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Sascha Frühholz

Professor - Cognitive psychology, Neuroscience and Neuropsychology

Email sascha.fruhholz@psykologi.uio.no

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Visiting address Forskningsveien 3A Harald Schjelderups hus 0373 Oslo

Postal address Postboks 1094 Blindern 0317 Oslo

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Academic interests

•   Digital communication, cybersecurity, and psychology of deepfakes
*    Bayesian modelling of brain-computer interfaces
•   Neural mechanisms of voice communication and psychoacoustics
•   Affect processing from human faces, voices, and music
•   Anatomy of the limbic system
•   Forensic analysis of serious crimes, witness’ reports, and digital fraud
•   Digital archaeo-acoustics: Psychoacoustics and digital recreation of ancient instruments

Projects

Human abilities for deepfake detection
Digital emotions
Chances and risks of digital voice technology
Neurocognitive Mechanisms of Auditory Perception: Challenging the Human Auditory System at the Limits of Hearing
Perceptual and neuronal investigations on the neurocognitive mechanisms of perceiving whispered emotions
Auditory emotion recognition from vocally and musically expressed emotions

Background

Professional

11/20 – now Full Professor at the Department of Psychology, University of Oslo, Norway

03/20 – 10/20 Associate Professor at the Department of Psychology, University of Oslo, Norway

09/15 – 01/20 SNSF Professor at the Department of Psychology, University of Zürich, Switzerland

01/13 – 08/15 Senior Research Associate and Principal Investigator (PI) at the Swiss Center for Affective Sciences; University of Geneva, Geneva, Switzerland

01/10 – 12/12 Post-doctoral Research Associate at the Department of Psychology, Uni-versity of Geneva, Geneva, Switzerland

12/08 – 12/09 Post-doctoral Research Associate at the Department of Neuro-psychology and Behavioral Neurobiology; University of Bremen, Bremen, Germany

02/06 – 11/08 Ph.D. Student and Research Associate at the Department of Neuro-psychology and Behavioral Neurobiology, University of Bremen, Bremen, Germany

09/07 Visiting Scientist at the Cognitive Neuroscience Research Group; Universi-ty of Barcelona, Barcelona, Spain

07/05 – 12/05 Student Assistant at the Department of Neuropsychology and Behavioral Neurobiology; University of Bremen, Bremen, Germany

Awards

2015 SNSF Professorship, University of Zurich, Zurich, Switzerland
2005 Nominated for the best Teaching Award at the University of Bremen, Bremen, Germany.

Abrahamsson, Liv Merve Akca; Frühholz, Sascha & Vuoskoski, Jonna Katariina (2026). Domain-specific perception of emotional intensity in brief musical and vocal expressions. JASA Express Letters. 6(2). doi: 10.1121/10.0042460. Full text in Research Archive Show summary
Auditory emotional intensity perception was investigated using behavioral ratings of voice and music stimuli. Principal component analysis revealed distinct domain-specific structures [principal component 1 (PC1) 48%, PC2 11.2%), with the primary dimension for music intensity judgments explaining larger variance. Domain-specific analyses converged on a two-dimensional valence–arousal space, indicating shared structure yet differing variability. These findings advance theoretical understanding of how emotional intensity is organized across auditory domains of voice and music and highlight music as a particularly rich substrate for inter-individual differences in affective intensity perception.
Beinnes, Gard Kvammen; Skjegstad, Christine Leilani & Frühholz, Sascha (2025). Differential neural decoding of alarm and avoidance information from vocal alarm calls in humans. Communications Biology. 8(1). doi: 10.1038/s42003-025-08248-9. Full text in Research Archive Show summary
Many animals and humans use scream calls to signal imminent threats, which typically evoke alarm and escape responses in recipients. Compared to animals, human scream calls are more diversified with varying levels of alarm signaling. Certain low-alarm human screams thus might not elicit full neural alarm cascades and threat avoidance actions. Here we investigated the neural circuits for decoding alarm and avoid-approach information from positive and negative scream calls in humans. Alarm and avoid-approach decisions showed minimal neural overlap, with alarm decisions recruiting neural cascades of sensory-affective decoding for action preparation, whereas avoid-approach judgments recruited neural systems for spatio-affective decoding for social decision-making. Furthermore, decision patterns revealed both an alarm quotient and an avoid quotient for risk arbitration, which linked the likelihood of an urgent response (alarm, avoid) to a slowing of choosing a potential safe option in response to scream calls. While the avoid quotient positively predicted neural activity in a broad cortico-limbic network, the alarm quotient predicted neural suppression with increasing alarm levels, especially in the amygdala as part of a presumed limbic alarm system. This points to a critical involvement of the amygdala at neural levels of choice arbitrations rather than in threat evaluations signaled by screams.
Gruber, T.; Briefer, E.F.; Grütter, A.; Xanthos, A.; Grandjean, D. & Manser, M.B. [Show all 7 contributors for this article] (2025). Emotion in Nonverbal Communication: Comparing Animal and Human Vocalizations and Human Text Messages. Emotion Review. ISSN 1754-0739. 17(1), p. 30–45. doi: 10.1177/17540739241303505. Full text in Research Archive
Nussbaum, Christine; Frühholz, Sascha & Schweinberger, Stefan R. (2025). Understanding voice naturalness. Trends in Cognitive Sciences. ISSN 1364-6613. 29(5), p. 467–480. doi: 10.1016/j.tics.2025.01.010. Full text in Research Archive
Khalil, Radwa; Frühholz, Sascha & Godde, Ben (2025). Emotion Induction Modulates Neural Dynamics Related to the Originality of Ideational Creativity. Human Brain Mapping. ISSN 1065-9471. 46(4). doi: 10.1002/hbm.70182. Full text in Research Archive
Frühholz, Sascha; Dietziker, Joris; Staib, Matthias; Bobin, Marine & Steiner, Florence (2025). Evolutionary Continuities and Discontinuities in Affective Voice Signaling. Emotion. ISSN 1528-3542. doi: 10.1037/emo0001484. Full text in Research Archive
Popovova, Jeanette; Mazloum, Reza; Macauda, Gianluca; Stämpfli, Philipp; Vuilleumier, Patrik & Frühholz, Sascha [Show all 9 contributors for this article] (2024). Enhanced attention-related alertness following right anterior insular cortex neurofeedback training. iScience. 27(2). doi: 10.1016/j.isci.2024.108915. Full text in Research Archive
Bobin, Marine; Sulzer, Neil; Bründler, Gina; Staib, Matthias; Imbach, Lukas L. & Stieglitz, Lennart H. [Show all 10 contributors for this article] (2024). Direct subthalamic nucleus stimulation influences speech and voice quality in Parkinson's disease patients. Brain Stimulation. ISSN 1935-861X. 17(1), p. 112–124. doi: 10.1016/j.brs.2024.01.006. Full text in Research Archive
Trevor, Caitlyn & Frühholz, Sascha (2024). Music as an Evolved Tool for Socio-Affective Fiction. Emotion Review. ISSN 1754-0739. doi: 10.1177/17540739241259562. Full text in Research Archive
Roswandowitz, Claudia; Kathiresan, Thayabaran; Pellegrino, Elisa; Dellwo, Volker & Frühholz, Sascha (2024). Cortical-striatal brain network distinguishes deepfake from real speaker identity. Communications Biology. 7(1). doi: 10.1038/s42003-024-06372-6. Full text in Research Archive
Trost, Wiebke; Trevor, Caitlyn; Fernandez, Natalia; Steiner, Florence & Frühholz, Sascha (2024). Live music stimulates the affective brain and emotionally entrains listeners in real time. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 121(10). doi: 10.1073/pnas.2316306121. Full text in Research Archive
Brasser, Maria; Frühholz, Sascha; Schneeberger, Andres R.; Trevor, Caitlyn; Ruschetti, Gian G. & Held, Felipe Enzo [Show all 8 contributors for this article] (2024). The effectiveness of cognitive training in people in psychiatry with depressive symptoms – A randomized controlled study. Journal of Affective Disorders Reports. 17. doi: 10.1016/j.jadr.2024.100805. Full text in Research Archive
Brookes, Jack; Hall, Samson; Frühholz, Sascha & Bach, Dominik R (2023). Immersive VR for investigating threat avoidance: The VRthreat toolkit for Unity. Behavior Research Methods. ISSN 1554-351X. doi: 10.3758/s13428-023-02241-y. Full text in Research Archive
Staib, Matthias & Frühholz, Sascha (2023). Distinct functional levels of human voice processing in the auditory cortex. Cerebral Cortex. ISSN 1047-3211. 33(4), p. 1170–1185. doi: 10.1093/cercor/bhac128. Full text in Research Archive
Lie, Hanne Cathrine; Gerwing, Jennifer; Bondevik, Hilde; Bostad, Inga; Ellingsen, Dan-Mikael & Frühholz, Sascha [Show all 12 contributors for this article] (2022). Studying clinical communication through multiple lenses: The underused potential of inter-disciplinary collaborations. Patient Education and Counseling. ISSN 0738-3991. doi: 10.1016/j.pec.2022.04.010. Full text in Research Archive Show summary
In the era of evidence-based medicine, surprisingly little attention is given to the practice of evidence-based communication skills and strategies to provide the best and most efficient patient care, perhaps due to the infinitely complex nature of clinical communication. Multiple models for ‘best practice’ exist, but they tend to focus on what skills and strategies to use, paying less attention to how they should be used in which contexts and situations for best effects [1]. Disentangling the complexities of effective clinical communication would therefore require insights from other disciplines outside medicine, including their theoretical models, empirical knowledge, and research methods, concerning the study of human communication and interaction, as well as medical, ethical, legal, philosophical, existential, cultural, and organizational perspectives. Although several disciplines study clinical communication, this is often done in isolation, without integrating efforts beyond a few selected disciplines, e.g., medicine, linguistics, or social psychology [[1], [2], [3], [4]]. Given the multiple levels of complexity in clinical communication research, we need to move beyond this fragmented approach to answer questions about what works, for what reasons, and in which contexts. These Association Pages aim to provide insights to move forward towards interdisciplinary research of clinical communication. As a primer to help build bridges across disciplines, we have asked experts from medicine, cognitive neuroscience, psychology, philosophy, linguistics, medical ethics, and educational sciences these two questions: “What fascinates you about clinical communication?” and “Which methodological tools do you tend to use to study it?“. We have summarized the responses below and provided a suggestion for how these different experts may work together in an interdisciplinary effort to generate new and needed knowledge of what is effective clinical communication, how it works and why, which can be translated into clinical practice and training.
Brasser, Maria; Frühholz, Sascha; Schneeberger, Andres R.; Ruschetti, Gian G.; Schaerli, Rahel & Häner, Michèle [Show all 7 contributors for this article] (2022). A Randomized Controlled Trial Study of a Multimodal Intervention vs. Cognitive Training to Foster Cognitive and Affective Health in Older Adults. Frontiers in Psychology. 13. doi: 10.3389/fpsyg.2022.866613. Full text in Research Archive
Eiff, Celina Isabelle von; Frühholz, Sascha; Korth, Daniela; Guntinas-Lichius, Orlando & Schweinberger, Stefan Robert (2022). Crossmodal benefits to vocal emotion perception in cochlear implant users. iScience. 25(12). doi: 10.1016/j.isci.2022.105711. Full text in Research Archive
Skjegstad, Christine Leilani; Trevor, Caitlyn; Swanborough, Huw; Roswandowitz, Claudia; Mokros, Andreas & Habermeyer, Elmar [Show all 7 contributors for this article] (2022). Psychopathic and autistic traits differentially influence the neural mechanisms of social cognition from communication signals. Translational Psychiatry. 12(1). doi: 10.1038/s41398-022-02260-x. Full text in Research Archive Show summary
Abstract Psychopathy is associated with severe deviations in social behavior and cognition. While previous research described such cognitive and neural alterations in the processing of rather specific social information from human expressions, some open questions remain concerning central and differential neurocognitive deficits underlying psychopathic behavior. Here we investigated three rather unexplored factors to explain these deficits, first, by assessing psychopathy subtypes in social cognition, second, by investigating the discrimination of social communication sounds (speech, non-speech) from other non-social sounds, and third, by determining the neural overlap in social cognition impairments with autistic traits, given potential common deficits in the processing of communicative voice signals. The study was exploratory with a focus on how psychopathic and autistic traits differentially influence the function of social cognitive and affective brain networks in response to social voice stimuli. We used a parametric data analysis approach from a sample of 113 participants (47 male, 66 female) with ages ranging between 18 and 40 years (mean 25.59, SD 4.79). Our data revealed four important findings. First, we found a phenotypical overlap between secondary but not primary psychopathy with autistic traits. Second, primary psychopathy showed various neural deficits in neural voice processing nodes (speech, non-speech voices) and in brain systems for social cognition (mirroring, mentalizing, empathy, emotional contagion). Primary psychopathy also showed deficits in the basal ganglia (BG) system that seems specific to the social decoding of communicative voice signals. Third, neural deviations in secondary psychopathy were restricted to social mirroring and mentalizing impairments, but with additional and so far undescribed deficits at the level of auditory sensory processing, potentially concerning deficits in ventral auditory stream mechanisms (auditory object identification). Fourth, high autistic traits also revealed neural deviations in sensory cortices, but rather in the dorsal auditory processing streams (communicative context encoding). Taken together, social cognition of voice signals shows considerable deviations in psychopathy, with differential and newly described deficits in the BG system in primary psychopathy and at the neural level of sensory processing in secondary psychopathy. These deficits seem especially triggered during the social cognition from vocal communication signals.
Eiff, Celina I. Von; Skuk, Verena G.; Zäske, Romi; Nussbaum, Christine; Frühholz, Sascha & Feuer, Ute [Show all 8 contributors for this article] (2022). Parameter-Specific Morphing Reveals Contributions of Timbre to the Perception of Vocal Emotions in Cochlear Implant Users. Ear and Hearing. ISSN 0196-0202. 43(4), p. 1178–1188. doi: 10.1097/AUD.0000000000001181. Full text in Research Archive
Steiner, Florence; Fernandez, Natalia; Dietziker, Joris; Stämpfli, Philipp; Seifritz, Erich & Rey, Anton [Show all 7 contributors for this article] (2022). Affective speech modulates a cortico-limbic network in real time. Progress in Neurobiology. ISSN 0301-0082. 214. doi: 10.1016/j.pneurobio.2022.102278. Full text in Research Archive
Trevor, Caitlyn & Frühholz, Sascha (2021). The evolutionary benefit of less-credible affective musical signals for emotion induction during storytelling. Behavioral and Brain Sciences. ISSN 0140-525X. 44, p. 127–129. doi: 10.1017/S0140525X20001004. Full text in Research Archive
Frühholz, Sascha; Dietziker, Joris; Staib, Matthias & Trost, Wiebke (2021). Neurocognitive processing efficiency for discriminating human non-alarm rather than alarm scream calls. PLoS Biology. ISSN 1544-9173. 19(4), p. 1–30. doi: 10.1371/journal.pbio.3000751. Full text in Research Archive
Ceravolo, Leonardo; Frühholz, Sascha; Pierce, Jordan; Grandjean, Didier & Péron, Julie (2021). Basal ganglia and cerebellum contributions to vocal emotion processing as revealed by high-resolution fMRI. Scientific Reports. 11(1). doi: 10.1038/s41598-021-90222-6. Full text in Research Archive
Handler, Alexander & Frühholz, Sascha (2021). Eyewitness Memory for Person Identification: Predicting Mugbook Recognition Accuracy According to Person Description Abilities and Subjective Confidence of Witnesses. Frontiers in Psychology. 12. doi: 10.3389/fpsyg.2021.675956. Full text in Research Archive
Steiner, Florence; Bobin, Marine & Frühholz, Sascha (2021). Auditory cortical micro-networks show differential connectivity during voice and speech processing in humans. Communications Biology. 4(1), p. 801–801. doi: 10.1038/s42003-021-02328-2. Full text in Research Archive
Dietziker, Joris; Staib, Matthias & Frühholz, Sascha (2021). Neural competition between concurrent speech production and other speech perception. NeuroImage. ISSN 1053-8119. 228. doi: 10.1016/j.neuroimage.2020.117710. Full text in Research Archive
Young, Andrew W.; Frühholz, Sascha & Schweinberger, Stefan R. (2020). Face and voice perception: Understanding commonalities and differences. Trends in Cognitive Sciences. ISSN 1364-6613. 24(5), p. 398–410. doi: 10.1016/j.tics.2020.02.001. Full text in Research Archive
Frühholz, Sascha; Trost, Wiebke; Grandjean, Didier & Belin, Pascal (2020). Neural oscillations in human auditory cortex revealed by fast fMRI during auditory perception. NeuroImage. ISSN 1053-8119. doi: 10.1016/j.neuroimage.2019.116401. Full text in Research Archive
Roswandowitz, Claudia; Swanborough, Huw & Frühholz, Sascha (2020). Categorizing human vocal signals depends on an integrated auditory-frontal cortical network. Human Brain Mapping. ISSN 1065-9471. doi: 10.1002/hbm.25309. Full text in Research Archive
Frühholz, Sascha; Trost, Wiebke; Constantinescu, Irina & Grandjean, Didier (2020). Neural Dynamics of Karaoke-Like Voice Imitation in Singing Performance. Frontiers in Human Neuroscience. 14. doi: 10.3389/fnhum.2020.00135. Full text in Research Archive
Trevor, Caitlyn; Arnal, Luc H. & Frühholz, Sascha (2020). Terrifying film music mimics alarming acoustic feature of human screams. Journal of the Acoustical Society of America. ISSN 0001-4966. 147(6), p. EL540–EL545. doi: 10.1121/10.0001459. Full text in Research Archive
Staib, Matthias & Frühholz, Sascha (2020). Cortical voice processing is grounded in elementary sound analyses for vocalization relevant sound patterns. Progress in Neurobiology. ISSN 0301-0082. p. 1–10. doi: 10.1016/j.pneurobio.2020.101982. Full text in Research Archive
Frühholz, Sascha & Schweinberger, Stefan (2020). Nonverbal auditory communication – Evidence for integrated neural systems for voice signal production and perception. Progress in Neurobiology. ISSN 0301-0082. p. 1–19. doi: 10.1016/j.pneurobio.2020.101948. Full text in Research Archive
Swanborough, Huw; Staib, Matthias & Frühholz, Sascha (2020). Neurocognitive dynamics of near-threshold voice signal detection and affective voice evaluation. Science Advances. 6(50). doi: 10.1126/sciadv.abb3884. Full text in Research Archive
Dricu, Mihai & Frühholz, Sascha (2019). A neurocognitive model of perceptual decision-making on emotional signals. Human Brain Mapping. ISSN 1065-9471. doi: 10.1002/hbm.24893. Full text in Research Archive
Frühholz, Sascha; Schlegel, Katja & Grandjean, Didier (2017). Amygdala structure and core dimensions of the affective personality. Brain Structure and Function. ISSN 1863-2653. doi: 10.1007/s00429-017-1444-9. Full text in Research Archive
Frühholz, Sascha & Staib, Matthias (2017). Neurocircuitry of impaired affective sound processing. Neuroscience and Biobehavioral Reviews. ISSN 0149-7634. doi: 10.1016/j.neubiorev.2017.09.009. Full text in Research Archive
Pannese, Alessia; Grandjean, Didier & Frühholz, Sascha (2016). Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions. Cortex. ISSN 0010-9452. doi: 10.1016/j.cortex.2016.10.013. Full text in Research Archive
Dricu, Mihai & Frühholz, Sascha (2016). Perceiving emotional expressions in others: activation likelihood estimation meta-analyses of explicit evaluation, passive perception and incidental perception of emotions. Neuroscience and Biobehavioral Reviews. ISSN 0149-7634. doi: 10.1016/j.neubiorev.2016.10.020. Full text in Research Archive
Frühholz, Sascha; Trost, Wiebke & Kotz, Sonja (2016). The sound of emotions—Towards a unifying neural network perspective of affective sound processing. Neuroscience and Biobehavioral Reviews. ISSN 0149-7634. doi: 10.1016/j.neubiorev.2016.05.002. Full text in Research Archive
Frühholz, Sascha; Hofstetter, Christoph; Cristinzio, Chiara; Saj, Arnaud; Seeck, Margitta & Vuilleumier, Patrik [Show all 7 contributors for this article] (2015). Asymmetrical effects of unilateral right or left amygdala damage on auditory cortical processing of vocal emotions. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. doi: 10.1073/pnas.1411315112. Full text in Research Archive
Frühholz, Sascha; Klaas, Hannah; Patel, Sona & Grandjean, Didier (2014). Talking in Fury: The Cortico-Subcortical Network Underlying Angry Vocalizations. Cerebral Cortex. ISSN 1047-3211. doi: 10.1093/cercor/bhu074. Full text in Research Archive
Frühholz, Sascha; Trost, Wiebke & Grandjean, Didier (2014). The role of the medial temporal limbic system in processing emotions in voice and music. Progress in Neurobiology. ISSN 0301-0082. doi: 10.1016/j.pneurobio.2014.09.003. Full text in Research Archive
Frühholz, Sascha; Ceravolo, Leonardo & Grandjean, Didier (2011). Specific Brain Networks during Explicit and Implicit Decoding of Emotional Prosody. Cerebral Cortex. ISSN 1047-3211. doi: 10.1093/cercor/bhr184. Full text in Research Archive

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Abrahamsson, Liv Merve Akca; Egger, Katharina; Vuoskoski, Jonna Katariina & Frühholz, Sascha (2025). Brain Responses to Musical Emotions in Autism. Full text in Research Archive
Skjegstad, Christine Leilani; Abrahamsson, Liv Merve Akca & Frühholz, Sascha (2025). Social traits influence behavioral and neural responses to emotional AI and human voices. doi: https:/www.abstractsonline.com/pp8/#%21%2F21171%2Fpresentation%2F23566. Full text in Research Archive Show summary
Individual differences tint our perception of reality. Our previous work showed certain personality traits influence how the brain responds to human voices. Recently, we found the brain responds differently to voices generated by artificial intelligence (AI) compared to human voices, despite challenges in perceptual discrimination. This study investigates whether social traits further influence differential neural processing of AI and human voices. 61 participants (40 females, mean age = 31.93, SD = 7.75) listened to vocal emotional pseudo-speech expressions (neutral, angry, fear, happy, pleasure) from both AI-generated and human sources. The protocol included an fMRI study with a classification task, followed by a perceptual task, as well as personality trait assessments. Traits related to social and emotional cognition (Callous-Unemotional [CU], Alexithymia [ALX], Affective Empathy [AE], and Social Information Processing [SIP]) were selected. Correlations between the traits and outcome measures were performed (p <0.05, FDR corrected). ALX correlated with a tendency to classify voices as AI (r = -0.26) while SIP correlated with a tendency to classify voices as human (r = 0.3). AE and SIP were positively correlated with perceived naturalness of human voices (r = 0.32 and r = 0.27). Conversely, ALX and CU were negatively associated with perceived naturalness of human voices (r = -0.28 and r = -0.28). CU negatively correlated with perceived naturalness of AI voices (r = -0.28), whereas AE positively correlated with it (r = 0.29). Our fMRI multiple regression analysis included the traits with age, sex, and handedness as covariates of no interest (p < 0.005, k > 21). Our findings reveal distinct neural patterns: in response to AI voices (versus human), AE was associated with increased activity in the left angular gyrus, left inferior frontal gyrus-triangular part, left hippocampus, right nucleus accumbens and bilateral amygdalae. SIP was associated with increased activity in the right dorsolateral superior frontal gyrus. In response to human voices (versus AI), AE was associated with increased activity in the left precentral gyrus, while CU was associated with increased activity in the bilateral precentral gyri. SIP was associated with increased activity in the right cuneus, right superior temporal gyrus, right fusiform gyrus, left middle cingulate and paracingulate gyri, left insula, and bilateral middle occipital gyri. When processing AI voices, AE may relate to emotional engagement and SIP to more cognitive effort. In the context of human voices, AE and CU may differentially engage the mirror neuron system, while SIP may engage multimodal processing.
Skjegstad, Christine Leilani & Frühholz, Sascha (2024). Neural Dynamics of Processing Natural and Digital Emotional Vocalizations. Full text in Research Archive Show summary
AI-generated voices have a high level of auditory quality and resemble human voices, such that they might mimic human emotions to a high degree. In our study, we investigated how the human brain distinguishes between emotional natural (human) and synthetic (AI-generated) voices. 35 participants (23 females, mean age = 32.23, SD = 7.66) listened to vocal pseudo-speech emotional expressions (neutral, angry, fear, happy, pleasure) from both human and AI-generated sources. The experiment consisted of three parts: an fMRI study with a classification task to identify the voices as synthetic or natural, a perceptual task where participants rated characteristics of the voice stimuli, and an assessment of personality traits. Neutral AI voices were identified with 74.9% accuracy compared to only 23% accuracy for neutral human voices. Happy human voices were correctly identified 77% of the time while happy AI voices were identified with 34.5% accuracy. In general, human voices were rated as more natural, trustworthy, and authentic, especially the happy and pleasure expressions. Neuroimaging results revealed significant differences in brain activity in response to the AI and human voices. AI voices activated the right anterior midcingulate cortex, right dorsolateral prefrontal cortex and left thalamus, which may indicate increased vigilance and cognitive regulation. In contrast, human voices elicited stronger responses in the right hippocampus as well as regions associated with emotional processing and empathy such as the right inferior frontal gyrus, anterior cingulate cortex and angular gyrus. Human voices may elicit a sense of relatedness and AI voices may elicit heightened alertness.

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Published Apr. 20, 2020 8:35 AM - Last modified May 11, 2023 12:37 PM

Sascha Frühholz

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