Gamma-frequency transcranial alternating current stimulation (gamma-tACS) is a promising neuromodulatory approach for Alzheimer’s disease (AD), given the central role of gamma-band dysfunctions in AD-related neuropathology and cognitive decline. Although multi-session gamma-tACS has shown beneficial cognitive and electrophysiological effects in AD, its impact in Mild Cognitive Impairment due to AD (MCI-AD), particularly on blood-based biomarkers and gamma entrainment, remains poorly understood. This case series provides preliminary evidence on the feasibility, tolerability, and multidimensional effects of 40 Hz tACS in individuals with biomarker-confirmed MCI-AD. Three participants completed 20 sessions of bilateral temporal gamma-tACS (40 Hz, 2 mA, 60 minutes/day, 5 days/week for 4 weeks). Assessments were conducted at baseline, post-intervention, and at 3-month follow-up. Outcome measures included neuropsychological testing, functional scales, blood biomarkers, resting-state electroencephalography (EEG), and 40 Hz auditory entrainment. Change magnitudes were descriptively estimated using within-subject Hedges’ g. Gamma-tACS was highly feasible and well tolerated, with high adherence and only mild transient side effects. Cognitive outcomes showed overall positive trends, including improvements in global cognition and delayed associative memory. Functional outcomes (i.e., autonomies, cognitive complaints and affective evaluation) were mixed, while blood biomarkers had heterogeneous changes, except for a consistent reduction in the Aβ42/Aβ40 ratio. EEG analyses revealed participant-specific modulations and enhanced offline gamma entrainment. Despite limitations related to sample size and study design, these findings support further investigation of gamma-tACS as an early intervention targeting oscillatory dysfunctions AD-MCI.

Difficulties in learning and recalling face-name associations are common in aging and may reflect early cognitive decline. This cross-sectional between-subject study examines whether face-naming and face-name associative learning predict objective and subjective cognitive decline in healthy adults. One-hundred-twenty community-dwelling older adults completed the Montreal Cognitive Assessment, the Subjective Cognitive Decline Questionnaire, measures of mood, cognitive reserve, and either the Italian Famous Face Test or the Italian Face-Name Association Test. Regression analyses showed no associations between face-naming tasks and either objective or subjective cognitive decline. Instead, objective cognition was explained by age and cognitive reserve, whereas subjective decline was predicted solely by depressive symptoms. These findings suggest that, in healthy older adults, face-naming abilities are not informative markers of cognitive decline, while subjective concerns primarily reflect emotional distress.

Associating names with faces is crucial for social interactions and reflects cognitive health. To address the need for reliable tools to assess associative memory, we developed and validated the Italian Face-Name Associative Test (ItFNAT), a tool allows clinicians to monitor cognitive functioning and detect early signs of cognitive decline. 101 Italian participants (51 females) aged 18–80 years completed the three parallel versions of the ItFNAT, which assessed immediate recall (IR), delayed free recall (DFR), and delayed recall with cues (DTR). ItFNAT was administered alongside other neuropsychological tests to explore its relationship with memory and attention. ItFNAT demonstrated high internal consistency across its three versions. Principal Component Analysis revealed that IR, DFR, and DTR loaded strongly onto a single factor in each version. Kruskal-Wallis ANOVA indicated no significant differences in scores across versions. Non-parametric analyses showed that years of education significantly influenced all three scores, while age negatively correlated with DTR. Spearman’s correlations revealed strong associations between ItFNAT scores and other widespread memory and attentive tests. This study introduces the ItFNAT, a test designed to assess cross-modal associative memory. It includes three parallel versions with good internal consistency, and minimal score differences. Scores—IR, DFR, and DTR—reflect a shared underlying cognitive construct, correlating with both traditional memory tests and scales assessing working memory and attention. Education significantly influenced all three scores, while age negatively impacted DTR. Future research should refine its application for tracking cognitive function and detecting neurodegenerative changes.

Introduction:Borderline personality disorder (BPD) is one of the most frequently diagnosed disorders in psychiatric settings. Beyond the categorical diagnosis, borderline personality traits (BPT) are common in the general population and vary along a continuum from mild to severe. While prior research has reported functional connectivity alterations in the default mode network (DMN), the salience network (SN), and the central-executive network (CEN) in patients with BPD, the impairment of these networks in subclinical BPT remain underexplored. To fill this gap, this study aims to investigate dynamic functional connectivity alterations associated with BPT in a subclinical population. We expect to find abnormal connectivity inside the DMN, the SN and in regions ascribed to mentalization processes associated with BPT. We also expect these networks to be associated with psychological symptoms experienced by borderline patients such as impulsivity and anger issues, as well as lack of self-control and neuroticism among others. Method:An unsupervised machine learning method known as Group-ICA, was applied to resting state fMRI images of 200 individuals to predict BPT from the temporal variability of independent macro networks. Results:Results indicated abnormal dynamic functional connectivity inside the SN including areas implicated in emotional reactivity and sensitivity, and in a network that partially overlaps with the DMN, including regions involved in social cognition and mind reading. Specifically, the higher the BPT, the higher the temporal variability inside the SN, and the lower the temporal variability in a network that includes DMN and mentalization regions. Notably, the BOLD variability of the SN correlated with neuroticism, anger problems, lack of self- control, and distorted inner dialogue, all symptoms displayed by individuals with borderline personality. Discussion:These findings indicate that abnormalities in resting state networks are visible in subclinical populations with varying degrees of borderline traits, with impaired DMN and SN. These insights may pave the way for designing interventions to prevent the development of the full disorder.

Accurate face recognition is crucial for navigating social interactions. While neurotypical individuals generally show no issues with face processing, persons with Autism Spectrum Disorder (ASD) often exhibit impairments in this area. This study explores the extent of these face recognition deficits in autistic adults, focusing on their ability to identify famous faces, along with the awareness (metacognition) of their face recognition skills. Using the Italian Famous Face Test (IT-FFT) and the Prosopagnosia Index-20 (PI-20), to compare face recognition performance and self-awareness of face recognition abilities between 50 non-autistic and 49 individuals diagnosed with level 1 ASD. Autistic people had significantly lower face identification scores and greater difficulties recognizing famous faces than non-autistic participants. Additionally, autistic individuals reported more face recognition challenges on the PI-20, highlighting their awareness of these deficits. These findings suggest that face recognition impairments in ASD extend to famous faces and underscore the importance of further research to explore targeted interventions aimed at improving different aspects of face recognition in autistic people.

Objective: This study aimed to enhance the psychometric robustness and normative utility of the Italian Face-Name Association Test (ItFNAT), designed to assess cross-modal associative memory, by validating three parallel versions and introducing scores adjusting formula and equivalent scores (ESs) for clinical application. Method: A total of 286 cognitively healthy Italian adults (ages 20-89) completed one of three equivalent ItFNAT versions, evaluating Immediate Recall (IRs), Delayed Free Recall (DFRs) and Delayed Total Recall (DTRs). Four derived indices were also computed. Internal consistency, test-retest reliability, principal component analysis (PCA), and regression-based demographic adjustments were performed. Convergent validity was examined using the Montreal Cognitive Assessment (MoCA). Results: All three versions showed strong psychometric performance, with high internal consistency and robust test-retest reliability. PCA confirmed a stable one-factor structure. Significant correlations with MoCA supported convergent validity. Regression models identified age (linear or transformed) as the only consistent predictor across all scores. Accordingly, adjustment spreadsheet and ES were developed. Derived indices revealed age-related shifts in memory strategies and error types, suggesting their clinical interpretability. Conclusions: The ItFNAT is a reliable and valid tool for assessing associative memory in Italian adults. Its three parallel forms and corrected norms support its clinical and research use, particularly for repeated assessments and early detection of memory impairment in neurodegenerative disorders.

Ketamine, an NMDA receptor (NMDA-R) antagonist, produces psychotomimetic effects when administered in sub-anesthetic dosages. While previous research suggests that Ketamine alters the excitation/inhibition (E/I)-balance in cortical microcircuits, the precise neural mechanisms by which Ketamine produces these effects are not well understood. We analyzed resting-state MEG data from n = 12 participants who were administered Ketamine to assess changes in gamma-band (30-90 Hz) power and the slope of the aperiodic power spectrum compared to placebo. In addition, correlations of these effects with gene-expression of GABAergic interneurons and NMDA-Rs subunits were analyzed. Finally, we compared Ketamine-induced spectral changes to the effects of systematically changing NMDA-R levels on pyramidal cells, and parvalbumin-, somatostatin- and vasoactive intestinal peptide-expressing interneurons in a computational model of cortical layer-2/3 to identify crucial sites of Ketamine action. Ketamine resulted in a flatter aperiodic slope and increased gamma-band power across brain regions, with pronounced effects in prefrontal and central areas. These effects were correlated with the spatial distribution of parvalbumin and GluN2D gene expression. Computational modeling revealed that reduced NMDA-R activity in parvalbumin or somatostatin interneurons could reproduce increased gamma-band power by increasing pyramidal neuron firing rate, but did not account for changes in the aperiodic slope. The results suggest that parvalbumin and somatostatin interneurons may underlie increased gamma-band power following Ketamine administration in healthy volunteers, while changes in the aperiodic component could not be recreated. These findings have implications for current models of E/I-balance, as well as for understanding the mechanisms underlying the circuit effects of Ketamine.

Mild cognitive impairment (MCI) represents an intermediate stage between typical aging and early cognitive decline. As such, an early and accurate diagnosis is essential in making timely interventions. Digital tools, including mobile applications, web platforms, wearable devices, and artificial intelligence-driven systems, have been developed and validated to capture multidimensional data, offering innovative screening solutions. This meta-analysis aims to evaluate the diagnostic accuracy of digital tools for MCI detection in different populations and settings, with a particular focus on three key issues: (i) the overall diagnostic performance of digital tools, (ii) the influence of methodological quality of studies, and (iii) the impact of demographic factors and familiarity with technologies on diagnostic accuracy. This meta-analysis assessed diagnostic accuracy across 32 studies, reporting pooled sensitivity (0.808, 95

INTRODUCTION:Impulsivity has been widely associated to risky decision-making and addictive behaviours. Recent research is investigating transcranial direct current stimulation (tDCS) as a potential tool to improve gambling disorder symptomatology; however, few studies have considered the influence of impulsivity on tDCS effects targeting different brain areas to modulate gambling-related behaviours. METHODS:Two experiments were performed with two-session crossover designs using the same methodology and different samples of low and high impulsive participants (N=64). Multielectrode tDCS montages were designed to target right dorsolateral prefrontal cortex (rDLPFC) and ventromedial prefrontal cortex (vmPFC) during Cambridge gambling task (GCT) performance. RESULTS:Results showed tDCS effects on CGT in both low and high impulsive individuals, revealing specific findings associated to rDLPFC and vmPFC targets respectively. A potential influence of impulsivity on tDCS effects was suggested by the differences in delay aversion between LI and HI, shown only in real stimulation but not in sham. Low and high impulsive participants showed differences in task performance, especially in the lowest and highest risk conditions. CONCLUSION:Future neuromodulation research may benefit from taking into consideration factors including personality traits, such as impulsivity and participants individual differences that may impact the responsiveness to tDCS, as well as from employing neuroimaging techniques to identify the underlaying tDCS effects on specific brain circuits.

ABSTRACTBackgroundAlzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30–90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal “Perturbation‐based” transcranial Alternating Current Stimulation‐Electroencephalography (tACS)‐EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype.MethodsFourteen participants with mild to moderate dementia due to AD underwent a baseline assessment including cognitive status, peripheral neuroinflammation, and resting‐state (rs)EEG. The tACS‐EEG recordings included brief (6′) tACS blocks of gamma (i.e., 40 Hz) stimulation administered through 4 different montages, with Pre/Post 32‐Channels EEG for each block. Changes in tACS‐EEG and rsEEG γ band power with respect to baseline were adopted as a metric of induction and compared with cognitive scores and neuroinflammatory biomarkers.ResultsWe found positive correlations between 40 Hz‐induced γ activity in fronto‐central‐parietal areas and patient cognitive status and negative ones with neuroinflammatory markers. Participants with greater cognitive impairment exhibited less γ induction and higher peripheral neuroinflammation. The same analysis performed with spectral power from baseline rsEEG resulted in no significant correlations, promoting the value of tACS‐based perturbation for capturing individual differences in pathology‐related brain features.ConclusionsOur work suggests a link between tACS‐induced γ band spectral power and clinical severity, with weaker γ induction corresponding to more severe clinical/cognitive impairment. This study provides preliminary support for the development of novel physiological biomarkers and therapeutic targets based on disease severity.

Personality traits are linked to a variety of cognitive and socio-emotional factors, including lateralization patterns. Autism, prosopagnosia, and atypical cradling have been associated with altered lateralization and socio-emotional processing. This study explores how autism traits, cradling-side preferences, and face recognition abilities relate to individual personality differences. Three-hundred neurotypical adults (150 males) completed an online survey including the imaged cradling preference and three validated questionnaires: the Autism spectrum Quotient (AQ), Prosopagnosia Index-20 (PI-20), and the Big Five Personality Questionnaire (BFQ). Results showed a strong left-cradling bias (LCB) unaffected by sex, handedness, parental status, autism traits, or face recognition abilities. AQ negatively predicted Extraversion, Agreeableness, Emotional Stability, and Openness. LCB correlated with higher Agreeableness and moderated the negative association between AQ and Extraversion. These findings suggest a potential link between cradling preferences, autism traits, and personality, possibly reflecting reduced right-hemisphere specialization in emotional processing and social behaviour.

Sports trainers have recently shown increasing interest in innovative methods, including transcranial electric stimulation, to enhance motor performance and boost the acquisition of new skills during training. However, studies on the effectiveness of these tools on fast visuomotor learning and brain activity are still limited. In this randomized single-blind, sham-controlled, between-subjects study, we investigated whether a single training session, either coupled or not with 2 mA online high-frequency transcranial random noise stimulation (hf-tRNS) over the bilateral primary motor cortex (M1), would affect dart-throwing performance (i.e., radial error, arm range of motion, and movement variability) in 37 healthy volunteers. In addition, potential neurophysiological correlates were monitored before and after the training through a 32-electrode portable electroencephalogram (EEG). Results revealed that a single training session improved radial error and arm range of motion during the dart-throwing task, but not movement variability. Furthermore, after the training, resting state-EEG data showed a decrease in theta power. Radial error, arm movement, and EEG were not further modulated by hf-tRNS. This indicates that a single training session, regardless of hf-tRNS administration, improves dart-throwing precision and movement accuracy. However, it does not improve movement variability, which might require multiple training sessions (expertise resulting in slow learning). Theta power decrease could describe a more efficient use of cognitive resources (i.e., attention and visuomotor skills) due to the fast dart-throwing learning. Further research could explore different sports by applying longer stimulation protocols and evaluating other EEG variables to enhance our understanding of the lasting impacts of multi-session hf-tRNS on the sensorimotor cortex within the framework of slow learning and training assistance.

Associative memory is a pivotal component of social cognition. The loss of this ability, frequently reported in the initial stages of Alzheimer's Disease (AD), is among the earliest indications of cognitive impairment. Recent studies have demonstrated that brain oscillations in the gamma band (γ, 30-120 Hz) play a pivotal role in higher-order cognitive functions, including multisensory integration (Senkowski et al., 2009) and memory consolidation (Fernandez-Ruiz et al., 2021). This study aims to establish whether resting-state EEG (rsEEG) spectral power can serve as a predictive biomarker of associative memory ability, possibly identifying early signs of memory challenges that may also be observed in AD patients. Forty-eight healthy adults underwent rsEEG recording, followed by a face-name association task (FNAT; Manippa et al., 2025), assessing immediate (IR) and delayed recall (DR). Results showed that endogenous slow-gamma (s-γ, 30–49 Hz) power significantly predicted DR, accounting for 22% of the variance ( p  = 0.024). Increased s-γ power in temporal regions was positively associated with memory performance ( p  = 0.038). Fast-gamma (f-γ, 51–100 Hz) power significantly predicted DR, accounting for 27% of the variance ( p  = 0.006), with increased frontal ( p  = 0.045) and reduced posterior ( p  <0.001) f-γ power predicting better performance. Lastly, a trend was observed where increased temporal f-γ power and reduced posterior f-γ power were associated with better IR performance. The correlation between increased temporal s-γ and improved accuracy confirms temporal lobe involvement in the consolidation and retrieval of associative memories (Mayes et al., 2007), consistent with reports of reduced gamma power in the medial temporal lobe in AD patients (Babiloni et al., 2020). Moreover, increased frontal f-γ activity suggests greater reliance on executive control processes, typically located in the prefrontal cortex, facilitating retrieval (Wang et al., 2018). Reduced posterior f-γ activity may indicate a shift from sensory integration to higher-order cognitive processing, with disruptions potentially reflecting imbalanced network dynamics, as observed in AD (Verret et al., 2012). These findings offer novel insights into the neurophysiological mechanisms underlying associative memory, possibly facilitating monitoring and prevention of cognitive decline in populations at risk for AD.

Resting-state EEG (rsEEG) provides insights into neural mechanisms underlying memory by reflecting intrinsic brain activity. This study tested whether rsEEG spectral power and theta-gamma phase-amplitude coupling (PAC) can predict memory performance in healthy adults. Twenty-four healthy adults participated in two rsEEG recording sessions, followed by memory tests assessing multimodal Working Memory (WM), Immediate Recall (IR), and Delayed Recall (DR). The predictive value of rsEEG spectral power across frequency bands and theta-gamma PAC was analyzed in relation to memory performance. High-gamma (h-γ, 51–100 Hz) power significantly predicted IR and DR, accounting for over 43

INTRODUCTION:Distinguishing between frontotemporal dementia (FTD) and Alzheimer's disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). METHOD:CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated. RESULTS:Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus. CONCLUSION:Overall, while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

The faces we see in daily life exist on a continuum of familiarity, ranging from personally familiar to famous to unfamiliar faces. Thus, when assessing face recognition abilities, adequate evaluation measures should be employed to discriminate between each of these processes and their relative impairments. We here developed the Italian Famous Face Test (IT-FFT), a novel assessment tool for famous face recognition in typical and clinical populations. Normative data on a large sample (N = 436) of Italian individuals were collected, assessing both familiarity (d ') and recognition accuracy. Furthermore, this study explored whether individuals possess insights into their overall face recognition skills by correlating the Prosopagnosia Index-20 (PI-20) with the IT-FFT; a negative correlation between these measures suggests that people have a moderate insight into their face recognition skills. Overall, our study provides the first online-based Italian test for famous faces (IT-FFT), a test that could be used alongside other standard tests of face recognition because it complements them by evaluating real-world face familiarity, providing a more comprehensive assessment of face recognition abilities. Testing different aspects of face recognition is crucial for understanding both typical and atypical face recognition.

While sounds are essential for human development, existing research primarily emphasizes visual and spatial memory and speech in relation to auditory processes, with a lack of a cohesive understanding of memory mechanisms for non-verbal sounds. This systematic review and coordinate-based meta-analysis of neuroimaging findings aims to comprehensively organize the literature for identifying the key brain mechanisms involved in short-term memory, working memory, and long-term memory for non-verbal auditory information. Additionally, we aimed to identify whether and how individual differences in neural memory processes related to auditory expertise (musicianship), aging or auditory impairments such as amusia are explored in the literature. Our review included ninety studies meeting the selection criteria, with only thirteen studies containing brain coordinates could be included in the meta-analysis. The coordinate-based meta-analysis identified a frontal hub for non-verbal auditory memory encompassing the medial frontal gyrus, cingulate gyrus and superior frontal gyrus. ### Competing Interest Statement The authors have declared no competing interest.

Investigating the biophysiological substrates of psychiatric illnesses is of great interest to our understanding of disorders’ etiology, the identification of reliable biomarkers, and potential new therapeutic avenues. Schizophrenia represents a consolidated model of γ alterations arising from the aberrant activity of parvalbumin-positive GABAergic interneurons, whose dysfunction is associated with perineuronal net impairment and neuroinflammation. This model of pathogenesis is supported by molecular, cellular, and functional evidence. Proof for alterations of γ oscillations and their underlying mechanisms has also been reported in bipolar disorder and represents an emerging topic for major depressive disorder. Although evidence from animal models needs to be further elucidated in humans, the pathophysiology of γ-band alteration represents a common denominator for different neuropsychiatric disorders. The purpose of this narrative review is to outline a framework of converging results in psychiatric conditions characterized by γ abnormality, from neurochemical dysfunction to alterations in brain rhythms.