Open MindPub Date : 2024-03-26eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00127
Samuel J Cheyette, Steven T Piantadosi
{"title":"Response to Difficulty Drives Variation in IQ Test Performance.","authors":"Samuel J Cheyette, Steven T Piantadosi","doi":"10.1162/opmi_a_00127","DOIUrl":"10.1162/opmi_a_00127","url":null,"abstract":"<p><p>In a large (<i>N</i> = 300), pre-registered experiment and data analysis model, we find that individual variation in overall performance on Raven's Progressive Matrices is substantially driven by differential strategizing in the face of difficulty. Some participants choose to spend more time on hard problems while others choose to spend less and these differences explain about 42% of the variance in overall performance. In a data analysis jointly predicting participants' reaction times and accuracy on each item, we find that the Raven's task captures at most half of participants' variation in time-controlled ability (48%) down to almost none (3%), depending on which notion of ability is assumed. Our results highlight the role that confounding factors such as motivation play in explaining individuals' differential performance in IQ testing.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"265-277"},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10990577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140858301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-26eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00130
Joseph R Coffey, Margarita Zeitlin, Jean Crawford, Jesse Snedeker
{"title":"It's All in the Interaction: Early Acquired Words Are Both Frequent and Highly Imageable.","authors":"Joseph R Coffey, Margarita Zeitlin, Jean Crawford, Jesse Snedeker","doi":"10.1162/opmi_a_00130","DOIUrl":"https://doi.org/10.1162/opmi_a_00130","url":null,"abstract":"<p><p>Prior studies have found that children are more likely to learn words that are frequent in the input and highly imageable. Many theories of word learning, however, predict that these variables should interact, particularly early in development: frequency of a form is of little use if you cannot infer its meaning, and a concrete word cannot be acquired if you never hear it. The present study explores this interaction, how it changes over time and its relationship to syntactic category effects in children acquiring American English. We analyzed 1461 monolingual English-speaking children aged 1;4-2;6 from the MB-CDI norming study (Fenson et al., 1994). Word frequency was estimated from the CHILDES database, and imageability was measured using adult ratings. There was a strong over-additive interaction between frequency and imageability, such that children were more likely to learn a word if it was both highly imageable and very frequent. This interaction was larger in younger children than in older children. There were reliable differences between syntactic categories independent of frequency and imageability, which did not interact with age. These findings are consistent with theories in which children's early words are acquired by mapping frequent word forms onto concrete, perceptually available referents, such that highly frequent items are only acquired if they are also imageable, and vice versa.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"309-332"},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10990573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140868360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-26eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00135
Rebecca Tollan, Bilge Palaz
{"title":"What Does <i>That</i> Mean? Complementizers and Epistemic Authority.","authors":"Rebecca Tollan, Bilge Palaz","doi":"10.1162/opmi_a_00135","DOIUrl":"https://doi.org/10.1162/opmi_a_00135","url":null,"abstract":"<p><p>A core goal of research in language is to understand the factors that guide choice of linguistic form where more than one option is syntactically well-formed. We discuss one case of optionality that has generated longstanding discussion: the choice of either using or dropping the English complementizer <i>that</i> in sentences like <i>I think (that) the cat followed the dog</i>. Existing psycholinguistic analyses tie <i>that</i>-usage to production pressures associated with sentence planning (Ferreira & Dell, 2000), avoidance of ambiguity (Hawkins, 2004), and relative information density (Jaeger, 2010). Building on observations from cross-linguistic fieldwork, we present a novel proposal in which English <i>that</i> can serve to mark a speaker's \"epistemic authority\" over the information packaged within the embedded clause; that is, it indicates that the speaker has more knowledge of the embedded proposition compared with their addressee and thus has a perspective that they believe their addressee doesn't share. Testing this proposal with a forced-choice task and a series of corpus surveys, we find that English <i>that</i> is keyed to the use of embedded speaker (first-person) subject pronouns and occurs in sentences containing newsworthy information. Our account of <i>that</i>-optionality takes into account why <i>that</i> is associated with both (i) a dense information signal and (ii) semantic-pragmatic content, as well as extending to cases of non-optionality in subject/sentence-initial clauses (e.g., *<i>(That) the cat is following the dog, I already know</i>) and fragment answers (e.g., <i>What do you already know?</i> *<i>(That) the cat is following the dog</i>), where <i>that</i> is required.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"366-394"},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10990574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140863179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-05eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00124
Vanessa Kudrnova, Elizabeth S Spelke, Ashley J Thomas
{"title":"Infants Infer Social Relationships Between Individuals Who Engage in Imitative Social Interactions.","authors":"Vanessa Kudrnova, Elizabeth S Spelke, Ashley J Thomas","doi":"10.1162/opmi_a_00124","DOIUrl":"10.1162/opmi_a_00124","url":null,"abstract":"<p><p>Infants are born into rich social networks and are faced with the challenge of learning about them. When infants observe social interactions, they make predictions about future behavior, but it is not clear whether these predictions are based on social dispositions, social relationships, or both. The current studies (N = 188, N = 90 males) address this question in 12-month-old infants and 16- to 18-month-old toddlers who observe social interactions involving imitation. In Studies 1 and 3, infants and toddlers expected that imitators, compared to non-imitators, would respond to their social partners' distress. Likewise, they expected the targets of imitation, compared to non-targets, to respond to their partner's distress. In Study 2, these expectations did not generalize to interactions with a new partner, providing evidence that infants learned about the relationships between individuals as opposed to their dispositions. In Study 3, infants did not make predictions about responses to laughter, suggesting that infants see imitation as indicative of a specific kind of social relationship. Together, these results provide evidence that imitative interactions support infants' and toddlers' learning about the social relationships connecting unknown individuals.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"202-216"},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10932586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140112614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-05eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00119
Cory Shain
{"title":"Word Frequency and Predictability Dissociate in Naturalistic Reading.","authors":"Cory Shain","doi":"10.1162/opmi_a_00119","DOIUrl":"10.1162/opmi_a_00119","url":null,"abstract":"<p><p>Many studies of human language processing have shown that readers slow down at less frequent or less predictable words, but there is debate about whether frequency and predictability effects reflect separable cognitive phenomena: are cognitive operations that retrieve words from the mental lexicon based on sensory cues distinct from those that predict upcoming words based on context? Previous evidence for a frequency-predictability dissociation is mostly based on small samples (both for estimating predictability and frequency and for testing their effects on human behavior), artificial materials (e.g., isolated constructed sentences), and implausible modeling assumptions (discrete-time dynamics, linearity, additivity, constant variance, and invariance over time), which raises the question: do frequency and predictability dissociate in ordinary language comprehension, such as story reading? This study leverages recent progress in open data and computational modeling to address this question at scale. A large collection of naturalistic reading data (six datasets, >2.2 M datapoints) is analyzed using nonlinear continuous-time regression, and frequency and predictability are estimated using statistical language models trained on more data than is currently typical in psycholinguistics. Despite the use of naturalistic data, strong predictability estimates, and flexible regression models, results converge with earlier experimental studies in supporting dissociable and additive frequency and predictability effects.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"177-201"},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10932590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140111558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-05eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00125
Tom S Juzek
{"title":"Signal Smoothing and Syntactic Choices: A Critical Reflection on the UID Hypothesis.","authors":"Tom S Juzek","doi":"10.1162/opmi_a_00125","DOIUrl":"10.1162/opmi_a_00125","url":null,"abstract":"<p><p>The Smooth Signal Redundancy Hypothesis explains variations in syllable length as a means to more uniformly distribute information throughout the speech signal. The Uniform Information Density hypothesis seeks to generalize this to choices on all linguistic levels, particularly syntactic choices. While there is some evidence for the Uniform Information Density hypothesis, it faces several challenges, four of which are discussed in this paper. First, it is not clear what exactly counts as uniform. Second, there are syntactic alternations that occur systematically but that can cause notable fluctuations in the information signature. Third, there is an increasing body of negative results. Fourth, there is a lack of large-scale evidence. As to the fourth point, this paper provides a broader array of data-936 sentence pairs for nine syntactic constructions-and analyzes them in a test setup that treats the hypothesis as a classifier. For our data, the Uniform Information Density hypothesis showed little predictive capacity. We explore ways to reconcile our data with theory.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"217-234"},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10932588/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140111557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-01eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00117
Yang Wu, Megan Merrick, Hyowon Gweon
{"title":"Expecting the Unexpected: Infants Use Others' Surprise to Revise Their Own Expectations.","authors":"Yang Wu, Megan Merrick, Hyowon Gweon","doi":"10.1162/opmi_a_00117","DOIUrl":"10.1162/opmi_a_00117","url":null,"abstract":"<p><p>Human infants show systematic responses to events that violate their expectations. Can they also revise these expectations based on others' expressions of surprise? Here we ask whether infants (<i>N</i> = 156, mean = 15.2 months, range: 12.0-18.0 months) can use an experimenter's expression of surprise to revise their own expectations about statistically probable vs. improbable events. An experimenter sampled a ball from a box of red and white balls and briefly displayed either a surprised or an unsurprised expression at the outcome before revealing it to the infant. Following an unsurprised expression, the results were consistent with prior work; infants looked longer at a statistically improbable outcome than a probable outcome. Following a surprised expression, however, this standard pattern disappeared or was even reversed. These results suggest that even before infants can observe the unexpected events themselves, they can use others' surprise to <i>expect the unexpected</i>. Starting early in life, human learners can leverage social information that signals others' prediction error to update their own predictions.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"67-83"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10898783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140022738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-01eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00123
Andrew J Nam, James L McClelland
{"title":"Systematic Human Learning and Generalization From a Brief Tutorial With Explanatory Feedback.","authors":"Andrew J Nam, James L McClelland","doi":"10.1162/opmi_a_00123","DOIUrl":"10.1162/opmi_a_00123","url":null,"abstract":"<p><p>We investigate human adults' ability to learn an abstract reasoning task quickly and to generalize outside of the range of training examples. Using a task based on a solution strategy in Sudoku, we provide Sudoku-naive participants with a brief instructional tutorial with explanatory feedback using a narrow range of training examples. We find that most participants who master the task do so within 10 practice trials and generalize well to puzzles outside of the training range. We also find that most of those who master the task can describe a valid solution strategy, and such participants perform better on transfer puzzles than those whose strategy descriptions are vague or incomplete. Interestingly, fewer than half of our human participants were successful in acquiring a valid solution strategy, and this ability was associated with completion of high school algebra and geometry. We consider the implications of these findings for understanding human systematic reasoning, as well as the challenges these findings pose for building computational models that capture all aspects of our findings, and we point toward a role for learning from instructions and explanations to support rapid learning and generalization.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"148-176"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10898786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140022740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-01DOI: 10.1162/opmi_a_00126
Cory Shain, William Schuler
{"title":"A Deep Learning Approach to Analyzing Continuous-Time Cognitive Processes","authors":"Cory Shain, William Schuler","doi":"10.1162/opmi_a_00126","DOIUrl":"https://doi.org/10.1162/opmi_a_00126","url":null,"abstract":"Abstract The dynamics of the mind are complex. Mental processes unfold continuously in time and may be sensitive to a myriad of interacting variables, especially in naturalistic settings. But statistical models used to analyze data from cognitive experiments often assume simplistic dynamics. Recent advances in deep learning have yielded startling improvements to simulations of dynamical cognitive processes, including speech comprehension, visual perception, and goal-directed behavior. But due to poor interpretability, deep learning is generally not used for scientific analysis. Here, we bridge this gap by showing that deep learning can be used, not just to imitate, but to analyze complex processes, providing flexible function approximation while preserving interpretability. To do so, we define and implement a nonlinear regression model in which the probability distribution over the response variable is parameterized by convolving the history of predictors over time using an artificial neural network, thereby allowing the shape and continuous temporal extent of effects to be inferred directly from time series data. Our approach relaxes standard simplifying assumptions (e.g., linearity, stationarity, and homoscedasticity) that are implausible for many cognitive processes and may critically affect the interpretation of data. We demonstrate substantial improvements on behavioral and neuroimaging data from the language processing domain, and we show that our model enables discovery of novel patterns in exploratory analyses, controls for diverse confounds in confirmatory analyses, and opens up research questions in cognitive (neuro)science that are otherwise hard to study.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"192 ","pages":"235-264"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140278413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open MindPub Date : 2024-03-01eCollection Date: 2024-01-01DOI: 10.1162/opmi_a_00122
Leo Westebbe, Yibiao Liang, Erik Blaser
{"title":"The Accuracy and Precision of Memory for Natural Scenes: A Walk in the Park.","authors":"Leo Westebbe, Yibiao Liang, Erik Blaser","doi":"10.1162/opmi_a_00122","DOIUrl":"10.1162/opmi_a_00122","url":null,"abstract":"<p><p>It is challenging to quantify the accuracy and precision of scene memory because it is unclear what 'space' scenes occupy (how can we quantify error when misremembering a natural scene?). To address this, we exploited the ecologically valid, metric space in which scenes occur and are represented: routes. In a delayed estimation task, participants briefly saw a target scene drawn from a video of an outdoor 'route loop', then used a continuous report wheel of the route to pinpoint the scene. Accuracy was high and unbiased, indicating there was no net boundary extension/contraction. Interestingly, precision was higher for routes that were <i>more</i> self-similar (as characterized by the half-life, in meters, of a route's Multiscale Structural Similarity index), consistent with previous work finding a 'similarity advantage' where memory precision is regulated according to task demands. Overall, scenes were remembered to within a few meters of their actual location.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"131-147"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10898787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140022741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}