Explicit Sequence Research Articles

Severe publication bias contributes to illusory sleep consolidation in the motor sequence learning literature.

We explored the possibility of publication bias in the sleep and explicit motor sequence learning literature by applying precision effect test (PET) and precision effect test with standard errors (PEESE) weighted regression analyses to the 88 effect sizes from a recent comprehensive literature review (Pan & Rickard, 2015). Basic PET analysis indicated pronounced publication bias; that is, the effect sizes were strongly predicted by their standard error. When variables that have previously been shown to both moderate the sleep gain effect and substantially reduce unaccounted for effect size heterogeneity were included in that analysis, evidence for publication bias remained strong. The estimated postsleep gain was negative, suggesting forgetting rather than facilitation, and it was statistically indistinguishable from the estimated postwake gain. In a qualitative review of a smaller group of more recent studies we observed that (a) small sample sizes-a major factor behind the publication bias-are still the norm, (b) use of demonstrably flawed experimental design and analysis remains prevalent, and (c) when authors conclude in favor of sleep-dependent consolidation, they frequently do not cite the articles in which those methodological flaws have been demonstrated. We conclude that there is substantial publication bias, that there is no consolidation-based, absolute performance gain following sleep, and that strong conclusions regarding the hypothesis of less forgetting after sleep than after wakefulness should await further research. Recommendations are made for reducing publication bias in future work. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Dimer states of Rydberg atoms on the Kagome lattice as resources for universal measurement-based quantum computation

We show that the quantum dimer state on the Kagome lattice, which was recently realized with high fidelity in a Rydberg quantum simulator [G. Semeghini et al., Science 374, 6572 (2021)], offers a sufficient resource for universal measurement-based quantum computations. In particular, we provide an efficient encoding of logical qubits in this state and give explicit measurement sequences that implement a universal set of gates on these qubits. Since the building blocks of the proposed measurements have already been experimentally implemented, our work highlights one possible path toward promoting Rydberg simulators to universal quantum computers relying on the measurement-based model of quantum computation with currently existing technology.

How Can Talented Professionals Realizing the Gem 2.0 (Government Excellence Model) in UAE

The current study was launched as an attempt to determine the extent to which talented professionals understand the concept of GEM 2.0 and the standards associated with it, which including (Vision Realizing, Distinctive Value and Enablers). The current study adopted the quantitative approach in collecting primary data. The questionnaire was used as a research tool and was distributed to a sample of (233) talented professional employees within the fiscal year 2021-2022. By relying on SPSS, the study came to the conclusion that there is a high level realization of the concept of GEM 2.0 by talented professionals and that realization is attributed to the explicit and clear sequence of development of the model over time, in addition to the idea that the model took into account the differences and specializations in the nature of governmental services. Study recommended that talented professionals must pass the torch for younger talents to know their worth and employ themselves in the service of a country that will support them and present to them rare opportunities that can change their future to a better approach.

Raising the Roof in Cædmon's Hymn

Raising the Roof in <i>Cædmon's Hymn</i>

On the structure tensor of [formula omitted

The structure tensor of sln, denoted Tsln, is the tensor arising from the Lie bracket bilinear operation on the set of traceless n×n matrices over C. This tensor is intimately related to the well studied matrix multiplication tensor. Studying the structure tensor of sln may provide further insight into the complexity of matrix multiplication and the “hay in a haystack” problem of finding explicit sequences tensors with high rank or border rank. We aim to find new bounds on the rank and border rank of this structure tensor in the case of sl3 and sl4. We additionally provide bounds in the case of the lie algebras so4 and so5. The lower bounds on the border ranks were obtained via various recent techniques, namely Koszul flattenings, border substitution, and border apolarity. Upper bounds on the rank of Tsl3 are obtained via numerical methods that allowed us to find an explicit rank decomposition.

Optimizing Thermalization.

We present a rigorous approach, based on the concept of continuous thermomajorization, to algorithmically characterize the full set of energy occupations of a quantum system accessible from a given initial state through weak interactions with a heat bath. The algorithm can be deployed to solve complex optimization problems in out-of-equilibrium setups and it returns explicit elementary control sequences realizing optimal transformations. We illustrate this by finding optimal protocols in the context of cooling, work extraction, and catalysis. The same tools also allow one to quantitatively assess the role played by memory effects in the performance of thermodynamic protocols. We obtained exhaustive solutions on a laptop machine for systems with dimension d≤7, but with heuristic methods one could access much higher d.

Effective cerebello-cerebral connectivity during implicit and explicit social belief sequence learning using dynamic causal modeling.

To study social sequence learning, earlier functional magnetic resonance imaging (fMRI) studies investigated the neural correlates of a novel Belief Serial Reaction Time task in which participants learned sequences of beliefs held by protagonists. The results demonstrated the involvement of the mentalizing network in the posterior cerebellum and cerebral areas (e.g. temporoparietal junction, precuneus and temporal pole) during implicit and explicit social sequence learning. However, little is known about the neural functional interaction between these areas during this task. Dynamic causal modeling analyses for both implicit and explicit belief sequence learning revealed that the posterior cerebellar Crus I & II were effectively connected to cerebral mentalizing areas, especially the bilateral temporoparietal junction, via closed loops (i.e. bidirectional functional connections that initiate and terminate at the same cerebellar and cerebral areas). There were more closed loops during implicit than explicit learning, which may indicate that the posterior cerebellum may be more involved in implicitly learning sequential social information. Our analysis supports the general view that the posterior cerebellum receives incoming signals from critical mentalizing areas in the cerebrum to identify sequences of social actions and then sends signals back to the same cortical mentalizing areas to better prepare for others' social actions and one's responses to it.

Sequence space representations for spaces of smooth functions and distributions via Wilson bases

We provide explicit sequence space representations for the test function and distribution spaces occurring in the Valdivia-Vogt structure tables by making use of Wilson bases generated by compactly supported smooth windows. Furthermore, we show that these kind of bases are common unconditional Schauder bases for all separable spaces occurring in these tables. Our work implies that the Valdivia-Vogt structure tables for test functions and distributions may be interpreted as one large commutative diagram.

New techniques for bounding stabilizer rank

In this work, we present number-theoretic and algebraic-geometric techniques for bounding the stabilizer rank of quantum states. First, we refine a number-theoretic theorem of Moulton to exhibit an explicit sequence of product states with exponential stabilizer rank but constant approximate stabilizer rank, and to provide alternate (and simplified) proofs of the best-known asymptotic lower bounds on stabilizer rank and approximate stabilizer rank, up to a log factor. Second, we find the first non-trivial examples of quantum states with multiplicative stabilizer rank under the tensor product. Third, we introduce and study the generic stabilizer rank using algebraic-geometric techniques.

Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition

Sequence learning in serial reaction time tasks (SRTTs) is usually inferred through the reaction time measured by a keyboard. However, this chronometric parameter offers no information beyond the time point of the button-press. We therefore examined whether sequence learning can be measured by muscle activations via electromyography (EMG) in a dual-task paradigm. The primary task was a SRTT, in which the stimuli followed a fixed sequence in some blocks, whereas the sequence was random in the control condition. The secondary task stimulus was always random. One group was informed about the fixed sequence, and the other not. We assessed three dependent variables. The chronometric parameter premotor time represents the duration between stimulus onset and the onset of EMG activity, which indicates the start of the response. The other variables describe the response itself considering the EMG activity after response start. The EMG integral was analyzed, and additionally, tensor decomposition was implemented to assess sequence dependent changes in the contribution of the obtained subcomponents. The results show explicit sequence learning in this dual-task setting. Specifically, the informed group show shorter premotor times in fixed than random sequences as well as larger EMG integral and tensor contributions. Further, increased activity seems to represent response certainty, since a decrease is found for both groups in trials following erroneous responses. Interestingly, the sensitivity to sequence and post-error effects varies between the subcomponents. The results indicate that muscle activity can be a useful indicator of response behavior in addition to chronometric parameters.

Constructive Exact Control of Semilinear 1D Wave Equations by a Least-Squares Approach

It has been proved by Zuazua in the nineties that the internally controlled semilinear 1D wave equation $\partial_{tt}y-\partial_{xx}y + g(y)=f 1_{\omega}$, with Dirichlet boundary conditions, is exactly controllable in $H^1_0(0,1)\cap L^2(0,1)$ with controls $f\in L^2((0,1)\times(0,T))$, for any $T>0$ and any nonempty open subset $\omega$ of (0,1), assuming that $g\in \mathcal{C}^1(\mathbb{R})$ does not grow faster than $\beta\vert x\vert \ln^{2}\vert x\vert$ at infinity for some $\beta>0$ small enough. The proof, based on the Leray--Schauder fixed point theorem, is, however, not constructive. In this article, we design a constructive proof and algorithm for the exact controllability of semilinear 1D wave equations. Assuming that $g^\prime$ does not grow faster than $\beta \ln^{2}\vert x\vert$ at infinity for some $\beta>0$ small enough and that $g^\prime$ is uniformly Hölder continuous on $\mathbb{R}$ with exponent $s\in[0,1]$, we design a least-squares algorithm yielding an explicit sequence converging to a controlled solution for the semilinear equation, at least with order $1+s$ after a finite number of iterations.

Anodal Transcranial Direct Current Stimulation Over Prefrontal Cortex Slows Sequence Learning in Older Adults.

Aging is associated with declines in sensorimotor function. Several studies have demonstrated that transcranial direct current stimulation (tDCS), a form of non-invasive brain stimulation, can be combined with training to mitigate age-related cognitive and motor declines. However, in some cases, the application of tDCS disrupts performance and learning. Here, we applied anodal tDCS either over the left prefrontal cortex (PFC), right PFC, supplementary motor complex (SMC), the left M1, or in a sham condition while older adults (n = 63) practiced a Discrete Sequence Production (DSP), an explicit motor sequence, task across 3 days. We hypothesized that stimulation to either the right or left PFC would enhance motor learning for older adults, based on the extensive literature showing increased prefrontal cortical activity during motor task performance in older adults. Contrary to our predictions, stimulation to the right and left PFC resulted in slowed motor learning, as evidenced by a slower reduction rate of reduction of reaction time and the number of sequence chunks across trials relative to sham in session one and session two, respectively. These findings suggest an integral role of the right PFC early in sequence learning and a role of the left PFC in chunking in older adults, and contribute to mounting evidence of the difficultly of using tDCS in an aging population.

Explicit commutative sequence space representations of function and distribution spaces on the real half-line

We provide explicit commutative sequence space representations for classical function and distribution spaces on the real half-line. This is done by evaluating at the Fourier transforms of the elements of an orthonormal wavelet basis.

How does the length of short rest periods affect implicit probabilistic learning?

Memory consolidation has been mainly investigated for extended periods, from hours to days. Recent studies focused on memory consolidation occurring within shorter periods, from seconds to minutes. Yet, these studies focused on explicit sequence learning with fixed rest periods. Our study aimed at determining whether short rest periods enhance implicit probabilistic sequence learning and whether the length of rest duration influences such offline changes. Participants performed an implicit probabilistic sequence learning task throughout 45 blocks. Between blocks, participants were allowed to rest and then to continue the task at their pace. The results show that probabilistic sequence knowledge decreased from pre-to post-rest periods, and this decrement was not related to the length of rest duration. These results suggest that probabilistic sequence knowledge decays during short rest periods and that such forgetting is not time-dependent. Overall, our findings highlight that ultra-fast consolidation differently affects distinct cognitive processes.

Habitual or hyper-controlled behavior: OCD symptoms and explicit sequence learning

Background and objectivesThis study examined whether ritualistic behaviors characteristic of obsessive-compulsive disorder (OCD) are a product of dysfunctional goal-directed behavior leading to habitual behavior (Gillan & Robbins, 2014). We used an explicit motor sequence learning task to investigate the repetition of chunked action sequences across the OC spectrum. As sequential motor behavior is practiced, action movements appear to get bundled together, and the initial movement of the sequence activates the entire sequence, leaving it relatively insensitive to change. Therefore, compulsive behavior in OCD may be a result of failing to inhibit the full activation of an extensively learned action sequence. Methods: Fifty-seven participants across the range of OCD symptoms practiced one sequence and then tested on a novel sequence in which one of the middle movements was omitted. Optimal performance for the new sequence required goal-directed inhibition of the original sequence and goal-directed execution of the new sequence instead. To manipulate activation of goal-directed behavior, we added a dual-task condition with a competing auditory tonal N-Back task. Data were analyzed using mixed-effects models. Results: Although we did observe expected learning patterns during learning of the original sequence, slower reaction times for the new sequences, and higher errors in the dual-task condition, performance was not significantly related to either obsessive-compulsive symptoms or distress symptoms. Limitations: The current study used an analog sample; replication in a treatment seeking sample is warranted. Conclusions: These findings challenge the goal-directed dysfunction model of OCD.

Molecularly Engineered Aptamers Targeting Tumor Tissue and Cancer Cells for Efficient in Vivo Recognition and Enrichment

Molecularly Engineered Aptamers Targeting Tumor Tissue and Cancer Cells for Efficient in Vivo Recognition and Enrichment

Offline low-frequency rTMS of the primary and premotor cortices does not impact motor sequence memory consolidation despite modulation of corticospinal excitability

Motor skills are acquired and refined across alternating phases of practice (online) and subsequent consolidation in the absence of further skill execution (offline). Both stages of learning are sustained by dynamic interactions within a widespread motor learning network including the premotor and primary motor cortices. Here, we aimed to investigate the role of the dorsal premotor cortex (dPMC) and its interaction with the primary motor cortex (M1) during motor memory consolidation. Forty-eight healthy human participants (age 22.1 ± 3.1 years) were assigned to three different groups corresponding to either low-frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) of left dPMC, rTMS of left M1, or sham rTMS. rTMS was applied immediately after explicit motor sequence training with the right hand. Motor evoked potentials were recorded before training and after rTMS to assess potential stimulation-induced changes in corticospinal excitability (CSE). Participants were retested on motor sequence performance after eight hours to assess consolidation. While rTMS of dPMC significantly increased CSE and rTMS of M1 significantly decreased CSE, no CSE modulation was induced by sham rTMS. However, all groups demonstrated similar significant offline learning indicating that consolidation was not modulated by the post-training low-frequency rTMS intervention despite evidence of an interaction of dPMC and M1 at the level of CSE. Motor memory consolidation ensuing explicit motor sequence training seems to be a rather robust process that is not affected by low-frequency rTMS-induced perturbations of dPMC or M1. Findings further indicate that consolidation of explicitly acquired motor skills is neither mediated nor reflected by post-training CSE.

Existence and uniqueness of positive solutions for fractional relaxation equation in terms of ψ-Caputo fractional derivative

Abstract This manuscript is committed to deal with the existence and uniqueness of positive solutions for fractional relaxation equation involving ψ-Caputo fractional derivative. The existence of solution is carried out with the help of Schauder’s fixed point theorem, while the uniqueness of the solution is obtained by applying the Banach contraction principle, along with Bielecki type norm. Moreover, two explicit monotone iterative sequences are constructed for the approximation of the extreme positive solutions to the proposed problem. Lastly, two examples are presented to support the obtained results.

The exact upper bound for the sum of reciprocals of least common multiples

Let r be a positive number with r≥2 and let A={ai}i=1∞ be an arbitrarily given strictly increasing sequence of positive integers. Let SrA:=∑i=1∞1[ai,ai+1,⋯,ai+r−1]. In 1978, Borwein obtained S2A≤1 with equality occurring if and only if ai=2i−1 for i≥1. Qian and Zhao et al. obtained exact upper bounds for SrA as 3≤r≤7 and 8≤r≤11 respectively in 2017 and 2019. In this paper, we give several methods to obtain the upper bounds for S12A and S13A with explicit sequences which reach the corresponding upper bounds. We propose a conjecture that the exact upper bounds for SrA are τ(h)−r+2h for all r≥2, where h is a highly composite number and τ(h) denotes the number of divisors of h. In addition, we offer some sequences that reach the exact upper bounds.

Single session transcranial direct current stimulation to the primary motor cortex fails to enhance early motor sequence learning in Parkinson’s disease

IntroductionExplicit motor sequence learning is impaired in Parkinson’s disease (PD). Transcranial direct current stimulation (tDCS) applied over the motor cortex in healthy can improve explicit motor learning, but comparative effects in PD are unknown. This exploratory study aims to examine the effect of single session tDCS on explicit motor sequence learning in PD. MethodsThirty-three people with mild to moderate PD learnt a short and long finger tapping sequence with their right hand. Participants received either anodal, cathodal, or sham tDCS applied over the left primary motor cortex during task practice. Single- and dual-task finger tapping performance was assessed before and after task practice and functional near-infrared spectroscopy used to measure task related changes of oxygenated haemoglobin. ResultsFinger tapping performance of short and long sequences under single-task conditions significantly improved following practice (p = 0.010 and p < 0.001, respectively). A condition-by-time interaction trend was observed for the long finger tapping sequence (p = 0.069) driven by improved performance in the cathodal (p = 0.001) and sham (p < 0.001) tDCS conditions, but not anodal tDCS (p = 0.198). The primary and premotor cortex and supplementary motor area were active in all tasks. No interaction or main effects were observed for task related changes of oxygenated haemoglobin. ConclusionsPD patients retain the capacity to learn an explicit sequence of movements. Motor cortex tDCS does not improve explicit motor learning in PD and anodal tDCS may even suppress the rate of learning.