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Collective intelligence underpins the success of groups, organizations, markets and societies. Through distributed cognition and coordination, collectives can achieve outcomes that exceed the capabilities of individuals-even experts-resulting in improved accuracy and novel capabilities. Often, collective intelligence is supported by information technology, such as online prediction markets that elicit the 'wisdom of crowds', online forums that structure collective deliberation or digital platforms that crowdsource knowledge from the public. Large language models, however, are transforming how information is aggregated, accessed and transmitted online. Here we focus on the unique opportunities and challenges this transformation poses for collective intelligence. We bring together interdisciplinary perspectives from industry and academia to identify potential benefits, risks, policy-relevant considerations and open research questions, culminating in a call for a closer examination of how large language models affect humans' ability to collectively tackle complex problems., (© 2024. Springer Nature Limited.)

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging remains unclear. To help fill this gap, we outline an empirical agenda that utilizes network analysis and involves the concurrent assessment of large-scale semantic networks and cognitive performance in younger and older adults. We present preliminary data to establish the feasibility and limitations of such empirical, network-analytical approaches., (© 2021 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)

Craving and stress frequently drive compulsive heroin use. Although methadone attenuates craving, drug-conditioned stimuli can trigger craving and possibly stress arousal in heroin-dependent patients receiving methadone maintenance. This study investigated drug cue-related craving, affectivity, and cortisol reactivity in 16 methadone-maintained patients before and after daily methadone. Unexpectedly, drug cues significantly increased craving after (t[15]=-4.27, p=0.001), but not before methadone intake. Patients displayed blunted cortisol response after post-methadone drug cues (t[15]=3.05, p=0.008) suggesting dissociated craving and cortisol reactivity after methadone intake of possible clinical relevance.

Theories of tonal consonance have primarily sought to explain consonance of chords smaller than the octave drawn from the conventional semitone musical scale. Critical evaluation of such theories requires a new body of data. The present study reports consonance ratings for two-tone chords drawn from a quartertone scale and for chords larger than an octave as well as for the chords normally studied. Subjects were drawn from undergraduate psychology courses without preselection for musical aptitude or background. The results were compared with predictions derived from several current theories: psychoacoustic models, in which consonance is attributed to a lack of dissonance or harshsounding pairs of components, and a psychological complexity model which relates consonance to the perceived simplicity of the stimulus. The latter theory, which makes allowance for the unfamiliarity of quartertone chords and for the equivalence of extra-octave and within-octave chords, provided the best qualitative account of the data. It was concluded that a valid theory of tonal consonance must acknowledge the effects of musical experience on musical judgment.