Who Learns More? Cultural Differences in Implicit Sequence Learning

Background

It is well documented that East Asians differ from Westerners in conscious perception and attention. However, few studies have explored cultural differences in unconscious processes such as implicit learning.

Methodology/Principal Findings

The global-local Navon letters were adopted in the serial reaction time (SRT) task, during which Chinese and British participants were instructed to respond to global or local letters, to investigate whether culture influences what people acquire in implicit sequence learning. Our results showed that from the beginning British expressed a greater local bias in perception than Chinese, confirming a cultural difference in perception. Further, over extended exposure, the Chinese learned the target regularity better than the British when the targets were global, indicating a global advantage for Chinese in implicit learning. Moreover, Chinese participants acquired greater unconscious knowledge of an irrelevant regularity than British participants, indicating that the Chinese were more sensitive to contextual regularities than the British.

Conclusions/Significance

The results suggest that cultural biases can profoundly influence both what people consciously perceive and unconsciously learn.     

Do Implicit Attitudes Predict Actual Voting Behavior Particularly for Undecided Voters?

The prediction of voting behavior of undecided voters poses a challenge to psychologists and pollsters. Recently, researchers argued that implicit attitudes would predict voting behavior particularly for undecided voters whereas explicit attitudes would predict voting behavior particularly for decided voters. We tested this assumption in two studies in two countries with distinct political systems in the context of real political elections. Results revealed that (a) explicit attitudes predicted voting behavior better than implicit attitudes for both decided and undecided voters, and (b) implicit attitudes predicted voting behavior better for decided than undecided voters. We propose that greater elaboration of attitudes produces stronger convergence between implicit and explicit attitudes resulting in better predictive validity of both, and less incremental validity of implicit over explicit attitudes for the prediction of voting behavior. However, greater incremental predictive validity of implicit over explicit attitudes may be associated with less elaboration.     

Sleep-Effects on Implicit and Explicit Memory in Repeated Visual Search

In repeated visual search tasks, facilitation of reaction times (RTs) due to repetition of the spatial arrangement of items occurs independently of RT facilitation due to improvements in general task performance. Whereas the latter represents typical procedural learning, the former is a kind of implicit memory that depends on the medial temporal lobe (MTL) memory system and is impaired in patients with amnesia. A third type of memory that develops during visual search is the observers’ explicit knowledge of repeated displays. Here, we used a visual search task to investigate whether procedural memory, implicit contextual cueing, and explicit knowledge of repeated configurations, which all arise independently from the same set of stimuli, are influenced by sleep. Observers participated in two experimental sessions, separated by either a nap or a controlled rest period. In each of the two sessions, they performed a visual search task in combination with an explicit recognition task. We found that (1) across sessions, MTL-independent procedural learning was more pronounced for the nap than rest group. This confirms earlier findings, albeit from different motor and perceptual tasks, showing that procedural memory can benefit from sleep. (2) Likewise, the sleep group compared with the rest group showed enhanced context-dependent configural learning in the second session. This is a novel finding, indicating that the MTL-dependent, implicit memory underlying contextual cueing is also sleep-dependent. (3) By contrast, sleep and wake groups displayed equivalent improvements in explicit recognition memory in the second session. Overall, the current study shows that sleep affects MTL-dependent as well as MTL-independent memory, but it affects different, albeit simultaneously acquired, forms of MTL-dependent memory differentially.     

Negative Affect Reduces Performance in Implicit Sequence Learning

Background

It is well documented that positive rather than negative moods encourage integrative processing of conscious information. However, the extent to which implicit or unconscious learning can be influenced by affective states remains unclear.

Methodology/Principal Findings

A Serial Reaction Time (SRT) task with sequence structures requiring integration over past trials was adopted to examine the effect of affective states on implicit learning. Music was used to induce and maintain positive and negative affective states. The present study showed that participants in negative rather than positive states learned less of the regularity. Moreover, the knowledge was shown by a Bayesian analysis to be largely unconscious as participants were poor at recognizing the regularity.

Conclusions/Significance

The results demonstrated that negative rather than positive affect inhibited implicit learning of complex structures. Our findings help to understand the effects of affective states on unconscious or implicit processing.     

Awareness modifies the skill-learning benefits of sleep

Behind every skilled movement lies months of practice. However, practice alone is not responsible for the acquisition of all skill; performance can improve between, not just within, practice sessions. An important principle shaping these offline improvements may be an individual's awareness of learning a new skill. New skills, such as a sequence of finger movements, can be learned unintentionally (with little awareness for the sequence, implicit learning) or intentionally (explicit learning). We measured skill in an implicit and explicit sequence-learning task before and after a 12 hr interval. This interval either did (8 p.m. to 8 a.m.) or did not (8 a.m. to 8 p.m.) include a period of sleep. Following explicit sequence learning, offline skill improvements were only observed when the 12 hr interval included sleep. This overnight improvement was correlated with the amount of NREM sleep. The same improvement could also be observed in the evening (with an interval from 8 p.m. to 8 p.m.), so it was not coupled to retesting at a particular time of day and cannot therefore be attributed to circadian factors. In contrast, in the implicit learning task, offline learning was observed regardless of whether the 12 hr interval did or did not contain a period of sleep. However, these improvements were not observed with only a 15 min interval between sessions. Therefore, the practice available within each session cannot account for these skill improvements. Instead, sufficient time is necessary for offline learning to occur. These results show a behavioral dissociation, based upon an individual's awareness for having learned a sequence of finger movements. Offline learning is sleep dependent for explicit skills but time dependent for implicit skills.     

Decisions among the Undecided: Implicit Attitudes Predict Future Voting Behavior of Undecided Voters

Implicit attitudes have been suggested as a key to unlock the hidden preferences of undecided voters. Past research, however, offered mixed support for this hypothesis. The present research used a large nationally representative sample and a longitudinal design to examine the predictive utility of implicit and explicit attitude measures in the 2008 U.S. presidential election. In our analyses, explicit attitudes toward candidates predicted voting better for decided than undecided voters, but implicit candidate attitudes were predictive of voting for both decided and undecided voters. Extending our examination to implicit and explicit racial attitudes, we found the same pattern. Taken together, these results provide convergent evidence that implicit attitudes predict voting about as well for undecided as for decided voters. We also assessed a novel explanation for these effects by evaluating whether implicit attitudes may predict the choices of undecided voters, in part, because they are neglected when people introspect about their confidence. Consistent with this idea, we found that the extremity of explicit but not implicit attitudes was associated with greater confidence. These analyses shed new light on the utility of implicit measures in predicting future behavior among individuals who feel undecided. Considering the prior studies together with this new evidence, the data seem to be consistent that implicit attitudes may be successful in predicting the behavior of undecided voters.     

Sleep-dependent consolidation of contextual learning

Memory consolidation is facilitated by sleep. Specifying the functional domain of sleep-dependent consolidation (SDC) is important for identifying the neural mechanisms underlying this phenomenon. Previous work indicates that SDC may be limited to conditions in which learning is explicit. In the present study, we tested the hypothesis that SDC may also occur with implicit learning when learning benefits from the formation of contextual associations, a function associated with the hippocampus. Three versions of the serial-reaction-time task (SRTT) were examined, and SDC was assessed by comparing performance after 12 hr breaks that included or did not include sleep. SDC was observed in the Explicit condition. Two implicit conditions were compared. In the Implicit Noncontextual condition, participants performed a concurrent tone-counting task with the pitch of each tone selected at random, precluding cross-dimensional associations. In the Implicit Contextual condition, participants responded to the color of the cues while the spatial location of the cues followed a correlated sequence. Whereas learning was observed in both implicit conditions, SDC was restricted to the contextual condition. Given that the formation of contextual associations is dependent on the hippocampus, we suggest that SDC is a hippocampus-mediated process.     

Brain networks of explicit and implicit learning

Are explicit versus implicit learning mechanisms reflected in the brain as distinct neural structures, as previous research indicates, or are they distinguished by brain networks that involve overlapping systems with differential connectivity? In this functional MRI study we examined the neural correlates of explicit and implicit learning of artificial grammar sequences. Using effective connectivity analyses we found that brain networks of different connectivity underlie the two types of learning: while both processes involve activation in a set of cortical and subcortical structures, explicit learners engage a network that uses the insula as a key mediator whereas implicit learners evoke a direct frontal-striatal network. Individual differences in working memory also differentially impact the two types of sequence learning.     

Comparison of sequence masking algorithms and the detection of biased protein sequence regions

MOTIVATION: Separation of protein sequence regions according to their local information complexity and subsequent masking of low complexity regions has greatly enhanced the reliability of function prediction by sequence similarity. Comparisons with alternative methods that focus on compositional sequence bias rather than information complexity measures have shown that removal of compositional bias yields at least as sensitive and much more specific results. Besides the application of sequence masking algorithms to sequence similarity searches, the study of the masked regions themselves is of great interest. Traditionally, however, these have been neglected despite evidence of their functional relevance. RESULTS: Here we demonstrate that compositional bias seems to be a more effective measure for the detection of biologically meaningful signals. Typical results on proteins are compared to results for sequences that have been randomized in various ways, conserving composition and local correlations for individual proteins or the entire set. It is remarkable that low-complexity regions have the same form of distribution in proteins as in randomized sequences, and that the signal from randomized sequences with conserved local correlations and amino acid composition almost matches the signal from proteins. This is not the case for sequence bias, which hence seems to be a genuinely biological phenomenon in contrast to patches of low complexity.     

Use of a structural alphabet to find compatible folds for amino acid sequences

The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence‐search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino‐acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as “Protein Blocks” (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence‐search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z‐score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales‐up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web‐server that is freely available at http://www.bo‐protscience.fr/forsa .     

Cerebellum,temporal predictability and the updating of a mental model

We live in a dynamic and changing environment, which necessitates that we adapt to and efficiently respond to changes of stimulus form (‘what’) and stimulus occurrence (‘when’). Consequently, behaviour is optimal when we can anticipate both the ‘what’ and ‘when’ dimensions of a stimulus. For example, to perceive a temporally expected stimulus, a listener needs to establish a fairly precise internal representation of its external temporal structure, a function ascribed to classical sensorimotor areas such as the cerebellum. Here we investigated how patients with cerebellar lesions and healthy matched controls exploit temporal regularity during auditory deviance processing. We expected modulations of the N2b and P3b components of the event-related potential in response to deviant tones, and also a stronger P3b response when deviant tones are embedded in temporally regular compared to irregular tone sequences. We further tested to what degree structural damage to the cerebellar temporal processing system affects the N2b and P3b responses associated with voluntary attention to change detection and the predictive adaptation of a mental model of the environment, respectively. Results revealed that healthy controls and cerebellar patients display an increased N2b response to deviant tones independent of temporal context. However, while healthy controls showed the expected enhanced P3b response to deviant tones in temporally regular sequences, the P3b response in cerebellar patients was significantly smaller in these sequences. The current data provide evidence that structural damage to the cerebellum affects the predictive adaptation to the temporal structure of events and the updating of a mental model of the environment under voluntary attention.     

Protein Design by Sampling an Undirected Graphical Model of Residue Constraints

This paper develops an approach for designing protein variants by sampling sequences that satisfy residue constraints encoded in an undirected probabilistic graphical model. Due to evolutionary pressures on proteins to maintain structure and function, the sequence record of a protein family contains valuable information regarding position-specific residue conservation and coupling (or covariation) constraints. Representing these constraints with a graphical model provides two key benefits for protein design: a probabilistic semantics enabling evaluation of possible sequences for consistency with the constraints, and an explicit factorization of residue dependence and independence supporting efficient exploration of the constrained sequence space. We leverage these benefits in developing two complementary MCMC algorithms for protein design: constrained shuffling mixes wild-type sequences positionwise and evaluates graphical model likelihood, while component sampling directly generates sequences by sampling clique values and propagating to other cliques. We apply our methods to design WW domains. We demonstrate that likelihood under a model of wild-type WWs is highly predictive of foldedness of new WWs. We then show both theoretical and rapid empirical convergence of our algorithms in generating high-likelihood, diverse new sequences. We further show that these sequences capture the original sequence constraints, yielding a model as predictive of foldedness as the original one.     

An FMRI study of the role of the medial temporal lobe in implicit and explicit sequence learning

fMRI was used to investigate the neural substrates supporting implicit and explicit sequence learning, focusing especially upon the role of the medial temporal lobe. Participants performed a serial reaction time task (SRTT). For implicit learning, they were naive about a repeating pattern, whereas for explicit learning, participants memorized another repeating sequence. fMRI analyses comparing repeating versus random sequence blocks demonstrated activation of frontal, parietal, cingulate, and striatal regions implicated in previous SRTT studies. Importantly, mediotemporal lobe regions were active in both explicit and implicit SRTT learning. Moreover, the results provide evidence of a role for the hippocampus and related cortices in the formation of higher order associations under both implicit and explicit learning conditions, regardless of conscious awareness of sequence knowledge.     

What are the determinants of explicit and implicit motor imagery ability in stroke patients?: a controlled study

Abstract

Purpose: The purposes of the study were to (a) investigate both explicit and implicit motor imagery ability (MIA) impairment after stroke, (b) examine predictive effects of clinical characteristics for MIA after stroke.

Materials and Methods: Forty one patients with stroke (PwS) (mean age 59.41?±?10.19?years; %41 female) and 36 healthy participants (mean age 62.47?±?9.29?years; %47 female) completed Chaotic Motor Imagery Assessment-Hand Rotation for implicit MIA and Movement Imagery Questionnaire-3 (MIQ-3) and Box and Block Test (BBT) for explicit MIA. The severity of motor and sensory impairments were determined by the Fugl-Meyer Assessment-Upper Extremity (FMAUE) scores. The Turkish version of Motor Activity Log-28 was used to assess amount of use (AUS) and quality of movement in daily life.

Results: Our results indicated that both implicit and explicit MIA (except kinaesthetic imagery of MIQ-3) in PwS were statistically impaired compared to controls (p?<?0.05). The sensorimotor impairment level, amount of use and movement quality of the affected upper limb were found to be correlated with MIA in various degrees. Total motor scores in FMAUE and AUS were significant predictors of explicit MIA (p?<?0.01). Additionally, explicit MIA scores of stroke subgroups were statistically different between severely and mildly impaired patients, in favour of mildly impaired group (p?<?0.05).

Conclusion: In conclusion, both motor impairment level and amount of daily use of upper extremity were found to be predictive factors for explicit MIA. Further investigation with brain imaging techniques is needed to explore the validity of these findings in establishing MIA.     

Dissociation of Neural Substrates of Response Inhibition to Negative Information between Implicit and Explicit Facial Go/Nogo Tasks: Evidence from an Electrophysiological Study

Background

Although ample evidence suggests that emotion and response inhibition are interrelated at the behavioral and neural levels, neural substrates of response inhibition to negative facial information remain unclear. Thus we used event-related potential (ERP) methods to explore the effects of explicit and implicit facial expression processing in response inhibition.

Methods

We used implicit (gender categorization) and explicit emotional Go/Nogo tasks (emotion categorization) in which neutral and sad faces were presented. Electrophysiological markers at the scalp and the voxel level were analyzed during the two tasks.

Results

We detected a task, emotion and trial type interaction effect in the Nogo-P3 stage. Larger Nogo-P3 amplitudes during sad conditions versus neutral conditions were detected with explicit tasks. However, the amplitude differences between the two conditions were not significant for implicit tasks. Source analyses on P3 component revealed that right inferior frontal junction (rIFJ) was involved during this stage. The current source density (CSD) of rIFJ was higher with sad conditions compared to neutral conditions for explicit tasks, rather than for implicit tasks.

Conclusions

The findings indicated that response inhibition was modulated by sad facial information at the action inhibition stage when facial expressions were processed explicitly rather than implicitly. The rIFJ may be a key brain region in emotion regulation.     

Voting Intention and Choices: Are Voters Always Rational and Deliberative?

Human rationality–the ability to behave in order to maximize the achievement of their presumed goals (i.e., their optimal choices)–is the foundation for democracy. Research evidence has suggested that voters may not make decisions after exhaustively processing relevant information; instead, our decision-making capacity may be restricted by our own biases and the environment. In this paper, we investigate the extent to which humans in a democratic society can be rational when making decisions in a serious, complex situation–voting in a local political election. We believe examining human rationality in a political election is important, because a well-functioning democracy rests largely upon the rational choices of individual voters. Previous research has shown that explicit political attitudes predict voting intention and choices (i.e., actual votes) in democratic societies, indicating that people are able to reason comprehensively when making voting decisions. Other work, though, has demonstrated that the attitudes of which we may not be aware, such as our implicit (e.g., subconscious) preferences, can predict voting choices, which may question the well-functioning democracy. In this study, we systematically examined predictors on voting intention and choices in the 2014 mayoral election in Taipei, Taiwan. Results indicate that explicit political party preferences had the largest impact on voting intention and choices. Moreover, implicit political party preferences interacted with explicit political party preferences in accounting for voting intention, and in turn predicted voting choices. Ethnic identity and perceived voting intention of significant others were found to predict voting choices, but not voting intention. In sum, to the comfort of democracy, voters appeared to engage mainly explicit, controlled processes in making their decisions; but findings on ethnic identity and perceived voting intention of significant others may suggest otherwise.     

Implicit, predictive timing draws upon the same scalar representation of time as explicit timing

It is not yet known whether the scalar properties of explicit timing are also displayed by more implicit, predictive forms of timing. We investigated whether performance in both explicit and predictive timing tasks conformed to the two psychophysical properties of scalar timing: the Psychophysical law and Weber's law. Our explicit temporal generalization task required overt estimation of the duration of an empty interval bounded by visual markers, whereas our temporal expectancy task presented visual stimuli at temporally predictable intervals, which facilitated motor preparation thus speeding target detection. The Psychophysical Law and Weber's Law were modeled, respectively, by (1) the functional dependence between mean subjective time and real time (2) the linearity of the relationship between timing variability and duration. Results showed that performance for predictive, as well as explicit, timing conformed to both psychophysical properties of interval timing. Both tasks showed the same linear relationship between subjective and real time, demonstrating that the same representational mechanism is engaged whether it is transferred into an overt estimate of duration or used to optimise sensorimotor behavior. Moreover, variability increased with increasing duration during both tasks, consistent with a scalar representation of time in both predictive and explicit timing. However, timing variability was greater during predictive timing, at least for durations greater than 200 msec, and ascribable to temporal, rather than non-temporal, mechanisms engaged by the task. These results suggest that although the same internal representation of time was used in both tasks, its external manifestation varied as a function of temporal task goals.     

Fine Sampling of Sequence Space for Membrane Protein Structural Biology

We describe an enhancement of traditional genomics-based approaches to improve the success of structure determination of membrane proteins. Following a broad screen of sequence space to identify initial expression-positive targets, we employ a second step to select orthologs with closely related sequences to these hits. We demonstrate that a greater percentage of these latter targets express well and are stable in detergent, increasing the likelihood of identifying candidates that will ultimately yield structural information.