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The coupling of gamma oscillation (~ 40+ Hz) amplitude to the phase of ongoing theta (~ 6 Hz) oscillations has been proposed to be directly relevant for memory performance. Current theories suggest that memory capacity scales with number of gamma cycles that can be fitted into the preferred phase of a theta cycle. Following this logic, transcranial alternating current stimulation (tACS) may be used to adjust theta cycles (increasing/decreasing theta frequency) to decrease or increase memory performance during stimulation. Here, we used individualized EEG-informed theta tACS to (1) experimentally “slow down” individual theta frequency (ITF), (2) evaluate cognitive after effects on a battery of memory and learning tasks, and (3) link the cognitive performance changes to tACS-induced effects on theta-band oscillations as measured by post EEG. We found frequency- and task-specific tACS after effects demonstrating a specific enhancement in memory capacity. This tACS-induced cognitive enhancement was specific to the visual memory task performed immediately after tACS offset, and specific to the ITF-1 Hz (slowing) stimulation condition and thus following a protocol specifically designed to slow down theta frequency to enhance memory capacity. Follow-up correlation analyses in this group linked the enhanced memory performance to increased left frontal-parietal theta-band connectivity. Interestingly, resting-state theta power immediately after tACS offset revealed a theta power increase not for the ITF-1 Hz group, but only for the ITF group where the tACS frequency was ‘optimal’ for entrainment. These results suggest that while individually calibrated tACS at peak frequency maximally modulates resting-state oscillatory power, tACS stimulation slightly below this optimal peak theta frequency is better suited to enhance memory capacity performance. Importantly, our results further suggest that such cognitive enhancement effects can last beyond the period of stimulation and are linked to increased network connectivity, opening the door towards more clinical and applied relevance of using tACS in cognitive rehabilitation and/or neurocognitive enhancement.

•ML used to identify optimal Individual theta frequency (ITF) for memory modulation.•Global task-state ITF best separated high vs. low memory performers.•Resting-state ITF at left parietal site predicted both auditory and visual recall.•Task-related ITFs showed modality-specificity in predicting auditory memory.•Our data-driven pipeline revealed optimal ITF markers to guide future tACS protocols. Recent transcranial alternating current stimulation (tACS) studies suggest that theta-frequency stimulation can modulate memory performance, with evidence highlighting individual variability in optimal stimulation frequency. However, it remains unclear which brain state (\"when\") and cortical region (\"where\") are most predictive of memory-related theta frequencies. This study aimed to identify the most relevant individualized theta frequency (ITF) parameters for episodic memory modulation using a machine learning approach. EEG data were collected from 46 healthy young-adults during rest and while performing visual (VM) and auditory (AM) memory tasks, followed by free-recall assessments. ITFs were extracted as peak theta frequencies from power spectra across 18 electrode sites and a global average (“where”), across three states: resting, task-encoding, and task-delay (\"when\"). Participants were clustered into high- and low-performing groups based on ITFs using K-means clustering, and candidate ITFs were further examined via correlation and Bayesian regression analyses to assess their predictive power. All ITF candidates showed some clustering success, but global task-state ITFs best distinguished between performance groups, independent of task modality. Notably, resting-state left posterior parietal (LPP) ITF was negatively correlated with both VM and AM performance, suggesting a domain-general role in baseline memory capacity. Additionally, task-specific contributions were observed: encoding-related left temporoparietal and delay-related left central ITFs were significantly associated with AM performance, potentially reflecting auditory-specific processes. These findings highlight the importance of “when” and “where” specificity in defining individualized stimulation protocols. Resting-state LPP ITF, in particular, may serve as a promising biomarker for tailoring tACS at sub-ITF frequencies to enhance memory performance.

•Age influenced overall problem-solving performance.•Delta response differed by question in central, temporal, and occipital locations.•Age effects appeared only in the 0–500 ms delta response.•Theta response showed no age differences.•Theta response was notable in occipital location regardless of question type. This study investigates alterations in problem-solving and problem-solving abilities associated with aging, utilizing EEG-Brain Oscillations. The study included 30 young and 30 middle-aged subjects. During the EEG recording, four questions were used for problem-solving. The analysis focused on delta and theta oscillatory patterns. In addition, correlation analysis examined relationships between EEG data and the correct answers' scores. There was a significant result in the delta response for 0-500 ms; the young group had a higher delta response over the frontal area for arithmetic and insight questions; over the parietal area for general knowledge questions, and over the temporoparietal area for basic operation questions. The middle-aged group had a higher delta response over the occipital area for arithmetic, general knowledge, and insight questions, over the central area for basic operation questions. Theta responses showed no differences between groups or question types, remaining consistently high in the occipital area. Significant correlations existed between correct answer scores, especially temporal area. The findings underscore the diverse oscillatory profiles engendered during cognitive tasks, further indicating age-related modifications in these dynamics.

•Slow oscillatory responses differentially contribute to the digit span task performance.•Delta responses matched nicely the suggested “serial position curve” model.•Theta responses reflect the probably chunked items.•Anterior delta responses during encoding positively correlated with the recall scores.•Digit encoding elicited higher right parietal EEG responses. The human brain has limited storage capacity often challenging the encoding and recall of a long series of multiple items. Different encoding strategies are therefore employed to optimize performance in memory processes such as chunking where particular items are ‘grouped’ to reduce the number of items to store artificially. Additionally, related to the position of an item within a series, there is a tendency to remember the first and last items on the list better than the middle ones, which calls the “serial position effect”. Although relatively well-established in behavioral research, the neuronal mechanisms underlying such encoding strategies and memory effects remain poorly understood. Here, we used event-related EEG oscillation analyses to unravel the neuronal substrates of serial encoding strategies and effects during the behaviorally controlled execution of the digit span task. We recorded EEG in forty-four healthy young-adult participants during a backward digit span (ds) task with two difficulty levels (i.e., 3-ds and 5-ds). Participants were asked to recall the digits in reverse order after the presentation of each set. We analyzed the pattern of event-related delta and theta oscillatory power in the time-frequency domain over fronto-central and parieto-occipital areas during the item (digit) list encoding, focusing on how these oscillatory responses changed with each subsequent digit being encoded in the series. Results showed that the development of event-related delta power evoked by digits in each series matched the ‘serial position curve’, with higher delta power being present during the first, and especially last, digits as compared to digits presented in the middle of a set, for both difficulty levels. Event-related theta power, in contrast, rather resembled a neural correlate of a chunking pattern where, during the 5-ds encoding, a clear change in event-related theta occurred around the third/fourth positions, with decreasing power values for later digits. This suggests that different oscillatory mechanisms linked to different frequency bands may code for the different encoding strategies and effects in serial item presentation. Furthermore, recall-EEG correlations suggested that participants with higher fronto-central delta responses during digit encoding showed also higher recall scores. The here presented findings contribute to our understanding of the neural oscillatory mechanisms underlying multiple item encoding, directly informing recent efforts towards memory enhancement through targeted oscillation-based neuromodulation. [Display omitted]

Alongside rapid population ageing, we are experiencing increasing numbers of people with cognitive impairment and dementia. There is great scientific effort being committed to understanding cognitive and brain functioning, with the aim of helping to promote healthy ageing and independence, and improve quality of life. This Cognitive Ageing Collection brings together cutting-edge research using a variety of methods and from diverse disciplinary perspectives, with example topics including cognitive strategies, genetic risk factors, and emotion regulation. Articles in the Collection highlight advances in our understanding of cognitive and brain health, and outline important directions for future research.

Human cognition is derived from functional cortical long-range connectivity, as reflected by phase synchronization between electrode pairs of low-frequency electroencephalographic (EEG) activity <8 Hz related to cognitive tasks. We tested the hypothesis that such an EEG marker, combined with machine learning, can discriminate between Parkinson's disease (PD) with mild cognitive impairment (MCI) and dementia (D) and those with dementia with Lewy bodies (DLB). Event-related EEG delta (1-3.5 Hz) and theta (4-7 Hz) phase coherence were computed from EEG activity recorded during a visual oddball task in healthy controls (HC,  = 24) and PD-MCI (  = 20), PDD (  = 18), and DLB (  = 11) patients. Using delta-band coherence as input, the comparison between HC and PD-MCI yielded an AUC of approximately 0.79 and an accuracy of 86.4%. Higher discriminative performance was observed for HC versus PDD, reaching an AUC near 0.92 with an overall accuracy of 94.6%. In the classification of HC versus DLB participants, the model achieved 83.3% sensitivity and 88.9% specificity, with an AUC around 0.77. Theta-band models showed comparable results, with average AUC values of about 0.75 for HC vs. DLB and slightly above 0.80 for HC vs. PDD, while classification of HC vs. PD-MCI remained in a moderate range. These findings suggest that event-related EEG phase coherence at <8 Hz is a promising EEG correlate of cognitive deficits in patients with PDD and DLB, offering insights into disrupted network dynamics of cortical activity related to cognitive processes and potential biomarkers for testing new drugs for cognitive enhancement and disease monitoring.

Introduction The neural substrates of reasoning, a cognitive ability we use constantly in daily life, are still unclear. Reasoning can be divided into two types according to how the inference process works and the certainty of the conclusions. In deductive reasoning, certain conclusions are drawn from premises by applying the rules of logic. On the other hand, in probabilistic reasoning, possible conclusions are drawn by interpreting the semantic content of arguments. Methods We examined event‐related oscillations associated with deductive and probabilistic reasoning. To better represent the natural use of reasoning, we adopted a design that required participants to choose what type of reasoning they would use. Twenty healthy participants judged the truth values of alternative conclusion propositions following two premises while the EEG was being recorded. We then analyzed event‐related delta and theta power and phase‐locking induced under two different conditions. Results We found that the reaction time was shorter and the accuracy rate was higher in deductive reasoning than in probabilistic reasoning. High delta and theta power in the temporoparietal, parietal, and occipital regions of the brain were observed in deductive reasoning. As for the probabilistic reasoning, prolonged delta response in the right hemisphere and high frontal theta phase‐locking were noted. Conclusion Our results suggest that the electrophysiological signatures of the two types of reasoning have distinct characteristics. There are significant differences in the delta and theta responses that are associated with deductive and probabilistic reasoning. Although our findings suggest that deductive and probabilistic reasoning have different neural substrates, consistent with most of the studies in the literature, there is not yet enough evidence to make a comprehensive claim on the subject. There is a need to diversify the growing literature on deductive and probabilistic reasoning with different methods and experimental paradigms. There are significant differences in the event‐related delta and theta responses of deductive and probabilistic reasoning. In deductive reasoning, high delta and theta power were detected in posterior brain regions. A prolonged delta response in the right hemisphere and high frontal theta phase‐locking were detected in probabilistic reasoning.

Objectives Working memory performances are based on brain functional connectivity, so that connectivity may be deranged in individuals with mild cognitive impairment (MCI) and patients with dementia due to Alzheimer’s disease (ADD). Here we tested the hypothesis of abnormal functional connectivity as revealed by the imaginary part of coherency (ICoh) at electrode pairs from event-related electroencephalographic oscillations in ADD and MCI patients. Methods The study included 43 individuals with MCI, 43 with ADD, and 68 demographically matched healthy controls (HC). Delta, theta, alpha, beta, and gamma bands event-related ICoh was measured during an oddball paradigm. Inter-hemispheric, midline, and intra-hemispheric ICoh values were compared in ADD, MCI, and HC groups. Results The main results of the present study can be summarized as follows: (1) A significant increase of midline frontal and temporal theta coherence in the MCI group as compared to the HC group; (2) A significant decrease of theta, delta, and alpha intra-hemispheric coherence in the ADD group as compared to the HC and MCI groups; (3) A significant decrease of theta midline coherence in the ADD group as compared to the HC and MCI groups; (4) Normal inter-hemispheric coherence in the ADD and MCI groups. Conclusions Compared with the MCI and HC, the ADD group showed disrupted event-related intra-hemispheric and midline low-frequency band coherence as an estimate of brain functional dysconnectivity underlying disabilities in daily living. Brain functional connectivity during attention and short memory demands is relatively resilient in elderly subjects even with MCI (with preserved abilities in daily activities), and it shows reduced efficiency at multiple operating oscillatory frequencies only at an early stage of ADD.

Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications.

Inhibitory control develops gradually from infancy to childhood and improves further during adolescence as the brain matures. Related previous studies showed the indispensable role of task-related alpha power during inhibition both in children and young adults. Nonetheless, none of the studies have been able to investigate the direct differences in brain responses between children and young adults when confronted with a stimulus that should be inhibited. Because, unlike event-related designs, task-related designs involve continuous tasks over a certain period, which precludes the possibility of making such a comparison. Accordingly, by employing event-related design, the present study first time in the literature, aimed to analyze the event-related alpha phase locking and event-related alpha synchronization/desynchronization to differentiate the inhibitory processes in children compared to young adults. 20 children between the ages of 6 to 7 years and 20 healthy young adult subjects between the ages of 18 to 30 years were included in the study. Day-night Stroop task was applied to all subjects during 18-channel EEG recordings. Event-related time-frequency analysis was performed with the complex Morlet Wavelet Transform for the alpha frequency band (8-13 Hz). Event-related spectral perturbation (ERSP) in three different time windows (0-200 ms, 200-400 ms, 400-600 ms) and Event-related phase locking in the early time window (0-400ms) was calculated. The children had increased alpha power in early and late time windows but decreased alpha phase locking in the early time windows compared to young adults. There were also topological differences between groups; while young adults had increased alpha phase-locking in frontal and parietal electrode sites, children had increased occipital alpha power and phase locking. The shift in event-related alpha power observed from posterior to anterior regions with age may suggest a progressive maturation of the frontal areas involved in inhibitory processes from childhood to adulthood. The results of the present study showed that children and young adults had different EEG oscillatory dynamics during inhibitory processes at alpha frequency range.