Publication | Open Access
Emotion, Language, and the Brain
166
Citations
131
References
2011
Year
Language FunctioningAffective VariableNeurolinguisticsAffective NeurosciencePsycholinguisticsSocial InteractionsPsychologySocial SciencesAffective ScienceBrain PotentialEmotional ResponseAffective ComputingCognitive NeuroscienceBrain NetworkHealth SciencesCognitive ScienceSpeech ProductionCommunication NeuroscienceLanguage NetworkEmotion ProcessingSpeech CommunicationSystems NeuroscienceNeural SpeechNeuroscienceSpeech Neural SystemsSpeech PerceptionEmotionEmotion Recognition
Humans convey emotions through both verbal content and non‑verbal cues, and while decoding vocal emotions is rapid, electrophysiological evidence indicates a multilayered process with distinct temporal and functional stages. This review aims to synthesize concepts and empirical evidence on emotional speech and language processing. It examines behavioral, event‑related potential, and functional MRI studies to map the neural substrates of emotional communication. Neuroimaging and lesion studies reveal a functionally differentiated brain network underpinning these processing stages, supporting a multistep model of vocal and visual emotion expression that clarifies how emotions are communicated via speech and language.
Abstract In social interactions, humans can express how they feel in what (verbal) they say and how (non‐verbal) they say it. Although decoding of vocal emotion expressions occurs rapidly, accumulating electrophysiological evidence suggests that this process is multilayered and involves temporally and functionally distinct processing steps. Neuroimaging and lesion data confirm that these processing steps, which support emotional speech and language comprehension, are anchored in a functionally differentiated brain network. The present review on emotional speech and language processing discusses concepts and empirical clinical and neuroscientific evidence on the basis of behavioral, event‐related brain potential, and functional magnetic resonance imaging data. These data allow shaping our understanding of how we communicate emotions to others through speech and language. It leads to a multistep processing model of vocal and visual emotion expressions.
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