Thompson, D., Ferreira, F., & Scheepers, C. (2018). One step at a time: Representational overlap between active voice, be-passive, and get-passive forms in English. Journal of Cognition, 1(1): 35, pp. 1–24, DOI: https://doi.org/10.5334/joc.36.
Jicol, C., Proulx, M. J., Pollick, F. E., & Petrini, K. (2018). Long-term music training modulates the recalibration of audiovisual simultaneity. Experimental brain research, 1-12.
Abstract: To overcome differences in physical transmission time and neural processing, the brain adaptively recalibrates the point of simultaneity between auditory and visual signals by adapting to audiovisual asynchronies. Here, we examine whether the prolonged recalibration process of passively sensed visual and auditory signals is affected by naturally occurring multisensory training known to enhance audiovisual perceptual accuracy. Hence, we asked a group of drummers, of non-drummer musicians and of non-musicians to judge the audiovisual simultaneity of musical and non-musical audiovisual events, before and after adaptation with two fixed audiovisual asynchronies. We found that the recalibration for the musicians and drummers was in the opposite direction (sound leading vision) to that of non-musicians (vision leading sound), and change together with both increased music training and increased perceptual accuracy (i.e. ability to detect asynchrony). Our findings demonstrate that long-term musical training reshapes the way humans adaptively recalibrate simultaneity between auditory and visual signals.
Until 6 July, 2018 there is free access to the paper/chapter at:
Pollick, F. E., Vicary, S., Noble, K., Kim, N., Jang, S., & Stevens, C. J. (2018). Exploring collective experience in watching dance through intersubject correlation and functional connectivity of fMRI brain activity. Progress in brain research. https://doi.org/10.1016/bs.pbr.2018.03.016
Abstract: How the brain contends with naturalistic viewing conditions when it must cope with concurrent streams of diverse sensory inputs and internally generated thoughts is still largely an open question. In this study, we used fMRI to record brain activity while a group of 18 participants watched an edited dance duet accompanied by a soundtrack. After scanning, participants performed a short behavioral task to identify neural correlates of dance segments that could later be recalled. Intersubject correlation (ISC) analysis was used to identify the brain regions correlated among observers, and the results of this ISC map were used to define a set of regions for subsequent analysis of functional connectivity. The resulting network was found to be composed of eight subnetworks and the significance of these subnetworks is discussed. While most subnetworks could be explained by sensory and motor processes, two subnetworks appeared related more to complex cognition. These results inform our understanding of the neural basis of common experience in watching dance and open new directions for the study of complex cognition.
Abstract: Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent’s visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the “like me” hypothesis, and discuss the key role played by the Theory‐of‐Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long‐term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents
Frank Pollick will present his new research with Yashar Moshfeghi at the World Wide Web Conference in Lyon. This is part of the ongoing research collaboration joining together cognitive neuroscience and information retrieval/data science approaches to understand search.
Moshfeghi, Y., & Pollick, F. E. (2018, April). Search Process as Transitions Between Neural States. In Proceedings of the 2018 World Wide Web Conference on World Wide Web (pp. 1683-1692). International World Wide Web Conferences Steering Committee.
Search is one of the most performed activities on the World Wide Web. Various conceptual models postulate that the search process can be broken down into distinct emotional and cognitive states of searchers while they engage in a search process. These models significantly contribute to our understanding of the search process. However, they are typically based on self-report measures, such as surveys, questionnaire, etc. and therefore, only indirectly monitor the brain activity that supports such a process. With this work, we take one step further and directly measure the brain activity involved in a search process. To do so, we break down a search process into five time periods: a realisation of Information Need, Query Formulation, Query Submission, Relevance Judgment and Satisfaction Judgment. We then investigate the brain activity between these time periods. Using functional Magnetic Resonance Imaging (fMRI), we monitored the brain activity of twenty-four participants during a search process that involved answering questions carefully selected from the TREC-8 and TREC 2001 Q/A Tracks. This novel analysis that focuses on transitions rather than states reveals the contrasting brain activity between time periods – which enables the identification of the distinct parts of the search process as the user moves through them. This work, therefore, provides an important first step in representing the search process based on the transitions between neural states. Discovering more precisely how brain activity relates to different parts of the search process will enable the development of brain-computer interactions that better support search and search interactions, which we believe our study and conclusions advance.
Fouragnan, E., Retzler, C., & Philiastides, M. G. (in press). Separate neural representations of prediction error valence and surprise: evidence from an fMRI meta-analysis, Human Brain Mapping. DOI: 10.1002/hbm.24047.
Abstract: Learning occurs when an outcome differs from expectations, generating a reward prediction error signal (RPE). The RPE signal has been hypothesized to simultaneously embody the valence of an outcome (better or worse than expected) and its surprise (how far from expectations). Nonetheless, growing evidence suggests that separate representations of the two RPE components exist in the human brain. Meta‐analyses provide an opportunity to test this hypothesis and directly probe the extent to which the valence and surprise of the error signal are encoded in separate or overlapping networks. We carried out several meta‐analyses on a large set of fMRI studies investigating the neural basis of RPE, locked at decision outcome. We identified two valence learning systems by pooling studies searching for differential neural activity in response to categorical positive‐versus‐negative outcomes. The first valence network (negative > positive) involved areas regulating alertness and switching behaviours such as the midcingulate cortex, the thalamus and the dorsolateral prefrontal cortex whereas the second valence network (positive > negative) encompassed regions of the human reward circuitry such as the ventral striatum and the ventromedial prefrontal cortex. We also found evidence of a largely distinct surprise‐encoding network including the anterior cingulate cortex, anterior insula and dorsal striatum. Together with recent animal and electrophysiological evidence this meta‐analysis points to a sequential and distributed encoding of different components of the RPE signal, with potentially distinct functional roles.
The final paper from the award winning PhD thesis of Polina Zioga has come out in Frontiers in Neuroscience. Polina was a joint student between the School of Psychology and the Glasgow School of Art and supervised by the team of Minhua Ma, Paul Chapman and Frank Pollick who were coauthors on the paper. Another coauthor was Kristian Stefanov, an undergraduate from Neurosciences who helped with the data analysis. The paper describes the results of an experiment using an EEG based brain computer interface that was used in a live performance.
Our Chapter with Marie-Helene Grosbras, qualitative researcher Matthew Reason, former masters student Haodan Tan,choreographer Rosie Kay and Frank Pollick is finally out in this new Oxford Handbook. The handbook is a major contribution with 49 chapters that broadly cover the field of dance. Our chapter includes a novel combination of data from rTMS, fMRI and qualitative analysis to investigate a causal link between regional brain activity in parietal cortex and subjective emotional response to watching dance.
Barsalou, L. W., Dutriaux, L., & Scheepers, C. (in press). Moving beyond the distinction between concrete and abstract concepts. Philosophical Transactions of the Royal Society B. DOI: 10.1098/rstb.2017.0144