolving knowledge of sex differences in brain structure, function and chemistry. Biol. Psychiatry 62, 847–855 (2007).

    Google Scholar 

  30. Beani, L. & Zuk, M. Beyond sexual selection: The evolution of sex differences from brain to behavior. Neurosci. Biobehav. Rev. 46, 497–500 (2014).

    Google Scholar 

  31. Archer, J. The reality and evolutionary significance of human psychological sex differences. Biol. Rev. 94, 1381–1415 (2019).

    Google Scholar 

  32. Kappeler, P. M. et al. Sex roles and sex ratios in animals. Biol. Rev. 98, 462–480 (2023).

    Google Scholar 

  33. Ngun, T. C., Ghahramani, N., Sánchez, F. J., Bocklandt, S. & Vilain, E. The genetics of sex differences in brain and behavior. Front. Neuroendocr. 32, 227–246 (2011).

    Google Scholar 

  34. Brück, C., Kreifelts, B. & Wildgruber, D. Emotional voices in context: a neurobiological model of multimodal affective information processing. Phys. Life Rev. 8, 383–403 (2011).

    Google Scholar 

  35. Kotz, S. A. & Paulmann, S. Emotion, language, and the brain. Lang. Linguist Compas 5, 108–125 (2011).

    Google Scholar 

  36. Van Essen, D. C. et al. The WU-Minn Human Connectome Project: an overview. Neuroimage 80, 62–79 (2013).

    Google Scholar 

  37. Schirmer, A. & Kotz, S. A. Beyond the right hemisphere: brain mechanisms mediating vocal emotional processing. Trends Cogn. Sci. 10, 24–30 (2006).

    Google Scholar 

  38. Alba-Ferrara, L., Hausmann, M., Mitchell, R. L. & Weis, S. The neural correlates of emotional prosody comprehension: disentangling simple from complex emotion. PLOS One 6, e28701 (2011).

    Google Scholar 

  39. Escoffier, N., Zhong, J., Schirmer, A. & Qiu, A. Emotional expressions in voice and music: same code, same effect? Hum. Brain Mapp. 34, 1796–1810 (2013).

    Google Scholar 

  40. Liang, B. & Du, Y. The functional neuroanatomy of lexical tone perception: an activation likelihood estimation meta-analysis. Front. Neurosci. 12, 495 (2018).

    Google Scholar 

  41. Silva, A. B. et al. A neurosurgical functional dissection of the middle precentral gyrus during speech production. J. Neurosci. 42, 8416–8426 (2022).

    Google Scholar 

  42. Belyk, M. & Brown, S. Perception of affective and linguistic prosody: an ALE meta-analysis of neuroimaging studies. Soc. Cogn. Affect Neur 9, 1395–1403 (2014).

    Google Scholar 

  43. Wildgruber, D., Ackermann, H., Kreifelts, B. & Ethofer, T. Cerebral processing of linguistic and emotional prosody: fMRI studies. In Progress in Brain Research, Vol. 156, 249–268 (Elsevier, 2006).

  44. Witteman, J., Van Heuven, V. J. P. & Schiller, N. O. Hearing feelings: a quantitative meta-analysis on the neuroimaging literature of emotional prosody perception. Neuropsychologia 50, 2752–2763 (2012).

    Google Scholar 

  45. Fischer, A. H. & Evers, C. The social costs and benefits of anger as a function of gender and relationship context. Sex. Roles 65, 23–34 (2011).

    Google Scholar 

  46. Forni-Santos, L. & Osório, F. L. Influence of gender in the recognition of basic facial expressions: a critical literature review. World J. Psychiatry 5, 342 (2015).

    Google Scholar 

  47. Lausen, A. & Schacht, A. Gender differences in the recognition of vocal emotions. Front. Psychol. 9, 882 (2018).

    Google Scholar 

  48. Sokolov, A. A., Krüger, S., Enck, P., Krägeloh-Mann, I. & Pavlova, M. A. Gender affects body language reading. Front. Psychol. 2, 16 (2011).

  49. Thompson, A. E. & Voyer, D. Sex differences in the ability to recognise non-verbal displays of emotion: a meta-analysis. Cognit. Emot. 28, 1164–1195 (2014).

    Google Scholar 

  50. Pell, M. D. & Kotz, S. A. On the time course of vocal emotion recognition. PLoS One 6, e27256 (2011).

    Google Scholar 

  51. Goddard, A. W. et al. Current perspectives of the roles of the central norepinephrine system in anxiety and depression. Depress Anxiety 27, 339–350 (2010).

    Google Scholar 

  52. Harrison, N. A., Morgan, R. & Critchley, H. D. From facial mimicry to emotional empathy: a role for norepinephrine? Soc. Neurosci. 5, 393–400 (2010).

    Google Scholar 

  53. Rodrigues, S. M., Bauer, E. P., Farb, C. R., Schafe, G. E. & LeDoux, J. E. The Group I metabotropic glutamate receptor mGluR5 is required for fear memory formation and long-term potentiation in the lateral amygdala. J. Neurosci. 22, 5219–5229 (2002).

    Google Scholar 

  54. Banerjee, P., Mehta, M. & Kanjilal, B. The 5-HT1A receptor: a signaling hub linked to emotional balance. In Serotonin Receptors in Neurobiology (ed. Chattopadhyay, A.) (CRC Press/Taylor & Francis, 2007).

  55. Bernasconi, F. et al. Spatiotemporal brain dynamics of emotional face processing modulations induced by the serotonin 1A/2A receptor agonist psilocybin. Cereb. Cortex 24, 3221–3231 (2014).

    Google Scholar 

  56. Lutz, B. Endocannabinoid signals in the control of emotion. Curr. Opin. Pharm. 9, 46–52 (2009).

    Google Scholar 

  57. Spies, M., Handschuh, P. A., Lanzenberger, R. & Kranz, G. S. Sex and the serotonergic underpinnings of depression and migraine. In Handbook of Clinical Neurology, Vol. 175, 117–140 (Elsevier, 2020).

  58. Acosta, J. I. et al. Transitional versus surgical menopause in a rodent model: etiology of ovarian hormone loss impacts memory and the acetylcholine system. Endocrinology 150, 4248–4259 (2009).

    Google Scholar 

  59. Muth, E. A., Crowley, W. R. & Jacobowitz, D. M. Effect of gonadal hormones on luteinizing hormone in plasma and on choline acetyltransferase activity and acetylcholine levels in discrete nuclei of the rat brain. Neuroendocrinology 30, 329–336 (2008).

    Google Scholar 

  60. Schirmer, A. & Adolphs, R. Emotion perception from face, voice, and touch: comparisons and convergence. Trends Cogn. Sci. 21, 216–228 (2017).

    Google Scholar 

  61. Mauchand, M. & Zhang, S. Disentangling emotional signals in the brain: an ALE meta-analysis of vocal affect perception. Cogn., Affect. Behav. Neurosci. 23, 17–29 (2023).

    Google Scholar 

  62. Van Essen, D. C. et al. The Human Connectome Project: a data acquisition perspective. Neuroimage 62, 2222–2231 (2012).

    Google Scholar 

  63. Glasser, M. F. et al. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80, 105–124 (2013).

    Google Scholar 

  64. Hansen, J. Y. et al. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities. Nat. Commun. 13, 4682 (2022).

    Google Scholar 

  65. Dong, X. et al. How brain structure–function decoupling supports individual cognition and its molecular mechanism. Hum. Brain Mapp. 45, e26575 (2024).

    Google Scholar 

  66. Joliot, M. et al. AICHA: an atlas of intrinsic connectivity of homotopic areas. J. Neurosci. Methods 254, 46–59 (2015).

    Google Scholar 

  67. Liu, J., Xia, M., Wang, X., Liao, X. & He, Y. The spatial organization of the chronnectome associates with cortical hierarchy and transcriptional profiles in the human brain. NeuroImage 222, 117296 (2020).

    Google Scholar 

  68. Aleksander, S. A. et al. The Gene Ontology knowledgebase in 2023. Genetics 224, iyad031 (2023).

    Google Scholar 

  69. Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

    Google Scholar 

  70. Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).

    Google Scholar 

  71. Piñero, J. et al. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res. gkz1021, https://doi.org/10.1093/nar/gkz1021 (2019).

  72. Elizarraras, J. M. et al. WebGestalt 2024: faster gene set analysis and new support for metabolomics and multi-omics. Nucleic Acids Res. 52, W415–W421 (2024).

    Google Scholar 

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Acknowledgements

This research project is supported in part by the National Natural Science Foundation of China (81701783 to S.Z., 81801782 to X.S.), New Talent Project of Beijing University of Posts and Telecommunications (2021RC40, 2023RC59), STI 2030--Major Projects (2021ZD0200500), Science Foundation of Beijing Language and Culture University (supported by “the Fundamental Research Funds for the Central Universities”) (19YBB39, 20YJ090001).

Author information

Authors and Affiliations

  1. Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China

    Pinyuan Hu, Yuwei Su, Min Lan, Wenjiang Zhang & Suyu Zhong

  2. Institute of Linguistic Sciences, Beijing Language and Culture University, Beijing, China

    Xiaochen Sun, Xingyu Ouyang & Xinyu Zhang

  3. Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    Shaoling Peng

  4. Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Shaoling Peng

  5. Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Lingshui, Hainan, China

    Suyu Zhong

Authors
  1. Pinyuan Hu
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  2. Xiaochen Sun
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  3. Xingyu Ouyang
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  4. Xinyu Zhang
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  7. Min Lan
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Contributions

Conceptualization: S.Z., X.S., X.Z. Methodology: S.Z., S.P., P.H., Y.S., M.L., X.Z., Visualization: P.H., X.O., Supervision: S.Z., X.S., Writing—original draft: P.H., S.Z., X.S., X.O., X.Z., Writing—review & editing: P.H., S.Z., X.S., X.O., S.P., Y.S., W.Z.

Corresponding author

Correspondence to Suyu Zhong.

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Communications Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Jasmine Pan. A peer review file is available.

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Hu, P., Sun, X., Ouyang, X. et al. Gender and task type effects on the neural network of emotional prosody processing. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09625-8

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  • Received: 04 March 2025

  • Accepted: 20 January 2026

  • Published: 02 February 2026

  • DOI: https://doi.org/10.1038/s42003-026-09625-8

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