Background/Objectives: Slow oscillation (SO) brainwaves observed during sleep have been shown to reflect the process of memory consolidation, that underlies the critical role of sleep in learning, memory, and other cognitive functions. Closed-loop auditory stimulation (CLAS) uses tones presented in phase with SOs to increase their amplitude and number, along with other brainwave signatures related to memory consolidation. Prior studies have found that CLAS maximizes the ability to perform rote memorization tasks, although this remains controversial. The present study examined whether CLAS affects a broader range of learning tasks than has been tested previously, including a rote language learning task requiring basic memorization and also two discovery learning tasks requiring insight, hypothesis testing, and integration of experience, all processes that benefit from memory consolidation. Methods: Twenty-eight healthy participants performed language and discovery learning tasks before sleeping in our laboratory for three continuous nights per week over two weeks, with verum or control CLAS using a prototype NeuroGevity system (NeuroGeneces, Inc., Santa Fe, NM, USA) in a crossed, randomized, double-blind manner. Results: Language learning showed a 35% better word recall (p = 0.048), and discovery learning showed a 26% better performance (p < 0.001) after three continuous nights of CLAS vs. control. EEG measures showed increased SO amplitude and entrainment, SO-spindle coupling, and other features that may underlie the learning benefits of CLAS. Conclusions: Taken together, the present results show that CLAS can alter brain dynamics and enhance learning, especially in complex discovery learning tasks that may benefit more from memory consolidation compared with rote word pair or language learning.

Background/Objectives: Transcranial electrical stimulation (tES) shows potential for enhancing attention and learning, yet its effects in applied contexts remain underexplored. This study investigated whether transcranial direct current stimulation (tDCS) either alone or in combination with high-frequency transcranial random noise stimulation (hf-tRNS) over the right inferior frontal gyrus (rIFG) could enhance performance in a visual search task requiring target identification and change detection, compared with a low-current control condition. Methods: Sixty-four participants were randomly assigned to receive tDCS alone (2.0 mA), tDCS with hf-tRNS (1.8 mA DC offset combined with 100–500 Hz noise at ±0.18 mA), or low-current control stimulation during training. The task involved identifying vehicles and detecting changes between image presentations. Performance accuracy and EEG oscillatory power were assessed at baseline and post-stimulation. Results: ANCOVA revealed significant effects of stimulation on target identification accuracy (F(2,60) = 3.27, p = 0.045, ηp² = 0.098), with tDCS showing greater improvement than the low-current control condition (p = 0.017). No significant effects were found for change detection for any stimulation condition, or for either the target or change detection for hf-tRNS. Baseline performance moderated stimulation effects: low performers receiving tDCS showed the greatest improvements (F(2,26) = 3.80, p = 0.036, ηp² = 0.226), surpassing even high-baseline performers post-training. EEG analyses revealed that participants who showed greater decreases in frontal theta power demonstrated larger improvements in accuracy with tDCS alone (r = −0.634, p = 0.005) but not with hf-tRNS or the control. Conclusions: tDCS over rIFG selectively enhanced target identification accuracy in a complex visual search, particularly benefiting individuals with lower-baseline performance. These findings suggest tDCS may facilitate training in lower-performing novice populations.

Transcranial direct current stimulation (tDCS) is a noninvasive form of brain stimulation that involves passing a weak electrical current between electrodes on the scalp to modulate underlying neural tissue. TDCS has been shown to modulate cognition in a variety of domains, including memory, attention, and visual processing. Prior work from our laboratory has shown positive effects of tDCS on learning to detect target objects hidden in complex naturalistic visual scenes and learn rules for categorizing images, though the mechanism for these benefits remains unknown. One possibility is that tDCS optimizes visual search by modulating visual attention or via the reduction in search errors. One method of quantifying visual attention is to use eye tracking to record search patterns to determine if and how visual search is adjusted under verum stimulation conditions. Eye tracking data allows classification of errors into error types, including sampling errors (failing to look in the relevant region), recognition errors (looking at the critical portion of a scene, but failing to recognize it as such as evidenced by visual fixation), and decision-making errors (fixating on the relevant portion of a scene, but making the wrong determination). Our results indicate that the benefit tDCS confers on visual search for targets stems from the reduction in decision-making errors when targets are present (Cohen’s d = 0.86). Also reported is a replication of previous findings showing a tDCS-dependent improvement in learning this task, learning score (Cohen’s d = 0.88); d’ (Cohen’s d = 1.00). This provides support for moving tDCS into the application space by pairing it with analysts who are concerned with the type of search error that is corrected via stimulation.