Sequential learning in non-human primates

The order of stimuli matters when learning second-order transitional probabilities

The order of stimuli within sequences and the transitional probabilities (TPs) it generates are central information in sequence processing. However, less is known about what type of information and how it is extracted by general learning mechanisms. The present study focused on statistical learning of second-order TPs. Second-order TPs are involved when only the combination of two stimuli predicts the third. In a first experiment, TPs depended crucially on the order of presentation of a pair A - B , which led to different predictions depending on the order of the stimuli (i.e., ABC vs. BAF). Eight visuomotor sequences governed by second-order TPs were used and response times (RTs) were recorded for each transition. The task included a learning phase followed by a switch phase during which the second-order TP were reversed (e.g., the sequences ABC and BAF became respectively ABF and BAC). A decrease of RTs between the second and the third stimulus during the learning phase and an increase of RTs during the switch phase suggested that variations of orders within second-order TPs could be learned. Further analyses, however, indicated that such learning was difficult for most participants. A second experiment showed that the difficulty of learning was not solely due to the difficulty to pick up the effect of order of presentation, but that learning second-order transitional probabilities in addition to order would be the main obstacle. These experiments suggest that statistical learning is capable of learning complex associations, even if this remains a challenge for human cognition.

Honey Bees Can Use Sequence Learning to Predict Rewards from a Prior Unrewarded Visual Stimulus

Learning to anticipate upcoming events can increase fitness by allowing animals to choose the best course of action, and many species can learn sequences of events and anticipate rewards. To date, most studies have focused on sequences over short time scales such as a few seconds. Whereas events separated by a few seconds are easily learned, events separated by longer delays are typically more difficult to learn. Here, we show that honey bees (Apis mellifera) can learn a sequence of two visually distinct food sources alternating in profitability every few minutes. Bees were challenged to learn that the rewarded pattern was the one that was non-rewarded on the prior visit. We show that bees can predict and choose the feeder that will be rewarding upon their next approach more frequently than predicted by chance, and they improve with experience, with 64% correct choices made in the second half of their visit sequence (N = 320 visits by 20 different bees). These results increase our understanding of honey bee visual sequential learning and further demonstrate the flexibility of foragers' learning strategies.

Taking time: Auditory statistical learning benefits from distributed exposure

In an auditory statistical learning paradigm, listeners learn to partition a continuous stream of syllables by discovering the repeating syllable patterns that constitute the speech stream. Here, we ask whether auditory statistical learning benefits from spaced exposure compared with massed exposure. In a longitudinal online study on Prolific, we exposed 100 participants to the regularities in a spaced way (i.e., with exposure blocks spread out over 3 days) and another 100 in a massed way (i.e., with all exposure blocks lumped together on a single day). In the exposure phase, participants listened to streams composed of pairs while responding to a target syllable. The spaced and massed groups exhibited equal learning during exposure, as indicated by a comparable response-time advantage for predictable target syllables. However, in terms of resulting long-term knowledge, we observed a benefit from spaced exposure. Following a 2-week delay period, we tested participants' knowledge of the pairs in a forced-choice test. While both groups performed above chance, the spaced group had higher accuracy. Our findings speak to the importance of the timing of exposure to structured input and also for statistical learning outside of the laboratory (e.g., in language development), and imply that current investigations of auditory statistical learning likely underestimate human statistical learning abilities.

Flexible Learning and Re-ordering of Context-dependent Object Sequences in Nonhuman Primates

Intelligent behavior involves mentally arranging learned information in novel ways and is particularly well developed in humans. While nonhuman primates (NHP) will learn to arrange new items in complex serial order and re-arrange neighboring items within that order, it has remained contentious whether they are capable to re-assign items more flexibly to non-adjacent positions. Such mental re-indexing is facilitated by inferring the latent temporal structure of experiences as opposed to learning serial chains of item-item associations. Here, we tested the ability for flexible mental re-indexing in rhesus macaques. Subjects learned to serially order five objects. A change of the background context indicated when the object order changed, probing the subjects to mentally re-arrange objects to non-adjacent positions of the learned serial structure. Subjects successfully used the context cue to pro-actively re-index items to new, non-adjacent positions. Mental re-indexing was more likely when the initial order had been learned at a higher level, improved with more experience of the re-indexing rule and correlated with working memory performance in a delayed match-to-sample task. These findings suggest that NHPs inferred the latent serial structure of experiences beyond a chaining of item-item associations and mentally rearrange items within that structure. The pattern of results indicates that NHPs form non-spatial cognitive maps of their experiences, which is a hallmark for flexible mental operations in many serially ordered behaviors including communication, counting or foraging.

Towards a neurodevelopmental cognitive perspective of temporal processing

The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.

Probing Beat Perception with Event-Related Potentials (ERPs) in Human Adults, Newborns, and Nonhuman Primates

The aim of this chapter is to give an overview of how the perception of rhythmic temporal regularity such as a regular beat in music can be studied in human adults, human newborns, and nonhuman primates using event-related brain potentials (ERPs). First, we discuss different aspects of temporal structure in general, and musical rhythm in particular, and we discuss the possible mechanisms underlying the perception of regularity (e.g., a beat) in rhythm. Additionally, we highlight the importance of dissociating beat perception from the perception of other types of structure in rhythm, such as predictable sequences of temporal intervals, ordinal structure, and rhythmic grouping. In the second section of the chapter, we start with a discussion of auditory ERPs elicited by infrequent and frequent sounds: ERP responses to regularity violations, such as mismatch negativity (MMN), N2b, and P3, as well as early sensory responses to sounds, such as P1 and N1, have been shown to be instrumental in probing beat perception. Subsequently, we discuss how beat perception can be probed by comparing ERP responses to sounds in regular and irregular sequences, and by comparing ERP responses to sounds in different metrical positions in a rhythm, such as on and off the beat or on strong and weak beats. Finally, we will discuss previous research that has used the aforementioned ERPs and paradigms to study beat perception in human adults, human newborns, and nonhuman primates. In doing so, we consider the possible pitfalls and prospects of the technique, as well as future perspectives.

Fractals in Neuropsychology and Cognitive Neuroscience

The fractal dimension of cognition refers to the idea that the cognitive processes of the human brain exhibit fractal properties. This means that certain patterns of cognitive activity, such as visual perception, memory, language, or problem-solving, can be described using the mathematical concept of fractal dimension.The idea that cognition is fractal has been proposed by some researchers as a way to understand the complex, self-similar nature of the human brain. However, it's a relatively new idea and is still under investigation, so it's not yet clear to what extent cognitive processes exhibit fractal properties or what implications this might have for our understanding of the brain and clinical practice. Indeed, the mission of the "fractal neuroscience" field is to define the characteristics of fractality in human cognition in order to differently characterize the emergence of brain disorders.

The gradual coevolution of syntactic combinatorics and categorization under the effects of human self-domestication: a proposal

The gradual emergence of syntax has been claimed to be engaged in a feedback loop with Human Self-Domestication (HSD), both processes resulting from, and contributing to, enhanced connectivity in selected cortico-striatal networks, which is the mechanism for attenuating reactive aggression, the hallmark of HSD, but also the mechanism of cross-modality, relevant for syntax. Here, we aim to bridge the gap between these brain changes and further changes facilitated by the gradual complexification of grammars. We propose that increased cross-modality would have enabled and supported, more specifically, a feedback loop between categorization abilities relevant for vocabulary building and the gradual emergence of syntactic structure, including Merge. In brief, an enhanced categorization ability not only brings about more distinct categories, but also a critical number of tokens in each category necessary for Merge to take off in a systematic and productive fashion; in turn, the benefits of expressive capabilities brought about by productive Merge encourage more items to be categorized, and more categories to be formed, thus further potentiating categorization abilities, and with it, syntax again. We support our hypothesis with evidence from the domains of language development and animal communication, but also from biology, neuroscience, paleoanthropology, and clinical linguistics.

Molecular archaeology of human cognitive traits

The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.

The Evolution of Chunks in Sequence Learning

Chunking mechanisms are central to several cognitive processes and notably to the acquisition of visuo-motor sequences. Individuals segment sequences into chunks of items to perform visuo-motor tasks more fluidly, rapidly, and accurately. However, the exact dynamics of chunking processes in the case of extended practice remain unclear. Using an operant conditioning device, 18 Guinea baboons (Papio papio) produced a fixed sequence of nine movements during 1000 trials by pointing to a moving target on a touch screen. Response times analyses revealed a specific chunking pattern of the sequence for each baboon. More importantly, we found that these patterns evolved during the course of the experiment, with chunks becoming progressively fewer and longer. We identified two chunk reorganization mechanisms: the recombination of preexisting chunks and the concatenation of two distinct chunks into a single one. These results provide new evidence on chunking mechanisms in sequence learning and challenge current models of associative and statistical learning.

Working Memory for Spatial Sequences: Developmental and Evolutionary Factors in Encoding Ordinal and Relational Structures

Sequence learning is a ubiquitous facet of human and animal cognition. Here, using a common sequence reproduction task, we investigated whether and how the ordinal and relational structures linking consecutive elements are acquired by human adults, children, and macaque monkeys. While children and monkeys exhibited significantly lower precision than adults for spatial location and temporal order information, only monkeys appeared to exceedingly focus on the first item. Most importantly, only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used a chunking strategy to compress sequences in working memory. Monkeys did not detect such relational structures, even after extensive training. Monkey behavior was captured by a conjunctive coding model, whereas a chunk-based conjunctive model explained more variance in humans. These age- and species-related differences are indicative of developmental and evolutionary mechanisms of sequence encoding and may provide novel insights into the uniquely human cognitive capacities.SIGNIFICANCE STATEMENT Sequence learning, the ability to encode the order of discrete elements and their relationships presented within a sequence, is a ubiquitous facet of cognition among humans and animals. By exploring sequence-processing abilities at different human developmental stages and in nonhuman primates, we found that only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used an internal language to compress sequences in working memory. The findings provided insights into understanding the origins of sequence capabilities in humans and how they evolve through development to identify the unique aspects of human cognitive capacity, which includes the comprehension, learning, and production of sequences, and perhaps, above all, language processing.

Where to sleep next? Evidence for spatial memory associated with sleeping sites in Skywalker gibbons (Hoolock tianxing)

Finding suitable sleeping sites is highly advantageous but challenging for wild animals. While suitable sleeping sites provide protection against predators and enhance sleep quality, these sites are heterogeneously distributed in space. Thus, animals may generate memories associated with suitable sleeping sites to be able to approach them efficiently when needed. Here, we examined traveling trajectories (i.e., direction, linearity, and speed of traveling) in relation to sleeping sites to assess whether Skywalker gibbons (Hoolock tianxing) use spatial memory to locate sleeping trees. Our results show that about 30% of the sleeping trees were efficiently revisited by gibbons and the recursive use of trees was higher than a randomly simulated visiting pattern. When gibbons left the last feeding tree for the day, they traveled in a linear fashion to sleeping sites out-of-sight (> 40 m away), and linearity of travel to sleeping trees out-of-sight was higher than 0.800 for all individuals. The speed of the traveling trajectories to sleeping sites out-of-sight increased not only as sunset approached, but also when daily rainfall increased. These results suggest that gibbons likely optimized their trajectories to reach sleeping sites under increasing conditions of predatory risk (i.e., nocturnal predators) and uncomfortable weather. Our study provides novel evidence on the use of spatial memory to locate sleeping sites through analyses of movement patterns, which adds to an already extensive body of literature linking cognitive processes and sleeping patterns in human and non-human animals.

Nonhuman primates learn adjacent dependencies but fail to learn nonadjacent dependencies in a statistical learning task with a salient cue

There is ample evidence that humans and nonhuman animals can learn complex statistical regularities presented within various types of input. However, humans outperform their nonhuman primate counterparts when it comes to recognizing relationships that exist across one or several intervening stimuli (nonadjacent dependencies). This is especially true when the two elements in the dependency do not share any perceptual similarity (arbitrary associations). In the present study, we investigated whether manipulating the saliency of the predictive stimulus would enhance nonadjacent dependency learning in nonhuman primates. Rhesus macaques and tufted capuchins engaged in a computerized signal detection task that included sequences that were random in nature, included an adjacent dependency, or included a nonadjacent dependency. We manipulated the saliency of the predictive stimulus, such that the predictor jittered in place on the screen in some grammar blocks, as well as the transitional probability (the likelihood of the stimulus preceding the target to accurately predict the target's appearance) from block to block. Some monkeys evidenced learning of adjacent dependencies by faster response times to targets that followed a predictive stimulus compared to targets that were not preceded by a predictor. However, consistent with the body of evidence that indicates that nonhuman animals' statistical learning mechanisms are not at the same level of sophistication as humans', there was no evidence that monkeys learned nonadjacent dependencies of arbitrary associations, even when the salient cue was present.

Formalizing planning and information search in naturalistic decision-making

Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection.

Frontal circuit specialisations for decision making

There is widespread consensus that distributed circuits across prefrontal and anterior cingulate cortex (PFC/ACC) are critical for reward-based decision making. The circuit specialisations of these areas in primates were likely shaped by their foraging niche, in which decision making is typically sequential, attention-guided and temporally extended. Here, I argue that in humans and other primates, PFC/ACC circuits are functionally specialised in two ways. First, microcircuits found across PFC/ACC are highly recurrent in nature and have synaptic properties that support persistent activity across temporally extended cognitive tasks. These properties provide the basis of a computational account of time-varying neural activity within PFC/ACC as a decision is being made. Second, the macrocircuit connections (to other brain areas) differ between distinct PFC/ACC cytoarchitectonic subregions. This variation in macrocircuit connections explains why PFC/ACC subregions make unique contributions to reward-based decision tasks and how these contributions are shaped by attention. They predict dissociable neural representations to emerge in orbitofrontal, anterior cingulate and dorsolateral prefrontal cortex during sequential attention-guided choice, as recently confirmed in neurophysiological recordings.

Up to the magical number seven: An evolutionary perspective on the capacity of short term memory

Working memory and its components are among the most determinant factors in human cognition. However, in spite of their critical importance, many aspects of their evolution remain underinvestigated. The present study is devoted to reviewing the literature of memory studies from an evolutionary, comparative perspective, focusing particularly on short term memory capacity. The findings suggest the limited capacity to be the common attribute of different species of birds and mammals. Moreover, the results imply an increasing trend of capacity from our non-human ancestors to modern humans. The present evidence shows that non-human mammals and birds, regardless of their limitations, are capable of performing memory strategies, although there seem to be some differences between their ability and that of humans in terms of flexibility and efficiency. These findings have several implications relevant to the psychology of memory and cognition, and are likely to explain differences between higher cognitive abilities of humans and non-humans. The adaptive benefits of the limited capacity and the reasons for the growing trend found in the present study are broadly discussed.

Human language evolution: a view from theoretical linguistics on how syntax and the lexicon first came into being

Human language is a multi-componential function comprising several sub-functions each of which may have evolved in other species independently of language. Among them, two sub-functions, or modules, have been claimed to be truly unique to the humans, namely hierarchical syntax (known as “Merge” in linguistics) and the “lexicon.” This kind of species-specificity stands as a hindrance to our natural understanding of human language evolution. Here we challenge this issue and advance our hypotheses on how human syntax and lexicon may have evolved from pre-existing cognitive capacities in our ancestors and other species including but not limited to nonhuman primates. Specifically, we argue that Merge evolved from motor action planning, and that the human lexicon with the distinction between lexical and functional categories evolved from its predecessors found in animal cognition through a process we call “disintegration.” We build our arguments on recent developments in generative grammar but crucially depart from some of its core ideas by borrowing insights from other relevant disciplines. Most importantly, we maintain that every sub-function of human language keeps evolutionary continuity with other species’ cognitive capacities and reject a saltational emergence of language in favor of its gradual evolution. By doing so, we aim to offer a firm theoretical background on which a promising scenario of language evolution can be constructed.

Understanding Human Cognitive Uniqueness

Humanity has regarded itself as intellectually superior to other species for millennia, yet human cognitive uniqueness remains poorly understood. Here, we evaluate candidate traits plausibly underlying our distinctive cognition (including mental time travel, tool use, problem solving, social cognition, and communication) as well as domain generality, and we consider how human cognitive uniqueness may have evolved. We conclude that there are no traits present in humans and absent in other animals that in isolation explain our species' superior cognitive performance; rather, there are many cognitive domains in which humans possess unusually potent capabilities compared to those found in other species. Humans are flexible cognitive all-rounders, whose proficiency arises through interactions and reinforcement between cognitive domains at multiple scales.

A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

Working memory capacity can be improved by recoding the memorized information in a condensed form. Here, we tested the theory that human adults encode binary sequences of stimuli in memory using an abstract internal language and a recursive compression algorithm. The theory predicts that the psychological complexity of a given sequence should be proportional to the length of its shortest description in the proposed language, which can capture any nested pattern of repetitions and alternations using a limited number of instructions. Five experiments examine the capacity of the theory to predict human adults' memory for a variety of auditory and visual sequences. We probed memory using a sequence violation paradigm in which participants attempted to detect occasional violations in an otherwise fixed sequence. Both subjective complexity ratings and objective violation detection performance were well predicted by our theoretical measure of complexity, which simply reflects a weighted sum of the number of elementary instructions and digits in the shortest formula that captures the sequence in our language. While a simpler transition probability model, when tested as a single predictor in the statistical analyses, accounted for significant variance in the data, the goodness-of-fit with the data significantly improved when the language-based complexity measure was included in the statistical model, while the variance explained by the transition probability model largely decreased. Model comparison also showed that shortest description length in a recursive language provides a better fit than six alternative previously proposed models of sequence encoding. The data support the hypothesis that, beyond the extraction of statistical knowledge, human sequence coding relies on an internal compression using language-like nested structures.

Exploring the Neural Structures Underlying the Procedural Memory Network as Predictors of Language Ability in Children and Adolescents With Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Introduction: There is significant overlap in the type of structural language impairments exhibited by children with autism spectrum disorder (ASD) and children with attention deficit hyperactivity disorder (ADHD). This similarity suggests that the cognitive impairment(s) contributing to the structural language deficits in ASD and ADHD may be shared. Previous studies have speculated that procedural memory deficits may be the shared cognitive impairment. The procedural deficit hypothesis (PDH) argues that language deficits can be explained by differences in the neural structures underlying the procedural memory network. This hypothesis is based on the premise that the neural structures comprising the procedural network support language learning. In this study, we aimed to test the PDH in children with ASD, ADHD, and typical development (TD).

Methods: One hundred and sixty-three participants (ages 10–21): 91 with ASD, 26 with ADHD, and 46 with TD, completed standardized measures of cognitive and language ability as well as structural magnetic resonance imaging. We compared the structural language abilities, the neural structures underlying the procedural memory network, and the relationship between structural language and neural structure across diagnostic groups.

Results: Our analyses revealed that while the structural language abilities differed across ASD, ADHD, and TD groups, the thickness, area, and volume of the structures supporting the procedural memory network were not significantly different between diagnostic groups. Also, several neural structures were associated with structural language abilities across diagnostic groups. Only two of these structures, the inferior frontal gyrus, and the left superior parietal gyrus, are known to be linked to the procedural memory network.

Conclusions: The inferior frontal gyrus and the left superior parietal gyrus, have well-established roles in language learning independent of their role as part of the procedural memory system. Other structures such as the caudate and cerebellum, with critical roles in the procedural memory network, were not associated with structural language abilities across diagnostic groups. It is unclear whether the procedural memory network plays a fundamental role in language learning in ASD, ADHD, and TD.

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.

Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability

In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences. The switch between the two types of activation occurs through the modulation of biological parameters, without altering the connectivity matrix. Some of the parameters included in our model are neuronal gain, strength of inhibition, synaptic depression and noise. We investigate how these parameters enable the existence of sequences and influence the type of sequences observed. In particular we show that synaptic depression and noise drive the transitions from one memory item to the next and neuronal gain controls the switching between regular and irregular (random) activation.

Variations in the Beneficial Effects of Spatial Structure and Serial Organisation on Working Memory Span in Humans and Other Species

This chapter reviews studies of spontaneous search in large-scale settings and studies featuring variations of the Corsi test in humans and animals. It aims to highlight a synergy of working memory (WM) processes and the use of spatio-temporal structure and explain its underpinnings within a comparative framework. The chapter starts by showing that the degree of organisation of serial search patterns spontaneously deployed by humans and animals in simulated foraging tasks is associated with a reduction of WM errors. Then, by comparing studies conducted on different species, it exposes a parallel between the degree of search organisation and taxonomic relatedness to humans. Such a parallel could indicate that a hallmark of the cognition of humans and closely related species is the ability to offload WM by developing serially organised search patterns that exploit the spatial structure of the environment. However, a causal relationship between serial organisation and search efficiency can only be inferred with serial recall tasks, where the structure of specific sequences can be systematically manipulated. Thus, studies using variations of the Corsi test are considered subsequently, which suggest that humans might enjoy an exceptional aptitude to benefit from the spatio-temporal structure in serial tasks, despite remarkable memory abilities shown by other primate species as well. The extent to which the benefit of spatial organisation in human WM span must be mediated by perceptual grouping processes is then considered. To clarify this issue, recent experiments using virtual reality to compare serial recall in small visual displays that afford perceptual grouping and in immersive navigational spaces that cannot do so are discussed. The results of these latter experiments indicate that the effects of structure in serial recall emerge in conditions not affording grouping at perceptual level. Thus, it is suggested that more central representational processes play a role in the interaction between spatio-temporal organisation and working memory span in humans.

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 predictive structure without a teacher: decision strategies and brain routes

Extracting the structure of complex environments is at the core of our ability to interpret the present and predict the future. This skill is important for a range of behaviours from navigating a new city to learning music and language. Classical approaches that investigate our ability to extract the principles of organisation that govern complex environments focus on reward-based learning. Yet, the human brain is shown to be expert at learning generative structure based on mere exposure and without explicit reward. Individuals are shown to adapt to-unbeknownst to them-changes in the environment's temporal statistics and predict future events. Further, we present evidence for a common brain architecture for unsupervised structure learning and reward-based learning, suggesting that the brain is built on the premise that 'learning is its own reward' to support adaptive behaviour.

Dyslexia-related impairments in sequence learning predict linguistic abilities

Dyslexia is often characterized by disordered word recognition and spelling, though dysfunction on various non-linguistic tasks suggests a more pervasive deficit may underlie reading and spelling abilities. The serial-order learning impairment in dyslexia (SOLID) hypothesis proposes that sequence learning impairments fundamentally disrupt cognitive abilities, including linguistic processes, among individuals with dyslexia; yet only some studies report sequence learning deficits in people with dyslexia relative to controls. Evidence may be mixed because traditional sequence learning tasks often require strong motor demands, working memory processes and/or executive functions, wherein people with dyslexia can show impairments. Thus, observed sequence learning deficits in dyslexia may only appear to the extent that comorbid motor-based processes, memory capacity, or executive processes are involved. The present study measured sequence learning in college-aged students with and without dyslexia using a single task that evaluates sequencing and non-sequencing components but without strong motor, executive, or memory demands. During sequencing, each additional link in a sequence of stimuli leading to a reward is trained step-by-step, until a complete sequence is acquired. People with dyslexia made significantly more sequencing errors than controls, despite equivalent performance on non-sequencing components. Mediation analyses further revealed that sequence learning accounted for a large portion of the variance between dyslexia status and linguistic abilities, particularly pseudo-word reading. These findings extend the SOLID hypothesis by showing difficulties in the ability to acquire sequences that may play an underlying role in literacy acquisition.

Concurrent Learning of Adjacent and Nonadjacent Dependencies in Visuo-Spatial and Visuo-Verbal Sequences

Both adjacent and non-adjacent dependencies (AD and NAD) are present in natural language and other domains, yet the learning of non-adjacent sequential dependencies generally only occurs under favorable circumstances. It is currently unknown to what extent adults can learn AD and NAD, presented concurrently in spatial and verbal sequences during a single session, and whether a second session improves performance. In addition, the relationship between AD and NAD learning and other theoretically related cognitive and language processes has not yet been fully established. In this study, participants reproduced two types of sequences generated from an artificial grammar: visuo-spatial sequences with stimuli presented in four spatial locations, and visuo-verbal sequences with printed syllables. Participants were tested for incidental learning by reproducing novel sequences, half consistent with the grammar and half containing violations of either AD or NAD. The procedure was repeated on a second day. Results showed that both AD and NAD were learned in both visuo-spatial and visuo-verbal tasks, although AD learning was better than NAD and learning of NAD decreased over time. Furthermore, NAD learning for both spatial and verbal tasks was positively correlated with a language measure, whereas AD learning for both spatial and verbal tasks was negatively associated with working memory measures in the opposite domain. These results demonstrate that adults can learn both AD and NAD within a single session, but NAD learning is more easily disrupted than AD and both types of learning are sub-served by partially distinct cognitive processes. These findings increase our understanding of the processes governing the learning of AD and NAD in verbal and spatial domains.

Recursion in action: An fMRI study on the generation of new hierarchical levels in motor sequences

Generation of hierarchical structures, such as the embedding of subordinate elements into larger structures, is a core feature of human cognition. Processing of hierarchies is thought to rely on lateral prefrontal cortex (PFC). However, the neural underpinnings supporting active generation of new hierarchical levels remain poorly understood. Here, we created a new motor paradigm to isolate this active generative process by means of fMRI. Participants planned and executed identical movement sequences by using different rules: a Recursive hierarchical embedding rule, generating new hierarchical levels; an Iterative rule linearly adding items to existing hierarchical levels, without generating new levels; and a Repetition condition tapping into short term memory, without a transformation rule. We found that planning involving generation of new hierarchical levels (Recursive condition vs. both Iterative and Repetition) activated a bilateral motor imagery network, including cortical and subcortical structures. No evidence was found for lateral PFC involvement in the generation of new hierarchical levels. Activity in basal ganglia persisted through execution of the motor sequences in the contrast Recursive versus Iteration, but also Repetition versus Iteration, suggesting a role of these structures in motor short term memory. These results showed that the motor network is involved in the generation of new hierarchical levels during motor sequence planning, while lateral PFC activity was neither robust nor specific. We hypothesize that lateral PFC might be important to parse hierarchical sequences in a multi‐domain fashion but not to generate new hierarchical levels.

Spontaneous eyeblinks are sensitive to sequential learning

Although sequential learning and spontaneous eyeblink rate (EBR) have both been shown to be tightly related to cerebral dopaminergic activity, they have never been investigated at the same time. In the present study, EBR, taken as an indirect marker of dopaminergic activity, was investigated in two resting state conditions, both before and after visuomotor sequence learning in a serial reaction time task (SRT) and during task practice. Participants' abilities to produce and manipulate their knowledge about the sequential material were probed in a generation task. We hypothesized that the time course of spontaneous EBR might follow the progressive decrease of RTs during the SRT session. Additionally, we manipulated the structure of the transfer blocks as well as their respective order, assuming that (1) fully random trials might generate a larger psychophysiological response than an unlearned but structured material, and (2) a second (final) block of transfer might give rise to larger effects given that the sequential material was better consolidated after further practice. Finally, we tentatively hypothesized that, in addition to their online version, spontaneous EBR recorded during the pre- and post-learning resting sessions might be predictive of (1) the SRT learning curve, (2) the magnitude of the transfer effects, and (3) performance in the generation task. Results showed successful sequence learning with decreased accuracy and increased reaction times (RTs) in transfer blocks featuring a different material (random trials or a structured, novel sequence). In line with our hypothesis that EBR reflects dopaminergic activity associated with sequential learning, we observed increased EBR in random trials as well as when the second transfer block occurred at the end of the learning session. There was a positive relationship between the learning curve (RTs) and the slope of EBR during the SRT session. Additionally, inter-individual differences in resting and real-time EBR predicted the magnitude of accuracy and RTs transfer effects, respectively, but they were not related to participants' performances during the generation task. Notwithstanding, our results suggest that the degree of explicit sequential knowledge modulates the association between the magnitude of the transfer effect in EBR and SRT performance. Overall, the present study provides evidence that EBR may represent a valid indirect psychophysiological correlate of dopaminergic activity coupled to sequential learning.

Recursive Combination Has Adaptability in Diversifiability of Production and Material Culture

It has been suggested that hierarchically structured symbols, a remarkable feature of human language, are produced via the operation of recursive combination. Recursive combination is frequently observed in human behavior, not only in language but also in action sequences, mind-reading, technology, etc. in contrast, it is rarely observed in animals. Why is it that only humans use this operation? What is the adaptability of recursive combination? We aim (1) to identify the environmental feature(s) in which recursive combination is effective for survival and reproduction, and that has facilitated the evolution of this ability, and (2) to demonstrate the possible evolutionary processes of recursive combination. To achieve this, we constructed an evolutionary simulation of agents that generated products using recursive combination and used the results to explore the types of fitness functions (that reflect the kinds of adaptive environments) that give rise to this ability. We identified two types of adaptability of the recursive combination: (1) diversifiability of production and (2) diversifiability of products. Through the former, recursive combination promotes robustness against failure of production caused by inaccurate manipulations or irreversible changes. In an environment in which diversified products are preferable, sharing a portion of the production process for these products entails producing multiple products in which recursive combination plays a key role. We suppose that recursive combination works as a driving force of material culture. Finally, we discuss the possible evolutionary scenarios of recursive combination that is later generalized to encompass many aspects of human cognition, including human language.

Production of Supra-regular Spatial Sequences by Macaque Monkeys

Understanding and producing embedded sequences in language, music, or mathematics, is a central characteristic of our species. These domains are hypothesized to involve a human-specific competence for supra-regular grammars, which can generate embedded sequences that go beyond the regular sequences engendered by finite-state automata. However, is this capacity truly unique to humans? Using a production task, we show that macaque monkeys can be trained to produce time-symmetrical embedded spatial sequences whose formal description requires supra-regular grammars or, equivalently, a push-down stack automaton. Monkeys spontaneously generalized the learned grammar to novel sequences, including longer ones, and could generate hierarchical sequences formed by an embedding of two levels of abstract rules. Compared to monkeys, however, preschool children learned the grammars much faster using a chunking strategy. While supra-regular grammars are accessible to nonhuman primates through extensive training, human uniqueness may lie in the speed and learning strategy with which they are acquired.

Non-adjacent Dependencies Processing in Human and Non-human Primates

Human and non-human primates share the ability to extract adjacent dependencies and, under certain conditions, non-adjacent dependencies (i.e., predictive relationships between elements that are separated by one or several intervening elements in a sequence). In this study, we explore the online extraction dynamics of non-adjacent dependencies in humans and baboons using a serial reaction time task. Participants had to produce three-target sequences containing deterministic relationships between the first and last target locations. In Experiment 1, participants from the two species could extract these non-adjacent dependencies, but humans required less exposure than baboons. In Experiment 2, the data show for the first time in a non-human primate species the successful generalization of sequential non-adjacent dependencies over novel intervening items. These findings provide new evidence to further constrain current theories about the nature and the evolutionary origins of the learning mechanisms allowing the extraction of non-adjacent dependencies.

Rethinking foundations of language from a multidisciplinary perspective

The issue of language foundations has been of great controversy ever since it was first raised in Lenneberg's (1967) monograph Biological Foundations of Language. Based on a survey of recent findings relevant to the study of language acquisition and evolution, we propose that: (i) the biological predispositions for language are largely domain-general, not necessarily language-specific or human-unique; (ii) the socio-cultural environment of language serves as another important foundation of language, which helps shape language components, induce and drive language shift; and (iii) language must have coevolved with the cognitive mechanisms associated with it through intertwined biological and cultural evolution. In addition to theoretical issues, this paper also evaluates the primary approaches recently joining the endeavor of studying language foundations and evolution, including human experiments and computer simulations. Most of the evidence surveyed in this paper comes from a variety of disciplines, and methodology therein complements each other to form a global picture of language foundations. These reflect the complexity of the issue of language foundations and the necessity of taking a multidisciplinary perspective to address it.

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.

Learning predictive statistics from temporal sequences: Dynamics and strategies

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

The role of nondeclarative memory in the skill for language: Evidence from syntactic priming in patients with amnesia

Syntactic priming, the phenomenon in which participants adopt the linguistic behaviour of their partner, is widely used in psycholinguistics to investigate syntactic operations. Although the phenomenon of syntactic priming is well documented, the memory system that supports the retention of this syntactic information long enough to influence future utterances, is not as widely investigated. We aim to shed light on this issue by assessing patients with Korsakoff's amnesia on an active-passive syntactic priming task and compare their performance to controls matched in age, education, and premorbid intelligence. Patients with Korsakoff's syndrome display deficits in all subdomains of declarative memory, yet their nondeclarative memory remains intact, making them an ideal patient group to determine which memory system supports syntactic priming. In line with the hypothesis that syntactic priming relies on nondeclarative memory, the patient group shows strong priming tendencies (12.6% passive structure repetition). Our healthy control group did not show a priming tendency, presumably due to cognitive interference between declarative and nondeclarative memory. We discuss the results in relation to amnesia, aging, and compensatory mechanisms.

Cognitive representation of "musical fractals": Processing hierarchy and recursion in the auditory domain

The human ability to process hierarchical structures has been a longstanding research topic. However, the nature of the cognitive machinery underlying this faculty remains controversial. Recursion, the ability to embed structures within structures of the same kind, has been proposed as a key component of our ability to parse and generate complex hierarchies. Here, we investigated the cognitive representation of both recursive and iterative processes in the auditory domain. The experiment used a two-alternative forced-choice paradigm: participants were exposed to three-step processes in which pure-tone sequences were built either through recursive or iterative processes, and had to choose the correct completion. Foils were constructed according to generative processes that did not match the previous steps. Both musicians and non-musicians were able to represent recursion in the auditory domain, although musicians performed better. We also observed that general ‘musical’ aptitudes played a role in both recursion and iteration, although the influence of musical training was somehow independent from melodic memory. Moreover, unlike iteration, recursion in audition was well correlated with its non-auditory (recursive) analogues in the visual and action sequencing domains. These results suggest that the cognitive machinery involved in establishing recursive representations is domain-general, even though this machinery requires access to information resulting from domain-specific processes.

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37: , 310-343).This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

A sequence learning impairment in dyslexia? It depends on the task

Language acquisition is argued to be dependent upon an individuals' sensitivity to serial-order regularities in the environment (sequential learning), and impairments in reading and spelling in dyslexia have recently been attributed to a deficit in sequential learning. The present study examined the learning and consolidation of sequential knowledge in 30 adults with dyslexia and 29 typical adults matched on age and nonverbal ability using two tasks previously reported to be sensitive to a sequence learning deficit. Both groups showed evidence of sequential learning and consolidation on a serial response time (SRT) task (i.e., faster and more accurate responses to sequenced spatial locations than randomly ordered spatial locations during training that persisted one week later). Whilst typical adults showed evidence of sequential learning on a Hebb repetition task (i.e., more accurate serial recall of repetitive sequences of nonwords versus randomly ordered sequences), adults with dyslexia showed initial advantages for repetitive versus randomly ordered sequences in the first half of training trials, but this effect disappeared in the second half of trials. This Hebb repetition effect was positively correlated with spelling in the dyslexic group; however, there was no correlation between sequential learning on the two tasks, placing doubt over whether sequential learning in different modalities represents a single capacity. These data suggest that sequential learning difficulties in adults with dyslexia are not ubiquitous, and when present may be a consequence of task demands rather than sequence learning per se.

Influence of Perceptual Saliency Hierarchy on Learning of Language Structures: An Artificial Language Learning Experiment

Psychological experiments have revealed that in normal visual perception of humans, color cues are more salient than shape cues, which are more salient than textural patterns. We carried out an artificial language learning experiment to study whether such perceptual saliency hierarchy (color > shape > texture) influences the learning of orders regulating adjectives of involved visual features in a manner either congruent (expressing a salient feature in a salient part of the form) or incongruent (expressing a salient feature in a less salient part of the form) with that hierarchy. Results showed that within a few rounds of learning participants could learn the compositional segments encoding the visual features and the order between them, generalize the learned knowledge to unseen instances with the same or different orders, and show learning biases for orders that are congruent with the perceptual saliency hierarchy. Although the learning performances for both the biased and unbiased orders became similar given more learning trials, our study confirms that this type of individual perceptual constraint could contribute to the structural configuration of language, and points out that such constraint, as well as other factors, could collectively affect the structural diversity in languages.

Self-similarity and recursion as default modes in human cognition

Humans generate recursive hierarchies in a variety of domains, including linguistic, social and visuo-spatial modalities. The ability to represent recursive structures has been hypothesized to increase the efficiency of hierarchical processing. Theoretical work together with recent empirical findings suggests that the ability to represent the self-similar structure of hierarchical recursive stimuli may be supported by internal neural representations that compress raw external information and increase efficiency. In order to explicitly test whether the representation of recursive hierarchies depends on internalized rules we compared the processing of visual hierarchies represented either as recursive or non-recursive, using task-free resting-state fMRI data. We aimed to evaluate the relationship between task-evoked functional networks induced by cognitive representations with the corresponding resting-state architecture. We observed increased connectivity within Default Mode Network (DMN) related brain areas during the representation of recursion, while non-recursive representations yielded increased connectivity within the Fronto-Parietal Control-Network. Our results suggest that human hierarchical information processing using recursion is supported by the DMN. In particular, the representation of recursion seems to constitute an internally-biased mode of information-processing that is mediated by both the core and dorsal-medial subsystems of the DMN. Compressed internal rule representations mediated by the DMN may help humans to represent and process hierarchical structures in complex environments by considerably reducing information processing load.

Homo imitans? Seven reasons why imitation couldn't possibly be associative

Many comparative and developmental psychologists believe that we are Homo imitans; humans are more skilled and prolific imitators than other animals, because we have a special, inborn 'intermodal matching' mechanism that integrates representations of others with representations of the self. In contrast, the associative sequence learning (ASL) model suggests that human infants learn to imitate using mechanisms that they share with other animals, and the rich resources provided by their sociocultural environments. This article answers seven objections to the ASL model: (i) it presents evidence that newborns do not imitate; (ii) argues that infants receive a plentiful supply of the kind of experience necessary for learning to imitate; (iii) suggests that neither infants nor adults can imitate elementally novel actions; (iv) explains why non-human animals have a limited capacity for imitation; (v) discusses the goal-directedness of imitation; (vi) presents evidence that improvement in imitation depends on visual feedback; and (vii) reflects on the view that associative theories steal 'the soul of imitation'. The empirical success of the ASL model indicates that the mechanisms which make imitation possible, by aligning representations of self with representations of others, have been tweaked by cultural evolution, not built from scratch by genetic evolution.