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Introduction: This study aimed to establish normative data for the Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN), a brief computer-based test for global cognitive assessment through accuracy and response times on tasks related to memory, attention, temporal orientation, visuo-constructional abilities, math (calculation), executive functions, and reading speed., Methods: A sample of 323 Italian individuals with Montreal Cognitive Assessment (MoCA) equivalent score ≥1 (180 females; average age: 61.33 years; average education: 11.32 years), stratified by age, education, and sex, completed SATURN using PsychoPy, and a paper-and-pencil protocol consisting of Mini-Mental State Examination (MMSE) and MoCA. Data analyses included: (i) correlations between the total accuracy scores of SATURN and those of MMSE and MoCA; (ii) multiple regressions to determine the impact of sex, age, and education, along with the computation of adjusted scores; (iii) the calculation of inner and outer tolerance limits, equivalent scores, and the development of correction grids., Results: The mean total time on tasks was 6.72 ± 3.24 min. Age and education significantly influence the SATURN total accuracy, while sex influences the total time on tasks. Specific sociodemographic characteristics influence subdomain accuracies and times on task differently. For the adjusted SATURN total score, the outer limit corresponds to 16.56 out of 29.00 (cut-off), while the inner limit is 18.57. SATURN significantly correlates with MMSE and MoCA., Discussion: In conclusion, SATURN is the first open-source digital tool for initial cognitive assessment in Italy, showing potential for self-administration in primary care, and remote administration. Future studies need to assess its sensitivity and specificity in detecting pathological cognitive decline., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Giaquinto, Assecondi, Leccese, Romano and Angelelli.)

A significant amount of European basic and clinical neuroscience research includes the use of transcranial magnetic stimulation (TMS) and low intensity transcranial electrical stimulation (tES), mainly transcranial direct current stimulation (tDCS). Two recent changes in the EU regulations, the introduction of the Medical Device Regulation (MDR) (2017/745) and the Annex XVI have caused significant problems and confusions in the brain stimulation field. The negative consequences of the MDR for non-invasive brain stimulation (NIBS) have been largely overlooked and until today, have not been consequently addressed by National Competent Authorities, local ethical committees, politicians and by the scientific communities. In addition, a rushed bureaucratic decision led to seemingly wrong classification of NIBS products without an intended medical purpose into the same risk group III as invasive stimulators. Overregulation is detrimental for any research and for future developments, therefore researchers, clinicians, industry, patient representatives and an ethicist were invited to contribute to this document with the aim of starting a constructive dialogue and enacting positive changes in the regulatory environment., (Copyright © 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Widespread cognitive test screening as part of tele-public health initiatives necessitates a test that is self-administered online and automatically scored, with no clinician effort. The feasibility of unsupervised cognitive screening is unclear. We adapted the Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN) to make it suitable for self-administration and automatic scoring. A sample of 364 healthy older adults completed SATURN via a web browser, in a fully independent manner. SATURN's overall score was not modulated by gender, education, reading speed, the time of day at which the test was taken, or an individual's familiarity with technology. SATURN proved extremely portable across operating systems. Importantly, comments from participants reported satisfaction with the experience and the clarity of the instructions. SATURN represents a fast and easy screening tool that can be used for a first assessment, during a routine test or clinical evaluation, or during periodic health monitoring, in person or remotely.

Learning results from online (within-session) and offline (between-sessions) changes. Heterogeneity of age-related effects in learning may be ascribed to aging differentially affecting these two processes. We investigated the contribution of online and offline consolidation in visuo-spatial working memory (vWM). Younger and older participants performed a vWM task on day one and after nine days, allowing us to disentangle online and offline learning effects. To test whether offline consolidation needs continuous practice, two additional groups of younger and older adults performed the same vWM task in between the two assessments. Similarly to other cognitive domains, older adults improved vWM through online (during session one) but not through offline learning. Practice was necessary to improve vWM between sessions in older participants. Younger adults instead exhibited only offline improvement, regardless of practice. The findings suggest that while online learning remains efficient in aging, practice is instead required to support more fragile offline mechanisms.

Aging is a very diverse process: successful agers retain most cognitive functioning, while others experience mild to severe cognitive decline. This decline may eventually negatively impact one's everyday activities. Therefore, scientists must develop approaches to counteract or, at least, slow down the negative change in cognitive performance of aging individuals. Combining cognitive training and transcranial direct current stimulation (tDCS) is a promising approach that capitalizes on the plasticity of brain networks. However, the efficacy of combined methods depends on individual characteristics, such as the cognitive and emotional state of the individual entering the training program. In this report, we explored the effectiveness of working memory training, combined with tDCS to the right dorsolateral prefrontal cortex (DLPFC), to manipulate working memory performance in older individuals. We hypothesized that individuals with lower working memory capacity would benefit the most from the combined regimen. Thirty older adults took part in a 5-day combined regimen. Before and after the training, we evaluated participants' working memory performance with five working memory tasks. We found that individual characteristics influenced the outcome of combined cognitive training and tDCS regimens, with the intervention selectively benefiting old-old adults with lower working memory capacity. Future work should consider developing individualized treatments by considering individual differences in cognitive profiles., Competing Interests: A patent application has been submitted by the University of Birmingham and Dalhousie University with SA, KS, and GE named as inventors. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Assecondi, Hu, Kroeker, Eskes and Shapiro.)

The neural activity of human brain changes in healthy individuals during aging. The most frequent variation in patterns of neural activity are a shift from posterior to anterior areas and a reduced asymmetry between hemispheres. These patterns are typically observed during task execution and by using functional magnetic resonance imaging data. In the present study we investigated whether analogous effects can also be detected during rest and by means of source-space time series reconstructed from electroencephalographic recordings. By analyzing oscillatory power distribution across the brain we indeed found a shift from posterior to anterior areas in older adults. We additionally examined this shift by evaluating connectivity and its changes with age. The findings indicated that inter-area connections among frontal, parietal and temporal areas were strengthened in older individuals. A more complex pattern was shown in intra-area connections, where age-related activity was enhanced in parietal and temporal areas, and reduced in frontal areas. Finally, the resulting network exhibits a loss of modularity with age. Overall, the results extend to resting-state condition the evidence of an age-related shift of brain activity from posterior to anterior areas, thus suggesting that this shift is a general feature of the aging brain rather than being task-specific. In addition, the connectivity results provide new information on the reorganization of resting-state brain activity in aging., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: A patent application titled “Improving cognitive functions” has been submitted by the University of Birmingham and Dalhousie University with SA figuring as one of the inventors., (Copyright © 2022. Published by Elsevier Inc.)

Our brains are often under pressure to process a continuous flow of information in a short time, therefore facing a constantly increasing demand for cognitive resources. Recent studies have highlighted that a lasting improvement of cognitive functions may be achieved by exploiting plasticity, i.e., the brain's ability to adapt to the ever-changing cognitive demands imposed by the environment. Transcranial direct current stimulation (tDCS), when combined with cognitive training, can promote plasticity, amplify training gains and their maintenance over time. The availability of low-cost wearable devices has made these approaches more feasible, albeit the effectiveness of combined training regimens is still unclear. To quantify the effectiveness of such protocols, many researchers have focused on behavioral measures such as accuracy or reaction time. These variables only return a global, non-specific picture of the underlying cognitive process. Electrophysiology instead has the finer grained resolution required to shed new light on the time course of the events underpinning processes critical to cognitive control, and if and how these processes are modulated by concurrent tDCS. To the best of our knowledge, research in this direction is still very limited. We investigate the electrophysiological correlates of combined 3-day working memory training and non-invasive brain stimulation in young adults. We focus on event-related potentials (ERPs), instead of other features such as oscillations or connectivity, because components can be measured on as little as one electrode. ERP components are, therefore, well suited for use with home devices, usually equipped with a limited number of recording channels. We consider short-, mid-, and long-latency components typically elicited by working memory tasks and assess if and how the amplitude of these components are modulated by the combined training regimen. We found no significant effects of tDCS either behaviorally or in brain activity, as measured by ERPs. We concluded that either tDCS was ineffective (because of the specific protocol or the sample under consideration, i.e., young adults) or brain-related changes, if present, were too subtle. Therefore, we suggest that other measures of brain activity may be more appropriate/sensitive to training- and/or tDCS-induced modulations, such as network connectivity, especially in young adults., Competing Interests: A patent application has been submitted by the University of Birmingham (United Kingdom) and Dalhousie University (Canada), with SA, KS figuring among the inventors. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Assecondi, Villa-Sánchez and Shapiro.)

Interventions to improve working memory, e.g. by combining task rehearsal and non-invasive brain stimulation, are gaining popularity. Many factors, however, affect the outcome of these interventions. We hypothesize that working memory capacity at baseline predicts how an individual performs on a working memory task, by setting limits on the benefit derived from tDCS when combined with strategy instructions; specifically, we hypothesize that individuals with low capacity will benefit the most. Eighty-four participants underwent two sessions of an adaptive working memory task (n-back) on two consecutive days. Participants were split into four independent groups (SHAM vs ACTIVE stimulation and STRATEGY vs no STRATEGY instructions). For the purpose of analysis, individuals were divided based on their baseline working memory capacity. Results support our prediction that the combination of tDCS and strategy instructions is particularly beneficial in low capacity individuals. Our findings contribute to a better understanding of factors affecting the outcome of tDCS when used in conjunction with cognitive training to improve working memory. Moreover, our results have implications for training regimens, e.g., by designing interventions predicated on baseline cognitive abilities, or focusing on strategy development for specific attentional skills.

Background: Acquired Brain Injury (ABI) admissions have an incidence of 385 per 100,000 of the population in the UK, and as brain injury often involves the frontal networks, cognitive domains affected are likely to be executive control, working memory, and problem-solving deficits, resulting in difficulty with everyday activities. The above observations make working memory, and related constructs such as attention and executive functioning attractive targets for neurorehabilitation. We propose a combined home-based rehabilitation protocol involving the concurrent administration of a working memory training program (adaptive N-back task) with non-invasive transcranial direct current stimulation (tDCS) of the right dorsolateral prefrontal cortex to promote long-lasting modification of brain areas underlying working memory function., Method: Patients with a working memory deficit will be recruited and assigned to two age-matched groups receiving working memory training for 2 weeks: an active group, receiving tDCS (2 mA for 20 min), and a control group, receiving sham stimulation. After the end of the first 2 weeks, both groups will continue the working memory training for three more weeks. Outcome measures will be recorded at timepoints throughout the intervention, including baseline, after the 2 weeks of stimulation, at the end of the working memory training regimen and 1 month after the completion of the training., Discussion: The aim of the study is to assess if non-invasive tDCS stimulation has an impact on performance and benefits of a working memory training regimen. Specifically, we will examine the impact of brain stimulation on training gains, if changes in gains would last, and whether changes in training performance transfer to other cognitive domains. Furthermore, we will explore whether training improvements impact on everyday life activities and how the home-based training regimen is received by participants, with the view to develop an effective home healthcare tool that could enhance working memory and daily functioning., Trial Registration: This study was registered with clinicaltrials.gov: NCT04010149 on July 8, 2019.

A decline in visuospatial Working Memory (vWM) is a hallmark of cognitive aging across various tasks, and facing this decline has become the target of several studies. In the current study we tested whether older adults can benefit from task repetition in order to improve their performance in a vWM task. While learning by task repetition has been shown to improve vWM performance in young adulthood, little is known on whether a similar enhancement can be achieved also by the aging population. By combining different behavioral and electrophysiological measures, we investigated whether practicing a specific task (delayed match-to-sample judgement) over four consecutive sessions could improve vWM in healthy aging, and which are the neurophysiological and cognitive mechanisms modulated by learning. Behavioral data revealed that task repetition boosted performance in older participants, both in terms of sensitivity to change (as revealed by d' measures) as well as capacity estimate (as measured by k values). At the electrophysiological level, results indicated that only after task repetition both target individuation (as evidenced by the N2pc) and vWM maintenance (as reflected by the CDA) were modulated by target numerosity. Our results suggest that repetition learning is effective in enhancing vWM in aging and acts through modifications at different stages of stimulus processing.

Conscious perception is crucial for adaptive behaviour yet access to consciousness varies for different types of objects. The visual system comprises regions with widely distributed category information and exemplar-level representations that cluster according to category. Does this categorical organisation in the brain provide insight into object-specific access to consciousness? We address this question using the Attentional Blink approach with visual objects as targets. We find large differences across categories in the attentional blink. We then employ activation patterns extracted from a deep convolutional neural network to reveal that these differences depend on mid- to high-level, rather than low-level, visual features. We further show that these visual features can be used to explain variance in performance across trials. Taken together, our results suggest that the specific organisation of the higher-tier visual system underlies important functions relevant for conscious perception of differing natural images.

Background: The use of concurrent EEG-fMRI recordings has increased in recent years, allowing new avenues of medical and cognitive neuroscience research; however, currently used setups present problems with data quality and reproducibility., New Method: We propose a compact experimental setup for concurrent EEG-fMRI at 4T and compare it to a more standard reference setup. The compact setup uses short EEG cables connecting to the amplifiers, which are placed right at the back of the head RF coil on a form-fitting extension force-locked to the patient MR bed. We compare the two setups in terms of sensitivity to MR-room environmental noise, interferences between measuring devices (EEG or fMRI), and sensitivity to functional responses in a visual stimulation paradigm., Results: The compact setup reduces the system sensitivity to both external noise and MR-induced artefacts by at least 60%, with negligible EEG noise induced from the mechanical vibrations of the cryogenic cooling compression pump., Comparison With Existing Methods: The compact setup improved EEG data quality and the overall performance of MR-artifact correction techniques. Both setups were similar in terms of the fMRI data, with higher reproducibility for cable placement within the scanner in the compact setup., Conclusions: This improved compact setup may be relevant to MR laboratories interested in reducing the sensitivity of their EEG-fMRI experimental setup to external noise sources, setting up an EEG-fMRI workplace for the first time, or for creating a more reproducible configuration of equipment and cables. Implications for safety and ergonomics are discussed., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Objective: The objective of this study was to investigate whether previously reported early blood oxygen level dependent (BOLD) changes in epilepsy could occur as a result of the modelling techniques rather than physiological changes., Methods: EEG-fMRI data were analysed from seven patients with focal epilepsy, six control subjects undergoing a visual experiment, in addition to simulations. In six separate analyses the event timing was shifted by either -9,-6,-3,+3,+6 or +9 s relative to the onset of the interictal epileptiform discharge (IED) or stimulus., Results: The visual dataset and simulations demonstrated an overlap between modelled haemodynamic response function (HRF) at event onset and at ± 3 s relative to onset, which diminished at ± 6s. Pre-spike analysis at -6s improved concordance with the assumed IED generating lobe relative to the standard HRF in 43% of patients., Conclusion: The visual and simulated dataset findings indicate a form of "temporal bleeding", an overlap between the modelled HRF at time 0 and at ± 3s which attenuated at ± 6s. Pre-spike analysis at -6s may improve concordance., Significance: This form of analysis should be performed at 6s prior to onset of IED to minimise temporal bleeding effect. The results support the presence of relevant BOLD responses occurring prior to IEDs., (Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Most studies involving simultaneous electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data rely on the first-order, affine-linear correlation of EEG and fMRI features within the framework of the general linear model. An alternative is the use of information-based measures such as mutual information and entropy, which can also detect higher-order correlations present in the data. The estimate of information-theoretic quantities might be influenced by several parameters, such as the numerosity of the sample, the amount of correlation between variables, and the discretization (or binning) strategy of choice. While these issues have been investigated for invasive neurophysiological data and a number of bias-correction estimates have been developed, there has been no attempt to systematically examine the accuracy of information estimates for the multivariate distributions arising in the context of EEG-fMRI recordings. This is especially important given the differences between electrophysiological and EEG-fMRI recordings. In this study, we drew random samples from simulated bivariate and trivariate distributions, mimicking the statistical properties of EEG-fMRI data. We compared the estimated information shared by simulated random variables with its numerical value and found that the interaction between the binning strategy and the estimation method influences the accuracy of the estimate. Conditional on the simulation assumptions, we found that the equipopulated binning strategy yields the best and most consistent results across distributions and bias correction methods. We also found that within bias correction techniques, the asymptotically debiased (TPMC), the jackknife debiased (JD), and the best upper bound (BUB) approach give similar results, and those are consistent across distributions.

Multimodal approaches are of growing interest in the study of neural processes. To this end much attention has been paid to the integration of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data because of their complementary properties. However, the simultaneous acquisition of both types of data causes serious artifacts in the EEG, with amplitudes that may be much larger than those of EEG signals themselves. The most challenging of these artifacts is the ballistocardiogram (BCG) artifact, caused by pulse-related electrode movements inside the magnetic field. Despite numerous efforts to find a suitable approach to remove this artifact, still a considerable discrepancy exists between current EEG-fMRI studies. This paper attempts to clarify several methodological issues regarding the different approaches with an extensive validation based on event-related potentials (ERPs). More specifically, Optimal Basis Set (OBS) and Independent Component Analysis (ICA) based methods were investigated. Their validation was not only performed with measures known from previous studies on the average ERPs, but most attention was focused on task-related measures, including their use on trial-to-trial information. These more detailed validation criteria enabled us to find a clearer distinction between the most widely used cleaning methods. Both OBS and ICA proved to be able to yield equally good results. However, ICA methods needed more parameter tuning, thereby making OBS more robust and easy to use. Moreover, applying OBS prior to ICA can optimize the data quality even more, but caution is recommended since the effect of the additional ICA step may be strongly subject-dependent., (Copyright 2010 Elsevier Inc. All rights reserved.)

Objective: This article proposes a method to automatically identify and label event-related potential (ERP) components with high accuracy and precision., Methods: We present a framework, referred to as peak-picking Dynamic Time Warping (ppDTW), where a priori knowledge about the ERPs under investigation is used to define a reference signal. We developed a combination of peak-picking and Dynamic Time Warping (DTW) that makes the temporal intervals for peak-picking adaptive on the basis of the morphology of the data. We tested the procedure on experimental data recorded from a control group and from children diagnosed with developmental dyslexia., Results: We compared our results with the traditional peak-picking. We demonstrated that our method achieves better performance than peak-picking, with an overall precision, recall and F-score of 93%, 86% and 89%, respectively, versus 93%, 80% and 85% achieved by peak-picking., Conclusion: We showed that our hybrid method outperforms peak-picking, when dealing with data involving several peaks of interest., Significance: The proposed method can reliably identify and label ERP components in challenging event-related recordings, thus assisting the clinician in an objective assessment of amplitudes and latencies of peaks of clinical interest.

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can give new insights into how the brain functions. However, the strong electromagnetic field of the MR scanner generates artifacts that obscure the EEG and diminish its readability. Among them, the ballistocardiographic artifact (BCGa) that appears on the EEG is believed to be related to blood flow in scalp arteries leading to electrode movements. Average artifact subtraction (AAS) techniques, used to remove the BCGa, assume a deterministic nature of the artifact. This assumption may be too strong, considering the blood flow related nature of the phenomenon. In this work we propose a new method, based on canonical correlation analysis (CCA) and blind source separation (BSS) techniques, to reduce the BCGa from simultaneously recorded EEG-fMRI. We optimized the method to reduce the user's interaction to a minimum. When tested on six subjects, recorded in 1.5 T or 3 T, the average artifact extracted with BSS-CCA and AAS did not show significant differences, proving the absence of systematic errors. On the other hand, when compared on the basis of intra-subject variability, we found significant differences and better performance of the proposed method with respect to AAS. We demonstrated that our method deals with the intrinsic subject variability specific to the artifact that may cause averaging techniques to fail.