Processing abstract sequence structure: learning without knowing, or knowing without learning?

White matter microstructural correlates of associative learning in the oldest-old

The ability to learn associations between events is critical for everyday functioning (e.g., decision making, social interactions) and has been attributed to structural differences in white matter tracts connecting cortical regions to the hippocampus (e.g., fornix) and striatum (e.g., internal capsule) in younger-old adults (ages 65-85 years). However, evidence of associative learning has not been assessed within oldest-old adults (ages 90+ years), despite its relevance to other extensively characterized cognitive abilities in the oldest-old and the relatively large effect of advanced age on the microstructural composition of these white matter tracts. We acquired multicompartment diffusion-weighted magnetic resonance imaging data from 22 oldest-old adults without dementia (mean age = 92.91 ± 1.44 years) who also completed an associative learning task. Behavioral results revealed significantly better associative learning performance during later task stages, as expected if participants incidentally learned the cue-cue-target associations for frequently occurring event triplets. Moreover, better learning performance was significantly predicted by better microstructure of cortico-striatal white matter (posterior limb of the internal capsule). Finding that associative learning abilities in the 10^th decade of life are supported by better microstructure of white matter tracts connecting the cortex to the striatum underscores their importance to learning performance across the entire lifespan.

Age group differences in learning-related activity reflect task stage, not learning stage

Healthy aging is accompanied by declines in the ability to learn associations between events, even when their relationship cannot be described. Previous functional magnetic resonance imaging (fMRI) studies have attributed these implicit associative learning (IAL) deficits to differential engagement of the hippocampus and basal ganglia in older relative to younger adults in early and late stages of the task, respectively. However, these task stages have been confounded with age group differences in learning performance that emerge later and to a lesser degree in older adults. To disentangle the effects of task stage from learning stage (i.e., when there is significant evidence of learning) on age group differences in the neural substrates of IAL, we acquired fMRI data while 28 younger (20.8 ± 2.3 years) and 22 older (73.6 ± 6.8 years) healthy adults completed the Triplets Learning Task, in which the location of two cues predicted the location of a target with high (HF) or low (LF) frequency. When matched for task stage, results revealed worse learning performance and increased IAL-related activity in the hippocampus during the early stage and in the globus pallidum during the late stage in older relative to younger adults. However, when matched for learning stage, there were no significant age group differences in learning performance or IAL-related activity. Thus, although learning emerges later for older adults, they are engaging similar brain regions as younger adults when learning the associations, suggesting that previous reports of age group differences reflect effects of age on task stage, but not learning stage.

A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning

Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network (DSRN) model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning effects in the serial reaction time (SRT) task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning.

Implicit sequence learning of chunking and abstract structures

The current study investigated whether people can simultaneously acquire knowledge about concrete chunks and abstract structures in implicit sequence learning; and whether the degree of abstraction determines the conscious status of the acquired knowledge. We adopted three types of stimuli in a serial reaction time task in three experiments. The RT results indicated that people could simultaneously acquire knowledge about concrete chunks and abstract structures of the temporal sequence. Generation performance revealed that ability to control was mainly based on abstract structures rather than concrete chunks. Moreover, ability to control was not generally accompanied with awareness of knowing or knowledge, as measured by confidence ratings and attribution tests, confirming that people could control the use of unconscious knowledge of abstract structures. The results present a challenge to computational models and theories of implicit learning.

Lack of frequency-tagged magnetic responses suggests statistical regularities remain undetected during NREM sleep

Hypnopedia, or the capacity to learn during sleep, is debatable. De novo acquisition of reflex stimulus-response associations was shown possible both in man and animal. Whether sleep allows more sophisticated forms of learning remains unclear. We recorded during diurnal Non-Rapid Eye Movement (NREM) sleep auditory magnetoencephalographic (MEG) frequency-tagged responses mirroring ongoing statistical learning. While in NREM sleep, participants were exposed at non-awakenings thresholds to fast auditory streams of pure tones, either randomly organized or structured in such a way that the stream statistically segmented in sets of 3 elements (tritones). During NREM sleep, only tone-related frequency-tagged MEG responses were observed, evidencing successful perception of individual tones. No participant showed tritone-related frequency-tagged responses, suggesting lack of segmentation. In the ensuing wake period however, all participants exhibited robust tritone-related responses during exposure to statistical (but not random) streams. Our data suggest that associations embedded in statistical regularities remain undetected during NREM sleep, although implicitly learned during subsequent wakefulness. These results suggest intrinsic limitations in de novo learning during NREM sleep that might confine the NREM sleeping brain's learning capabilities to simple, elementary associations. It remains to be ascertained whether it similarly applies to REM sleep.

Predictive Movements and Human Reinforcement Learning of Sequential Action

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse movement trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model.

Physical Activity Is Associated with Reduced Implicit Learning but Enhanced Relational Memory and Executive Functioning in Young Adults

Accumulating evidence suggests that physical activity improves explicit memory and executive cognitive functioning at the extreme ends of the lifespan (i.e., in older adults and children). However, it is unknown whether these associations hold for younger adults who are considered to be in their cognitive prime, or for implicit cognitive functions that do not depend on motor sequencing. Here we report the results of a study in which we examine the relationship between objectively measured physical activity and (1) explicit relational memory, (2) executive control, and (3) implicit probabilistic sequence learning in a sample of healthy, college-aged adults. The main finding was that physical activity was positively associated with explicit relational memory and executive control (replicating previous research), but negatively associated with implicit learning, particularly in females. These results raise the intriguing possibility that physical activity upregulates some cognitive processes, but downregulates others. Possible implications of this pattern of results for physical health and health habits are discussed.

Implicit learning of between-group intervals in auditory temporal structures

Implicit learning of temporal structure has primarily been reported when events within a sequence (e.g., visual-spatial locations, tones) are systematically ordered and correlated with the temporal structure. An auditory serial reaction time task was used to investigate implicit learning of temporal intervals between pseudorandomly ordered syllables. Over exposure, participants identified syllables presented in sequences with weakly metrical temporal structures. In a test block, the temporal structure differed from exposure only in the duration of the interonset intervals (IOIs) between groups. It was hypothesized that reaction time (RT) to syllables following between-group IOIs would decrease with exposure and increase at test. In Experiments 1 and 2, the sequences presented over exposure and test were counterbalanced across participants (Pattern 1 and Pattern 2 conditions). An RT increase at test to syllables following between-group IOIs was only evident in the condition that presented an exposure structure with a slightly stronger meter (Pattern 1 condition). The Pattern 1 condition also elicited a global expectancy effect: Test block RT slowed to earlier-than-expected syllables (i.e., syllables shifted to an earlier beat) but not to later-than-expected syllables. Learning of between-group IOIs and the global expectancy effect extended to the Pattern 2 condition when meter was strengthened with an external pulse (Experiment 2). Experiment 3 further demonstrated implicit learning of a new weakly metrical structure with only earlier-than-expected violations at test. Overall findings demonstrate learning of weakly metrical rhythms without correlated event structures (i.e., sequential syllable orders). They further suggest the presence of a global expectancy effect mediated by metrical strength.

The Effects of Structural Complexity on Age-Related Deficits in Implicit Probabilistic Sequence Learning

OBJECTIVE

The primary objective was to determine whether age deficits in implicit sequence learning occur not only for second-order probabilistic regularities (event n - 2 predicts n), as reported earlier, but also for first-order regularities (event n - 1 predicts event n). A secondary goal was to determine whether age differences in learning vary with level of structure.

METHOD

Younger and older adults completed a nonmotor sequence learning task containing either a first- or second-order structure. Learning scores were calculated for each subject and compared to address our research objectives.

RESULTS

Age deficits in implicit learning emerged not only for second-order probabilistic structure, but also for simple, first-order structure. In addition, age differences did not vary significantly with structure; both first and second order yielded similar age deficits.

DISCUSSION

These findings are consistent with the view that there is an associative binding deficit in aging and that this deficit occurs for implicit as well as explicit learning and across simple and more complex sequence structures.

Caudate resting connectivity predicts implicit probabilistic sequence learning

Abstract Implicit probabilistic sequence learning (IPSL) involves extracting statistical regularities from sequences of events without awareness, and is thought to underlie learning of language and behavioral repertoires of everyday life. We examined whether resting-state functional connectivity networks of the caudate predicted individual differences in IPSL performance measured on a separate day. Whole-brain connectivity maps of a bilateral dorsal caudate (DC) seed were created for each subject and examined for voxelwise correlations with sequence learning performance, as well as with overall response speed. Higher learning scores (but not overall response speed) were associated with stronger resting-state connectivity between the DC and right medial temporal lobe, as well as with lower resting-state connectivity between the DC and premotor regions involved in motor planning. Thus, how well one learns probabilistic regularities without awareness is predicted by the strength of a striato-cortical network in the resting brain.

Neurocognitive contributions to motor skill learning: the role of working memory

Researchers have begun to delineate the precise nature and neural correlates of the cognitive processes that contribute to motor skill learning. The authors review recent work from their laboratory designed to further understand the neurocognitive mechanisms of skill acquisition. The authors have demonstrated an important role for spatial working memory in 2 different types of motor skill learning, sensorimotor adaptation and motor sequence learning. They have shown that individual differences in spatial working memory capacity predict the rate of motor learning for sensorimotor adaptation and motor sequence learning, and have also reported neural overlap between a spatial working memory task and the early, but not late, stages of adaptation, particularly in the right dorsolateral prefrontal cortex and bilateral inferior parietal lobules. The authors propose that spatial working memory is relied on for processing motor error information to update motor control for subsequent actions. Further, they suggest that working memory is relied on during learning new action sequences for chunking individual action elements together.

Visual Sequence Learning in Infancy: Domain-General and Domain-Specific Associations with Language

Research suggests that non-linguistic sequence learning abilities are an important contributor to language development (Conway, Bauernschmidt, Huang, & Pisoni, 2010). The current study investigated visual sequence learning as a possible predictor of vocabulary development in infants. Fifty-eight 8.5-month-old infants were presented with a three-location spatiotemporal sequence of multi-colored geometric shapes. Early language skills were assessed using the MacArthur-Bates CDI. Analyses of children's reaction times to the stimuli suggest that the extent to which infants demonstrated learning was significantly correlated with their vocabulary comprehension at the time of test and with their gestural comprehension abilities 5 months later. These findings suggest that visual sequence learning may have both domain-general and domain-specific associations with language learning.

Automatic generation of randomized trial sequences for priming experiments

In most psychological experiments, a randomized presentation of successive displays is crucial for the validity of the results. For some paradigms, this is not a trivial issue because trials are interdependent, e.g., priming paradigms. We present a software that automatically generates optimized trial sequences for (negative-) priming experiments. Our implementation is based on an optimization heuristic known as genetic algorithms that allows for an intuitive interpretation due to its similarity to natural evolution. The program features a graphical user interface that allows the user to generate trial sequences and to interactively improve them. The software is based on freely available software and is released under the GNU General Public License.

Now you see it, now you don't: controlling for contingencies and stimulus repetitions eliminates the Gratton effect

The Gratton (or sequential congruency) effect is the finding that conflict effects (e.g., Stroop and Eriksen flanker effects) are larger following congruent trials relative to incongruent trials. The standard account given for this is that a cognitive control mechanism detects conflict when it occurs and adapts to this conflict on the following trial. Others, however, have questioned the conflict adaptation account and suggested that sequential biases might account for the Gratton effect. In two experiments, contingency biases were removed from the task and stimulus repetitions were deleted to control for stimulus bindings. This eliminated the Gratton effect in the response times in both experiments, supporting a non-conflict explanation of the Gratton effect. A Gratton effect did persist in the errors of Experiment 1; however, this effect was not produced by the type of errors (word reading errors) that a conflict adaptation account should predict. Instead, tentative support was found for a congruency switch cost hypothesis. In all, the conflict adaptation account failed to account for any of the reported data. Implications for future work on cognitive control are discussed.

The effects of aging on the neural basis of implicit associative learning in a probabilistic triplets learning task

Few studies have investigated how aging influences the neural basis of implicit associative learning, and available evidence is inconclusive. One emerging behavioral pattern is that age differences increase with practice, perhaps reflecting the involvement of different brain regions with training. Many studies report hippocampal involvement early on with learning becoming increasingly dependent on the caudate with practice. We tested the hypothesis that the contribution of these regions to learning changes with age because of differential age-related declines in the striatum and hippocampi. We assessed age-related differences in brain activation during implicit associative learning using the Triplets Learning Task. Over three event-related fMRI runs, 11 younger and 12 healthy older adults responded to only the third (target) stimulus in sequences of three stimuli ("triplets") by corresponding key press. Unbeknown to participants, the first stimulus' location predicted one target location for 80% of trials and another target location for 20% of trials. Both age groups learned associative regularities but differences in favor of the younger adults emerged with practice. The neural basis of learning (response to predictability) was examined by identifying regions that showed a greater response to triplets that occurred more frequently. Both age groups recruited the hippocampus early, but with training, the younger adults recruited their caudate whereas the older adults continued to rely on their hippocampus. This pattern enables older adults to maintain near-young levels of performance early in training, but not later, and adds to evidence that implicit associative learning is supported by different brain networks in younger and older adults.

Age differences in implicit learning of probabilistic unstructured sequences

OBJECTIVE

It is unclear whether implicit probabilistic learning, the acquisition of regularities without intent or explicit knowledge, declines with healthy aging.

METHODS

Because age differences in previous work might reflect motor or rule learning deficits, we used the implicit Triplets Learning Task with reduced motor sequencing and non-rule-based associations. Fifteen young and 15 old adults responded only to the last event in a series of discrete 3-event sequences or triplets. A randomly chosen set of triplets occurred with high frequency, so there was no underlying rule to be learned.

RESULTS

Both age groups learned associative regularities, but age differences in favor of the young emerged with practice. Discussion. Age differences may reflect the different neural regions that are involved as training progresses, which differ in the extent to which they are compromised by aging.

Dopamine transporter genotype predicts implicit sequence learning

Implicit learning, the non-conscious acquisition of sequential and spatial environmental regularities, underlies skills such as language, social intuition, or detecting a target in a complex scene. We examined relationships between a variation of the dopamine transporter (DAT1) gene (SLC6A3), which influences dopamine transporter expression in the striatum, and two forms of implicit learning that differ in the regularity to be learned and in striatal involvement. Participants, grouped as 9-repeat carriers or 10/10 homozygotes, completed the triplets learning task (TLT) and the spatial contextual cueing task (SCCT). The TLT assesses sequence learning, recruiting the striatal system, particularly as training continues. In contrast, the SCCT assesses spatial context learning, recruiting medial temporal brain networks. For both tasks, participants demonstrated learning in faster and/or more accurate responses to repeating patterns or spatial arrays. As predicted, TLT learning was greater for the 9-repeat carriers than the 10/10 group (despite equal overall accuracy and response speed) whereas there were no significant group differences in SCCT. Thus, presence of the DAT1 9-repeat allele was beneficial only for implicit sequence learning, indicating the influence of DAT1 genotype on one form of implicit learning and supporting evidence that implicit learning of sequential dependencies and spatial layouts recruit different neural systems.

Visuospatial sequence learning without seeing

BACKGROUND

The ability to detect and integrate associations between unrelated items that are close in space and time is a key feature of human learning and memory. Learning sequential associations between non-adjacent visual stimuli (higher-order visuospatial dependencies) can occur either with or without awareness (explicit vs. implicit learning) of the products of learning. Existing behavioural and neurocognitive studies of explicit and implicit sequence learning, however, are based on conscious access to the sequence of target locations and, typically, on conditions where the locations for orienting, or motor, responses coincide with the locations of the target sequence.

METHODOLOGY/PRINCIPAL FINDINGS

Dichoptic stimuli were presented on a novel sequence learning task using a mirror stereoscope to mask the eye-of-origin of visual input from conscious awareness. We demonstrate that conscious access to the sequence of target locations and responses that coincide with structure of the target sequence are dispensable features when learning higher-order visuospatial associations. Sequence knowledge was expressed in the ability of participants to identify the trained higher-order visuospatial sequence on a recognition test, even though the trained and untrained recognition sequences were identical when viewed at a conscious binocular level, and differed only at the level of the masked sequential associations.

CONCLUSIONS/SIGNIFICANCE

These results demonstrate that unconscious processing can support perceptual learning of higher-order sequential associations through interocular integration of retinotopic-based codes stemming from monocular eye-of-origin information. Furthermore, unlike other forms of perceptual associative learning, visuospatial attention did not need to be directed to the locations of the target sequence. More generally, the results pose a challenge to neural models of learning to account for a previously unknown capacity of the human visual system to support the detection, learning and recognition of higher-order sequential associations under conditions where observers are unable to see the target sequence or perform responses that coincide with structure of the target sequence.

Direct Associations or Internal Transformations? Exploring the Mechanisms Underlying Sequential Learning Behavior

We evaluate two broad classes of cognitive mechanisms that might support the learning of sequential patterns. According to the first, learning is based on the gradual accumulation of direct associations between events based on simple conditioning principles. The other view describes learning as the process of inducing the transformational structure that defines the material. Each of these learning mechanisms predict differences in the rate of acquisition for differently organized sequences. Across a set of empirical studies, we compare the predictions of each class of model with the behavior of human subjects. We find that learning mechanisms based on transformations of an internal state, such as recurrent network architectures (e.g., Elman, 1990), have difficulty accounting for the pattern of human results relative to a simpler (but more limited) learning mechanism based on learning direct associations. Our results suggest new constraints on the cognitive mechanisms supporting sequential learning behavior.

Visuospatial working memory capacity predicts the organization of acquired explicit motor sequences

Studies have suggested that cognitive processes such as working memory and temporal control contribute to motor sequence learning. These processes engage overlapping brain regions with sequence learning, but concrete evidence has been lacking. In this study, we determined whether limits in visuospatial working memory capacity and temporal control abilities affect the temporal organization of explicitly acquired motor sequences. Participants performed an explicit sequence learning task, a visuospatial working memory task, and a continuous tapping timing task. We found that visuospatial working memory capacity, but not the CV from the timing task, correlated with the rate of motor sequence learning and the chunking pattern observed in the learned sequence. These results show that individual differences in short-term visuospatial working memory capacity, but not temporal control, predict the temporal structure of explicitly acquired motor sequences.

Implicit learning of second-, third-, and fourth-order adjacent and nonadjacent sequential dependencies

Serial reaction time (SRT) task studies have established that people can implicitly learn first- and second-order adjacent dependencies. Sequential confounds have made it impossible to draw conclusions regarding learning of nonadjacent dependencies and learning of third- and fourth-order adjacent dependencies. Addressing the confounds, the present study shows that people can implicitly learn second-, third-, and fourth-order adjacent and nonadjacent dependencies embedded in probabilistic sequences of target locations.

Age-related differences in implicit learning of subtle third-order sequential structure

Age-related implicit learning deficits increase with sequence complexity, suggesting there might be limits to the level of structure that older adults can learn implicitly. To test for such limits, we had 12 younger and 12 older adults complete an alternating serial reaction time task containing subtle structure in which every third trial follows a repeating sequence and intervening trials are determined randomly. Results revealed significant age deficits in learning. However, both groups did learn the subtle regularity without explicit awareness, indicating that older adults remain sensitive to highly complex sequential regularities in their environment, albeit to a lesser degree than younger adults.