Emotional Axes: Psychology, Psychophysiology and Neuroanatomical Correlates

Emotional Axes: Psychology, Psychophysiology and Neuroanatomical Correlates

Didem Gökçay (Middle East Technical University, Turkey)
DOI: 10.4018/978-1-61692-892-6.ch003
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The dimensional account of emotions has gained impetus over the last decade. The quantitative representation provided by the dimensional view of emotions is very valuable for applications in affective computing. The two principal axes, valence and arousal, obtained from semantic maps through factor analysis differentially modulate the psychophysiology measures and event related potentials. In addition, there exists distict localizations for valence/arousal-related emotional evaluation processes. Our current knowledge regarding these differences are reviewed in this chapter. Two different models (circumplex, PANA) have been coined to account for the distribution of data clustered within emotional categories. In this chapter, these models are also discussed comparatively in detail.
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It has been slightly over a decade since the investigations regarding the role of emotions in cognitive functionality has gained popularity. Earlier, ‘traditional approaches to the study of cognition emphasized an information-processing view that has generally excluded emotion’ (Phelps, 2006). Then Damasio (1999) introduced the Somatic Marker Hypothesis indicating that emotions interfere with the information processing streams of our brain through preserved somatic signals relating to the body-state structure and regulation either consciously or unconsciously. Nowadays the computer metaphor, which has inspired the human cognition studies is definitely augmented by a new player: affect. Although the main areas in the human brain that subserve emotional processing are already identified at the gross level (Pessoa, 2008), the nature of their interaction with each other, and the nature of their interference with cognitive processes remain elusive. This chapter is an attempt to clarify the dimensional approach to emotional processing, which can be briefly summarized as follows: The representation and expression of emotions is possible through a few orthogonal components. A data point along these components refer to the instantiation of a specific emotion, and emotion instances can be clustered creating emotional categories such as happiness, sadness, fear or anger. In the following sections, details about the main components of emotions will be introduced. However, it is important to mention that other than the dimensional account provided here, there is still ongoing research attempting to identify distinct physiological signatures that represent basic emotions. Most recent reviews in this regard can be found in Kreibig (2010) and Stephens et. al. (2010).

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