Domain generality versus modality specificity: the paradox of statistical learning

Visual statistical learning requires attention

Statistical learning is a person's ability to automatically learn environmental regularities through passive exposure. Since the earliest studies of statistical learning in infants, it has been debated exactly how "passive" this learning can be (i.e., whether attention is needed for learning to occur). In Experiment 1 of the current study, participants performed a serial feature search task where they searched for a target shape among heterogenous nontarget shapes. Unbeknownst to the participants, one of these nontarget shapes was presented much more often in location. Even though the regularity concerned a nonsalient, nontarget item that did not receive any attentional priority during search, participants still learned its regularity (responding faster when it was presented at this high-probability location). While this may suggest that not much, if any, attention is needed for learning to occur, follow-up experiments showed that if an attentional strategy (i.e., color subset search or exogenous cueing) effectively prevents attention from being directed to this critical regularity, incidental learning is no longer observed. We conclude that some degree of attention to a regularity is needed for visual statistical learning to occur.

Statistical learning across cognitive and affective domains: a multidimensional review

Statistical learning (SL) is a fundamental cognitive ability enabling individuals to detect and exploit regularities in environmental input. It plays a crucial role in language acquisition, perceptual processing, and social learning, supporting development from infancy through adulthood. In this review, we adopt a multidimensional perspective to synthesize empirical and theoretical findings on SL, covering experimental paradigms, developmental trajectories, and neural mechanisms. Furthermore, we extend the discussion to the emerging intersection between SL and affective processes. Although emotional factors have recently been proposed to modulate SL performance, this area remains underexplored. We highlight current insights and theoretical frameworks addressing the SL-emotion interaction, such as predictive coding theory, and propose directions for future research. This review provides a comprehensive yet focused overview of SL across cognitive and affective domains, aiming to clarify the scope and future potential of this growing field.

Statistical learning as a buffer: Investigating its impact on the link between home environment and reading achievement

The current study investigated the association between home environment and children's reading outcomes, with a focus on the mediating roles of vocabulary and morphological awareness (MA) and the moderating roles of statistical learning (SL). A sample of 191 8-year-old Chinese children (92 girls) with diverse socioeconomic status (SES) backgrounds completed assessments of vocabulary knowledge, MA, nonlinguistic visual and auditory SL, Chinese positional and phonetic SL, reading tasks, nonverbal reasoning, and verbal working memory. Results showed that both vocabulary and MA mediated the relationship between SES and reading, but only vocabulary mediated the relationship between home literacy environment (HLE) and reading. Importantly, children who were better in domain-specific SL, particularly those with strong Chinese radical positional SL, were less affected by SES disparities in reading outcomes. However, SL did not moderate the associations between HLE and reading outcomes.

Implicitly learned bias impacts decision-making but not metacognition

People can implicitly learn biases that affect decisions. It is unclear if implicit and explicit learning of priors differentially influenced performance. Participants judged the orientation of moving dot patterns with stimuli occurring more frequently in one of the orientations depending on the color. Participants were or were not told about the base-rate differences. The explicitly informed group showed a greater application of the prior, although participants who were not aware of the two priors also showed a response bias. For participants who learned the priors implicitly there was only an effect of the prior when no diagnostic sensory information was available. Those who were instructed of the priors were more confident for prior-consistent stimuli while this was not seen in participants who merely experienced the priors.These results suggest that base-rate priors can be learned implicitly and can bias perceptual decisions, but this bias does not appear to affect confidence.

Direct brain recordings reveal implicit encoding of structure in random auditory streams

The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where such modeling proceeds is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of the temporal structure of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain automatically and continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Our work provides a comprehensive picture of the neural correlates of automatic encoding of implicit structure that can be the crucial substrate for the swift detection of patterns and unexpected events in the environment.

Visual Statistical Learning Alters Low-Dimensional Cortical Architecture

Our brains are in a constant state of generating predictions, implicitly extracting environmental regularities to support later cognition and behavior, a process known as statistical learning (SL). While prior work investigating the neural basis of SL has focused on the activity of single brain regions in isolation, much less is known about how distributed brain areas coordinate their activity to support such learning. Using fMRI and a classic visual SL task, we investigated changes in whole-brain functional architecture as human female and male participants implicitly learned to associate pairs of images, and later, when predictions generated from learning were violated. By projecting individuals' patterns of cortical and subcortical functional connectivity onto a low-dimensional manifold space, we found that SL was associated with changes along a single neural dimension describing covariance across the visual-parietal and perirhinal cortex (PRC). During learning, we found regions within the visual cortex expanded along this dimension, reflecting their decreased communication with other networks, whereas regions within the dorsal attention network (DAN) contracted, reflecting their increased connectivity with higher-order cortex. Notably, when SL was interrupted, we found the PRC and entorhinal cortex, which did not initially show learning-related effects, now contracted along this dimension, reflecting their increased connectivity with the default mode and DAN, and decreased covariance with visual cortex. While prior research has linked SL to either broad cortical or medial temporal lobe changes, our findings suggest an integrative view, whereby cortical regions reorganize during association formation, while medial temporal lobe regions respond to their violation.

Impaired visual and verbal statistical learning in children with Dyslexia in a transparent orthography

Recent research suggests that performance on Statistical Learning (SL) tasks may be lower in children with dyslexia in deep orthographies such as English. However, it is debated whether the observed difficulties may vary depending on the modality and stimulus of the task, opening a broad discussion about whether SL is a domain-general or domain-specific construct. Besides, little is known about SL in children with dyslexia who learn transparent orthographies, where the transparency of grapheme-phoneme correspondences might reduce the reliance on implicit learning processes. The present study investigates the impact of SL in Spanish, a transparent orthography, among 50 children aged 9 to 12 years, with and without dyslexia. For this purpose, we used four SL tasks to evaluate two modalities (auditory/visual) and two stimulus type (verbal/nonverbal) and evaluated both accuracy and response times on each condition. The findings reveal that children with dyslexia in Spanish exhibit lower performance on SL tasks (accuracy) compared to the control group, regardless of the modality and stimulus type used. However, children with dyslexia struggle the most with tasks that involve visual material. This indicates that children with dyslexia in transparent orthographies have particular difficulties in extracting distributional probabilistic information in the absence of explicit learning instructions. Notably, difficulties were more pronounced in visual tasks involving verbal stimuli. The present results help to better understand the underlying mechanisms involved in reading acquisition in children with dyslexia.

Statistical learning of artificial orthographic regularity arises from coordinated activity across distinct brain regions

The human brain possesses the ability to automatically extract statistical regularities from environmental inputs, including visual-graphic symbols and printed units. However, the specific brain regions underlying the statistical learning of these visual-graphic symbols or artificial orthography remain unclear. This study utilized functional magnetic resonance imaging (fMRI) with an artificial orthography learning paradigm to measure brain activities associated with the statistical learning of radical positional regularities embedded in pseudocharacters containing high (100%), moderate (80%), and low (60%) levels of consistency, along with a series of random abstract figures. Thirty adults passively viewed a continuous stream of these pseudocharacters. fMRI data revealed that the left occipital area and the visual word form area (VWFA) exhibited greater responses at the low consistency level than at the high and moderate levels, suggesting implicit statistical learning of positional regularities. Functional connectivity analysis further revealed significant correlations between the occipital lobe, the VWFA, and other brain regions, such as the middle temporal gyrus (MTG), the superior occipital gyrus (SOG), and the cerebellum. Moreover, neural activity showed a tendency to correlate with behavioral recognition performance. These findings demonstrate that the incidental acquisition of statistical regularities in artificial orthography arises from the coordinated activation of multiple distinct neural circuits.

Schemas, reinforcement learning and the medial prefrontal cortex

Schemas are rich and complex knowledge structures about the typical unfolding of events in a context; for example, a schema of a dinner at a restaurant. In this Perspective, we suggest that reinforcement learning (RL), a computational theory of learning the structure of the world and relevant goal-oriented behaviour, underlies schema learning. We synthesize literature about schemas and RL to offer that three RL principles might govern the learning of schemas: learning via prediction errors, constructing hierarchical knowledge using hierarchical RL, and dimensionality reduction through learning a simplified and abstract representation of the world. We then suggest that the orbitomedial prefrontal cortex is involved in both schemas and RL due to its involvement in dimensionality reduction and in guiding memory reactivation through interactions with posterior brain regions. Last, we hypothesize that the amount of dimensionality reduction might underlie gradients of involvement along the ventral-dorsal and posterior-anterior axes of the orbitomedial prefrontal cortex. More specific and detailed representations might engage the ventral and posterior parts, whereas abstraction might shift representations towards the dorsal and anterior parts of the medial prefrontal cortex.

Neural mechanisms of learned suppression uncovered by probing the hidden attentional priority map

Attentional capture by an irrelevant salient distractor is attenuated when the distractor appears more frequently in one location, suggesting learned suppression of that location. However, it remains unclear whether suppression is proactive (before attention is directed) or reactive (after attention is allocated). Here, we investigated this using a 'pinging' technique to probe the attentional distribution before search onset. In an EEG experiment, participants searched for a shape singleton while ignoring a color singleton distractor at a high-probability location. To reveal the hidden attentional priority map, participants also performed a continuous recall spatial memory task, with a neutral placeholder display presented before search onset. Behaviorally, search was more efficient when the distractor appeared at the high-probability location. Inverted encoding analysis of EEG data showed tuning profiles that decayed during memory maintenance but were revived by the placeholder display. Notably, tuning was most pronounced at the to-be-suppressed location, suggesting initial spatial selection followed by suppression. These findings suggest that learned distractor suppression is a reactive process, providing new insights into learned spatial distractor suppression mechanisms.

Statistical learning beyond words in human neonates

Interest in statistical learning in developmental studies stems from the observation that 8-month-olds were able to extract words from a monotone speech stream solely using the transition probabilities (TP) between syllables (Saffran et al., 1996). A simple mechanism was thus part of the human infant's toolbox for discovering regularities in language. Since this seminal study, observations on statistical learning capabilities have multiplied across domains and species, challenging the hypothesis of a dedicated mechanism for language acquisition. Here, we leverage the two dimensions conveyed by speech -speaker identity and phonemes- to examine (1) whether neonates can compute TPs on one dimension despite irrelevant variation on the other and (2) whether the linguistic dimension enjoys an advantage over the voice dimension. In two experiments, we exposed neonates to artificial speech streams constructed by concatenating syllables while recording EEG. The sequence had a statistical structure based either on the phonetic content, while the voices varied randomly (Experiment 1) or on voices with random phonetic content (Experiment 2). After familiarisation, neonates heard isolated duplets adhering, or not, to the structure they were familiarised with. In both experiments, we observed neural entrainment at the frequency of the regularity and distinct Event-Related Potentials (ERP) to correct and incorrect duplets, highlighting the universality of statistical learning mechanisms and suggesting it operates on virtually any dimension the input is factorised. However, only linguistic duplets elicited a specific ERP component, potentially an N400 precursor, suggesting a lexical stage triggered by phonetic regularities already at birth. These results show that, from birth, multiple input regularities can be processed in parallel and feed different higher-order networks.

Intact ultrafast memory consolidation in adults with autism and neurotypicals with autism traits

The processes of learning and memory consolidation are closely interlinked. Therefore, to uncover statistical learning in autism spectrum disorder (ASD), an in-depth examination of memory consolidation is essential. Studies of the last five years have revealed that learning can take place not only during practice but also during micro rest (<1 min) between practice blocks, termed micro offline gains. The concept of micro offline gains refers to performance improvements during short rest periods interspersed with practice, rather than during practice itself. This phenomenon is crucial for the acquisition and consolidation of motor skills and has been observed across various learning contexts. Numerous studies on learning in autism have identified intact learning but there has been no investigation into this fundamental aspect of memory consolidation in autistic individuals to date. We conducted two studies with two different samples: 1) neurotypical adults with distinct levels of autistic traits (N = 166) and 2) ASD-diagnosed adults (NASD = 22, NNTP = 20). Participants performed a well-established probabilistic learning task, allowing us to measure two learning processes separately in the same experimental design: statistical learning (i.e., learning probability-based regularities) and visuomotor performance (i.e., speed-up regardless of probabilities). Here we show considerable individual differences in offline (between blocks) changes during statistical learning and between-blocks improvement during visuomotor performance. However, cumulative evidence from individual studies suggests that the degree of autistic traits and ASD status are not associated with micro offline gains, indicating that, like statistical learning, rapid memory consolidation is intact.

Attentional Capture and Control

The current review presents an integrated tripartite framework for understanding attentional control, emphasizing the interaction and competition among top-down, bottom-up, and selection-history influences. It focuses on attentional capture, which refers to conditions in which salient objects or events receive attentional priority even when they are inconsistent with the goals, tasks, and intentions of the observer. The review describes which components of the tripartite framework are in play when distraction by salient objects is prevented and the conditions in which there is no control over the occurrence of attentional capture. It then concludes that attentional capture can be controlled in a proactive way mainly by implicit statistical learning mechanisms associated with selection history. Current and lingering controversies regarding the control of attentional capture are also discussed.

The Domain-Specific Neural Basis of Auditory Statistical Learning in 5-7-Year-Old Children

Statistical learning (SL) is the ability to rapidly track statistical regularities and learn patterns in the environment. Recent studies show that SL is constrained by domain-specific features, rather than being a uniform learning mechanism across domains and modalities. This domain-specificity has been reflected at the neural level, as SL occurs in regions primarily involved in processing of specific modalities or domains of input. However, our understanding of how SL is constrained by domain-specific features in the developing brain is severely lacking. The present study aims to identify the functional neural profiles of auditory SL of linguistic and nonlinguistic regularities among children. Thirty children between 5 and 7 years old completed an auditory fMRI SL task containing interwoven sequences of structured and random syllable/tone sequences. Using traditional group univariate analyses and a group-constrained subject-specific analysis, frontal and temporal cortices showed significant activation when processing structured versus random sequences across both linguistic and nonlinguistic domains. However, conjunction analyses failed to identify overlapping neural indices across domains. These findings are the first to compare brain regions supporting SL of linguistic and nonlinguistic regularities in the developing brain and indicate that auditory SL among developing children may be constrained by domain-specific features.

Anticipating multisensory environments: Evidence for a supra-modal predictive system

Our perceptual experience is generally framed in multisensory environments abundant in predictive information. Previous research on statistical learning has shown that humans can learn regularities in different sensory modalities in parallel, but it has not yet determined whether multisensory predictions are generated through a modality-specific predictive mechanism or instead, rely on a supra-modal predictive system. Here, across two experiments, we tested these hypotheses by presenting participants with concurrent pairs of predictable auditory and visual low-level stimuli (i.e., tones and gratings). In different experimental blocks, participants had to attend the stimuli in one modality while ignoring stimuli from the other sensory modality (distractors), and perform a perceptual discrimination task on the second stimulus of the attended modality (targets). Orthogonal to the task goal, both the attended and unattended pairs followed transitional probabilities, so targets and distractors could be expected or unexpected. We found that participants performed better for expected compared to unexpected targets. This effect generalized to the distractors but only when relevant targets were expected. Such interactive effects suggest that predictions may be gated by a supra-modal system with shared resources across sensory modalities that are distributed according to their respective behavioural relevance.

Cortical tracking of language structures: Modality-dependent and independent responses

OBJECTIVES

The mental parsing of linguistic hierarchy is crucial for language comprehension, and while there is growing interest in the cortical tracking of auditory speech, the neurophysiological substrates for tracking written language are still unclear.

METHODS

We recorded electroencephalographic (EEG) responses from participants exposed to auditory and visual streams of either random syllables or tri-syllabic real words. Using a frequency-tagging approach, we analyzed the neural representations of physically presented (i.e., syllables) and mentally constructed (i.e., words) linguistic units and compared them between the two sensory modalities.

RESULTS

We found that tracking syllables is partially modality dependent, with anterior and posterior scalp regions more involved in the tracking of spoken and written syllables, respectively. The cortical tracking of spoken and written words instead was found to involve a shared anterior region to a similar degree, suggesting a modality-independent process for word tracking.

CONCLUSION

Our study suggests that basic linguistic features are represented in a sensory modality-specific manner, while more abstract ones are modality-unspecific during the online processing of continuous language input.

SIGNIFICANCE

The current methodology may be utilized in future research to examine the development of reading skills, especially the deficiencies in fluent reading among those with dyslexia.

Statistical learning ability at 17 months relates to early reading skills via oral language

Statistical learning ability has been found to relate to children's reading skills. Yet, statistical learning is also known to be vital for developing oral language skills, and oral language and reading skills relate strongly. These connections raise the question of whether statistical learning ability affects reading via oral language or directly. Statistical learning is multifaceted, and so different aspects of statistical learning might influence oral language and reading skills distinctly. In a longitudinal study, we determined how two aspects of statistical learning from an artificial language tested on 70 17-month-old infants-segmenting sequences from speech and generalizing the sequence structure-related to oral language skills measured at 54 months and reading skills measured at approximately 75 months. Statistical learning segmentation did not relate significantly to oral language or reading, whereas statistical learning generalization related to oral language, but only indirectly related to reading. Our results showed that children's early statistical learning ability was associated with learning to read via the children's oral language skills.

Instrumental music training relates to intensity assessment but not emotional prosody recognition in Mandarin

Building on research demonstrating the benefits of music training for emotional prosody recognition in nontonal languages, this study delves into its unexplored influence on tonal languages. In tonal languages, the acoustic similarity between lexical tones and music, along with the dual role of pitch in conveying lexical and affective meanings, create a unique interplay. We evaluated 72 participants, half of whom had extensive instrumental music training, with the other half serving as demographically matched controls. All participants completed an online test consisting of 210 Chinese pseudosentences, each designed to express one of five emotions: happiness, sadness, fear, anger, or neutrality. Our robust statistical analyses, which included effect size estimates and Bayesian factors, revealed that music and nonmusic groups exhibit similar abilities in identifying the emotional prosody of various emotions. However, the music group attributed higher intensity ratings to emotional prosodies of happiness, fear, and anger compared to the nonmusic group. These findings suggest that while instrumental music training is not related to emotional prosody recognition, it does appear to be related to perceived emotional intensity. This dissociation between emotion recognition and intensity evaluation adds a new piece to the puzzle of the complex relationship between music training and emotion perception in tonal languages.

Crossmodal Correspondence Mediates Crossmodal Transfer from Visual to Auditory Stimuli in Category Learning

This article investigated whether crossmodal correspondence, as a sensory translation phenomenon, can mediate crossmodal transfer from visual to auditory stimuli in category learning and whether multimodal category learning can influence the crossmodal correspondence between auditory and visual stimuli. Experiment 1 showed that the category knowledge acquired from elevation stimuli affected the categorization of pitch stimuli when there were robust crossmodal correspondence effects between elevation and size, indicating that crossmodal transfer occurred between elevation and pitch stimuli. Experiments 2 and 3 revealed that the size category knowledge could not be transferred to the categorization of pitches, but interestingly, size and pitch category learning determined the direction of the pitch-size correspondence, suggesting that the pitch-size correspondence was not stable and could be determined using multimodal category learning. Experiment 4 provided further evidence that there was no crossmodal transfer between size and pitch, due to the absence of a robust pitch-size correspondence. These results demonstrated that crossmodal transfer can occur between audio-visual stimuli with crossmodal correspondence, and multisensory category learning can change the corresponding relationship between audio-visual stimuli. These findings suggest that crossmodal transfer and crossmodal correspondence share similar abstract representations, which can be mediated by semantic content such as category labels.

Visual linguistic statistical learning is traceable through neural entrainment

The human brain can detect statistical regularities in the environment across a wide variety of contexts. The importance of this process is well-established not just in language acquisition but across different modalities; in addition, several neural correlates of statistical learning have been identified. A current technique for tracking the emergence of regularity learning and localizing its neural background is frequency tagging (FT). FT can detect neural entrainment not only to the frequency of stimulus presentation but also to that of a hidden structure. Auditory learning paradigms with linguistic and nonlinguistic stimuli, along with a visual paradigm using nonlinguistic stimuli, have already been tested with FT. To complete the picture, we conducted an FT experiment using written syllables as stimuli and a hidden triplet structure. Both behavioral and neural entrainment data showed evidence of structure learning. In addition, we localized two electrode clusters related to the process, which spread across the frontal and parieto-occipital areas, similar to previous findings. Accordingly, we conclude that fast-paced visual linguistic regularities can be acquired and are traceable through neural entrainment. In comparison with the literature, our findings support the view that statistical learning involves a domain-general network.

The relationship between neural phase entrainment and statistical word-learning: A scoping review

Statistical language-learning, the capacity to extract regularities from a continuous speech stream, arguably involves the ability to segment the stream before the discrete constituents can be stored in memory. According to recent accounts, the segmentation process is reflected in the alignment of neural activity to the statistical structure embedded in the input. However, the degree to which it can predict the subsequent leaning outcome is currently unclear. As this is a relatively new avenue of research on statistical learning, a scoping review approach was adopted to identify and explore the current body of evidence on the use of neural phase entrainment as a measure of online neural statistical language-learning and its relation to the learning outcome, as well as the design characteristics of these studies. All included studies (11) observed entrainment to the underlying statistical pattern with exposure to the structured speech stream. A significant association between entrainment and learning outcome was observed in six of the studies. We discuss these findings in light of what neural entrainment in statistical word-learning experiments might represent, and speculate that it might reflect a general auditory processing mechanism, rather than segmentation of the speech stream per se. Lastly, as we find the current selection of studies to provide inconclusive evidence for neural entrainment's role in statistical learning, future research avenues are proposed.

Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

Finding Pattern in the Noise: Persistent Implicit Statistical Knowledge Impacts the Processing of Unpredictable Stimuli

Humans can extract statistical regularities of the environment to predict upcoming events. Previous research recognized that implicitly acquired statistical knowledge remained persistent and continued to influence behavior even when the regularities were no longer present in the environment. Here, in an fMRI experiment, we investigated how the persistence of statistical knowledge is represented in the brain. Participants (n = 32) completed a visual, four-choice, RT task consisting of statistical regularities. Two types of blocks constantly alternated with one another throughout the task: predictable statistical regularities in one block type and unpredictable ones in the other. Participants were unaware of the statistical regularities and their changing distribution across the blocks. Yet, they acquired the statistical regularities and showed significant statistical knowledge at the behavioral level not only in the predictable blocks but also in the unpredictable ones, albeit to a smaller extent. Brain activity in a range of cortical and subcortical areas, including early visual cortex, the insula, the right inferior frontal gyrus, and the right globus pallidus/putamen contributed to the acquisition of statistical regularities. The right insula, inferior frontal gyrus, and hippocampus as well as the bilateral angular gyrus seemed to play a role in maintaining this statistical knowledge. The results altogether suggest that statistical knowledge could be exploited in a relevant, predictable context as well as transmitted to and retrieved in an irrelevant context without a predictable structure.

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.

Semantic and Syntactic Predictions in Reading Aloud: Are Good Predictors Good Statistical Learners?

Recent research suggests that becoming a fluent reader may partially rely on a domain-general statistical learning (SL) mechanism that allows a person to automatically extract predictable patterns from the sensory input. The goal of the present study was to investigate a potential link between SL and the ability to make linguistic predictions. All previous studies investigated quite general levels of reading ability rather than the dynamic process of making linguistic predictions. We thus used a recently developed predictive reading task, which consisted of having participants read aloud words that were preceded by either semantically or syntactically predictive contexts. To measure the componential nature of SL, we used a visual and an auditory SL task (VSL, ASL) and the classic serial reaction time task (SRT). General reading ability was assessed with a reading speed/comprehension test. The study was conducted online on a sample of 120 participants to make it possible to explore interindividual differences. The results showed only weak and sometimes even negative correlations between the various SL measures. ASL correlated positively and predicted general reading ability but neither semantic nor syntactic prediction effects. Similarly, one of the SRT measures was significantly associated with reading level and reading speed but not with linguistic prediction effects. In sum, there is little evidence that domain-general SL is a good predictor of people's ability to make domain-specific linguistic predictions. In contrast, SL shows a weak but significant association with general reading ability.

Dissociation Between Linguistic and Nonlinguistic Statistical Learning in Children with Autism

Statistical learning (SL), the ability to detect and extract regularities from inputs, is considered a domain-general building block for typical language development. We compared 55 verbal children with autism (ASD, 6-12 years) and 50 typically-developing children in four SL tasks. The ASD group exhibited reduced learning in the linguistic SL tasks (syllable and letter), but showed intact learning for the nonlinguistic SL tasks (tone and image). In the ASD group, better linguistic SL was associated with higher language skills measured by parental report and sentence recall. Therefore, the atypicality of SL in autism is not domain-general but tied to specific processing constraints related to verbal stimuli. Our findings provide a novel perspective for understanding language heterogeneity in autism.

Pupil diameter as an indicator of sound pair familiarity after statistically structured auditory sequence

Inspired by recent findings in the visual domain, we investigated whether the stimulus-evoked pupil dilation reflects temporal statistical regularities in sequences of auditory stimuli. We conducted two preregistered pupillometry experiments (experiment 1, n = 30, 21 females; experiment 2, n = 31, 22 females). In both experiments, human participants listened to sequences of spoken vowels in two conditions. In the first condition, the stimuli were presented in a random order and, in the second condition, the same stimuli were presented in a sequence structured in pairs. The second experiment replicated the first experiment with a modified timing and number of stimuli presented and without participants being informed about any sequence structure. The sound-evoked pupil dilation during a subsequent familiarity task indicated that participants learned the auditory vowel pairs of the structured condition. However, pupil diameter during the structured sequence did not differ according to the statistical regularity of the pair structure. This contrasts with similar visual studies, emphasizing the susceptibility of pupil effects during statistically structured sequences to experimental design settings in the auditory domain. In sum, our findings suggest that pupil diameter may serve as an indicator of sound pair familiarity but does not invariably respond to task-irrelevant transition probabilities of auditory sequences.

Response times are affected by mispredictions in a stochastic game

Acting as a goalkeeper in a video-game, a participant is asked to predict the successive choices of the penalty taker. The sequence of choices of the penalty taker is generated by a stochastic chain with memory of variable length. It has been conjectured that the probability distribution of the response times is a function of the specific sequence of past choices governing the algorithm used by the penalty taker to make his choice at each step. We found empirical evidence that besides this dependence, the distribution of the response times depends also on the success or failure of the previous prediction made by the participant. Moreover, we found statistical evidence that this dependence propagates up to two steps forward after the prediction failure.

Individual differences in auditory perception predict learning of non-adjacent tone sequences in 3-year-olds

Auditory processing of speech and non-speech stimuli oftentimes involves the analysis and acquisition of non-adjacent sound patterns. Previous studies using speech material have demonstrated (i) children's early emerging ability to extract non-adjacent dependencies (NADs) and (ii) a relation between basic auditory perception and this ability. Yet, it is currently unclear whether children show similar sensitivities and similar perceptual influences for NADs in the non-linguistic domain. We conducted an event-related potential study with 3-year-old children using a sine-tone-based oddball task, which simultaneously tested for NAD learning and auditory perception by means of varying sound intensity. Standard stimuli were A × B sine-tone sequences, in which specific A elements predicted specific B elements after variable × elements. NAD deviants violated the dependency between A and B and intensity deviants were reduced in amplitude. Both elicited similar frontally distributed positivities, suggesting successful deviant detection. Crucially, there was a predictive relationship between the amplitude of the sound intensity discrimination effect and the amplitude of the NAD learning effect. These results are taken as evidence that NAD learning in the non-linguistic domain is functional in 3-year-olds and that basic auditory processes are related to the learning of higher-order auditory regularities also outside the linguistic domain.

Limited but specific engagement of the mature language network during linguistic statistical learning

Statistical learning (SL) is the ability to detect and learn regularities from input and is foundational to language acquisition. Despite the dominant role of SL as a theoretical construct for language development, there is a lack of direct evidence supporting the shared neural substrates underlying language processing and SL. It is also not clear whether the similarities, if any, are related to linguistic processing, or statistical regularities in general. The current study tests whether the brain regions involved in natural language processing are similarly recruited during auditory, linguistic SL. Twenty-two adults performed an auditory linguistic SL task, an auditory nonlinguistic SL task, and a passive story listening task as their neural activation was monitored. Within the language network, the left posterior temporal gyrus showed sensitivity to embedded speech regularities during auditory, linguistic SL, but not auditory, nonlinguistic SL. Using a multivoxel pattern similarity analysis, we uncovered similarities between the neural representation of auditory, linguistic SL, and language processing within the left posterior temporal gyrus. No other brain regions showed similarities between linguistic SL and language comprehension, suggesting that a shared neurocomputational process for auditory SL and natural language processing within the left posterior temporal gyrus is specific to linguistic stimuli.

Contribution of statistical learning in learning to read across languages

Statistical Learning (SL) refers to human's ability to detect regularities from environment Kirkham, N. Z. (2002) & Saffran, J. R. (1996). There has been a growing interest in understanding how sensitivity to statistical regularities influences learning to read. The current study systematically examined whether and how non-linguistic SL, Chinese SL, and English SL contribute to Chinese and English word reading among native Chinese-speaking 4th, 6th and 8th graders who learn English as a second language (L2). Children showed above-chance learning across all SL tasks and across all grades. In addition, developmental improvements were shown across at least two of the three grade ranges on all SL tasks. In terms of the contribution of SL to reading, non-linguistic auditory SL (ASL), English visual SL (VSL), and Chinese ASL accounted for a significant amount of variance in English L2 word reading. Non-linguistic ASL, Chinese VSL, English VSL, and English ASL accounted for a significant amount of variance in Chinese word reading. Our results provide clear and novel evidence for cross-linguistic contribution from Chinese SL to English reading, and from English SL to Chinese reading, highlighting a bi-directional relationship between SL in one language and reading in another language.

Reliability of individual differences in distractor suppression driven by statistical learning

A series of recent studies has demonstrated that attentional selection is modulated by statistical regularities, even when they concern task-irrelevant stimuli. Irrelevant distractors presented more frequently at one location interfere less with search than distractors presented elsewhere. To account for this finding, it has been proposed that through statistical learning, the frequent distractor location becomes suppressed relative to the other locations. Learned distractor suppression has mainly been studied at the group level, where individual differences are treated as unexplained error variance. Yet these individual differences may provide important mechanistic insights and could be predictive of cognitive and real-life outcomes. In the current study, we ask whether in an additional singleton task, the standard measures of attentional capture and learned suppression are reliable and stable at the level of the individual. In an online study, we assessed both the within- and between-session reliability of individual-level measures of attentional capture and learned suppression. We show that the measures of attentional capture, but not of distractor suppression, are moderately stable within the same session (i.e., split-half reliability). Test-retest reliability over a 2-month period was found to be moderate for attentional capture but weak or absent for suppression. RT-based measures proved to be superior to accuracy measures. While producing very robust findings at the group level, the predictive validity of these RT-based measures is still limited when it comes to individual-level performance. We discuss the implications for future research drawing on inter-individual variation in the attentional biases that result from statistical learning.

Hebbian learning can explain rhythmic neural entrainment to statistical regularities

In many domains, learners extract recurring units from continuous sequences. For example, in unknown languages, fluent speech is perceived as a continuous signal. Learners need to extract the underlying words from this continuous signal and then memorize them. One prominent candidate mechanism is statistical learning, whereby learners track how predictive syllables (or other items) are of one another. Syllables within the same word predict each other better than syllables straddling word boundaries. But does statistical learning lead to memories of the underlying words-or just to pairwise associations among syllables? Electrophysiological results provide the strongest evidence for the memory view. Electrophysiological responses can be time-locked to statistical word boundaries (e.g., N400s) and show rhythmic activity with a periodicity of word durations. Here, I reproduce such results with a simple Hebbian network. When exposed to statistically structured syllable sequences (and when the underlying words are not excessively long), the network activation is rhythmic with the periodicity of a word duration and activation maxima on word-final syllables. This is because word-final syllables receive more excitation from earlier syllables with which they are associated than less predictable syllables that occur earlier in words. The network is also sensitive to information whose electrophysiological correlates were used to support the encoding of ordinal positions within words. Hebbian learning can thus explain rhythmic neural activity in statistical learning tasks without any memory representations of words. Learners might thus need to rely on cues beyond statistical associations to learn the words of their native language. RESEARCH HIGHLIGHTS: Statistical learning may be utilized to identify recurring units in continuous sequences (e.g., words in fluent speech) but may not generate explicit memory for words. Exposure to statistically structured sequences leads to rhythmic activity with a period of the duration of the underlying units (e.g., words). I show that a memory-less Hebbian network model can reproduce this rhythmic neural activity as well as putative encodings of ordinal positions observed in earlier research. Direct tests are needed to establish whether statistical learning leads to declarative memories for words.

Specificity of Motor Contributions to Auditory Statistical Learning

Statistical learning is the ability to extract patterned information from continuous sensory signals. Recent evidence suggests that auditory-motor mechanisms play an important role in auditory statistical learning from speech signals. The question remains whether auditory-motor mechanisms support such learning generally or in a domain-specific manner. In Experiment 1, we tested the specificity of motor processes contributing to learning patterns from speech sequences. Participants either whispered or clapped their hands while listening to structured speech. In Experiment 2, we focused on auditory specificity, testing whether whispering equally affects learning patterns from speech and non-speech sequences. Finally, in Experiment 3, we examined whether learning patterns from speech and non-speech sequences are correlated. Whispering had a stronger effect than clapping on learning patterns from speech sequences in Experiment 1. Moreover, whispering impaired statistical learning more strongly from speech than non-speech sequences in Experiment 2. Interestingly, while participants in the non-speech tasks spontaneously synchronized their motor movements with the auditory stream more than participants in the speech tasks, the effect of the motor movements on learning was stronger in the speech domain. Finally, no correlation between speech and non-speech learning was observed. Overall, our findings support the idea that learning statistical patterns from speech versus non-speech relies on segregated mechanisms, and that the speech motor system contributes to auditory statistical learning in a highly specific manner.

Playing hide and seek: Contextual regularity learning develops between 3 and 5 years of age

The ability to acquire contextual regularities is fundamental in everyday life because it helps us to navigate the environment, directing our attention where relevant events are more likely to occur. Sensitivity to spatial regularities has been largely reported from infancy. Nevertheless, it is currently unclear when children can use this rapidly acquired contextual knowledge to guide their behavior. Evidence of this ability is indeed mixed in school-aged children and, to date, it has never been explored in younger children and toddlers. The current study investigated the development of contextual regularity learning in children aged 3 to 5 years. To this aim, we designed a new contextual learning paradigm in which young children were presented with recurring configurations of bushes and were asked to guess behind which bush a cartoon monkey was hiding. In a series of two experiments, we manipulated the relevance of color and visuospatial cues for the underlying task goal and tested how this affected young children's behavior. Our results bridge the gap between the infant and adult literatures, showing that sensitivity to spatial configurations persists from infancy to childhood, but it is only around the fifth year of life that children naturally start to integrate multiple cues to guide their behavior.

Cognitive and sensory expectations independently shape musical expectancy and pleasure

Expectation is crucial for our enjoyment of music, yet the underlying generative mechanisms remain unclear. While sensory models derive predictions based on local acoustic information in the auditory signal, cognitive models assume abstract knowledge of music structure acquired over the long term. To evaluate these two contrasting mechanisms, we compared simulations from four computational models of musical expectancy against subjective expectancy and pleasantness ratings of over 1000 chords sampled from 739 US Billboard pop songs. Bayesian model comparison revealed that listeners' expectancy and pleasantness ratings were predicted by the independent, non-overlapping, contributions of cognitive and sensory expectations. Furthermore, cognitive expectations explained over twice the variance in listeners' perceived surprise compared to sensory expectations, suggesting a larger relative importance of long-term representations of music structure over short-term sensory-acoustic information in musical expectancy. Our results thus emphasize the distinct, albeit complementary, roles of cognitive and sensory expectations in shaping musical pleasure, and suggest that this expectancy-driven mechanism depends on musical information represented at different levels of abstraction along the neural hierarchy. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

The effect of hippocampal subfield damage on rapid temporal integration through statistical learning and associative inference

INTRODUCTION

The hippocampus (HPC) supports integration of information across time, often indexed by associative inference (AI) and statistical learning (SL) tasks. In AI, an indirect association between stimuli that never appeared together is inferred, whereas SL involves learning item relationships by extracting regularities across experiences. A recent model of hippocampal function (Schapiro et al., 2017) proposes that the HPC can support temporal integration in both paradigms through its two distinct pathways.

METHODS

We tested this models' predictions in four patients with varying degrees of bilateral HPC damage and matched healthy controls, with two patients with complementary damage to either the monosynaptic or trisynaptic pathway. During AI, participants studied overlapping paired associates (AB, BC) and their memory was tested for premise pairs (AB) and for inferred pairs (AC). During SL, participants passively viewed a continuous picture sequence that contained an underlying structure of triplets that later had to be recognized.

RESULTS

Binomial distributions were used to calculate above chance performance at the individual level. For AI, patients with focal HPC damage were impaired at inference but could correctly infer pairs above chance once premise pair acquisition was equated to controls; however, the patient with HPC and cortical damage showed severe impairment at recalling premise and inferred pairs, regardless of accounting for premise pair performance. For SL, none of the patients performed above chance, but notably neither did most controls.

CONCLUSIONS

Associative inference of indirect relationships can be intact with HPC damage to either hippocampal pathways or the HPC more broadly, provided premise pairs can first be formed. Inference may remain intact through residual HPC tissue supporting premise pair acquisition, and/or through extra-hippocampal structures supporting inference at retrieval. Clear conclusions about hippocampal contributions to SL are precluded by low performance in controls, which we caution is not dissimilar to previous amnesic studies using the same task. This complicates interpretations of studies claiming necessity of hippocampal contributions to SL and warrants the use of a common and reliable task before conclusions can be drawn.

Does bilingual experience influence statistical language learning?

Statistical language learning (SL) tasks measure different aspects of foreign language learning. Studies have used SL tasks to investigate whether bilingual experience confers advantages in acquiring additional languages through implicit processes. However, the results have been inconsistent, which may be related to bilingualism-related features (e.g., degree of dissimilarity between the specific language pair) and other variables such as specific processes that are targeted by the SL task. In the present study, we compared the performance of one Spanish monolingual and two bilingual (Spanish-Basque and Spanish-English) groups across three well-established SL tasks. Each task targeted a different aspect of foreign language learning; specifically, word segmentation, morphological rule generalization, and word-referent learning. In Experiment 1, we manipulated sub-lexical phonotactic patterns to vary the difficulty of three SL tasks, with the results showing no differences between the groups in word segmentation. In Experiment 2, we included non-adjacent dependencies to target affixal morphology rule learning, but again no group-related differences were found. In Experiment 3, we addressed word learning using an audio-visual SL task combining exclusive and multiple word-referent mappings, and found that bilinguals outperformed monolinguals, suggesting that bilingualism may exert influences on SL at the lexical level. This advantage might have been mediated by the high working memory demands required to perform the task. Summarizing, this study shows no evidence for a general bilingual advantage in SL, although bilinguals may outperform monolinguals under specific experimental conditions such as SL tasks that place high demands on working memory processes. In addition, the similar performance of Spanish-Basque and Spanish-English bilinguals across all three SL tasks suggests that the degree of dissimilarity between pairs of spoken languages does not modulate SL skills.

Of words and whistles: Statistical learning operates similarly for identical sounds perceived as speech and non-speech

Statistical learning is an ability that allows individuals to effortlessly extract patterns from the environment, such as sound patterns in speech. Some prior evidence suggests that statistical learning operates more robustly for speech compared to non-speech stimuli, supporting the idea that humans are predisposed to learn language. However, any apparent statistical learning advantage for speech could be driven by signal acoustics, rather than the subjective perception per se of sounds as speech. To resolve this issue, the current study assessed whether there is a statistical learning advantage for ambiguous sounds that are subjectively perceived as speech-like compared to the same sounds perceived as non-speech, thereby controlling for acoustic features. We first induced participants to perceive sine-wave speech (SWS)-a degraded form of speech not immediately perceptible as speech-as either speech or non-speech. After this induction phase, participants were exposed to a continuous stream of repeating trisyllabic nonsense words, composed of SWS syllables, and then completed an explicit familiarity rating task and an implicit target detection task to assess learning. Critically, participants showed robust and equivalent performance on both measures, regardless of their subjective speech perception. In contrast, participants who perceived the SWS syllables as more speech-like showed better detection of individual syllables embedded in speech streams. These results suggest that speech perception facilitates processing of individual sounds, but not the ability to extract patterns across sounds. Our findings suggest that statistical learning is not influenced by the perceived linguistic relevance of sounds, and that it may be conceptualized largely as an automatic, stimulus-driven mechanism.

Category Flexibility in Emotion Learning

Learners flexibly update category boundaries to adjust to the range of experiences they encounter. However, little is known about whether the degree of flexibility is consistent across domains. We examined whether categorization of social input, specifically emotions, is afforded more flexibility as compared to other biological input. To address this question, children (6-12 years; 32 female, 37 male; 7 Hispanic or Latino, 62 not Hispanic or Latino; 8 Black or African American, 14 multiracial, 46 White, 1 selected "other") categorized faces morphed from calm to upset and animals morphed from a horse to a cow across task phases that differed in the distribution of stimuli presented. Learners flexibly adjusted both emotion and animal category boundaries according to distributional information, yet children showed more flexibility when updating their category boundaries for emotions. These results provide support for the idea that children-who must adjust to the vast and varied emotional signals of their social partners-respond to social signals dynamically in order to make predictions about the internal states and future behaviors of others.

A multimodal cortical network of sensory expectation violation revealed by fMRI

The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities.

Brain-imaging evidence for compression of binary sound sequences in human memory

According to the language-of-thought hypothesis, regular sequences are compressed in human memory using recursive loops akin to a mental program that predicts future items. We tested this theory by probing memory for 16-item sequences made of two sounds. We recorded brain activity with functional MRI and magneto-encephalography (MEG) while participants listened to a hierarchy of sequences of variable complexity, whose minimal description required transition probabilities, chunking, or nested structures. Occasional deviant sounds probed the participants' knowledge of the sequence. We predicted that task difficulty and brain activity would be proportional to the complexity derived from the minimal description length in our formal language. Furthermore, activity should increase with complexity for learned sequences, and decrease with complexity for deviants. These predictions were upheld in both fMRI and MEG, indicating that sequence predictions are highly dependent on sequence structure and become weaker and delayed as complexity increases. The proposed language recruited bilateral superior temporal, precentral, anterior intraparietal, and cerebellar cortices. These regions overlapped extensively with a localizer for mathematical calculation, and much less with spoken or written language processing. We propose that these areas collectively encode regular sequences as repetitions with variations and their recursive composition into nested structures.

Concurrent visual sequence learning

Many researchers in the field of implicit statistical learning agree that there does not exist one general implicit learning mechanism, but rather, that implicit learning takes place in highly specialized encapsulated modules. However, the exact representational content of these modules is still under debate. While there is ample evidence for a distinction between modalities (e.g., visual, auditory perception), the representational content of the modules might even be distinguished by features within the same modalities (e.g., location, color, and shape within the visual modality). In implicit sequence learning, there is evidence for the latter hypothesis, as a stimulus-color sequence can be learned concurrently with a stimulus-location sequence. Our aim was to test whether this also holds true for non-spatial features within the visual modality. This has been shown in artificial grammar learning, but not yet in implicit sequence learning. Hence, in Experiment 1, we replicated an artificial grammar learning experiment of Conway and Christiansen (2006) in which participants were supposed to learn color and shape grammars concurrently. In Experiment 2, we investigated concurrent learning of sequences with an implicit sequence learning paradigm: the serial reaction time task. Here, we found evidence for concurrent learning of two sequences, a color and shape sequence. Overall, the findings converge to the assumption that implicit learning might be based on features.

Paired-associate versus cross-situational: How do verbal working memory and word familiarity affect word learning?

Word learning is one of the first steps into language, and vocabulary knowledge predicts reading, speaking, and writing ability. There are several pathways to word learning and little is known about how they differ. Previous research has investigated paired-associate (PAL) and cross-situational word learning (CSWL) separately, limiting the understanding of how the learning process compares across the two. In PAL, the roles of word familiarity and working memory have been thoroughly examined, but these same factors have received very little attention in CSWL. We randomly assigned 126 monolingual adults to PAL or CSWL. In each task, names of 12 novel objects were learned (six familiar words, six unfamiliar words). Logistic mixed-effects models examined whether word-learning paradigm, word type and working memory (measured with a backward digit-span task) predicted learning. Results suggest better learning performance in PAL and on familiar words. Working memory predicted word learning across paradigms, but no interactions were found between any of the predictors. This suggests that PAL is easier than CSWL, likely because of reduced ambiguity between the word and the referent, but that learning across both paradigms is equally enhanced by word familiarity, and similarly supported by working memory.

Learning to suppress a location is configuration-dependent

Where and what we attend is very much determined by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of locations that were likely to contain a distractor, effectively reducing the amount of attentional capture. Here, we asked whether this suppression effect due to statistical learning is dependent on the specific configuration within which it was learned. The current study employed the additional singleton paradigm using search arrays that had a configuration consisting of set sizes of either four or 10 items. Each configuration contained its own high probability distractor location. If learning would generalize across set size configurations, both high probability locations would be suppressed equally, regardless of set size. However, if learning to suppress is dependent on the configuration within which it was learned, one would expect only suppression of the high probability location that matched the configuration within which it was learned. The results show the latter, suggesting that implicitly learned suppression is configuration-dependent. Thus, we conclude that the high probability location is learned within the configuration context within which it is presented.

Separate but not independent: Behavioral pattern separation and statistical learning are differentially affected by aging

Our brains are capable of discriminating similar inputs (pattern separation) and rapidly generalizing across inputs (statistical learning). Are these two processes dissociable in behavior? Here, we asked whether cognitive aging affects them in a differential or parallel manner. Older and younger adults were tested on their ability to discriminate between similar trisyllabic words and to extract trisyllabic words embedded in a continuous speech stream. Older adults demonstrated intact statistical learning on an implicit, reaction time-based measure and an explicit, familiarity-based measure of learning. However, they performed poorly in discriminating similar items presented in isolation, both for episodically-encoded items and for statistically-learned regularities. These results indicate that pattern separation and statistical learning are dissociable and differentially affected by aging. The acquisition of implicit representations of statistical regularities operates robustly into old age, whereas pattern separation influences the expression of statistical learning with high representational fidelity and is subject to age-related decline.

Multisensory perception constrains the formation of object categories: a review of evidence from sensory-driven and predictive processes on categorical decisions

Although object categorization is a fundamental cognitive ability, it is also a complex process going beyond the perception and organization of sensory stimulation. Here we review existing evidence about how the human brain acquires and organizes multisensory inputs into object representations that may lead to conceptual knowledge in memory. We first focus on evidence for two processes on object perception, multisensory integration of redundant information (e.g. seeing and feeling a shape) and crossmodal, statistical learning of complementary information (e.g. the 'moo' sound of a cow and its visual shape). For both processes, the importance attributed to each sensory input in constructing a multisensory representation of an object depends on the working range of the specific sensory modality, the relative reliability or distinctiveness of the encoded information and top-down predictions. Moreover, apart from sensory-driven influences on perception, the acquisition of featural information across modalities can affect semantic memory and, in turn, influence category decisions. In sum, we argue that both multisensory processes independently constrain the formation of object categories across the lifespan, possibly through early and late integration mechanisms, respectively, to allow us to efficiently achieve the everyday, but remarkable, ability of recognizing objects. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Intact procedural memory and impaired auditory statistical learning in adults with dyslexia

Developmental dyslexia is a reading disorder that is associated with atypical brain function. One neuropsychological theory posits that dyslexia reflects a deficit in the procedural memory system, which supports implicit learning, or the acquisition of knowledge without conscious awareness or intention. This study investigated various forms of procedural learning in adults with dyslexia and typically-reading adults. Adults with dyslexia exhibited typical skill learning on mirror tracing and rotary pursuit tasks that have been well-established as reflecting purely procedural memory and dependent on basal ganglia and cerebellar structures. They also exhibited typical statistical learning for visual material, but impaired statistical learning for auditory material. Auditory statistical learning proficiency correlated positively with single-word reading performance across all participants and within the group with dyslexia, linking a major difficulty in dyslexia with impaired auditory statistical learning. These findings dissociate multiple forms of procedural memory that are intact in dyslexia from a specific impairment in auditory statistical learning that is associated with reading difficulty.

Pinging the brain to reveal the hidden attentional priority map using encephalography

Attention has been usefully thought of as organized in priority maps - putative maps of space where attentional priority is weighted across spatial regions in a winner-take-all competition for attentional deployment. Recent work has highlighted the influence of past experiences on the weighting of spatial priority - called selection history. Aside from being distinct from more well-studied, top-down forms of attentional enhancement, little is known about the neural substrates of history-mediated attentional priority. Using a task known to induce statistical learning of target distributions, in an EEG study we demonstrate that this otherwise invisible, latent attentional priority map can be visualized during the intertrial period using a 'pinging' technique in conjunction with multivariate pattern analyses. Our findings not only offer a method of visualizing the history-mediated attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behavior.

The effect of load on spatial statistical learning

Statistical learning (SL), the extraction of regularities embedded in the environment, is often viewed as a fundamental and effortless process. However, whether spatial SL requires resources, or it can operate in parallel to other demands, is still not clear. To examine this issue, we tested spatial SL using the standard lab experiment under concurrent demands: high- and low-cognitive load (Experiment 1) and, spatial memory load (Experiment 2) during the familiarization phase. We found that any type of high-load demands during the familiarization abolished learning. Experiment 3 compared SL under spatial low-load and no-load. We found robust learning in the no-load condition that was dramatically reduced in the low-load condition. Finally, we compared a no-load condition with a very low-load, infrequent dot-probe condition that posed minimal demands while still requiring attention to the display (Experiment 4). The results showed, once again, that any concurrent task during the familiarization phase largely impaired spatial SL. Taken together, we conclude that spatial SL requires resources, a finding that challenges the view that the extraction of spatial regularities is automatic and implicit and suggests that this fundamental learning process is not as effortless as was typically assumed. We further discuss the practical and methodological implications of these findings.