摘要：In this paper we sketch a new framework for affect elicitation, which is based on previous evolutionary and connectionist modeling and experimental work from our group. Affective monitoring is considered a local match-mismatch process within a module of the neural network. Negative affect is raised instantly by mismatches, incongruency, disfluency, novelty, incoherence, and dissonance, whereas positive affect follows from matches, congruency, fluency, familiarity, coherence, and resonance, at least when an initial mismatch can be solved quickly. Affective monitoring is considered an evolutionary-early conflict and change detection process operating at the same level as, for instance, attentional selection. It runs in parallel and imparts affective flavour to emotional behavior systems, which involve evolutionary-prepared stimuli and action tendencies related to for instance defensive, exploratory, attachment, or appetitive behavior. Positive affect is represented in the networks by high-frequency oscillations, presumably in the gamma band. Negative affect corresponds to more incoherent lower-frequency oscillations, presumably in the theta band. For affect to become conscious, large-scale synchronization of the oscillations over the network and the construction of emotional experiences are required. These constructions involve perceptions of bodily states and action tendencies, but also appraisals as well as efforts to regulate the emotion. Importantly, affective monitoring accompanies every kind of information processing, but conscious emotions, which result from the later integration of affect in a cognitive context, are much rarer events.
