101,899 research outputs found
Interindividual variability in functional connectivity as long-term correlate of temporal discounting.
No full textDuring intertemporal choice (IT) future outcomes are usually devaluated as a function of the delay, a phenomenon known as temporal discounting (TD). Based on task-evoked activity, previous neuroimaging studies have described several networks associated with TD. However, given its relevance for several disorders, a critical challenge is to define a specific neural marker able to predict TD independently of task execution. To this aim, we used resting-state functional connectivity MRI (fcMRI) and measured TD during economic choices several months apart in 25 human subjects. We further explored the relationship between TD, impulsivity and decision uncertainty by collecting standard questionnaires on individual trait/state differences. Our findings indicate that fcMRI within and between critical nodes of task-evoked neural networks associated with TD correlates with discounting behavior measured a long time afterwards, independently of impulsivity. Importantly, the nodes form an intrinsic circuit that might support all the mechanisms underlying TD, from the representation of subjective value to choice selection through modulatory effects of cognitive control and episodic prospection
Distinct connectivity profiles predict different in-time processes of motor skill learning
No full textLearning through intensive practice has been largely observed in motor, sensory and higher-order cognitive processing. Neuroimaging studies have shown that learning phases are associated with different patterns of functional and structural neural plasticity in spatially distributed brain systems. Yet, it is unknown whether distinct neural signatures before practice can foster different subsequent learning stages over time. Here, we employed a bimanual implicit sequence reaction time task (SRTT) to investigate whether the rates of early (one day after practice) and late (one month after practice) post-training motor skill learning were predicted by distinct patterns of pre-training resting state functional connectivity (rs-FC), recorded with functional MRI. We observed that both motor learning descriptors were positively correlated with the strength of rs-FC among pairs of regions within a SRTT-relevant network comprising cerebellar as well as cortical and subcortical motor areas. Crucially, we detected a double dissociation such that early post-training learning was significantly associated with the functional connections within cerebellar regions, whereas late post-training learning was significantly related to the functional connections between cortical and subcortical motor areas. These findings indicate that spontaneous brain activity prospectively carries out behaviorally relevant information to perform experience-dependent cognitive operations far distant in time
Magnetic stimulation selectively affects pre-stimulus EEG microstates
No full textDifferent electrophysiological (EEG) correlates may provide specific important assessment of the period that anticipates an imperative stimulus. Previous study of our group showed that a local (i.e. parietal) anticipatory EEG marker (i.e. the event related de-synchronization of the alpha rhythms; ERD) is selectively affected when transcranial magnetic stimulation (TMS) is delivered over crucial nodes belonging to well-known human networks involved in different cognitive domains. Here, we investigated whether such distinction is also present in the whole brain activity as seen through the pre-stimulus microstate’s topography, representing a global and reference-free measure of the neural activity. First, when subjects received a pseudo-stimulation (sham), we found two distinct pre-stimulus topographies during perceptual or memory task, respectively. Second, we reported that, during the visuo-spatial attention task, stimulation of left intraparietal sulcus (IPS), but not left angular gyrus (AG), significantly modifies the topography observed in the Sham condition. Conversely, stimulation of AG, but not IPS, changes the topography observed in the Sham condition during a semantic memory task. These findings provide the first causal evidence for the task and region specificity of the pre-stimulus EEG microstates, thus proposing this EEG index as of particular interest for the assessment of the period that precedes a predictable event
rTMS affects EEG microstates dynamic during evoked activity
No full textElectrophysiological (EEG) correlates both at time (i.e., event-related potentials, ERP) and frequency (i.e., event-related desynchronization, ERD) domains have been shown to be modulated by external magnetic interference. Parallel studies reported a similar interference also for the EEG microstate at rest and in the period that anticipates a task. Here we investigated whether such interference was prolonged during the evoked activity in the framework of the semantic decision task. To this aim, rTMS was delivered over a core region of both the Default mode network and the language network (i.e., left angular gyrus, AG), previously associated to the current task, and as active control we stimulated the left IPS. When subjects received a non-active stimulation (i.e., Sham), in the period that follows the target onset (i.e., 2 sec after the rTMS) we found an interesting alternation of two dominant microstates (MS1, MS3), previously associated to the phonological network and the Cingulo-Opercular Network (CON), respectively. This dynamic was not altered when TMS was delivered over the left IPS. On the contrary, rTMS over left AG selectively suppressed the phonological-related microstate. These findings provide the first causal evidence of region specificity of the EEG microstates topography during the evoked activity corroborating the idea of a crucial role of AG in the semantic memory. Moreover, the present results might provide insight for understanding the neurophysiological correlates of language disorders e.g., aphasia as well as for planning non-invasive brain stimulation protocols for the rehabilitation
Neuroimaging evidence supporting a dual-network architecture for the control of visuospatial attention in the human brain: a mini review
No full textNeuroimaging studies conducted in the last three decades have distinguished two frontoparietal networks responsible for the control of visuospatial attention. The present review summarizes recent findings on the neurophysiological mechanisms implemented in both networks and describes the evolution from a model centered on the distinction between top-down and bottom-up attention to a model that emphasizes the dynamic interplay between the two networks based on attentional demands. The role of the dorsal attention network (DAN) in attentional orienting, by boosting behavioral performance, has been investigated with multiple experimental approaches. This research effort allowed us to trace a distinction between DAN regions involved in shifting vs. maintenance of attention, gather evidence for the modulatory influence exerted by the DAN over sensory cortices, and identify the electrophysiological correlates of the orienting function. Simultaneously, other studies have contributed to reframing our understanding of the functions of the ventral attention network (VAN) and its relevance for behavior. The VAN is not simply involved in bottom-up attentional capture but interacts with the DAN during reorienting to behaviorally relevant targets, exhibiting a general resetting function. Further studies have confirmed the selective rightward asymmetry of the VAN, proposed a functional dissociation along the anteroposterior axis, and suggested hypotheses about its emergence during the evolution of the primate brain. Finally, novel models of network interactions explain the expression of complex attentional functions and the emergence and restorations of symptoms characterizing unilateral spatial neglect. These latter studies emphasize the importance of considering patterns of network interactions for understanding the consequences of brain lesions
A K-means multivariate approach for clustering independent components from magnetoencephalographic data
No full textIndependent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic
and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications,
ICA needs to be extended from single to multi‐session and multi‐subject studies for interpreting and
assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent
components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means
based (MAGMICK).
The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running
ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK
are: i) the implementation of an efficient set of “MEG fingerprints” designed to summarize properties of MEG
ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version
of the standard K-means procedure to improve its data-driven character. This algorithmgroups the obtained ICs
automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint
on the ICs independence, i.e. components coming from the same session (at subject level) or subject
(at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two
sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate
that the method can extract consistent patterns of spatial topography and spectral properties across sessions
and subjects that are in good agreement with the literature. In addition, these results are compared to those
from amodified version of affinity propagation clusteringmethod. The comparison, evaluated in terms of different
clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually,
these results are confirmed by a comparison with a MEG tailored version of the self-organizing group
ICA, which is largely used for fMRI IC clustering
Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization
No full textIn the last decades, several electrophysiological markers have been investigated to better understand how humans precede a signaled event. Among others, the pre-stimulus microstates' topography, representing the whole brain activity, has been proposed as a promising index of the anticipatory period in several cognitive tasks. However, to date, a clear relationship between the metrics of the pre-stimulus microstates [i.e., the global explained variance (GEV) and the frequency of occurrence (FOO)] and well-known electroencephalography marker of the anticipation (i.e., the alpha power reduction) has not been investigated. Here, after extracting the microstates during the expectancy of the semantic memory task, we investigate the correlations between the microstate features and the anticipatory alpha (8-12 Hz) power reduction (i.e., the event-related de-synchronization of the alpha rhythms; ERD) that is widely interpreted as a functional correlate of brain activation. We report a positive correlation between the occurrence of the dominant, but not non-dominant, microstate and both the mean amplitude of high-alpha ERD and the magnitude of the alpha ERD peak so that the stronger the decrease (percentage) in the alpha power, the higher the FOO of the dominant microstate. Moreover, we find a positive correlation between the occurrence of the dominant microstate and the latency of the alpha ERD peak, suggesting that subjects with higher FOO present the stronger alpha ERD closely to the target. These correlations are not significant between the GEV and all anticipatory alpha ERD indices. Our results suggest that only the occurrence of the dominant, but not non-dominant, microstate should be considered as a useful electrophysiological correlate of the cortical activation
Touch-screen system for assessing visuo-motor exploratory skills in neuropsychological disorders of spatial cognition.
No full textEnergy consumption of locomotion with orthosis versus Parastep-assisted gait: a single case study
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