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High-definition transcranial direct current stimulation (HD-tDCS) seems to overcome a drawback of traditional bipolar tDCS: the wide-spread diffusion of the electric field. Nevertheless, most of the differences that characterise the two techniques are based on mathematical simulations and not on real, behavioural and neurophysiological, data. The study aims to compare a widespread tDCS montage (i.e., a Conventional bipolar montage with extracephalic return electrode) and HD-tDCS, investigating differences both at a behavioural level, in terms of dexterity performance, and a neurophysiological level, as modifications of alpha and beta power as measured with EEG. Thirty participants took part in three sessions, one for each montage: Conventional tDCS, HD-tDCS, and sham. In all the conditions, the anode was placed over C4, while the cathode/s placed according to the montage. At baseline, during, and after each stimulation condition, dexterity was assessed with a Finger Tapping Task. In addition, resting-state EEG was recorded at baseline and after the stimulation. Power spectrum density was calculated, selecting two frequency bands: alpha (8–12 Hz) and beta (18–22 Hz). Linear mixed effect models (LMMs) were used to analyse the modulation induced by tDCS. To evaluate differences among the montages and consider state-dependency phenomenon, the post-stimulation measurements were covariate-adjusted for baseline levels. We observed that HD-tDCS induced an alpha power reduction in participants with lower alpha at baseline. Conversely, Conventional tDCS induced a beta power reduction in participants with higher beta at baseline. Furthermore, data showed a trend towards a behavioural effect of HD-tDCS in participants with lower beta at baseline showing faster response times. Conventional and HD-tDCS distinctively modulated cortical activity. The study highlights the importance of considering state-dependency to determine the effects of tDCS on individuals.

Recent studies have revealed that gamma‐band oscillatory and transient evoked potentials may change with age during childhood. It is hypothesized that these changes can be associated with a maturation of GABAergic neurotransmission and, subsequently, the age‐related changes of excitation–inhibition balance in the neural circuits. One of the reliable paradigms for investigating these effects in the auditory cortex is 40 Hz Auditory Steady‐State Response (ASSR), where participants are presented with the periodic auditory stimuli. It is known that such stimuli evoke two types of responses in magnetoencephalography (MEG)—40 Hz steady‐state gamma response (or 40 Hz ASSR) and auditory evoked response called sustained Event‐Related Field (ERF). Although several studies have been conducted in children, focusing on the changes of 40 Hz ASSR with age, almost nothing is known about the age‐related changes of the sustained ERF to the same periodic stimuli and their relationships with changes in the gamma strength. Using MEG, we investigated the association between 40 Hz steady‐state gamma response and sustained ERF response to the same stimuli and also their age‐related changes in the group of 30 typically developing 7‐to‐12‐year‐old children. The results revealed a tight relationship between 40 Hz ASSR and ERF, indicating that the age‐related increase in strength of 40 Hz ASSR was associated with the age‐related decrease of the amplitude of ERF. These effects were discussed in the light of the maturation of the GABAergic system and excitation–inhibition balance development, which may contribute to the changes in ASSR and ERF. Using magnetoencephalography (MEG), we aimed to investigate the association between 40 Hz steady‐state gamma response and sustained ERF response to the same stimuli and also their age‐related changes in the group of 30 typically developing 7‐to‐12‐year‐old children. The results revealed a tight relationship between 40 Hz ASSR and ERF.

Hemodynamic fluctuations in the default mode network (DMN), observed through functional magnetic resonance imaging (fMRI), have been linked to electrophysiological oscillations detected by electroencephalography (EEG). It has been reported that, among the electrophysiological oscillations, those in the alpha frequency range (8-13 Hz) are the most dominant during resting state. We hypothesized that DMN spatial configuration closely depends on the specific neuronal oscillations considered, and that alpha oscillations would mainly correlate with increased blood oxygen-level dependent (BOLD) signal in the DMN. To test this hypothesis, we used high-density EEG (hdEEG) data simultaneously collected with fMRI scanning in 20 healthy volunteers at rest. We first detected the DMN from source reconstructed hdEEG data for multiple frequency bands, and we then mapped the correlation between temporal profile of hdEEG-derived DMN activity and fMRI-BOLD signals on a voxel-by-voxel basis. In line with our hypothesis, we found that the correlation map associated with alpha oscillations, more than with any other frequency bands, displayed a larger overlap with DMN regions. Overall, our study provided further evidence for a primary role of alpha oscillations in supporting DMN functioning. We suggest that simultaneous EEG-fMRI may represent a powerful tool to investigate the neurophysiological basis of human brain networks.Hemodynamic fluctuations in the default mode network (DMN), observed through functional magnetic resonance imaging (fMRI), have been linked to electrophysiological oscillations detected by electroencephalography (EEG). It has been reported that, among the electrophysiological oscillations, those in the alpha frequency range (8-13 Hz) are the most dominant during resting state. We hypothesized that DMN spatial configuration closely depends on the specific neuronal oscillations considered, and that alpha oscillations would mainly correlate with increased blood oxygen-level dependent (BOLD) signal in the DMN. To test this hypothesis, we used high-density EEG (hdEEG) data simultaneously collected with fMRI scanning in 20 healthy volunteers at rest. We first detected the DMN from source reconstructed hdEEG data for multiple frequency bands, and we then mapped the correlation between temporal profile of hdEEG-derived DMN activity and fMRI-BOLD signals on a voxel-by-voxel basis. In line with our hypothesis, we found that the correlation map associated with alpha oscillations, more than with any other frequency bands, displayed a larger overlap with DMN regions. Overall, our study provided further evidence for a primary role of alpha oscillations in supporting DMN functioning. We suggest that simultaneous EEG-fMRI may represent a powerful tool to investigate the neurophysiological basis of human brain networks.

Remembering to execute delayed intentions (i.e., prospective memory, PM) entails the allocation of internal and external attention. These processes are crucial for rehearsing PM intentions in memory and for monitoring the presence of the PM cue in the environment, respectively. The study took advantage of the excellent spatial and temporal resolution of magnetoencephalography (MEG) to delineate the neural mechanisms of the memory and monitoring processes underlying PM. The spatio-temporal dynamic of theta and alpha oscillations were explored in 21 participants in two PM tasks compared to a baseline condition (i.e., a lexical decision task with no PM instruction). The PM tasks varied for the load of internally-directed attention (Retrospective-load task) vs externally-directed attention (Monitoring-load task). Increase in theta activity was observed in the Retrospective-load task, and was particularly expressed in the regions of the Default Mode Network, such as in medial temporal regions, precuneus, posterior cingulate cortex and medial prefrontal cortex. Alpha decrease was the most relevant feature of the Monitoring-load task, and it was expressed over bilateral occipital, occipito-parietal and fronto-temporal regions, as well as over left dorsal fronto-parietal regions. Theta and alpha oscillations are strictly associated with the direction of attention during the PM tasks. In particular, theta increase is linked to internal attention necessary for maintaining the intention active in working memory, whereas alpha decrease supports the external attention for detecting the PM cue in the environment. •The spatiotemporal dynamic of MEG signal during prospective memory (PM) tasks is measured.•Theta and alpha oscillations are associated with the direction of attention.•Theta increase over Default Mode network indicates internally directed attention.•Theta increase reflects internal attention to intention in memory.•Alpha decrease supports external attention towards PM cues linked to intention.

The posterior superior temporal sulcus (pSTS) is a critical node in a network specialized for perceiving emotional facial expressions that is reciprocally connected with early visual cortices (V1/V2). Current models of perceptual decision-making increasingly assign relevance to recursive processing for visual recognition. However, it is unknown whether inducing plasticity into reentrant connections from pSTS to V1/V2 impacts emotion perception. Using a combination of electrophysiological and neurostimulation methods, we demonstrate that strengthening the connectivity from pSTS to V1/V2 selectively increases the ability to perceive facial expressions associated with emotions. This behavior is associated with increased electrophysiological activity in both these brain regions, particularly in V1/V2, and depends on specific temporal parameters of stimulation that follow Hebbian principles. Therefore, we provide evidence that pSTS-to-V1/V2 back-projections are instrumental to perception of emotion from facial stimuli and functionally malleable via manipulation of associative plasticity. Temporo-occipital areas are involved in perceiving emotional faces. Here, the authors show that strengthening back-projections from temporal to occipital areas enhances visual cortex’s response to face stimuli and perception of emotions from them.

Prospective Memory (PM) is the ability to encode an intention in memory and retrieve it at the right time in the future. After the intention is formed, it must be maintained in memory while simultaneously monitoring the environment until the occurrence of the stimulus associated with its retrieval. Therefore, monitoring and maintenance processes must work in conjunction to subserve PM processing (monitoring/maintenance phase). Several brain regions play a role in PM, such as the anterior prefrontal cortex, inferior parietal lobules, and precuneus. Notably, these regions belong to different brain networks and are differently involved depending on the memory and attentional requests of the PM task. In this study, we investigate the neural bases of PM from a network perspective, using functional connectivity (FC) analysis to identify the networks involved in the attentional and memory mechanisms underlying PM. To this end, we analyzed MEG data collected in two different PM conditions, enhancing either the monitoring (i.e., attention) or the maintenance (i.e., memory) loads of the PM task. To disentangle the neural correlates of these mechanisms from other processes occurring after stimulus presentation, the analysis focused on the prestimulus time window (monitoring/maintenance phase). The monitoring-load condition was characterized by increased inter-network FC of the Dorsal Attention Network (DAN) in the alpha band, a marker of increased top-down monitoring. In contrast, the maintenance-load condition was associated with increased connectivity of the Ventral Attention Network (VAN) with the FrontoParietal Control and the Default-Mode Networks (FPCN and DMN, respectively). Additionally, response times were found to correlate with prestimulus alpha connectivity of different networks in the two conditions. These differences in connectivity within and between networks support the hypothesis that different networks (DAN, or VAN and DMN) and mechanisms (top-down or bottom-up, respectively) are involved in PM processing depending on the features of the PM task.

During the past decades there has been an increasing interest in tracking brain network fluctuations in health and disease by means of resting state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI however does not provide the ideal environmental setting, as participants are continuously exposed to noise generated by MRI coils during acquisition of Echo Planar Imaging (EPI). We investigated the effect of EPI noise on resting state activity and connectivity using magnetoencephalography (MEG), by reproducing the acoustic characteristics of rs-fMRI environment during the recordings. As compared to fMRI, MEG has little sensitivity to brain activity generated in deep brain structures, but has the advantage to capture both the dynamic of cortical magnetic oscillations with high temporal resolution and the slow magnetic fluctuations highly correlated with BOLD signal. Thirty healthy subjects were enrolled in a counterbalanced design study including three conditions: a) silent resting state (Silence), b) resting state upon EPI noise (fMRI), and c) resting state upon white noise (White). White noise was employed to test the specificity of fMRI noise effect. The amplitude envelope correlation (AEC) in alpha band measured the connectivity of seven Resting State Networks (RSN) of interest (default mode network, dorsal attention network, language, left and right auditory and left and right sensory-motor). Vigilance dynamic was estimated from power spectral activity. fMRI and White acoustic noise consistently reduced connectivity of cortical networks. The effects were widespread, but noise and network specificities were also present. For fMRI noise, decreased connectivity was found in the right auditory and sensory-motor networks. Progressive increase of slow theta-delta activity related to drowsiness was found in all conditions, but was significantly higher for fMRI . Theta-delta significantly and positively correlated with variations of cortical connectivity. rs-fMRI connectivity is biased by unavoidable environmental factors during scanning, which warrant more careful control and improved experimental designs. MEG is free from acoustic noise and allows a sensitive estimation of resting state connectivity in cortical areas. Although underutilized, MEG could overcome issues related to noise during fMRI, in particular when investigation of motor and auditory networks is needed.

Frailty has emerged as prevalent condition in ageing. While frailty has been assessed through physical and functional criteria, recent studies have explored the link between cognitive decline and frailty, which remains complex and warrants further investigation. Our aims were to compare differences at the brain level between robust and frail older people without dementia and to explore possible associations between brain measures and cognitive performance assessed with neuropsychological tests. Using data from the \"CAM-Cam\" project that recruited a community dwelling population, we identified robust and frail participants based on the Rockwood Frailty index. Magnetic Resonance Imaging was performed to probe the interplay between physical frailty and cognitive health. The main aims were: (i) to identify differences in cognitive performance using the Cattell Culture Fair test and the Tip of the Tongue test and (ii) to assess voxel-wise group-related effects, using a general linear model design to investigate potential differences between our two study groups (\"frail\" and \"robust\"). Our findings revealed significantly smaller grey matter volume in frail individuals, primarily localized in cerebellar areas and in the right supramarginal gyrus. Diffusion magnetic resonance imaging scans showed diminished axial diffusivity values in frail participants, particularly in the corticospinal tract. Resting-state functional MRI showed increased functional connectivity values within the Default Mode Network (DMN) in frail individuals, relative to the robust group in parietal and cerebellar portions of the DMN. Moreover, we observed significant correlations between cognitive score and brain measures for our study groups. The associations between cognitive test scores and anatomical and functional patterns in the brain highlight the complex interconnections between physical and cognitive aspects of frailty. This study brings novel insights into the early neurobiological markers associated with physical frailty in a cognitively healthy population.

Recent studies have shown a growing interest in the so-called “aperiodic” component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, this aperiodic component is associated both with age-related changes and performance on cognitive tasks. This study aims to elucidate the potential role of education in moderating the relationship between resting-state EEG features (including aperiodic component) and cognitive performance in aging. N = 179 healthy participants of the “Leipzig Study for Mind–Body-Emotion Interactions” (LEMON) dataset were divided into three groups based on age and education. Older adults exhibited lower exponent, offset (i.e. measures of aperiodic component), and Individual Alpha Peak Frequency (IAPF) as compared to younger adults. Moreover, visual attention and working memory were differently associated with the aperiodic component depending on education: in older adults with high education, higher exponent predicted slower processing speed and less working memory capacity, while an opposite trend was found in those with low education. While further investigation is needed, this study shows the potential modulatory role of education in the relationship between the aperiodic component of the EEG power spectrum and aging cognition.

In the domain of cognitive studies on the lexico-semantic representational system, one of the most important means of ensuring effective experimental designs is using ecological stimulus sets accompanied by normative data on the most relevant variables affecting the processing of their items. In the context of image sets, color photographs are particularly suited to this purpose as they reduce the difficulty of visual decoding processes that may emerge with traditional image sets of line drawings. This is especially so in clinical populations. In this study we provide Italian norms for a set of 357 high quality image-items belonging to 23 semantic subcategories from the Moreno-Martínez and Montoro database. Data from several variables affecting image processing were collected from a sample of 255 Italian-speaking participants: age of acquisition, familiarity, lexical frequency, manipulability, name agreement, typicality and visual complexity. Lexical frequency data were derived from the CoLFIS corpus. Furthermore, we collected data on image oral naming latencies to explore how the variance in these latencies could be explained by these critical variables. Multiple regression analyses on the naming latencies show classical psycholinguistic phenomena, such as the effects of age of acquisition and name agreement. In addition, manipulability was also a significant predictor. The described Italian normative data and naming latencies are available for download as supplementary material.