The causal role of DLPFC top-down control on the acquisition and the automatic expression of implicit learning: State of the art

Implicit Motor Learning Under Anodal or Cathodal tDCS During fMRI Induces Partially Distinct Network Responses

How anodal transcranial direct current stimulation (atDCS) and cathodal tDCS (ctDCS) affect brain networks is still unclear. Previous fMRI studies have yielded controversial results regarding the effects of atDCS and ctDCS on fMRI activation. The present study hypothesizes that the choice of fMRI paradigm may be a contributing factor to this divergence. Therefore, the present study employed two distinct fMRI paradigms, characterized by varying degrees of complexity: finger tapping as a simple fMRI paradigm and an implicit serial reaction time task (SRTT) as a more challenging paradigm. Seventy-five healthy subjects were randomized to receive either atDCS, ctDCS, or sham stimulation during fMRI. The main effects of the blood oxygenation level-dependent (BOLD) signal were contrasted between groups. SRTT, but not FT, was capable of eliciting differences in modulatory effects on the network between groups. Analysis of functional connectivity between ROIs showed that atDCS and ctDCS shared common and distinct SRTT networks. Correlations between BOLD signal (in ROIs) and the reaction time (RT) recorded during fMRI showed that in the atDCS group, faster RT was associated with higher BOLD signal in the most ROIs, while in the ctDCS group, faster RT was mostly associated with lower BOLD signal activity. The sham group exhibited a combination of these associations. We suggest that atDCS accelerates RT by "pushing" the network, while the network response under ctDCS was a "compensatory" response. The polarity of tDCS differentially modulated the adaptive plasticity of remotely connected regions, based on the concept of functional organization of distributed segregated networks.

Role of the dorsolateral prefrontal cortex in processing temporal anomalies retained in working memory

Introduction

Time is a crucial abstract construct, allowing us to perceive the duration of events. Working memory (WM) plays an important role in manipulating and storing the different features of environmental stimuli, including temporal features. Different brain structures, including the dorsolateral prefrontal cortex, are involved in time processing.

Methods

Here we investigated the functional aspects of time processing by using functional near-infrared spectroscopy (fNIRS) to assess changes in DLPFC activity. A modified version of the "Times Squares Sequences" (TSS) task was used, in which participants are required to match sequences of squares that have fixed or variable durations.

Results

Findings showed that the DLPFC activates when information necessary for later comparison needs to be maintained online, as is common in visuo-spatial WM tasks. Importantly, the DLPFC deactivates when a temporal anomaly is detected.

Discussion

This deactivation occurs because the temporal anomaly does not require ongoing maintenance for later comparison, thus demanding fewer cognitive resources from the DLPFC. This seemingly counterintuitive effect can be attributed to the temporal aspects being irrelevant to the primary task goals. This finding highlights the crucial role of implicit temporal interference and establishes a strong connection between timing and executive cognitive processes.

The Domain-Specific Neural Basis of Auditory Statistical Learning in 5-7-Year-Old Children

Statistical learning (SL) is the ability to rapidly track statistical regularities and learn patterns in the environment. Recent studies show that SL is constrained by domain-specific features, rather than being a uniform learning mechanism across domains and modalities. This domain-specificity has been reflected at the neural level, as SL occurs in regions primarily involved in processing of specific modalities or domains of input. However, our understanding of how SL is constrained by domain-specific features in the developing brain is severely lacking. The present study aims to identify the functional neural profiles of auditory SL of linguistic and nonlinguistic regularities among children. Thirty children between 5 and 7 years old completed an auditory fMRI SL task containing interwoven sequences of structured and random syllable/tone sequences. Using traditional group univariate analyses and a group-constrained subject-specific analysis, frontal and temporal cortices showed significant activation when processing structured versus random sequences across both linguistic and nonlinguistic domains. However, conjunction analyses failed to identify overlapping neural indices across domains. These findings are the first to compare brain regions supporting SL of linguistic and nonlinguistic regularities in the developing brain and indicate that auditory SL among developing children may be constrained by domain-specific features.

Theta Signal Transfer from Parietal to Prefrontal Cortex Ignites Conscious Awareness of Implicit Knowledge during Sequence Learning

Unconscious acquisition of sequence structure from experienced events can lead to explicit awareness of the pattern through extended practice. Although the implicit-to-explicit transition has been extensively studied in humans using the serial reaction time (SRT) task, the subtle neural activity supporting this transition remains unclear. Here, we investigated whether frequency-specific neural signal transfer contributes to this transition. A total of 208 participants (107 females) learned a sequence pattern through a multisession SRT task, allowing us to observe the transitions. Session-by-session measures of participants' awareness for sequence knowledge were conducted during the SRT task to identify the session when the transition occurred. By analyzing time course RT data using switchpoint modeling, we identified an increase in learning benefit specifically at the transition session. Electroencephalogram (EEG)/magnetoencephalogram (MEG) recordings revealed increased theta power in parietal (precuneus) regions one session before the transition (pretransition) and a prefrontal (superior frontal gyrus; SFG) one at the transition session. Phase transfer entropy (PTE) analysis confirmed that directional theta transfer from precuneus → SFG occurred at the pretransition session and its strength positively predicted learning improvement at the subsequent transition session. Furthermore, repetitive transcranial magnetic stimulation (TMS) modulated precuneus theta power and altered transfer strength from precuneus to SFG, resulting in changes in both transition rate and learning benefit at that specific point of transition. Our brain-stimulation evidence supports a role for parietal → prefrontal theta signal transfer in igniting conscious awareness of implicitly acquired knowledge.SIGNIFICANCE STATEMENT There exists a pervasive phenomenon wherein individuals unconsciously acquire sequence patterns from their environment, gradually becoming aware of the underlying regularities through repeated practice. While previous studies have established the robustness of this implicit-to-explicit transition in humans, the refined neural mechanisms facilitating conscious access to implicit knowledge remain poorly understood. Here, we demonstrate that prefrontal activity, known to be crucial for conscious awareness, is triggered by neural signal transfer originating from the posterior brain region, specifically the precuneus. By employing brain stimulation techniques, we establish a causal link between neural signal transfer and the occurrence of awareness. Our findings unveil a mechanism by which implicit knowledge becomes consciously accessible in human cognition.

Neural connectome features of procrastination: Current progress and future direction

Procrastination refers to an irrationally delay for intended courses of action despite of anticipating a negative consequence due to this delay. Previous studies tried to reveal the neural substrates of procrastination in terms of connectome-based biomarkers. Based on this, we proposed a unified triple brain network model for procrastination and pinpointed out what challenges we are facing in understanding neural mechanism of procrastination. Specifically, based on neuroanatomical features, the unified triple brain network model proposed that connectome-based underpinning of procrastination could be ascribed to the abnormalities of self-control network (i.e., dorsolateral prefrontal cortex, DLPFC), emotion-regulation network (i.e., orbital frontal cortex, OFC), and episodic prospection network (i.e., para-hippocampus cortex, PHC). Moreover, based on the brain functional features, procrastination had been attributed to disruptive neural circuits on FPN (frontoparietal network)-SCN (subcortical network) and FPN-SAN (salience network), which led us to hypothesize the crucial roles of interplay between these networks on procrastination in unified triple brain network model. Despite of these findings, poor interpretability and computational model limited further understanding for procrastination from theoretical and neural perspectives. On balance, the current study provided an overview to show current progress on the connectome-based biomarkers for procrastination, and proposed the integrative neurocognitive model of procrastination.

A vigilance decrement comes along with an executive control decrement: Testing the resource-control theory

A decrease in vigilance over time is often observed when performing prolonged tasks, a phenomenon known as “vigilance decrement.” The present study aimed at testing some of the critical predictions of the resource-control theory about the vigilance decrement. Specifically, the theory predicts that the vigilance decrement is mainly due to a drop in executive control, which fails to keep attentional resources on the external task, thus devoting a larger number of resources to mind-wandering across time-on-task. Datasets gathered from a large sample size (N = 617) who completed the Attentional Networks Test for Interactions and Vigilance—executive and arousal components in Luna, Roca, Martín-Arévalo, and Lupiáñez (2021b, Behavior Research Methods, 53[3], 1124–1147) were reanalyzed to test whether executive control decreases across time in a vigilance task and whether the vigilance decrement comes along with the decrement in executive control. Vigilance was examined as two dissociated components: executive vigilance, as the ability to detect infrequent critical signals, and arousal vigilance, as the maintenance of a fast reaction to stimuli. The executive control decrement was evidenced by a linear increase in the interference effect for mean reaction time, errors, and the inverse efficiency score. Critically, interindividual differences showed that the decrease in the executive—but not in the arousal—component of vigilance was modulated by the change in executive control across time-on-task, thus supporting the predictions of the resource-control theory. Nevertheless, given the small effect sizes observed in our large sample size, the present outcomes suggest further consideration of the role of executive control in resource-control theory.

Cautious or causal? Key implicit sequence learning paradigms should not be overlooked when assessing the role of DLPFC (Commentary on Prutean et al.)

The role of the dorsolateral prefrontal cortex (DLPFC) in implicit sequence/statistical learning has received considerable attention in recent cognitive neuroscience research. Studies have used non-invasive brain stimulation methods to test whether the DLPFC plays a role in the incidental acquisition and expression of implicit sequence learning. In a recent study, Prutean et al. has concluded that stimulating the left or the right DLPFC might not affect the expression of implicit sequence learning measured by the Serial Reaction Time (SRT) task. The authors speculated that the previous results revealing improved implicit sequence learning following DLPFC stimulation might have been found because explicit awareness accumulated with the use of Alternating Serial Reaction Time (ASRT) task. Our response presents solid evidence that the ASRT task measures implicit sequence learning that remains unconscious both at the judgment and structural level. Therefore, contrary to the conclusion of Prutean et al., we argue that the DLPFC could have a crucial effect on implicit sequence learning that may be task-dependent. We suggest that future research should focus on the specific cognitive processes that may be differentially involved in the SRT versus ASRT tasks, and test what the role of the DLPFC is in those specific cognitive processes.