Bayesian Surprise Predicts Human Event Segmentation in Story Listening
Cogn Sci. 2023 Oct;47(10):e13343. doi: 10.1111/cogs.13343.ABSTRACTEvent segmentation theory posits that people segment continuous experience into discrete events and that event boundaries occur when there are large transient increases in prediction error. Here, we set out to test this theory in the context of story listening, by using a deep learning language model (GPT-2) to compute the predicted probability distribution of the next word, at each point in the story. For three stories, we used the probability distributions generated by GPT-2 to compute the time series of prediction error. We also asked participants to list...
Source: Cognitive Science - October 23, 2023 Category: Neuroscience Authors: Manoj Kumar Ariel Goldstein Sebastian Michelmann Jeffrey M Zacks Uri Hasson Kenneth A Norman Source Type: research
Recurrence Quantification Analysis of Crowd Sound Dynamics
Cogn Sci. 2023 Oct;47(10):e13363. doi: 10.1111/cogs.13363.ABSTRACTWhen multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global aco...
Source: Cognitive Science - October 23, 2023 Category: Neuroscience Authors: Shannon Proksch Majerle Reeves Kent Gee Mark Transtrum Chris Kello Ramesh Balasubramaniam Source Type: research
Questions About Quantifiers: Symbolic and Nonsymbolic Quantity Processing by the Brain
Cogn Sci. 2023 Oct;47(10):e13346. doi: 10.1111/cogs.13346.ABSTRACTOne approach to understanding how the human cognitive system stores and operates with quantifiers such as "some," "many," and "all" is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link between quantifier processing and nonsymbolic quantity processing has been considered in the past, it has never been discussed extensively. Simultaneously, there is a long line of research within the field of numerical cognition on the relationship ...
Source: Cognitive Science - October 23, 2023 Category: Neuroscience Authors: Jakub Szymanik Arnold Kochari Heming Str ømholt Bremnes Source Type: research
When Native Speakers Are Not "Native-Like:" Chunking Ability Predicts (Lack of) Sensitivity to Gender Agreement During Online Processing
Cogn Sci. 2023 Oct;47(10):e13366. doi: 10.1111/cogs.13366.ABSTRACTPrevious work on individual differences has revealed limitations in the ability of existing measures (e.g., working memory) to predict language processing. Recent evidence suggests that an individual's sensitivity to detect the statistical regularities present in language (i.e., "chunk sensitivity") may significantly modulate online sentence processing. We investigated whether individual chunk sensitivity predicted the online processing of gender cues, a core linguistic feature of Spanish. In a self-paced reading task, we examined native speakers' processing...
Source: Cognitive Science - October 23, 2023 Category: Neuroscience Authors: Manuel F Pulido Priscila L ópez-Beltrán Source Type: research
Surface and Contextual Linguistic Cues in Dialog Act Classification: A Cognitive Science View
Cogn Sci. 2023 Oct;47(10):e13367. doi: 10.1111/cogs.13367.ABSTRACTWhat role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency-based, machine learning, and deep learning methods all yield similar per...
Source: Cognitive Science - October 23, 2023 Category: Neuroscience Authors: Guido M Linders Max M Louwerse Source Type: research
