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

Dynamic Motion and Human Agents Facilitate Visual Nonadjacent Dependency Learning

Many events that humans and other species experience contain regularities in which certain elements within an event predict certain others. While some of these regularities involve tracking the co-occurrences between temporally adjacent stimuli, others involve tracking the co-occurrences between temporally distant stimuli (i.e., nonadjacent dependencies, NADs). Prior research shows robust learning of adjacent dependencies in humans and other species, whereas learning NADs is more difficult, and often requires support from properties of the stimulus to help learners notice the NADs. Here, we report on seven experiments that examined NAD learning from various types of visual stimuli, exploring the effects of dynamic motion on adults' NAD learning from visual sequences involving human and nonhuman agents. We tested adults' NAD learning from visual sequences of human actions, object transformations, static images of human postures, and static images of an object in different postures. We found that dynamic motion aids the acquisition of NADs. We also found that learning NADs in sequences involving human agents is more robust compared to sequences involving nonhuman objects. We propose that dynamic motion and human agents both independently result in richer representations that provide a stronger signal for NAD learning.

Incidental auditory category learning and visuomotor sequence learning do not compete for cognitive resources

The environment provides multiple regularities that might be useful in guiding behavior if one was able to learn their structure. Understanding statistical learning across simultaneous regularities is important, but poorly understood. We investigate learning across two domains: visuomotor sequence learning through the serial reaction time (SRT) task, and incidental auditory category learning via the systematic multimodal association reaction time (SMART) task. Several commonalities raise the possibility that these two learning phenomena may draw on common cognitive resources and neural networks. In each, participants are uninformed of the regularities that they come to use to guide actions, the outcomes of which may provide a form of internal feedback. We used dual-task conditions to compare learning of the regularities in isolation versus when they are simultaneously available to support behavior on a seemingly orthogonal visuomotor task. Learning occurred across the simultaneous regularities, without attenuation even when the informational value of a regularity was reduced by the presence of the additional, convergent regularity. Thus, the simultaneous regularities do not compete for associative strength, as in overshadowing effects. Moreover, the visuomotor sequence learning and incidental auditory category learning do not appear to compete for common cognitive resources; learning across the simultaneous regularities was comparable to learning each regularity in isolation.

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.

The influence of variability on mismatch negativity amplitude

Mismatch Negativity (MMN) to pattern deviations reveals exquisite pattern detection ability in the brain. MMN amplitude is proposed to be precision-weighted, being inversely proportional to variability within a patterned sound sequence. Two experiments were conducted to determine whether pattern variability, shown to influence MMN to simple pattern deviance, also extends to MMN elicited to abstract pattern deviants. Participants were presented with 3-tone triplet sequences that were defined by regular frequency ascendance with adjacent (A<B<C) or non-adjacent (A<C) dependency. The triplets were defined by an abstract pattern in that the starting frequency of A roamed randomly between 500-3700 Hz. Using variants of these sequences over two studies the results show that MMN was elicited to rare A > C deviants for adjacent and non-adjacent dependencies, was smaller for the latter, was impervious to variance in tone loudness, but showed prolonged sensitivity to the level of variability at sequence onset.

Infants' learning of non-adjacent regularities from visual sequences

Tracking adjacent (AD) and non-adjacent (NAD) dependencies in a sequence of elements is critical for the development of many complex abilities, such as language acquisition and social interaction. While learning of AD in infancy is a domain-general ability that is functioning across different domains, infants' processing of NAD has been reported only for speech sequences. Here, we tested 9- to 12- and 13- to 15-month-olds' ability to extract AxB grammars in visual sequences of unfamiliar elements. Infants were habituated to a series of 3-visual arrays following an AxB grammar in which the first element (A) predicted the third element (B), while intervening X elements changed continuously. Following habituation, infants were tested with 3-item arrays in which initial and final positions were switched (novel) or kept consistent with the habituation phase (familiar). Older infants successfully recognized the familiar AxB grammar at test, whereas the younger group showed some sensitivity to extract to NAD, albeit in a less robust form. This finding provides the first evidence that the ability to track NAD is a domain-general ability that is present also in the visual domain and that the sensitivity to such dependencies is related to developmental changes, as demonstrated in the auditory domain.

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.

Distinct neural networks for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study

The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

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.