The third research question addressed the presence of laughter-specific effects in the priming paradigm. Schupp et al. (2003) reported that stimuli of evolutionary significance evoked larger ERP patterns than less important stimuli. This brings up the possibility that category specific emotion processing is evidenced in ERPs. Of interest along this vein is whether evolutionarily significant emotional meaning of stimuli such as pictures (e.g., erotica, mutilations) and sounds (e.g., threatening, happy) is preferentially processed compared to symbolic or learned emotional significance. This investigation is the first to use laughter, posited to have evolved as an important social signal. Although, laughs produced priming effects that were similar to other positive environmental sound, the ERP component differences suggest that there is some specificity with regard laughter processing that is only apparent at the neurocognitive level.
The behavioral results showed that, in general, laughs elicited effects in a similar manner as other positive prime sounds. In both accuracy and RT measures across all of the experiments laughs showed similar qualitative effects as positive sounds. In Experiment 3, laughs showed greater accuracy (but equal RT) of the prime-target congruency evaluation than positive sounds. This is likely due to the ease of recognition afforded to laughs compared to the other positive IADS sounds. Laughs were expected to signal positive emotion in a manner that is efficient and uses fewer attentional and processing resources than positive and negative sounds. This may
explain why laughs showed similar accuracy and RT in Experiment 3 as obtained in the other experiments, whereas other sounds showed decreased performance.
One ERP pattern window showed a clear distinction between laughs and positive and negative IADS. Within the MFN window over orbitofrontal sites, laughs evoked a less negative pattern than either positive or negative IADS. The pattern differences between positive and negative IADS were not statistically different. An orbitofrontal effect showed that laughs have a unique effect related to priming that begins approximately 200 ms after target onset and was sustained over the course of the ERP duration.
If laughs are a special category, they should be examined further with regard to other categories of stimuli. While there was variation within the sample of laughs used in the investigation, they represent a single stimulus category. The environmental sound categories compared to laughs contained a variety of sound types including mechanical, weather, musical, violence, cheers, environmental soundscapes, and human as well as animal vocalizations. If laughs do garner category-specific processing it is possible that the differences in behavioral and ERP measures might arise from their vocal nature. For instance, social characteristics associated with vocalizations may be processed differently than nonvocal sounds even when both are non- linguistic. In order to investigate this possibility, it may be necessary to first make comparisons of laughter to other positive and negative categories of human non-liguistic vocalizations, such as erotic sounds, pleasant surprise, screams, unpleasant moans, and crying. These comparisons could demonstrate how laughs differ from other affective nonlinguistic sounds produced by humans. Additionally, studies that vary prosody may be informative. For example, a simple acoustic sound “ahh” could be vocalized in manners that express happy, sad, and fearful prosodies that are compared to laugh burst prosody. This would maintain the frequency content
while varying the affective meaning. Further studies might investigate differences amongst mechanical, animal, and music that convey affective meaning. There is evidence for differential activations in the superior temporal that occur between human versus animal vocalizations (Fectau, Armony, Joanette, & Belin, 2004) human speech and non-liguistic vocalizations and a variety of environmental sounds (Belin, Zatorre, & Ahad, 2002).
A major challenge for future research is how to deal with individual differences in appraisal of different sound stimuli used in investigations. Since not everyone perceives the same stimulus as equally positive or negative, it may be necessary to create stimulus sets that are individualized. For example, study participants might rate a variety of stimuli prior to their experiment session, and the stimulus conditions are generated for each participant. Individualized stimuli would maximize affective differences amongst affective stimulus categories for participants, which increases the ability to detect behavioral and ERP differences. The downside to this method is that homogeneity of stimuli used across participants would be lost. A large corpus of auditory sounds is necessary to select enough stimuli of different types for use in paradigms such as ERPs, which require a large number of trials.
The understanding of the laughter network connectivity is not well understood (Meyer et al., 2007). Observations from clinical conditions, such as hypothalamic tumors (Striano et al. 2005) that result in pathological laughter, and stimulation of supplementary motor area cortex (Fried et al, 1998) and subthalamic nucleus (Krack et al. 2001) present a number of possible laugh network components involved in laughter production. A review by Wild et al. (2003) suggests that emotion related subcortical regions, such as the amygdala, thalamus, hypothalamus, and pons, as well as voluntary regions, such as frontal premotor and motor regions that are involved in the production of laughter. The findings of studies on laughter production point to a
division between involuntary and voluntary networks involved in laughter production (Owren & Amoss, In press). The perception of laughter, on the other hand, is associated with activations of bilateral amygdala and temporal auditory cortex regions (Sander & Scheich, 2001). Meyer et al. (2005) found that laughter, speech, and nonvocal sounds bilaterally activated the peri-sylvian cortex and were functionally separable using fMRI. Laughter in particular activated right hemisphere auditory and somatosensory regions, whereas nonvocal sounds activated medial Heschl’s gyrus, planum temporale and parietal operculum. Findings of Osaka et al (2003) suggest that the extrastriate, primary motor cortex, and the supplementary motor area may be components of a network involved in the representation of laughter. Such evidence suggests that laughter may receive preferential processing by brain regions distinct from those that process nonvocal sounds and regions that process speech. More research investigations are necessary to uncover neurocognitive specialization of processing during laughter perception. The corpus of laughter stimuli developed for the present investigation provides means for pursuing an answer to this question.