Stability of individual differences in implicitly guided attention

Daily activities often occur in familiar environments, affording us an opportunity to learn. Laboratory studies have shown that people readily acquire an implicit spatial preference for locations that frequently contained a search target in the past. These studies, however, have focused on group characteristics, downplaying the significance of individual differences. In a pre-registered study, we examined the stability of individual differences in two variants of an implicit location probability learning (LPL) task. We tested the possibility that individual differences were stable in variants that shared the same search process, but not in variants involving different search processes. In Experiment 1, participants performed alternating blocks of T-among-Ls and 5-among-2s search tasks. Unbeknownst to them, the search target appeared disproportionately often in one region of space; the high-probability regions differed between the two tasks. LPL transferred between the two tasks. In addition, individuals who showed greater LPL in the T-task also did so in the 5-task and vice versa. In Experiment 2, participants searched for either a camouflaged-T against background noise or a well-segmented T among well-segmented Ls. These two tasks produced task-specific learning that did not transfer between tasks. Moreover, individual differences in learning did not correlate between tasks. Thus, LPL is associated with stable individual differences across variants, but only when the variants share common search processes.

The effect of emotional faces on reward-related probability learning in depressed patients

BACKGROUND

Existing research indicates that individuals with Major Depressive Disorder (MDD) exhibit a bias toward salient negative stimuli. However, the impact of such biased stimuli on concurrent cognitive and affective processes in individuals with depression remains inadequately understood. This study aimed to investigate the effects of salient environmental stimuli, specifically emotional faces, on reward-associated processes in MDD.

METHODS

Thirty-three patients with recurrent MDD and thirty-two healthy controls (HC) matched for age, sex, and education were included in the study. We used a reward-related associative learning (RRAL) task primed with emotional (happy, sad, neutral) faces to investigate the effect of salient stimuli on reward-related learning and decision-making in functional magnetic resonance imaging (fMRI). Participants were instructed to ignore emotional faces during the task. The fMRI data were analyzed using a full-factorial general linear model (GLM) in Statistical Parametric Mapping (SPM12).

RESULTS

In depressed patients, cues primed with sad faces were associated with reduced amygdala activation. However, both HC and MDD group exhibited reduced ventral striatal activity while learning reward-related cues and receiving rewards.

LIMITATIONS

The patients'medication usage was not standardized.

CONCLUSIONS

This study underscores the functional alteration of the amygdala in response to cognitive tasks presented with negative emotionally salient stimuli in the environment of MDD patients. The observed alterations in amygdala activity suggest potential interconnected effects with other regions of the prefrontal cortex. Understanding the intricate neural connections and their disruptions in depression is crucial for unraveling the complex pathophysiology of the disorder.

Attenuation of spatial bias with target template variation

This study investigated the impact of target template variation or consistency on attentional bias in location probability learning. Participants conducted a visual search task to find a heterogeneous shape among a homogeneous set of distractors. The target and distractor shapes were either fixed throughout the experiment (target-consistent group) or unpredictably varied on each trial (target-variant group). The target was often presented in one possible search region, unbeknownst to the participants. When the target template was consistent throughout the biased visual search, spatial attention was persistently biased toward the frequent target location. However, when the target template was inconsistent and varied during the biased search, the spatial bias was attenuated so that attention was less prioritized to a frequent target location. The results suggest that the alternative use of target templates may interfere with the emergence of a persistent spatial bias. The regularity-based spatial bias depends on the number of attentional shifts to the frequent target location, but also on search-relevant contexts.

Statistical learning at a virtual cocktail party

Statistical learning - the ability to extract distributional regularities from input - is suggested to be key to language acquisition. Yet, evidence for the human capacity for statistical learning comes mainly from studies conducted in carefully controlled settings without auditory distraction. While such conditions permit careful examination of learning, they do not reflect the naturalistic language learning experience, which is replete with auditory distraction - including competing talkers. Here, we examine how statistical language learning proceeds in a virtual cocktail party environment, where the to-be-learned input is presented alongside a competing speech stream with its own distributional regularities. During exposure, participants in the Dual Talker group concurrently heard two novel languages, one produced by a female talker and one by a male talker, with each talker virtually positioned at opposite sides of the listener (left/right) using binaural acoustic manipulations. Selective attention was manipulated by instructing participants to attend to only one of the two talkers. At test, participants were asked to distinguish words from part-words for both the attended and the unattended languages. Results indicated that participants' accuracy was significantly higher for trials from the attended vs. unattended language. Further, the performance of this Dual Talker group was no different compared to a control group who heard only one language from a single talker (Single Talker group). We thus conclude that statistical learning is modulated by selective attention, being relatively robust against the additional cognitive load provided by competing speech, emphasizing its efficiency in naturalistic language learning situations.

Spatial transfer of object-based statistical learning

A large number of recent studies have demonstrated that efficient attentional selection depends to a large extent on the ability to extract regularities present in the environment. Through statistical learning, attentional selection is facilitated by directing attention to locations in space that were relevant in the past while suppressing locations that previously were distracting. The current study shows that we are not only able to learn to prioritize locations in space but also locations within objects independent of space. Participants learned that within a specific object, particular locations within the object were more likely to contain relevant information than other locations. The current results show that this learned prioritization was bound to the object as the learned bias to prioritize a specific location within the object stayed in place even when the object moved to a completely different location in space. We conclude that in addition to spatial attention prioritization of locations in space, it is also possible to learn to prioritize relevant locations within specific objects. The current findings have implications for the inferred spatial priority map of attentional weights as this map cannot be strictly retinotopically organized.

Contribution of peripheral vision to attentional learning

Attention is tuned towards locations that frequently contain a visual search target (location probability learning; LPL). Peripheral vision, covering a larger field than the fovea, often receives information about the target. Yet what is the role of peripheral vision in attentional learning? Using gaze-contingent eye tracking, we examined the impact of simulated peripheral vision loss on location probability learning. Participants searched for a target T among distractor Ls. Unbeknownst to them, the T appeared disproportionately often in one quadrant. Participants searched with either intact vision or "tunnel vision," restricting the visible search items to the central 6.7º (in diameter) of the current gaze. When trained with tunnel vision, participants in Experiment 1 acquired LPL, but only if they became explicitly aware of the target's location probability. The unaware participants were not faster finding the target in high-probability than in low-probability locations. When trained with intact vision, participants in Experiment 2 successfully acquired LPL, regardless of whether they were aware of the target's location probability. Thus, whereas explicit learning may proceed with central vision alone, implicit LPL is strengthened by peripheral vision. Consistent with Guided Search (Wolfe, 2021), peripheral vision supports a nonselective pathway to guide visual search.

Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning

Humans are capable of acquiring multiple types of information presented in the same information stream. It has been suggested that at least two parallel learning processes are important during learning of sequential patterns-statistical learning and rule-based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. To differentiate between the simultaneous mechanisms at the single trial level, we apply a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule-based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrate that concomitant but distinct aspects of information coded in the N2 time window play a role in these mechanisms: mismatch detection and response control underlie statistical learning and rule-based learning, respectively, albeit with different levels of time-sensitivity. Moreover, the effects of the two learning mechanisms in the different temporally decomposed clusters of neural activity also differed from each other in neural sources. Importantly, the right inferior frontal cortex (BA44) was specifically implicated in visuomotor statistical learning, confirming its role in the acquisition of transitional probabilities. In contrast, visuomotor rule-based learning was associated with the prefrontal gyrus (BA6). The results show how simultaneous learning mechanisms operate at the neurophysiological level and are orchestrated by distinct prefrontal cortical areas. The current findings deepen our understanding on the mechanisms of how humans are capable of learning multiple types of information from the same stimulus stream in a parallel fashion.

Cross-situational statistical learning in younger and older adults

Research investigating statistical learning, the process of tracking regularities in the environment, in older adults has been limited; with existing studies suggesting there are age-related declines. We aim to further understand older adults' statistical learning abilities using a cross-situational statistical learning paradigm in which learners map novel words to novel objects. In Experiment 1, we manipulated task difficulty and found an overall age deficit but no interaction between age and difficulty. In Experiment 2, after extended practice with a first set of object-word mappings, learners could remap a subset of previously learned words to novel objects. Based on hyper-binding, older adults might be more willing to remap previously learned words to novel objects. However, despite overall poorer learning, older adults were actually less likely to remap. Even though older adults may have an associative memory deficit, learned associations are not more weakly bound for older relative to younger adults.

Reliability and Replicability of Implicit and Explicit Reinforcement Learning Paradigms in People With Psychotic Disorders

BACKGROUND

Motivational deficits in people with psychosis may be a result of impairments in reinforcement learning (RL). Therefore, behavioral paradigms that can accurately measure these impairments and their change over time are essential.

METHODS

We examined the reliability and replicability of 2 RL paradigms (1 implicit and 1 explicit, each with positive and negative reinforcement components) given at 2 time points to healthy controls (n = 75), and people with bipolar disorder (n = 62), schizoaffective disorder (n = 60), and schizophrenia (n = 68).

RESULTS

Internal consistency was acceptable (mean α = 0.78 ± 0.15), but test-retest reliability was fair to low (mean intraclass correlation = 0.33 ± 0.25) for both implicit and explicit RL. There were no clear effects of practice for these tasks. Largely, performance on these tasks shows intact implicit and impaired explicit RL in psychosis. Symptom presentation did not relate to performance in any robust way.

CONCLUSIONS

Our findings replicate previous literature showing spared implicit RL and impaired explicit reinforcement in psychosis. This suggests typical basal ganglia dopamine release, but atypical recruitment of the orbitofrontal and dorsolateral prefrontal cortices. However, we found that these tasks have only fair to low test-retest reliability and thus may not be useful for assessing change over time in clinical trials.

Statistical learning of unbalanced exclusive-or temporal sequences in humans

A pervasive issue in statistical learning has been to determine the parameters of regularity extraction. Our hypothesis was that the extraction of transitional probabilities can prevail over frequency if the task involves prediction. Participants were exposed to four repeated sequences of three stimuli (XYZ) with each stimulus corresponding to the position of a red dot on a touch screen that participants were required to touch sequentially. The temporal and spatial structure of the positions corresponded to a serial version of the exclusive-or (XOR) that allowed testing of the respective effect of frequency and first- and second-order transitional probabilities. The XOR allowed the first-order transitional probability to vary while being not completely related to frequency and to vary while the second-order transitional probability was fixed (p(Z|X, Y) = 1). The findings show that first-order transitional probability prevails over frequency to predict the second stimulus from the first and that it also influences the prediction of the third item despite the presence of second-order transitional probability that could have offered a certain prediction of the third item. These results are particularly informative in light of statistical learning models.

Impairments in Probabilistic Prediction and Bayesian Learning Can Explain Reduced Neural Semantic Priming in Schizophrenia

It has been proposed that abnormalities in probabilistic prediction and dynamic belief updating explain the multiple features of schizophrenia. Here, we used electroencephalography (EEG) to ask whether these abnormalities can account for the well-established reduction in semantic priming observed in schizophrenia under nonautomatic conditions. We isolated predictive contributions to the neural semantic priming effect by manipulating the prime's predictive validity and minimizing retroactive semantic matching mechanisms. We additionally examined the link between prediction and learning using a Bayesian model that probed dynamic belief updating as participants adapted to the increase in predictive validity. We found that patients were less likely than healthy controls to use the prime to predictively facilitate semantic processing on the target, resulting in a reduced N400 effect. Moreover, the trial-by-trial output of our Bayesian computational model explained between-group differences in trial-by-trial N400 amplitudes as participants transitioned from conditions of lower to higher predictive validity. These findings suggest that, compared with healthy controls, people with schizophrenia are less able to mobilize predictive mechanisms to facilitate processing at the earliest stages of accessing the meanings of incoming words. This deficit may be linked to a failure to adapt to changes in the broader environment. This reciprocal relationship between impairments in probabilistic prediction and Bayesian learning/adaptation may drive a vicious cycle that maintains cognitive disturbances in schizophrenia.

Evidence that haloperidol impairs learning and motivation scores in a probabilistic task by reducing the reward expectation

Activation of midbrain dopamine neurons in response to positive prediction errors and reward predictive cues is proposed to "energize" reward seeking behaviors and approach responses to places where the reward is expected. In the present study, we tested the effect of the D2-dopamine receptor antagonist haloperidol on response latencies to enter two arms of a Y-maze with different reward probabilities. Adult male Wistar rats were trained to explore the Y-maze with sucrose pellets placed 30% of times at the end of one arm and 70% of times at the opposite arm. Therefore, the reward expectation was different among arms, and was updated in the trials when the reward was omitted. After training, rats received 0.05, 0.10, 0.15 mg/kg haloperidol, or saline 30 min before the test session. In the last, but not in the first trials, haloperidol caused a dose-dependent increase in arm choice latency and response latency. Saline, but not haloperidol, treated rats presented significantly longer response latencies for the 30% compared to the 70% reward probability arm. Haloperidol also caused a dose-dependent decrease in the number of entries in the 70% reward probability arm, increased the number of non-responses, and caused a dose-dependent increase in the number of re-entries in the 30% reward probability arm after non-rewarded trials. Control experiments suggested that haloperidol did not cause motor impairment or satiation, but rather impaired learning and motivation scores by reducing the reward expectation.

Electrophysiological signatures of visual statistical learning in 3-month-old infants at familial and low risk for autism spectrum disorder

Visual statistical learning (VSL) refers to the ability to extract associations and conditional probabilities within the visual environment. It may serve as a precursor to cognitive and social communication development. Quantifying VSL in infants at familial risk (FR) for Autism Spectrum Disorder (ASD) provides opportunities to understand how genetic predisposition can influence early learning processes which may, in turn, lay a foundation for cognitive and social communication delays. We examined electroencephalography (EEG) signatures of VSL in 3-month-old infants, examining whether EEG correlates of VSL differentiated FR from low-risk (LR) infants. In an exploratory analysis, we then examined whether EEG correlates of VSL at 3 months relate to cognitive function and ASD symptoms at 18 months. Infants were exposed to a continuous stream of looming shape pairs with varying probability that the shapes would occur in sequence (high probability-deterministic condition; low probability-probabilistic condition). EEG was time-locked to shapes based on their transitional probabilities. EEG analysis examined group-level characteristics underlying specific components, including the late frontal positivity (LFP) and N700 responses. FR infants demonstrated increased LFP and N700 response to the probabilistic condition, whereas LR infants demonstrated increased LFP and N700 response to the deterministic condition. LFP at 3 months predicted 18-month visual reception skills and not ASD symptoms. Our findings thus provide evidence for distinct VSL processes in FR and LR infants as early as 3 months. Atypical pattern learning in FR infants may lay a foundation for later delays in higher level, nonverbal cognitive skills, and predict ASD symptoms well before an ASD diagnosis is made.

Human free-operant performance varies with a concurrent task: Probability learning without a task, and schedule-consistent with a task

Three experiments examined human rates and patterns of responding during exposure to various schedules of reinforcement with or without a concurrent task. In the presence of the concurrent task, performances were similar to those typically noted for nonhumans. Overall response rates were higher on medium-sized ratio schedules than on smaller or larger ratio schedules (Experiment 1), on interval schedules with shorter than longer values (Experiment 2), and on ratio compared with interval schedules with the same rate of reinforcement (Experiment 3). Moreover, bout-initiation responses were more susceptible to influence by rates of reinforcement than were within-bout responses across all experiments. In contrast, in the absence of a concurrent task, human schedule performance did not always display characteristics of nonhuman performance, but tended to be related to the relationship between rates of responding and reinforcement (feedback function), irrespective of the schedule of reinforcement employed. This was also true of within-bout responding, but not bout-initiations, which were not affected by the presence of a concurrent task. These data suggest the existence of two strategies for human responding on free-operant schedules, relatively mechanistic ones that apply to bout-initiation, and relatively explicit ones, that tend to apply to within-bout responding, and dominate human performance when other demands are not made on resources.

Specificity of representations in infants' visual statistical learning

Past work has demonstrated infants' robust statistical learning across visual and auditory modalities. However, the specificity of representations produced via visual statistical learning has not been fully explored. The current study addressed this by investigating infants' abilities to identify previously learned object sequences when some object features (e.g., shape, face) aligned with prior learning and other features did not. Experiment 1 replicated past work demonstrating that infants can learn statistical regularities across sequentially presented objects and extended this finding to 16-month-olds. In Experiment 2, infants viewed test sequences in which one object feature (e.g., face) had been removed but the other feature (e.g., shape) was maintained, resulting in failure to identify familiar sequences. We further probed learning specificity by assessing infants' recognition of sequences when one feature was altered rather than removed (Experiment 3) and when one feature was uncorrelated with the original sequence structure (Experiment 4). In both cases, infants failed to identify sequences in which object features were not identical between learning and test. These findings suggest that infants are limited in their ability to generalize the statistical structure of an object sequence when the objects' features do not align between learning and test.

How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning

Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.

Functional brain network architecture supporting the learning of social networks in humans

Most humans have the good fortune to live their lives embedded in richly structured social groups. Yet, it remains unclear how humans acquire knowledge about these social structures to successfully navigate social relationships. Here we address this knowledge gap with an interdisciplinary neuroimaging study drawing on recent advances in network science and statistical learning. Specifically, we collected BOLD MRI data while participants learned the community structure of both social and non-social networks, in order to examine whether the learning of these two types of networks was differentially associated with functional brain network topology. We found that participants learned the community structure of the networks, as evidenced by a slower reaction time when a trial moved between communities than when a trial moved within a community. Learning the community structure of social networks was also characterized by significantly greater functional connectivity of the hippocampus and temporoparietal junction when transitioning between communities than when transitioning within a community. Furthermore, temporoparietal regions of the default mode were more strongly connected to hippocampus, somatomotor, and visual regions for social networks than for non-social networks. Collectively, our results identify neurophysiological underpinnings of social versus non-social network learning, extending our knowledge about the impact of social context on learning processes. More broadly, this work offers an empirical approach to study the learning of social network structures, which could be fruitfully extended to other participant populations, various graph architectures, and a diversity of social contexts in future studies.

Simultaneous training on overlapping grapheme phoneme correspondences augments learning and retention

An important component of learning to read is the acquisition of letter-to-sound mappings. The sheer quantity of mappings and many exceptions in opaque languages such as English suggests that children may use a form of statistical learning to acquire them. However, whereas statistical models of reading are item-based, reading instruction typically focuses on rule-based approaches involving small sets of regularities. This discrepancy poses the question of how different groupings of regularities, an unexamined factor of most reading curricula, may affect learning. Exploring the interplay between item statistics and rules, this study investigated how consonant variability, an item-level factor, and the degree of overlap among the to-be-trained vowel strings, a group-level factor, influence learning. English-speaking first graders (N = 361) were randomly assigned to be trained on vowel sets with high overlap (e.g., EA, AI) or low overlap (e.g., EE, AI); this was crossed with a manipulation of consonant frame variability. Whereas high vowel overlap led to poorer initial performance, it resulted in more learning when tested immediately and after a 2-week-delay. There was little beneficial effect of consonant variability. These findings indicate that online letter/sound processing affects how new knowledge is integrated into existing information. Moreover, they suggest that vowel overlap should be considered when designing reading curricula.

Specificity and persistence of statistical learning in distractor suppression

Statistical regularities in distractor location trigger suppression of high-probability distractor locations during visual search. The degree to which such suppression reflects generalizable, persistent changes in a spatial priority map has not been examined. We demonstrate that suppression of high-probability distractor locations persists after location probabilities are equalized and likely reflects a genuine reshaping of the priority map rather than more transient effects of selection history. Statistically learned suppression generalizes across contexts within a task during learning but does not generalize between task paradigms using unrelated stimuli in identical spatial locations. These findings suggest that stimulus features do play a role in learned spatial suppression, potentially gating the weights applied to a spatial priority map. However, the binding of location to context during learning is not automatic, in contrast to the previously reported interaction of location-based statistical learning and stimulus features. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Evidence for a dissociation between causal beliefs and instrumental actions

Human experiments have demonstrated that instrumental performance of an action and the causal beliefs of the effectiveness of an action in producing a reward are correlated and controlled by the probability of an action leading to a reward. The animal literature, however, shows that instrumental performance under free-operant training differs even when the reward probabilities are matched while subjects undergo training under ratio or interval schedules of reward. In two experiments, we investigated whether causal beliefs would correlate with instrumental performance under ratio and interval schedules for matched reward probabilities. In both experiments, we found that performance was higher under ratio than under interval training. However, causal beliefs were similar between these two conditions despite these differences in instrumental performance. When reward probabilities were increased by experimental manipulations in Experiment 2, the causal beliefs increased but performance decreased with respect to Experiment 1. This is evidence that instrumental performance and causal action-reward attribution may not follow from the same psychological process under free-operant training.

Interactions between human orbitofrontal cortex and hippocampus support model-based inference

Internal representations of relationships between events in the external world can be utilized to infer outcomes when direct experience is lacking. This process is thought to involve the orbitofrontal cortex (OFC) and hippocampus (HPC), but there is little evidence regarding the relative role of these areas and their interactions in inference. Here, we used a sensory preconditioning task and pattern-based neuroimaging to study this question. We found that associations among value-neutral cues were acquired in both regions during preconditioning but that value-related information was only represented in the OFC at the time of the probe test. Importantly, inference was accompanied by representations of associated cues and inferred outcomes in the OFC, as well as by increased HPC-OFC connectivity. These findings suggest that the OFC and HPC represent only partially overlapping information and that interactions between the two regions support model-based inference.

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

The implicit acquisition of complex probabilistic regularities has been found to be crucial in numerous automatized cognitive abilities, including language processing and associative learning. However, it has not been completely elucidated how the implicit extraction of second-order nonadjacent transitional probabilities is reflected by neurophysiological processes. Therefore, this study investigated the sensitivity of event-related brain potentials (ERPs) to these probabilistic regularities embedded in a sequence of visual stimuli without providing explicit information on the structure of the stimulus stream. Healthy young adults (N = 32) performed a four-choice RT task that included a sequential regularity between nonadjacent trials yielding a complex transitional probability structure. ERPs were measured relative to both stimulus and response onset. RTs indicated the rapid acquisition of the sequential regularity and the transitional probabilities. The acquisition process was also tracked by the stimulus-locked and response-locked P3 component: The P3 peak was larger for the sequence than for the random stimuli, while the late P3 was larger for less probable than for more probable short-range relations among the random stimuli. According to the RT and P3 effects, sensitivity to the sequential regularity is assumed to be supported by the initial sensitivity to the transitional probabilities. These results suggest that stimulus-response contingencies on the probabilistic regularities of the ongoing stimulus context are implicitly mapped and constantly revised. Overall, this study (1) highlights the role of predictive processes during implicit memory formation, and (2) delineates a potential to gain further insight into the dynamics of implicit acquisition processes.

Learning to construct sentences in Spanish: a replication of the Weird Word Order technique

In the present study, children's early ability to organise words into sentences was investigated using the Weird Word Order procedure with Spanish-speaking children. Spanish is a language that allows for more flexibility in the positions of subjects and objects, with respect to verbs, than other previously studied languages (English, French, and Japanese). As in prior studies (Abbot-Smith et al., 2001; Chang et al., 2009; Franck et al., 2011; Matthews et al., 2005, 2007), we manipulated the relative frequency of verbs in training sessions with two age groups (three- and four-year-old children). Results supported earlier findings with regard to frequency: children produced atypical word orders significantly more often with infrequent verbs than with frequent verbs. The findings from the present study support probabilistic learning models which allow higher levels of flexibility and, in turn, oppose hypotheses that defend early access to advanced grammatical knowledge.

Mark my words: High frequency marker words impact early stages of language learning

High frequency words have been suggested to benefit both speech segmentation and grammatical categorization of the words around them. Despite utilizing similar information, these tasks are usually investigated separately in studies examining learning. We determined whether including high frequency words in continuous speech could support categorization when words are being segmented for the first time. We familiarized learners with continuous artificial speech comprising repetitions of target words, which were preceded by high-frequency marker words. Crucially, marker words distinguished targets into 2 distributionally defined categories. We measured learning with segmentation and categorization tests and compared performance against a control group that heard the artificial speech without these marker words (i.e., just the targets, with no cues for categorization). Participants segmented the target words from speech in both conditions, but critically when the marker words were present, they influenced acquisition of word-referent mappings in a subsequent transfer task, with participants demonstrating better early learning for mappings that were consistent (rather than inconsistent) with the distributional categories. We propose that high-frequency words may assist early grammatical categorization, while speech segmentation is still being learned. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Statistical regularities bias overt attention

A previous study employing the additional singleton paradigm showed that a singleton distractor that appeared more often in one specific location interfered less with target search than when it appeared at any other location. These findings suggested that through statistical learning the location that was likely to contain a distractor was suppressed relative to all other locations. Even though feasible, it is also possible that this effect is due to faster disengagement of attention from the high-probability distractor location. The present study tested this hypothesis using a variant of the additional singleton task adapted for eye tracking in which observers made a speeded saccade to a shape singleton and gave a manual response. The singleton distractor was presented more often at one location than all other locations. Consistent with the suppression hypothesis, we found that fewer saccades landed at the high-probability distractor location than any other location. Also, when a target appeared at the high-probability location, saccade latencies towards the target were higher than latencies towards the target when it was presented at other locations. Furthermore, in addition to suppression, we also found evidence for faster disengagement from the high-probability distractor location than the low-probability distractor location; however, this effect was relatively small. The current findings support the notion that through statistical learning plasticity is induced in the spatial priority map of attentional selection so that the high-probability distractor location is suppressed compared to any other location.

A Single Paradigm for Implicit and Statistical Learning

Implicit learning generally refers to the acquisition of structures that, like knowledge of natural language grammar, are not available to awareness. In contrast, statistical learning has frequently been related to learning language structures that are explicitly available, such as vocabulary. In this paper, we report an experimental paradigm that enables testing of both classic implicit and statistical learning in language. The paradigm employs an artificial language comprising sentences that accompany visual scenes that they represent, thus combining artificial grammar learning with cross-situational statistical learning of vocabulary. We show that this methodology enables a comparison between acquisition of grammar and vocabulary, and the influences on their learning. We show that both grammar and vocabulary are promoted by explicit information about the language structure, that awareness of structure affects acquisition during learning, and awareness precedes learning, but is not distinctive at the endpoint of learning. The two traditions of learning-implicit and statistical-can be conjoined in a single paradigm to explore both the phenomenological and learning consequences of statistical structural knowledge.

Attentional instructions modulate differential context-switch effects after short and long training in human predictive learning

Three experiments in human predictive learning assessed the modulating role of instructions on context-switch effects on performance after different levels of training. Cue X (a food name) was paired with an outcome (gastric malaise) in Context A (a specific restaurant), whereas another cue, Y, was presented in the absence of outcome in Context B. The series manipulated the testing context (same or different from the acquisition context), the length of training (short vs. long), and the instructions participants received before testing (attentional or neutral). Attentional instructions intended to either focusing participants' attention on the context (Experiments 1 and 2) or to take attention away from the context (Experiment 3). In agreement with the predictions of the attentional theory of context processing, instructions that focused participants' attention on the context made retrieval of information after long training context specific, something that did not occur in the absence of attentional instructions. Conversely, instructions that took participants' attention away from the context (by focusing their attention on the cue) attenuated context-switch effects that otherwise appear after short training. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Statistics learned are statistics forgotten: Children's retention and retrieval of cross-situational word learning

Children are able to resolve the referential ambiguity of learning new words by tracking co-occurrence probabilities across moments in time, a behavior termed cross-situational word learning (CSWL). Although we know that children can use co-occurrence data to map words to objects, the literature has a striking limitation: research has focused on encoding of language and, consequently, children's CSWL has only been assessed at an immediate test. The current research addressed this gap in the literature by examining whether children can retain and retrieve learned words after a retention interval, and whether children's age and individual cognitive abilities contribute to their CSWL performance. The results revealed that children were able to retain and retrieve co-occurrence statistics, but only reliably so at the end of early childhood. Moreover, children's visual recognition memory abilities and the timing of learning events were the two key factors that contributed to children's performance. These findings have implications for theories and computational models of CSWL, and suggest that more research is needed to understand the processes that support CSWL after encoding. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Human Foragers: Searchers by Nature and Experience

Diverse studies of human foraging have revealed behavioral strategies that may have evolved as adaptations for foraging. Here, we used an outdoor experimental search task to explore the effect of three sources of information on participants' performance: (i) information obtained directly from performing a search, (ii) information obtained prior to testing in the form of a distilled snippet of knowledge intended to experimentally simulate information acquired culturally about the environment, and (iii) information obtained from experience of foraging for natural resources for economic gain. We found that (i) immediate searching experience improved performance from the beginning to the end of the short, 2-min task, (ii) information priming improved performance notably from the very beginning of the task, and (iii) natural resource foraging experience improved performance to a lesser extent. Our results highlight the role of culturally transmitted information as well as the presence of mechanisms to rapidly integrate and implement new information into searching choices, which ultimately influence performance in a foraging task.

Daily-life stress differentially impacts ventral striatal dopaminergic modulation of reward processing in first-degree relatives of individuals with psychosis

Emerging evidence shows that stress can impair the ability to learn from and pursue rewards, which in turn has been linked to motivational impairments characteristic of the psychotic disorder. Ventral striatal dopaminergic neurotransmission has been found to modulate reward processing, and appears to be disrupted by exposure to stress. We investigated the hypothesis that stress experienced in the everyday life has a blunting effect on reward-induced dopamine release in the ventral striatum of 16 individuals at a familial risk for psychosis compared to 16 matched control subjects. Six days of ecological momentary assessments quantified the amount of daily-life stress prior to [¹⁸F]fallypride PET imaging while performing a probabilistic reinforcement learning task. Relative to the controls, individuals at a familial risk for psychosis who encountered more daily-life stress showed significantly diminished extent of reward-induced dopamine release in the right ventral striatum, as well as poorer performance on the reward task. These findings provide the first neuromolecular evidence for stress-related deregulation of reward processing in familial predisposition to psychosis. The implication of daily-life stress in compromised modulation of reward function may facilitate the design of targeted neuropharmacological and ecological interventions.

Attractor-like Dynamics in Belief Updating in Schizophrenia

Subjects with a diagnosis of schizophrenia (Scz) overweight unexpected evidence in probabilistic inference: such evidence becomes "aberrantly salient." A neurobiological explanation for this effect is that diminished synaptic gain (e.g., hypofunction of cortical NMDARs) in Scz destabilizes quasi-stable neuronal network states (or "attractors"). This attractor instability account predicts that (1) Scz would overweight unexpected evidence but underweight consistent evidence, (2) belief updating would be more vulnerable to stochastic fluctuations in neural activity, and (3) these effects would correlate. Hierarchical Bayesian belief updating models were tested in two independent datasets (n = 80 male and n = 167 female) comprising human subjects with Scz, and both clinical and nonclinical controls (some tested when unwell and on recovery) performing the "probability estimates" version of the beads task (a probabilistic inference task). Models with a standard learning rate, or including a parameter increasing updating to "disconfirmatory evidence," or a parameter encoding belief instability were formally compared. The "belief instability" model (based on the principles of attractor dynamics) had most evidence in all groups in both datasets. Two of four parameters differed between Scz and nonclinical controls in each dataset: belief instability and response stochasticity. These parameters correlated in both datasets. Furthermore, the clinical controls showed similar parameter distributions to Scz when unwell, but were no different from controls once recovered. These findings are consistent with the hypothesis that attractor network instability contributes to belief updating abnormalities in Scz, and suggest that similar changes may exist during acute illness in other psychiatric conditions.SIGNIFICANCE STATEMENT Subjects with a diagnosis of schizophrenia (Scz) make large adjustments to their beliefs following unexpected evidence, but also smaller adjustments than controls following consistent evidence. This has previously been construed as a bias toward "disconfirmatory" information, but a more mechanistic explanation may be that in Scz, neural firing patterns ("attractor states") are less stable and hence easily altered in response to both new evidence and stochastic neural firing. We model belief updating in Scz and controls in two independent datasets using a hierarchical Bayesian model, and show that all subjects are best fit by a model containing a belief instability parameter. Both this and a response stochasticity parameter are consistently altered in Scz, as the unstable attractor hypothesis predicts.

Successful structure learning from observational data

Previous work suggests that humans find it difficult to learn the structure of causal systems given observational data alone. We identify two conditions that enable successful structure learning from observational data: people succeed if the underlying causal system is deterministic, and if each pattern of observations has a single root cause. In four experiments, we show that either condition alone is sufficient to enable high levels of performance, but that performance is poor if neither condition applies. A fifth experiment suggests that neither determinism nor root sparsity takes priority over the other. Our data are broadly consistent with a Bayesian model that embodies a preference for structures that make the observed data not only possible but probable.

Delay Discounting and Probability Discounting, But Not Response Inhibition, Are Associated With Sexual Risk Taking in Adults

Sexual risk behavior (SRB) is associated with impulsivity, but it is not clear whether different aspects of impulsivity are uniquely related to SRBs in adults. Unmarried adults ages 18 to 30 (N = 296; 41.0% male) recruited from the community reported their frequency of SRBs over the past six months using the Sexual Risk Survey (SRS; Turchik & Garske, 2009) and completed three behavioral measures of impulsivity: insensitivity to delayed consequences (delay discounting [DD]), insensitivity to probabilistic consequences (probability discounting [PD]) and response inhibition (stop signal task [SST]). SRS total scores were significantly related to both DD and PD but not SST. These findings suggest that insensitivity to delayed and probabilistic consequences, but not response inhibition, are meaningfully associated with SRBs in young adults. This may be important for the development of strategies to prevent or reduce sexual risk behaviors.

Learning unfamiliar pitch intervals: A novel paradigm for demonstrating the learning of statistical associations between musical pitches

While mastering a musical instrument takes years, becoming familiar with a new music system requires less time and skills. In this study, we examine whether musically untrained Western listeners can incidentally learn an unfamiliar, microtonal musical scale from simply engaging in a timbre discrimination task. The experiment is comprised of an Exposure and a Test phase. During Exposure, 21 non-musicians were instructed to detect a timbre shift (TS) within short microtonal melodies, and we hypothesised that they would incidentally learn about the pitch interval structure of the microtonal scale from attending to the melodies during the task. In a follow-up Test phase, the tone before the TS was either a member (congruent) or a non-member (incongruent) of the scale. Based on our statistical manipulation of the stimuli, incongruent tones would be a better predictor of an incoming TS than the congruent tones. We therefore expect a faster response time to the shift after the participants have heard an incongruent tone. Specifically, a faster response time observed after an incongruent tone would imply participants’ ability to differentiate tones from the microtonal and the diatonic scale, and reflect their learning of the microtonal pitch intervals. Results are consistent with our predictions. In investigating the learning of a microtonal scale, our study can offer directions for future research on the perception of computer music and new musical genres.

Human Pavlovian fear conditioning conforms to probabilistic learning

Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.

Bayesian validation of grammar productions for the language of thought

Probabilistic proposals of Language of Thoughts (LoTs) can explain learning across different domains as statistical inference over a compositionally structured hypothesis space. While frameworks may differ on how a LoT may be implemented computationally, they all share the property that they are built from a set of atomic symbols and rules by which these symbols can be combined. In this work we propose an extra validation step for the set of atomic productions defined by the experimenter. It starts by expanding the defined LoT grammar for the cognitive domain with a broader set of arbitrary productions and then uses Bayesian inference to prune the productions from the experimental data. The result allows the researcher to validate that the resulting grammar still matches the intuitive grammar chosen for the domain. We then test this method in the language of geometry, a specific LoT model for geometrical sequence learning. Finally, despite the fact of the geometrical LoT not being a universal (i.e. Turing-complete) language, we show an empirical relation between a sequence’s probability and its complexity consistent with the theoretical relationship for universal languages described by Levin’s Coding Theorem.

Habitual versus goal-driven attention

Recent research has expanded the list of factors that control spatial attention. Beside current goals and perceptual salience, statistical learning, reward, motivation and emotion also affect attention. But do these various factors influence spatial attention in the same manner, as suggested by the integrated framework of attention, or do they target different aspects of spatial attention? Here I present evidence that the control of attention may be implemented in two ways. Whereas current goals typically modulate where in space attention is prioritized, search habits affect how one moves attention in space. Using the location probability learning paradigm, I show that a search habit forms when people frequently find a visual search target in one region of space. Attentional cuing by probability learning differs from that by current goals. Probability cuing is implicit and persists long after the probability cue is no longer valid. Whereas explicit goal-driven attention codes space in an environment-centered reference frame, probability cuing is viewer-centered and is insensitive to secondary working memory load and aging. I propose a multi-level framework that separates the source of attentional control from its implementation. Similar to the integrated framework, the multi-level framework considers current goals, perceptual salience, and selection history as major sources of attentional control. However, these factors are implemented in two ways, controlling where spatial attention is allocated and how one shifts attention in space.

A universal cue for grammatical categories in the input to children: Frequent frames

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Data from typologically diverse languages shows common distributional patterns.

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Discontinuous repetitive patterns in the input provide cues for category assignment.

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Morphological frames accurately predict nouns and verbs in the input to children.

How does a child map words to grammatical categories when words are not overtly marked either lexically or prosodically? Recent language acquisition theories have proposed that distributional information encoded in sequences of words or morphemes might play a central role in forming grammatical classes. To test this proposal, we analyze child-directed speech from seven typologically diverse languages to simulate maximum variation in the structures of the world’s languages. We ask whether the input to children contains cues for assigning syntactic categories in frequent frames, which are frequently occurring nonadjacent sequences of words or morphemes. In accord with aggregated results from previous studies on individual languages, we find that frequent word frames do not provide a robust distributional pattern for accurately predicting grammatical categories. However, our results show that frames are extremely accurate cues cross-linguistically at the morpheme level. We theorize that the nonadjacent dependency pattern captured by frequent frames is a universal anchor point for learners on the morphological level to detect and categorize grammatical categories. Whether frames also play a role on higher linguistic levels such as words is determined by grammatical features of the individual language.

Explicit goal-driven attention, unlike implicitly learned attention, spreads to secondary tasks

To what degree does spatial attention for one task spread to all stimuli in the attended region, regardless of task relevance? Most models imply that spatial attention acts through a unitary priority map in a task-general manner. We show that implicit learning, unlike endogenous spatial cuing, can bias spatial attention within one task without biasing attention to a spatially overlapping secondary task. Participants completed a visual search task superimposed on a background containing scenes, which they were told to encode for a later memory task. Experiments 1 and 2 used explicit instructions to bias spatial attention to one region for visual search; Experiment 3 used location probability cuing to implicitly bias spatial attention. In location probability cuing, a target appeared in one region more than others despite participants not being told of this. In all experiments, search performance was better in the cued region than in uncued regions. However, scene memory was better in the cued region only following endogenous guidance, not after implicit biasing of attention. These data support a dual-system view of top-down attention that dissociates goal-driven and implicitly learned attention. Goal-driven attention is task general, amplifying processing of a cued region across tasks, whereas implicit statistical learning is task-specific. (PsycINFO Database Record

Infant statistical-learning ability is related to real-time language processing

Infants are adept at learning statistical regularities in artificial language materials, suggesting that the ability to learn statistical structure may support language development. Indeed, infants who perform better on statistical learning tasks tend to be more advanced in parental reports of infants' language skills. Work with adults suggests that one way statistical learning ability affects language proficiency is by facilitating real-time language processing. Here we tested whether 15-month-olds' ability to learn sequential statistical structure in artificial language materials is related to their ability to encode and interpret native-language speech. Specifically, we tested their ability to learn sequential structure among syllables (Experiment 1) and words (Experiment 2), as well as their ability to encode familiar English words in sentences. The results suggest that infants' ability to learn sequential structure among syllables is related to their lexical-processing efficiency, providing continuity with findings from children and adults, though effects were modest.

Relationship between effortful motivation and neurocognition in schizophrenia

Effortful motivation and reward valuation learning deficits are associated with negative symptoms and impaired cognition in schizophrenia (SZ) patients. Whereas clinical assessments of motivation and reward value typically rely upon clinician ratings or self-report scales, behavioral measures often confound these constructs. Simple reverse-translated behavioral tasks that independently quantify motivation and reward valuation-which could then be linked to cognition-may facilitate the development of pro-cognitive therapeutics by bridging the "preclinical-to-clinical" gap. This study determined whether novel behavioral measures of effortful motivation and reward valuation are associated with impaired cognition in SZ patients (n=36). Patients completed the Progressive Ratio Breakpoint task (PRBT; physical effort motivation) and the Probabilistic Learning Task (PLT; reward learning/valuation) in conjunction with the MATRICS Consensus Cognitive Battery (MCCB). SZ patients exhibited statistically significant deficits in global cognition and all individual MCCB subdomains. Significant correlations were observed between PRBT and MCCB global cognition (r=0.52), speed of processing (r=0.56) and attention vigilance (r=0.48) subdomains, but not with PLT or clinical symptoms. Results indicate that effort and reward learning deficits are dissociable targets that can improve our understanding of cognitive impairments associated among patients with SZ. More importantly, the results support the long-standing notion that the measurement of cognitive impairments in SZ is highly linked to a willingness to expend effort. The availability of a PRBT designed for use in both rodents and humans could improve our understanding of the nature of cognitive impairments in neuropsychiatric disorders and accelerate the development of novel pro-cognitive therapeutics.

The longevity of statistical learning: When infant memory decays, isolated words come to the rescue

Research over the past 2 decades has demonstrated that infants are equipped with remarkable computational abilities that allow them to find words in continuous speech. Infants can encode information about the transitional probability (TP) between syllables to segment words from artificial and natural languages. As previous research has tested infants immediately after familiarization, infants' ability to retain sequential statistics beyond the immediate familiarization context remains unknown. Here, we examine infants' memory for statistically defined words 10 min after familiarization with an Italian corpus. Eight-month-old English-learning infants were familiarized with Italian sentences that contained 4 embedded target words-2 words had high internal TP (HTP, TP = 1.0) and 2 had low TP (LTP, TP = .33)-and were tested on their ability to discriminate HTP from LTP words using the Headturn Preference Procedure. When tested after a 10-min delay, infants failed to discriminate HTP from LTP words, suggesting that memory for statistical information likely decays over even short delays (Experiment 1). Experiments 2-4 were designed to test whether experience with isolated words selectively reinforces memory for statistically defined (i.e., HTP) words. When 8-month-olds were given additional experience with isolated tokens of both HTP and LTP words immediately after familiarization, they looked significantly longer on HTP than LTP test trials 10 min later. Although initial representations of statistically defined words may be fragile, our results suggest that experience with isolated words may reinforce the output of statistical learning by helping infants create more robust memories for words with strong versus weak co-occurrence statistics. (PsycINFO Database Record

Altered Medial Frontal Feedback Learning Signals in Anorexia Nervosa

BACKGROUND

In their relentless pursuit of thinness, individuals with anorexia nervosa (AN) engage in maladaptive behaviors (restrictive food choices and overexercising) that may originate in altered decision making and learning.

METHODS

In this functional magnetic resonance imaging study, we employed computational modeling to elucidate the neural correlates of feedback learning and value-based decision making in 36 female patients with AN and 36 age-matched healthy volunteers (12-24 years). Participants performed a decision task that required adaptation to changing reward contingencies. Data were analyzed within a hierarchical Gaussian filter model that captures interindividual variability in learning under uncertainty.

RESULTS

Behaviorally, patients displayed an increased learning rate specifically after punishments. At the neural level, hemodynamic correlates for the learning rate, expected value, and prediction error did not differ between the groups. However, activity in the posterior medial frontal cortex was elevated in AN following punishment.

CONCLUSIONS

Our findings suggest that the neural underpinning of feedback learning is selectively altered for punishment in AN.

Predictions and causal estimations are not supported by the same associative structure

Studies performed by different researchers have shown that judgements about cue–outcome relationships are systematically influenced by the type of question used to request those judgements. It is now recognized that judgements about the strength of the causal link between a cue and an outcome are mostly determined by the cue–outcome contingency, whereas predictions of the outcome are more influenced by the probability of the outcome given the cue. Although these results make clear that those different types of judgement are mediated by some knowledge of the normative differences between causal estimations and outcome predictions, they do not speak to the underlying processes of these effects. The experiment presented here reveals an interaction between the type of question and the order of trials that challenges standard models of causal and predictive learning that are framed exclusively in associative terms or exclusively in higher order reasoning terms. However, this evidence could be easily explained by assuming the combined intervention of both types of process.

Inferences about unobserved causes in human contingency learning

Estimates of the causal efficacy of an event need to take into account the possible presence and influence of other unobserved causes that might have contributed to the occurrence of the effect. Current theoretical approaches deal differently with this problem. Associative theories assume that at least one unobserved cause is always present. In contrast, causal Bayes net theories (including Power PC theory) hypothesize that unobserved causes may be present or absent. These theories generally assume independence of different causes of the same event, which greatly simplifies modelling learning and inference. In two experiments participants were requested to learn about the causal relation between a single cause and an effect by observing their co-occurrence (Experiment 1) or by actively intervening in the cause (Experiment 2). Participants’ assumptions about the presence of an unobserved cause were assessed either after each learning trial or at the end of the learning phase. The results show an interesting dissociation. Whereas there was a tendency to assume interdependence of the causes in the online judgements during learning, the final judgements tended to be more in the direction of an independence assumption. Possible explanations and implications of these findings are discussed.

Mechanisms of the associated nontargets effect: Processes influenced by statistical learning in a simple visual environment

In three visual search experiments participants were asked to make a target response if either of two targets was present and to make a nontarget response if neither target was present. Some target-absent displays included only nontarget features that never occurred in the same displays as target features, whereas other target-absent displays included nontarget features that did sometimes occur with target features. Nontarget responses were reliably faster in the former case than in the latter. This “associated nontargets effect” appears to arise from participants’ ability to learn and to use contingencies between the presence of certain nontargets and the absence of any target.

Prior belief and polarity in multicue learning

We report two experiments in which participants are trained using a multicue probability learning (MCPL) task, which attempts to simulate the acquisition of expert judgement by experience in the real world. Participants were asked to predict performance in certain occupations given a profile of personality test results with trial-by-trial outcome feedback. Only some cues were relevant, and the polarity of the cues (positive or negative predictors) was unspecified. In addition, 25% of random noise was added to the feedback to simulate real world uncertainty. The main factor of interest was that the role of prior belief (determined in a separate study of stereotypes) interfered with the learning process. Experiment 1 failed to find any influence of prior belief in the cues that were irrelevant to the criterion being trained. However, in Experiment 2 people learned to use the relevant cues better when their effect conformed with rather than conflicted with prior belief. Both experiments showed strong effects of cue polarity, with positive predictors much more easily learned. The results are discussed with reference to the cognitive processes involved in MCPL and closely related tasks.

Constraints on Statistical Learning Across Species

Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process.

Generation of Hypotheses in Wason's 2–4–6 Task: an Information Theory Approach

We explored the “context of discovery” in Wason's 2–4–6 task, focusing on how the first hypothesis is generated. According to Oaksford and Chater (1994a) people generate hypotheses extracting “common features”, or regularities, from the available triples, but their model does not explain why some regularities contribute to the hypothesis more than do other regularities. Our conjecture is that some regularities contribute to the hypothesis more than do other regularities because people estimate the amount of information in the perceived regularities and try to preserve as much information as possible in their initial hypotheses. Experiment 1, which used two initial triples, showed that the presence of high-information relational regularities in the initial triples affected the information in the initial hypotheses more than did the presence of low-information object regularities. Experiment 2 extended the results to the classic situation in which only one initial triple is given. It also suggested that amount of information is the only aspect of the structure of the triple that affects hypotheses generation. Experiment 3 confirmed the latter finding: Although relations are commonly distinguished between first-order and higher order relations, the latter being most important for generating hypotheses (Gentner, 1983), higher order relations do have an effect on Wason's 2–4–6 task only if their presence increases information. In the conclusion we discuss the statistical soundness of human hypotheses generation processes, and we ask an unanswered question: Amount of information explains why some regularities are preferred to others, but only within a set of “nonarbitrary” regularities; there are object regularities that are rich in information content, but are considered “arbitrary”, and are not used in generating hypotheses. Which formal property can distinguish between these two sets of regularities?