Publications by authors named "Roberto Guidotti"

The brain is a highly complex physical system made of assemblies of neurons that work together to accomplish elaborate tasks such as motor control, memory and perception. How these parts work together has been studied for decades by neuroscientists using neuroimaging, psychological manipulations, and neurostimulation. Neurostimulation has gained particular interest, given the possibility to perturb the brain and elicit a specific response.

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Article Synopsis
  • Treatment-Resistant Depression (TRD) is a significant health issue that's hard to tackle due to its complex nature and varied symptoms, prompting the need for better treatment strategies.
  • The SelecTool Project is introduced as a computational tool that combines clinical data, EEG, and blood biomarkers using machine learning to personalize TRD treatments, specifically focusing on esketamine nasal spray and accelerated repetitive Transcranial Magnetic Stimulation.
  • The project involves two main phases: first, a study with 100 TRD subjects to evaluate the effectiveness of treatments, and then training the tool to assist in managing an additional 20 subjects, ultimately aiming to improve TRD treatment outcomes through advanced data analysis.
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State-dependent non-invasive brain stimulation (NIBS) informed by electroencephalography (EEG) has contributed to the understanding of NIBS inter-subject and inter-session variability. While these approaches focus on local EEG characteristics, it is acknowledged that the brain exhibits an intrinsic long-range dynamic organization in networks. This proof-of-concept study explores whether EEG connectivity of the primary motor cortex (M1) in the pre-stimulation period aligns with the Motor Network (MN) and how the MN state affects responses to the transcranial magnetic stimulation (TMS) of M1.

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We introduce a blockwise generalisation of the Antisymmetric Cross-Bicoherence (ACB), a statistical method based on bispectral analysis. The Multi-dimensional ACB (MACB) is an approach that aims at detecting quadratic lagged phase-interactions between vector time series in the frequency domain. Such a coupling can be empirically observed in functional neuroimaging data, e.

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Treatment-resistant depression (TRD) represents a severe clinical condition with high social and economic costs. Esketamine Nasal Spray (ESK-NS) has recently been approved for TRD by EMA and FDA, but data about predictors of response are still lacking. Thus, a tool that can predict the individual patients' probability of response to ESK-NS is needed.

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Coregistration of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows non-invasive probing of brain circuits: TMS induces brain activation due to the generation of a properly oriented focused electric field (E-field) using a coil placed on a selected position over the scalp, while EEG captures the effects of the stimulation on brain electrical activity. Moreover, the combination of these techniques allows the investigation of several brain properties, including brain functional connectivity. The choice of E-field parameters, such as intensity, orientation, and position, is crucial for eliciting cortex-specific effects.

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Neuroimaging studies have provided evidence that extensive meditation practice modifies the functional and structural properties of the human brain, such as large-scale brain region interplay. However, it remains unclear how different meditation styles are involved in the modulation of these large-scale brain networks. Here, using machine learning and fMRI functional connectivity, we investigated how focused attention and open monitoring meditation styles impact large-scale brain networks.

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The understanding of the neurobiological basis of perceptual decision-making has been profoundly shaped by studies in the monkey brain in tandem with mathematical models, providing the basis for the formulation of an intentional account of decision-making. Although much progress has been made in human studies, a characterization of the neural underpinnings of an integrative mechanism, where evidence accumulation and the selection and execution of responses are carried out by the same system, remains challenging. Here, by employing magnetoencephalographic recording in combination with an experimental protocol that measures saccadic response and leverages a systematic modulation of evidence levels, we obtained a spectral dissociation between evidence accumulation mechanisms and motor preparation within the same brain region.

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Memory for time is influenced by reconstructive processes, but the underlying mechanisms remain unclear. The present study investigated whether the effect of schematic prior knowledge on temporal memory for movie scenes, produced by the incomplete presentation (cut) of the movie at encoding, is modulated by cut position, retention interval, and task repetition. In a timeline positioning task, participants were asked to indicate when short video clips extracted from a previously encoded movie occurred on a horizontal timeline that represented the video duration.

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. Being able to characterize functional connectivity (FC) state dynamics in a real-time setting, such as in brain-computer interface, neurofeedback or closed-loop neurostimulation frameworks, requires the rapid detection of the statistical dependencies that quantify FC in short windows of data. The aim of this study is to characterize, through extensive realistic simulations, the reliability of FC estimation as a function of the data length.

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Objective: Being able to characterize functional connectivity (FC) state dynamics in a real-time setting, such as in brain-computer interface, neurofeedback or closed-loop neurostimulation frameworks, requires the rapid detection of the statistical dependencies that quantify FC in short windows of data. The aim of this study is to characterize, through extensive realistic simulations, the reliability of FC estimation as a function of the data length. In particular, we focused on FC as measured by phase-coupling (PC) of neuronal oscillations, one of the most functionally relevant neural coupling modes.

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(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators.

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Objective: The objective of the study is to identify phase coupling patterns that are shared across subjects via a machine learning approach that utilises source space magnetoencephalography (MEG) phase coupling data from a working memory (WM) task. Indeed, phase coupling of neural oscillations is putatively a key factor for communication between distant brain areas and is therefore crucial in performing cognitive tasks, including WM. Previous studies investigating phase coupling during cognitive tasks have often focused on a few a priori selected brain areas or a specific frequency band, and the need for data-driven approaches has been recognised.

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Remembering when events took place is a key component of episodic memory. Using a sensitive behavioral measure, the present study investigates whether spontaneous event segmentation and script-based prior knowledge affect memory for the time of movie scenes. In three experiments, different groups of participants were asked to indicate when short video clips extracted from a previously encoded movie occurred on a horizontal timeline that represented the video duration.

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Decision-making is in the service of action regardless of whether the decision concerns perceptual information, goods or memories. Compared to recent advances in the neurobiology of perceptual or value-based decisions, however, the neural bases supporting the sampling of evidence in long-term memory, and the transformation of memory-based decisions into appropriate actions, are still poorly understood. In the present fMRI study, we used multivariate pattern analysis to investigate the temporal dynamics of choice- and action-predictive signals during an item recognition task that manipulated the association between memory choices (old/new) and motor responses (eye/hand) across subjects.

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Neurobiological research has classically focused on perceptual decision-making, although many real-life decisions are based on information that is not currently available but stored in long-term memory. Previous studies have suggested that the lateral parietal cortex encodes decision-related signals during item recognition judgments. In the present fMRI study, we employed a parametric manipulation of evidence for source memory judgments and tested several hypotheses concerning memory decision signals in parietal cortex.

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The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization.

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This study investigated whether the visual and auditory Simon effects could be accounted for by the same mechanism. In a single experiment, we performed a detailed comparison of the visual and the auditory Simon effects arising in behavioural responses and in pupil dilation, a psychophysiological measure considered as a marker of the cognitive effort induced by conflict processing. To address our question, we performed sequential and distributional analyses on both reaction times and pupil dilation.

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The human ventral occipito-temporal cortex (OTC) contains areas specialized for particular perceptual/semantic categories, such as faces (fusiform face area, FFA) and places (parahippocampal place area, PPA). This organization has been interpreted as reflecting the visual structure of the world, i.e.

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Recent evidence showed that pupil dilation (PD) reflects modulations in the magnitude of the Simon interference effect due to correspondence sequence. In the present study we used this measure to assess whether these modulations, thought to result from cognitive control mechanisms, are influenced by prior practice with an incompatible stimulus-response (S-R) mapping. To this end, PD and reaction times (RTs) were recorded while participants performed a Simon task before and after executing a spatially incompatible practice.

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Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience.

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When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus.

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