Biology subjects

Fruhholz, S.

Publications and source records attributed to Fruhholz, S..

5 recordsLinked to original sources

bioRxiv2025

Neural affect decoding from minimal spectrotemporal glimpses of voice signals

Decoding affect information from voice signals is challenging in natural environments where noise masks the most diagnostic and discriminative acoustic voice information. The extent to which neural affect decoding is resilient against or vulnerable to extreme noise-masking of voice signals remains largely unknown. Here, we performed three experiments using an auditory "bubble" technique to randomly mask and unmask certain spectrotemporal voice features similar to natural noise masking. First, using psychoacoustic voice-in-noise testing, we observed that a substantial part of the full spectrotemporal space of voice signals contains diagnostic cues essential for accurate affect decoding, contributing to the partial robustness of the voice signals under noise masking. Affective voice signals (joy, aggression) were correctly identified from early broadband spectral and temporally extended high-frequency information. Neutral voices were primarily identified from low- to medium-level spectral information with high perceptual relevance near the voice offset. Second, using human neuroimaging, we mechanistically linked neural activity to minimal spectrotemporal patches that enable accurate affect classification from voice samples. A neural network composed of (sub-)cortical auditory and limbic nodes, fronto-insular regions, and vocal motor mirroring nodes supported the affective discrimination of voice signals. More specifically, activity in the orbitofrontal cortex and amygdala was mechanistically linked to correct affect decisions, as determined by a reverse brain-to-decision mapping approach. Thus, decoding affect from voice signals embedded in complex noise seems partially feasible, provided that the noise does not obscure the minimal diagnostic spectrotemporal information essential for engaging cortical and subcortical limbic affect decoding mechanisms.

neuroscience↗

bioRxiv2025

Real-time affect decoding in the amygdalo-hippocampal circuit from dynamic auditory signals

Affect decoding from auditory signals requires the temporal tracking and neural processing of dynamic sound patterns, such as in affective speech. Affective speech is commonly expressed to maximize its emotional impact and its neural decoding in integrated medial limbic circuits of recipients. Here we examined how affective speech, which was live produced by speakers to maximize amygdala-hippocampal connectivity in listeners, can evoke significant intralimbic and cortico-limbic affect decoding mechanisms. Aggressive and joyful affective speech that was produced based on real-time feedback of amygdala-hippocampal couplings in listeners increased intralimbic connectivity as well as activity in auditory cortical nodes as parts of a broader affective sound processing network. Neural time courses in the auditory cortex also correlated with acoustic patterns of adaptive speech indicative of a communicative speaker-listener coupling. Affective speech can thus meaningfully influence limbic circuit synchronizations with a specific significance of the amygdala-hippocampal circuit for affect decoding from auditory signals.

neuroscience↗

bioRxiv2024

Functional and causal neural mechanisms of human voice perception in noisy situations

Human communication entails an efficient way of simultaneously processing voice and reducing the impact of environmental noise. By manipulating background noise, we aimed at clarifying the neural mechanisms allowing voice comprehension in noisy situations. Our results point to spatial and temporal coexistence of lateral and medial temporal cortex networks when voice is easily detected in highly noisy conditions, revealing the necessary neural underpinnings of human communication in realistic situations.

neuroscience↗

bioRxiv2024

Emotion induction modulates neural dynamics during ideational originality

Emotions remarkably impact our creative minds; nevertheless, a comprehensive mapping of their underlying neural mechanisms remains elusive. Therefore, we explored the influence of induced emotional states on ideational originality and its associated neural dynamics. Participants were randomly presented with three short videos with sad, neutral, and happy content. After each video, ideational originality was evaluated using the alternate uses task (AUT). Ideational originality was significantly higher after induction of the happy state than the neutral state; in contrast, there was a nonsignificant difference between the sad and neutral states. Associated neural dynamics were assessed through EEG time-frequency (TF) power and phase-amplitude coupling (PAC) analysis. Our findings suggest that emotional states elicit distinct TF and PAC profiles associated with ideational originality. Relative to baseline, gamma activity was enhanced after the neutral induction and more enhanced after the induction of a happy state but reduced after the induction of a sad state in 2-4 seconds after starting the task. Our PAC findings suggest that the attention system may be silent after the induction of a happy emotional state to load rich materials into working memory (WM) and active in the sad state to maintain these materials in WM. HighlightO_LIIdeational originality was significantly higher after the induction of a happy state than in a neutral state. C_LIO_LIEmotional states elicited distinct EEG time-frequency and phase-amplitude coupling profiles associated with ideational originality. C_LIO_LIRelative to baseline, gamma activity was enhanced in the neutral state and more robust in a happy state but reduced in a sad state 2-4 seconds after starting AUT. C_LIO_LIEnhancing ideational originality requires the induction of emotional states to suppress overlearned associations and strengthen weaker coupling associations, which is the case after the induction of a happy emotional state. C_LI

neuroscience↗

bioRxiv2021

Disrupting inferior frontal cortex activity alters affect decoding efficiency from clear but not from ambiguous affective speech

The evaluation of socio-affective sound information is accomplished by the primate auditory cortex in collaboration with limbic and inferior frontal cortex (IFC)--often observed during affective voice classification. Partly opposing views have been proposed, with IFC either coding cognitive processing challenges in case of sensory ambiguity or representing categorical object and affect information for clear voices. Here, we presented clear and ambiguous affective speech to two groups of human participants during neuroimaging, while in one group we inhibited right IFC activity with transcranial magnetic stimulation. IFC activity inhibition led to faster affective decisions, more accurate choice probabilities, reduced auditory cortical activity and increased fronto-limbic connectivity for clear affective speech. This indicates a more intermediate functional property of the IFC than assumed--namely with normal activity representing a more deliberate form of affective sound processing (i.e., enforcing cognitive analysis) that flags categorical sound decisions with precaution (i.e., representation of categorical uncertainty). TeaserInferior frontal cortex enforces cognitive analyses during affect decisions with different levels of sensory ambiguity.

neuroscience↗