Stefania Della Penna

Dynamic functional connectivity: promise, issues, and interpretations.

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.

Temporal dynamics of spontaneous MEG activity in brain networks

Functional MRI (fMRI) studies have shown that low-frequency (<0.1 Hz) spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal during restful wakefulness are coherent within distributed large-scale cortical and subcortical networks (resting state networks, RSNs). The neuronal mechanisms underlying RSNs remain poorly understood. Here, we describe magnetoencephalographic correspondents of two well-characterized RSNs: the dorsal attention and the default mode networks. Seed-based correlation mapping was performed using time-dependent MEG power reconstructed at each voxel within the brain. The topography of RSNs computed on the basis of extended (5 min) epochs was similar to that observed with fMRI but confined to the same hemisphere as the seed region. Analyses taking into account the nonstationarity of MEG activity showed transient formation of more complete RSNs, including nodes in the contralateral hemisphere. Spectral analysis indicated that RSNs manifest in MEG as synchronous modulation of band-limited power primarily within the theta, alpha, and beta bands—that is, in frequencies slower than those associated with the local electrophysiological correlates of event-related BOLD responses.

A Cortical Core for Dynamic Integration of Functional Networks in the Resting Human Brain

We used magneto-encephalography to study the temporal dynamics of band-limited power correlation at rest within and across six brain networks previously defined by prior functional magnetic resonance imaging (fMRI) studies. Epochs of transiently high within-network band limited power (BLP) correlation were identified and correlation of BLP time-series across networks was assessed in these epochs. These analyses demonstrate that functional networks are not equivalent with respect to cross-network interactions. The default-mode network and the posterior cingulate cortex, in particular, exhibit the highest degree of transient BLP correlation with other networks especially in the 14-25 Hz (β band) frequency range. Our results indicate that the previously demonstrated neuroanatomical centrality of the PCC and DMN has a physiological counterpart in the temporal dynamics of network interaction at behaviorally relevant timescales. This interaction involved subsets of nodes from other networks during periods in which their internal correlation was low.

Comparison between SI and SII responses as a function of stimulus intensity.

In this MEG study we investigated the differences in responses to somatosensory electrical stimuli between primary (SI) and secondary (SII) sensory cortices using 10 different levels of stimulus intensity, starting from below the sensory threshold up to a weak painful level. SI dipole source linearly increased in amplitude as the stimulus intensity raised up to a strong motor level and then saturated at higher stimulation levels. The contralateral and ipsilateral SII dipole source strengths followed the stimulus intensity growing up to the motor threshold, but showed a decrease at the strong motor level, followed by an increase as the stimulus intensity raised towards the weak painful threshold. These results suggest different responses of SI and SII cortices as the intensity of stimulation rises from non-painful to painful values.

SQUID systems for biomagnetic imaging

This review paper illustrates the different SQUID based systems used for biomagnetic imaging. The review is divided into nine sections. The first three sections are introductory: section 1 is a short overview of the topic; section 2 summarizes how the biomagnetic fields are generated and what are the basic mathematical models for the field sources; section 3 illustrates the principles of operation of the SQUID device. Sections 4-8 are specifically devoted to the description of the different systems used for biomagnetic measurements: section 4 discusses the different types of detection coils; section 5 illustrates the SQUID sensors specifically designed for biomagnetic applications together with the necessary driving electronics, with special emphasis on high-temperature superconductivity (HTS) SQUIDs, since HTS devices are still in a developing stage; section 6 illustrates the different noise reduction techniques; section 7 describes the different multichannel sensors presently operating; and, finally, section 8 gives a hint of what kind of physiological and/or clinical information may be gathered by the biomagnetic technique. Section 9 suggests some future trends for the biomagnetic technique.

Topographic organization of the human primary and secondary somatosensory areas: an fMRI study.

The topographical organization of SI and SII somatosensory areas was investigated using fMRI at 1.5 T and electrical sensory stimulation. Electrical stimuli were delivered unilaterally to the median nerve at the wrist and to the tibial nerve at the medial malleolus, during a block paradigm study. In all subjects, activation was observed, contralaterally to the stimulated side, in the post-central gyrus, in the posterior parietal cortex, in the mesial pre-frontal region and, bilaterally, in the supratemporal region at the level of the Sylvian fissure. The latter region, corresponding presumably to SII, showed a rough but clearcut topographical organization, with the median nerve areas located more posteriorly. In addition, weaker activations were observed in some subjects in the ipsilateral mesial prefrontal region and in the ipsilateral posterior parietal cortex. Information contained in the present study represent an interesting database for future investigations on the effects of sensorimotor learning in normal individuals on plastic reorganization following a lesion of the primary sensorimotor centers, i.e. in stroke patients, on the topography and balance between upper and lower limb representations in primary and secondary somatosensory cortices.

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.

A signal-processing pipeline for magnetoencephalography resting-state networks.

To study functional connectivity using magnetoencephalographic (MEG) data, the high-quality source-level reconstruction of brain activity constitutes a critical element. MEG resting-state networks (RSNs) have been documented by means of a dedicated processing pipeline: MEG recordings are decomposed by independent component analysis (ICA) into artifact and brain components (ICs); next, the channel maps associated with the latter ones are projected into the source space and the resulting voxel-wise weights are used to linearly combine the IC time courses. An extensive description of the proposed pipeline is provided here, along with an assessment of its performances with respect to alternative approaches. The following investigations were carried out: (1) ICA decomposition algorithm. Synthetic data are used to assess the sensitivity of the ICA results to the decomposition algorithm, by testing FastICA, INFOMAX, and SOBI. FastICA with deflation approach, a standard solution, provides the best decomposition. (2) Recombination of brain ICs versus subtraction of artifactual ICs (at the channel level). Both the recombination of the brain ICs in the sensor space and the classical procedure of subtracting the artifactual ICs from the recordings provide a suitable reconstruction, with a lower distortion using the latter approach. (3) Recombination of brain ICs after localization versus localization of artifact-corrected recordings. The brain IC recombination after source localization, as implemented in the proposed pipeline, provides a lower source-level signal distortion. (4) Detection of RSNs. The accuracy in source-level reconstruction by the proposed pipeline is confirmed by an improved specificity in the retrieval of RSNs from experimental data.

The connectivity of functional cores reveals different degrees of segregation and integration in the brain at rest

The principles of functional specialization and integration in the resting brain are implemented in a complex system of specialized networks that share some degree of interaction. Recent studies have identified wider functional modules compared to previously defined networks and reported a small-world architecture of brain activity in which central nodes balance the pressure to evolve segregated pathways with the integration of local systems. The accurate identification of such central nodes is crucial but might be challenging for several reasons, e.g. inter-subject variability and physiological/pathological network plasticity, and recent works reported partially inconsistent results concerning the properties of these cortical hubs. Here, we applied a whole-brain data-driven approach to extract cortical functional cores and examined their connectivity from a resting state fMRI experiment on healthy subjects. Two main statistically significant cores, centered on the posterior cingulate cortex and the supplementary motor area, were extracted and their functional connectivity maps, thresholded at three statistical levels, revealed the presence of two complex systems. One system is consistent with the default mode network (DMN) and gradually connects to visual regions, the other centered on motor regions and gradually connects to more sensory-specific portions of cortex. These two large scale networks eventually converged to regions belonging to the medial aspect of the DMN, potentially allowing inter-network interactions.

Anatomical Segregation of Visual Selection Mechanisms in Human Parietal Cortex

Visual selection requires mechanisms for representing object salience and for shifting the focus of processing to novel objects. It is not clear from computational or neural models whether these operations are performed within the same or different brain regions. Here, we use repetitive transcranial magnetic stimulation to briefly interfere with neural activity in individually localized regions of human posterior parietal cortex (PPC) that are putatively involved in attending to contralateral locations or shifting attention between locations. Stimulation over right ventral intraparietal sulcus impaired target discrimination at contralateral locations, whereas stimulation over right medial superior parietal lobule impaired target discrimination after a shift of attention regardless of its location. This double dissociation is consistent with neuroimaging studies and indicates that mechanisms of visual selection are partly anatomically segregated in human PPC.