Mauro Gianni Perrucci

Electrophysiological signatures of resting state networks in the human brain

Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1–80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.

The sense of touch: Embodied simulation in a visuotactile mirroring mechanism for observed animate or inanimate touch

Previous studies have shown a shared neural circuitry in the somatosensory cortices for the experience of ones own body being touched and the sight of intentional touch. Using functional magnetic resonance imaging (fMRI), the present study aimed to elucidate whether the activation of a visuotactile mirroring mechanism during touch observation applies to the sight of any touch, that is, whether it is independent of the intentionality of observed touching agent. During fMRI scanning, healthy participants viewed video clips depicting a touch that was intentional or accidental, and occurring between animate or inanimate objects. Analyses showed equal overlapping activation for all the touch observation conditions and the experience of ones own body being touched in the bilateral secondary somatosensory cortex (SII), left inferior parietal lobule (IPL)/supramarginal gyrus, bilateral temporal-occipital junction, and left precentral gyrus. A significant difference between the sight of an intentional touch, compared to an accidental touch, was found in the left primary somatosensory cortex (SI/Brodmanns area [BA] 2). Interestingly, activation in SI/BA 2 significantly correlated with the degree of intentionality of the observed touch stimuli as rated by participants. Our findings show that activation of a visuotactile mirroring mechanism for touch observation might underpin an abstract notion of touch, whereas activation in SI might reflect a human tendency to resonate more with a present or assumed intentional touching agent.

Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis

The simultaneous recording of EEG and fMRI is a promising method for combining the electrophysiological and hemodynamic information on cerebral dynamics. However, EEG recordings performed in the MRI scanner are contaminated by imaging, ballistocardiographic (BCG) and ocular artifacts. A number of processing techniques for the cancellation of fMRI environment disturbances exist: the most popular is averaged artifact subtraction (AAS), which performs well for the imaging artifact, but has some limitations in removing the BCG artifact, due to the variability in cardiac wave duration and shape; furthermore, no processing method to attenuate ocular artifact is currently used in EEG/fMRI, and contaminated epochs are simply rejected before signal analysis. In this work, we present a comprehensive method based on independent component analysis (ICA) for simultaneously removing BCG and ocular artifacts from the EEG recordings, as well as residual MRI contamination left by AAS. The ICA method has been tested on event-related potentials (ERPs) obtained from a visual oddball paradigm: it is very effective in attenuating artifacts in order to reconstruct clear brain signals from EEG acquired in the MRI scanner. It performs significantly better than the AAS method in removing the BCG artifact. Furthermore, since ocular artifacts can be completely suppressed, a larger number of trials is available for analysis. A comparison of ERPs inside the magnetic environment with those obtained out of the MRI scanner confirms that no systematic bias in the ERP waveform is produced by the ICA method.

Neural correlates of focused attention and cognitive monitoring in meditation.

Meditation refers to a family of complex emotional and attentional regulatory practices, which can be classified into two main styles - focused attention (FA) and open monitoring (OM) - involving different attentional, cognitive monitoring and awareness processes. In a functional magnetic resonance study we originally characterized and contrasted FA and OM meditation forms within the same experiment, by an integrated FA-OM design. Theravada Buddhist monks, expert in both FA and OM meditation forms, and lay novices with 10 days of meditation practice, participated in the experiment. Our evidence suggests that expert meditators control cognitive engagement in conscious processing of sensory-related, thought and emotion contents, by massive self-regulation of fronto-parietal and insular areas in the left hemisphere, in a meditation state-dependent fashion. We also found that anterior cingulate and dorsolateral prefrontal cortices play antagonist roles in the executive control of the attention setting in meditation tasks. Our findings resolve the controversy between the hypothesis that meditative states are associated to transient hypofrontality or deactivation of executive brain areas, and evidence about the activation of executive brain areas in meditation. Finally, our study suggests that a functional reorganization of brain activity patterns for focused attention and cognitive monitoring takes place with mental practice, and that meditation-related neuroplasticity is crucially associated to a functional reorganization of activity patterns in prefrontal cortex and in the insula.

Large-scale brain networks account for sustained and transient activity during target detection

Target detection paradigms have been widely applied in the study of human cognitive functions, particularly those associated with arousal, attention, stimulus processing and memory. In EEG recordings, the detection of task-relevant stimuli elicits the P300 component, a transient response with latency around 300 ms. The P300 response has been shown to be affected by the amount of mental effort and learning, as well as habituation. Furthermore, trial-by-trial variability of the P300 component has been associated with inter-stimulus interval, target-to-target interval or target probability; however, understanding the mechanisms underlying this variability is still an open question. In order to investigate whether it could be related to the distinct cortical networks in which coherent intrinsic activity is organized, and to understand the contribution of those networks to target detection processes, we carried out a simultaneous EEG-fMRI study, collecting data from 13 healthy subjects during a visual oddball task. We identified five large-scale networks, that largely overlap with the dorsal attention, the ventral attention, the core, the visual and the sensory-motor networks. Since the P300 component has been consistently associated with target detection, we concentrated on the first two brain networks, the time-course of which showed a modulation with the P300 response as detected in simultaneous EEG recordings. A trial-by-trial EEG-fMRI correlation approach revealed that they are involved in target detection with different functional roles: the ventral attention network, dedicated to revealing salient stimuli, was transiently activated by the occurrence of targets; the dorsal attention network, usually engaged during voluntary orienting, reflected sustained activity, possibly related to search for targets.

Somato-motor inhibitory processing in humans: An event-related functional MRI study

Inhibiting inappropriate behavior and thoughts is an essential ability for humans, but the regions responsible for inhibitory processing are a matter of continuous debate. This is the first study of somatosensory go/nogo tasks using event-related functional magnetic resonance imaging (fMRI). Fifteen subjects preformed two different types of go/nogo task, i.e. (1) Movement and (2) Count, to compare with previous studies using visual go/nogo tasks, and confirm whether the inhibitory processing is dependent on sensory modalities. Go and nogo stimuli were presented with an even probability. Our data indicated that the response inhibition network involved the dorsolateral (DLPFC) and ventrolateral (VLPFC) prefrontal cortices, pre-supplementary motor area (pre-SMA), anterior cingulate cortex (ACC), inferior parietal lobule (IPL), insula, and temporoparietal junction (TPJ), which were consistent with previous results obtained using visual go/nogo tasks. These activities existed in both Movement and Count Nogo trials. Therefore, our results suggest that the network for inhibitory processing is not dependent on sensory modalities but reflects common neural activities. In addition, there were differences of activation intensity between Movement and Count Nogo trials in the prefrontal cortex, temporal lobe, and ACC. Thus, inhibitory processing would involve two neural networks, common and uncommon regions, depending on the required response mode.

The use of standardized infinity reference in EEG coherency studies

The study of large scale interactions in the brain from EEG signals is a promising method for the identification of functional networks. However, the validity of a large scale parameter is limited by two factors: the use of a non-neutral reference and the artifactual self-interactions between the measured EEG signals introduced by volume conduction. In this paper, we propose an approach to study large scale EEG coherency in which these factors are eliminated. Artifactual self-interaction by volume conduction is eliminated by using the imaginary part of the complex coherency as a measure of interaction and the Reference Electrode Standardization Technique (REST) is used for the approximate standardization of the reference of scalp EEG recordings to a point at infinity that, being far from all possible neural sources, acts like a neutral virtual reference. The application of our approach to simulated and real EEG data shows that the detection of interaction, as opposed to artifacts due to reference and volume conduction, is a goal that can be achieved from the study of a large scale parameter.

Human secondary somatosensory cortex is involved in the processing of somatosensory rare stimuli: An fMRI study

In the human somatosensory system, the contralateral primary somatosensory cortex (SI) is presumed to process and encode type and intensity of the sensory inputs, whereas the bilateral secondary somatosensory cortex (SII) is believed to perform higher order functions including sensorimotor integration, integration of information from the two body halves, attention, learning and memory. In this fMRI study we investigated the effect of attention on the activation of SI and SII, as induced by nonpainful and painful rare deviant electric stimuli during somatosensory oddball tasks. The working hypothesis is of stronger effects of attention on SII with respect to SI. Four runs were acquired according to an oddball scheme. Frequent nonpainful electrical stimuli were delivered to the ulnar nerve at motor threshold, whereas rare/deviant stimuli were delivered to median nerve in four conditions (one condition per run): nonpainful, painful, counting nonpainful, and counting painful. Results showed a statistically significant fMRI activation in bilateral SII but not in contralateral SI when the rare/deviant median nerve stimuli were delivered at nonpainful and painful levels as well as at the two levels of attention considered (i.e., associated with counting and non-counting tasks). Furthermore, fMRI activation in SII did not differ across the different levels of stimulus intensity (nonpainful, painful) and attention (non-counting, counting). These results corroborate the notion that SII is the target of independent pathways for the processing and integration of nonpainful and painful somatosensory stimuli salient for further high-order elaborations.

Dynamic reorganization of human resting-state networks during visuospatial attention

Significance The brain is never at rest, and patterns of ongoing correlated activity have been found to resemble patterns during active behavior. A fundamental problem in neuroscience concerns the relationship between spontaneous and task-driven activity. During a demanding task that requires selective attention to sensory stimuli, correlated patterns of spontaneous (rest) activity are generally preserved. However, specific changes in synchronization occur within and between networks that correlate with behavioral performance. These results indicate that attention modifies spontaneous activity patterns in support of task performance. Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing “idling” activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a “prior” for attention selection.

Interspecies activity correlations reveal functional correspondence between monkey and human brain areas

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. For cases in which functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assessed similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by temporal correlation. Using natural vision data, we revealed regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models.