Primate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and the inclusion of new data we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.
Successful social interaction relies on the accurate decoding of other peoples’ emotional signals, and their contextual integration. However, little is known about how contextual odors may lead to modulation of cortical processing in response to facial expressions. We investigated how unpleasant and pleasant contextual background odors affected emotion perception and cortical event-related potential (ERP) responses to pictures of faces expressing happy, neutral and disgusted facial expressions. Faces were, regardless of expression, rated more positively in the pleasant odor condition and more negatively in the unpleasant odor condition. Faces were overall rated as more emotionally arousing in the presence of an odor, irrespective of its valence. Contextual odors also interacted with facial expressions, such that happy faces were rated as especially non-arousing in the unpleasant odor condition. The early, face-sensitive N170 ERP component also displayed an interaction effect. Here, disgusted faces were affected by the odor context such that the N170 revealed a relatively larger negativity in the context of a pleasant odor compared with an unpleasant odor. There were no odor effects on the responses to faces in other measured ERP components (P1, VPP, P2, and LPP). These results suggest that odors bias socioemotional perception early stages of the visual processing stream. However, effects may vary across emotional expressions and measurements.
A widespread and popular belief posits that humans possess a cognitive capacity that is limited to keeping track of and maintaining stable relationships with approximately 150 people. This influential number, ‘Dunbar's number’, originates from an extrapolation of a regression line describing the relationship between relative neocortex size and group size in primates. Here, we test if there is statistical support for this idea. Our analyses on complementary datasets using different methods yield wildly different numbers. Bayesian and generalized least-squares phylogenetic methods generate approximations of average group sizes between 69–109 and 16–42, respectively. However, enormous 95% confidence intervals (4–520 and 2–336, respectively) imply that specifying any one number is futile. A cognitive limit on human group size cannot be derived in this manner.
Research Problem: The purpose of this research synthesis is to identify new opportunities for smell-enabled games based upon current olfactory research, and to present early game concepts that have emerged from our empirical assessments. Literature Review: We briefly summarize key projects in the history of scent technologies for film and media. Human-Computer Interaction researchers have also explored a number of uses for scent delivery in interactive digital media. Recent developments in olfactory psychology and neuroscience research suggest that a fruitful avenue for exploration is to develop learning games that expand olfactory capacity. Methodology: We have conducted two studies of computer-based perceptual and cognitive olfactory tasks. Mixture perception experiment: We designed a perceptual experiment where the task was to correctly estimate the intensity of odor components in a blend of coffee and tea. Blended odors were presented to 10 healthy adults by means of a computer-controlled olfactometer. Following each stimulation, the participant used a computer interface to estimate the intensity of components of the blend. Event-based memory experiment: We have developed a digital olfactory version of the children’s game “Memory.” The game interface consists of 32 white squares that are presented in a grid pattern on the screen and that, when participants click on them, triggers the release of one of eight possible smells from the olfactometer. Fifteen healthy adult participants were tested in 10 laboratory sessions distributed over three weeks. Results and Conclusions: Our empirical results suggest that smell training through learning games holds promise as a means of improving cognitive function. The results of our event-based memory experiment suggest that both olfactory and visual memory capacities might have benefitted from olfactory game training. The results of our mixture perception experiment indicate that binary odor mixtures might provide a suitable starting point for perceptual training, and we suggest that a smell-enabled game might include adaptive difficulty by progressively introducing more complex mixtures. We have used event-based memory and mixture perception as “olfactory targets” for game mechanic development, and present early design concepts for “Smelly Genes” and “Scenter.” Finally, we discuss future directions and challenges for this new, interdisciplinary research topic.
Primate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and a new, larger data set, we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.
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