Dynamic functional brain networks underlying the temporal inertia of negative emotions

Affective inertia represents the lasting impact of transient emotions at one time point on affective state at a subsequent time point. Here we describe the neural underpinnings of inertia following negative emotions elicited by sad events in movies. Using a co-activation pattern analysis of dynamic functional connectivity, we examined the temporal expression and reciprocal interactions among brain-wide networks during movies and subsequent resting periods in twenty healthy subjects. Our findings revealed distinctive spatiotemporal expression of visual (VIS), default mode (DMN), central executive (CEN), and frontoparietal control (FPCN) networks both in negative movies and in rest periods following these movies. We also identified different reciprocal relationships among these networks, in transitions from movie to rest. While FPCN and DMN expression increased during and after negative movies, respectively, FPCN occurrences during the movie predicted lower DMN and higher CEN expression during subsequent rest after neutral movies, but this relationship was reversed after the elicitation of negative emotions. Changes in FPCN and DMN activity correlated with more negative subjective affect. These findings provide new insights into the transient interactions of intrinsic brain networks underpinning the inertia of negative emotions. More specifically, they describe a major role of FPCN in emotion elicitation processes, with prolonged impact on DMN activity in subsequent rest, presumably involved in emotion regulation and restoration of homeostatic balance after negative events.

Whole-brain structural connectivity in temporal lobe epilepsy: a Diffusion Spectrum Imaging study

Alessandro Daducci, Alessandra Griffa, François Lazeyras, Alia Lemkaddem, Jean-Philippe Thiran

Introduction: Medial Temporal Lobe Epilepsy (mTLE) with hippocampal sclerosis is the most frequent cause of drug-resistant focal epilepsy in adults. These patients suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor Imaging and functional MRI studies. Diffusion spectrum imaging (DSI) is a new diffusion imaging technique with high angular resolution for improving the mapping of white matter tracts [1]. In this study, we used DSI to investigate the whole brain effect of TLE as reflected by topological measures of the structural connectivity network. Methods: Eight patients with right-sided mTLE and hippocampal sclerosis and 25 controls underwent our DSI protocol at 3T using a 32 channel coil: DSI (voxel size 2.2x2.2x3mm; 44 slices, 257 diffusion directions; max b-value = 6400 s/mm2), 3D T1-weighted MPRAGE and 3D T2-weighted images. The analysis was performed using the Connectome Mapper. The cortical and subcortical grey matters were parcellated into 86 Regions of Interest (ROI) with anatomical landmarks using Freesurfer 5.0. The ROIs were coregistered to the diffusion data by using a nonlinear registration between T1 and T2, then T2 to the diffusion space. The Diffusion Tool Kit was used for the reconstruction of the diffusion Orientation Distribution Function in each voxel. Streamline fibre-tracking was then performed from each voxel in the white matter areas using an in-house streamline-based algorithm. Two scalar maps, the Fractional Anisotropy and the Generalized Fractional Anisotropy were calculated. For each patient, the connectivity between every region pair was estimated was used to construct a connectivity matrix (the adjacency matrix of the structural network). Finally we used topological measures in order to reduce the data and obtain whole-brain characteristics of the network [2]: characteristic Path Length (L), Clustering Coefficient (C) and Small Worldness (S) where S=(C/Crand)/(L/ Lrand) with Crand and Lrand are computed for a random network. Significant differences between the mTLE and control groups were assessed using a Wilcoxon rank-sum test. Results: In patients, we found a higher characteristic path length (0.0288), with a lower clustering coefficient (0.0079) and reduced small-worldness (p=0.000058) compared to controls. Network nodes that contributed significantly to these alterations were located within as well as outside the temporal lobe in both hemispheres, although with a predominance for the ipsilateral hemisphere and bilateral limbic structures. The pattern of significant nodes showed concordance with brain regions known to be involved in epileptic networks in patients with mTLE. Conclusions: Our results show a reduced efficiency of structural brain networks and altered connectivity patterns that are concordant with the mapping of functional epileptic networks [3] and altered functional connectivity [4] in patients with mTLE. Therefore, the network in mTLE is less segregated than in controls with reduced global interactions between the nodes and reduced specialised communities. Further studies are needed to establish the relevance of these findings with respect to the propagation of epileptic activity, cognitive deficits in mTLE and outcome of epilepsy surgery in individual patients.

2012

Brain network analysis of patients with Temporal Lobe Epilepsy

Alessandro Daducci, Alessandra Griffa, François Lazeyras, Alia Lemkaddem, Djalel Eddine Meskaldji, Jean-Philippe Thiran

Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor MR Imaging, volumetric and functional MRI studies. Diffusion Spectrum Imaging (DSI) is a diffusion imaging technique with high angular resolution for improving the mapping of white matter pathways. In this study, we used DSI, connectivity matrices and topological measures to investigate how the alteration in structural connectivity influences whole brain structural networks. Eleven patients with right-sided TLE and hippocampal sclerosis and 18 controls underwent our DSI protocol at 3T. The cortical and subcortical grey matters were parcellated into 86 regions of interest and the connectivity between every region pair was estimated using global tractography and a connectivity matrix (the adjacency matrix of the structural network). We then compared the networks of patients and controls using topological measures. In patients, we found a higher characteristic path length and a lower clustering coefficient compared to controls. Local measures at node level of the clustering and efficiency showed a significant difference after a multiple comparison correction (Bonferroni). These significant nodes were located within as well outside the temporal lobe, and the localisation of most of them was consistent with regions known to be part of epileptic networks in TLE. Our results show altered connectivity patterns that are concordant with the mapping of functional epileptic networks in patients with TLE. Further studies are needed to establish the relevance of these findings for the propagation of epileptic activity, cognitive deficits in medial TLE and outcome of epilepsy surgery in individual patients.

2013

Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks

Sven Haller, Rotem Roza Kopel, Dimitri Nestor Alice Van De Ville

The default mode (DM) network is a major large-scale cerebral network that can be identified with functional magnetic resonance imaging (fMRI) during resting state. Most studies consider functional connectivity networks as stationary phenomena. Consequently, the transient behavior of the DM network and its subnetworks is still largely unexplored. Most functional connectivity fMRI studies assess the steady state of resting without any task. To specifically investigate the recovery of the DM network during the transition from activation to rest, we implemented a cognitively demanding real-time fMRI neurofeedback task that targeted down-regulation of the primary auditory cortex. Each of twelve healthy subjects performed 16 block-design fMRI runs (4 runs per day repeated on 4 days) resulting 192 runs in total. The analysis included data-driven independent component analysis (ICA) and high-resolution latency estimation between the four components that corresponded to subnetworks of the DM network. These different subnetworks reemerged after regulation with an average time lag or 3.3 s and a time lag of 4.4 s between the first and fourth components; i.e., the DM recovery first shifts from anterior to posterior, and then gradually focuses on the ventral part of the posterior cingulate cortex, which is known to be implicated in internally directed cognition. In addition, we found less reactivation in the early anterior subnetwork as regulation strength increased, but more reactivation with larger regulation for the late subnetwork that encompassed the ventral PCC. This finding confirms that the level of task engagement influences inversely the subsequent recovery of regions related to attention compared to those related to internally directed cognition. (C) 2012 Elsevier Inc. All rights reserved.

Elsevier2012