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The initial version of the article by Clithero, Karmarkar, Nave, and Plassmann (Journal of Consumer Psychology, 2024) was critiqued by open comments from a small group of scholars. Their suggestions encouraged the authors to clarify challenging relationships between brain processes and emotions, beliefs, and actions. The revision expanded fMRI and EEG to include measures of vision, facial expression, breathing, heart rhythms, and blood chemistry. The paper provides multiple avenues of joint work between neurological and psychological scholars. The comments below reflect different reactions to the final article. Wes Hutchinson acknowledges that neuroscience insights complement cognitive measures that generate explicit measures of thought, emotion, or preferences, but he warns that repeated measures over time are problematic for both types of measurement, and the inherent complexity of brain–behavior relationships is often underestimated. With both orientations, understanding the functioning of human behavior is akin to making sense of an orchestra, where the interactive blending of different instruments and musicians reflects a complex activity that generates sounds, emotions, and stories. Both consumer neuroscientists and psychologists need to broaden their paradigmatic approaches with bodily measures and advanced psychological procedures to overcome challenges to joint progress. Martin Reiman asserts that despite difficulties with measures that have different levels of abstraction or velocity, research has provided remarkable associations between brain activity and consumer behavior. Effective studies merging brain and behavior can effectively proceed with studies that differ in two dimensions: first, by altering the number of variables, and second, by shifting whether the scientific paradigm is inductive or deductive. In its simple form, the Excavation path explores brain activity when a person is exposed to specific statements or emotions. In its most challenging form, Integrative Studies generate predictions from theories that test the convergent validity of divergent measures and leverage skills from different researchers. Studies reflecting high levels on one dimension but low levels on the other can also provide fruitful research opportunities. Brian Knutson, like Reimann, counters the idea that consumer psychology has not lived up to its promises. He references studies showing that activity from very specific areas of the brain reliably predicts choices better than explicit ratings or choices. Such research generates deductions from increasingly precise neural maps that enable confirmation of theory. That said, he acknowledges that consumer neuroscience is not able to identify a brain button that would alter choice through manipulated neurostimulation. However, since human brains are similar across people, the depth of neural insights that are consistent across a small sample of 40 respondents may generate greater insights than conventional marketing research with 2000 respondents. The cost of neuroscience will further decrease with gains in reliability, validity, and generalizability, particularly if augmented with bodily measures. He acknowledges that the theoretical side has developed more slowly than applications, particularly applications that are supported by sponsoring organizations more satisfied with local insights than general models. [ABSTRACT FROM AUTHOR]

This paper presents arguments and evidence from psychology and neuroscience supporting Lipton's 2004 claim that scientists create knowledge through an abductive process that he calls "Inference to the Best Explanation". The paper develops two conclusions. Conclusion 1 is that without conscious effort on our part, our brains use a process very similar to abduction as a powerful way of interpreting sensory information. To support Conclusion 1, evidence from psychology and neuroscience is presented that suggests that what we humans perceive through our senses is not reality, but rather, our 'brain's "best guess" of the causes of its sensory input. The implication of this best guessing is that our brains use a process very similar to abduction throughout our lives to inform us of what is happening in the world around us. In addition, an argument based on Darwinian evolution is presented claiming that our brains do an excellent job of interpreting sensory information from the outside world. (If they did not, we, as a species, could hardly have survived.) Combining these two claims leads to Conclusion 1. Building on Conclusion 1, Conclusion 2 is that Lipton and others are correct in claiming that scientists use abduction when creating scientific theories. Abduction must be strong, because Nature chose abduction for its own sensemaking purposes. This paper's contribution to knowledge is in pointing out that recent psychological and neuroscientific research has major implications for the philosophical world's confidence in the probable validity of abductive inference. The punchline is simple: Nature chose abduction! [ABSTRACT FROM AUTHOR]

We present motivation and practical steps necessary to find parameter estimates of joint models of behavior and neural electrophysiological data. This tutorial is written for researchers wishing to build joint models of human behavior and scalp and intracranial electroencephalographic (EEG) or magnetoencephalographic (MEG) data, and more specifically those researchers who seek to understand human cognition. Although these techniques could easily be applied to animal models, the focus of this tutorial is on human participants. Joint modeling of M/EEG and behavior requires some knowledge of existing computational and cognitive theories, M/EEG artifact correction, M/EEG analysis techniques, cognitive modeling, and programming for statistical modeling implementation. This paper seeks to give an introduction to these techniques as they apply to estimating parameters from neurocognitive models of M/EEG and human behavior, and to evaluate model results and compare models. Due to our research and knowledge on the subject matter, our examples in this paper will focus on testing specific hypotheses in human decision-making theory. However, most of the motivation and discussion of this paper applies across many modeling procedures and applications. We provide Python (and linked R) code examples in the tutorial and appendix. Readers are encouraged to try the exercises at the end of the document. [ABSTRACT FROM AUTHOR]

Recent work in several fields of psychology has advanced understanding of how humans imaginatively construct, simulate and (pre‐)feel the future. These advances have not yet been substantively engaged in social and cultural geography. In this paper, we identify, review and begin to draw together scholarship in human geography and several subfields of psychology on the ways in which people imagine and navigate towards the future. The most influential existing work on the future in geography has concerned powerful institutional and discursive depictions of threatening times‐to‐come. In contrast, psychological and neuroscientific work on cognitive processes involved in prospection extends possibilities for a human geographical approach to the future considering how people relate to discursive imaginaries and spatial environments. Reinvigoration of the human geography‐psychology nexus can further critical understanding of the spatialities through which futures are imaginatively formed and felt by individuals, and are thereby brought into the realm of political and social possibility. [ABSTRACT FROM AUTHOR]

Many scientific disciplines give rise to research published under the moniker of aesthetics. For instance, both psychology and neuroscience have highly active subfields focused on aesthetics research, known as empirical aesthetics and neuroaesthetics. However, it remains unclear what aesthetics is about, and, consequently, if aesthetics research pursued by different scientific disciplines addresses common problems. It is, therefore, difficult to assess how well aesthetics is doing as a scientific enterprise, identify and compare its main subfields, and quantify its productivity. To give an unbiased account of what counts as aesthetics across scientific disciplines, we conducted a bibliometric analysis of every publication found in Web of Science tagged as aesthetics. Spanning, 1970 to 2018, the retrieved literature comprised a total of 27,159 papers, 45,832 authors, and 123 countries. Visualization and bibliometric techniques were used to investigate the main research trends and subfields, growth of publications, citation analysis, and country productivity and collaborations. From 1970 to 2018, there was a clear increase in aesthetics research over time, with a stronger growth in recent years. The retrieved documents received a total of 217,931 citations, with a mean of 8.02 citations per document (SD = 25.7). Both a cluster analysis of the data, and a comparative analysis a posteriori, revealed that the aesthetics literature clusters into distinct research areas that differ significantly in their object of interest, research productivity and impact. This finding suggests that aesthetics is better thought of as a confederate of research traditions than a whole unified by common problems and research strategies. [ABSTRACT FROM AUTHOR]

Although we are accustomed to thinking about technology as involving things—objects and processes—derived from scientific discoveries, science also creates a technology of ideas, ways of thinking both about the world and about human beings. And unlike "thing technology," "idea technology" can have powerful effects even when the ideas are false. This paper discusses false idea technology, or ideology, and suggests mechanisms by which it can have effects on both individuals and societies. It discusses neuroscience as the "next frontier" of ideology that may change our conceptions of human nature. [ABSTRACT FROM AUTHOR]

Reinforcement learning methods have recently been very successful at performing complex sequential tasks like playing Atari games, Go and Poker. These algorithms have outperformed humans in several tasks by learning from scratch, using only scalar rewards obtained through interaction with their environment. While there certainly has been considerable independent innovation to produce such results, many core ideas in reinforcement learning are inspired by phenomena in animal learning, psychology and neuroscience. In this paper, we comprehensively review a large number of findings in both neuroscience and psychology that evidence reinforcement learning as a promising candidate for modeling learning and decision making in the brain. In doing so, we construct a mapping between various classes of modern RL algorithms and specific findings in both neurophysiological and behavioral literature. We then discuss the implications of this observed relationship between RL, neuroscience and psychology and its role in advancing research in both AI and brain science. [ABSTRACT FROM AUTHOR]

This paper provides a critical review of several possible mechanisms at different levels of analysis underlying the effects and therapeutic potential of psychedelics. At the (1) biochemical level, psychedelics primarily affect the 5-HT 2A receptor, increase neuroplasticity, offer a critical period for social reward learning, and have anti-inflammatory properties. At the (2) neural level, psychedelics have been associated with reduced efficacy of thalamo-cortical filtering, the loosening of top-down predictive signaling and an increased sensitivity to bottom-up prediction errors, and activation of the claustro-cortical-circuit. At the (3) psychological level, psychedelics have been shown to induce altered and affective states, they affect cognition, induce belief change, exert social effects, and can result in lasting changes in behavior. We outline the potential for a unifying account of the mechanisms underlying psychedelics and contrast this with a model of pluralistic causation. Ultimately, a better understanding of the specific mechanisms underlying the effects of psychedelics could allow for a more targeted therapeutic approach. We highlight current challenges for psychedelic research and provide a research agenda to foster insight in the causal-mechanistic pathways underlying the efficacy of psychedelic research and therapy. • This paper comprehensively reviews the pharmacological, neural and psychological mechanisms underlying psychedelics. • We critically evaluate the merits and pitfalls of each explanatory mechanism. • We provide a research agenda for psychedelic research, including a theory of pluralistic causation. [ABSTRACT FROM AUTHOR]