Exploration and modulation of brain network interactions with noninvasive brain stimulation in combination with neuroimaging

Abstract

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to alter brain activity noninvasively, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional magnetic resonance imaging, positron emission tomography and electroencephalography, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner.

Conflict of interest statement

Conflict of interest

APL serves on the scientific advisory boards for Nexstim, Neuronix, Starlab Neuroscience, Allied Mind, Neosync, and Novavision, and is an inventor on patents and patent applications related to noninvasive brain stimulation and the real-time integration of transcranial magnetic stimulation with electroencephalography and magnetic resonance imaging. MMS, MBW, and MDF declare no conflicts.

© 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Figures

Figure 1. Network architectures and efficiency statistics

(A) Different types of networks. Regular network in which nodes are connected only to their two nearest neighbors on either side (left). Small world network, in which a small number of local connections are replaced by long-distance connections at random locations (center). Random network, in which nodes are connected at random, with a resulting loss of local connectivity (right). (B) Global efficiency (Eglobal, solid line) and local efficiency (Elocal, dashed line) as a function of the probability of random connections.

Figure 2. Theoretical mechanisms of network pathology

(A) The normal network, comprised of three densely connected local clusters, with a few long-range connections between clusters. (B) Loss of a node (and thus associated connections, dashed lines) in the top cluster. (C) A loss of connections (dashed lines) without a change in the nodes. (D) Increased connectivity (thick lines) within a local cluster (bottom right). (E) Increased local connectivity (thick line, top cluster) along with loss of a long-distance connection between clusters (dashed line). These changes would result in a substantial change in network information processing metrics (increased clustering coefficient and local efficiency, but also increased path length and decreased global efficiency).

Figure 3. Generation of resting-state correlation maps

(A) Seed region in the left somatomotor cortex (LSMC) is shown in yellow. (B) Time course of spontaneous BOLD activity recorded during resting fixation and extracted from the seed region. (C) Voxels significantly correlated with the extracted time course assessed using a random effects analysis across a population of ten subjects (Z score values). In addition to correlations with the right somatomotor cortex (RSMC) and medial motor areas, correlations are observed with secondary somatosensory association cortex (S2), posterior nuclei of the thalamus (Th), putamen (P), and cerebellum (Cer). Reproduced with permission from (Fox and Raichle 2007).

Figure 4. Brain regions with significant correlations between cerebral blood flow (CBF) and the number of TMS pulse trains in a rTMS-PET study

(A) Significant correlation in the stimulated area, the left frontal eye field (FEF). (B) Significant correlation in a distant area, the ipsilateral parieto-occipital (PO) region. (Modified with permission from Paus et al, 1997).

Figure 5. BOLD fMRI and EEG responses to TMS

(A) Bold fMRI response to rTMS of left dorsal premotor cortex. Six transverse sections showing activity changes in the cingulate gyrus, ventral premotor cortex, auditory cortex, caudate nucleus, left posterior temporal lobe, medial geniculate and cerebellum. (Modified with permission from Bestmann et al, 2005). (B) EEG response to single-pulse stimulation of left sensorimotor cortex. Top panels: Scalp potential with head shown as a two dimensional projection. The contour lines depict constant potentials; positive potentials are red, negative potentials are blue. Bottom panels: Current-density distributions: the calculated current-density at each time point is depicted as a percentage of the maximum current-density at that time point. For this subject, at 11 ms, the activation had spread from below the coil center to involve the surrounding frontal and parietal cortices. Contralateral activation emerged at 22 ms, and peaked at 24 ms. (Modified with permission from Komssi et al, 2002.)

Figure 6. Spatiotemporal TMS-evoked current maps during wakefulness and NREM sleep in two subjects

The black traces represent the global mean field power at each time point; when the black line is above the horizontal yellow line, the global power of the evoked field was significantly higher (>6 SD) than the mean prestimulus level. For each significant time sample, maximum current sources were plotted on the cortical surface and color-coded according to their latency of activation (light blue, 0 ms; red, 300 ms). The yellow cross indicates the location of the TMS target on the cortical surface. (Modified with permission from Massimini et al, 2005.)

Figure 7. Connectivity of left M1 hand region, based on structural equation modeling of PET data after TMS

TMS is applied to the left primary motor cortex, and blood flow changes examined with PET. The connectivity is determined using structural equation modeling in regions of interest based on the timing of activity changes in these different regions. The pink connections are the first order paths, where the TMS “signal” propagates immediately after motor cortex stimulation. The second-order paths, where the activity changes propagate from the first-order regions, are illustrated in green. The third order paths are shown in blue. Regions are as follows: LMI - Left primary sensorimotor cortex; LTHvpl - Left ventral posterolateral nucleus of the thalamus; LTHvl - Left ventral lateral nucleus of the thalamus; LPPC = Left posterior parietal cortex; LPMv - Left ventral premotor area; Cing - Cingulate gyrus; SMA - Supplementary motor area; RSII - Right secondary somatosensory Cortex; LSII - Left secondary somatosensory cortex; RTHvl - Right ventrolateral thalamus; Rcer - Right cerebellum. (Modified with permission from Laird et al, 2008)

Figure 8. Compensatory activation increases in the action selection network after left dorsal premotor cortex rTMS

1Hz (inhibitory) rTMS of left dorsal premotor cortex results in increased activation (BOLD signal) most prominently in right dorsal premotor cortex (rPMd) and right cingulate motor area (rCMA). Changes were also seen in the left supplementary motor area (lSMA), the left cingulate motor area (lCMA), and right primary motor cortex (rM1). The figures show the mean percent BOLD signal change (% BSC) when subjects performed the action selection (black bars) or the control action execution (white bars) tasks. Note that the TMS-induced activation increases occur only with action selection. (Modified with permission from O’Shea et al, 2007).

Figure 9. Changes in cerebral blood flow after rTMS for treatment of depression

The figure shows the significant increases in absolute regional cerebral blood flow (rCBF), relative to the pretreatment baseline, 72 hours after 2 weeks of 20-Hz rTMS at 100% of motor threshold over the left prefrontal cortex in a group of 10 depressed patients. A statistical parametric map shows voxels that occur within significant clusters and is color coded according to their raw p value. Increases in rCBF are displayed with a red– orange–yellow color scale. The number in the top right corner of each horizontal section (top two rows) indicates its position in mm with respect to the anterior commissure (AC)–posterior commissure plane. Twenty-hertz rTMS resulted in widespread increases in rCBF in the following regions: prefrontal cortex (L > R), cingulate gyrus (L >> R), bilateral insula, basal ganglia, uncus, hippocampus, parahippocampus, thalamus, cerebellum, and left amygdale. (Modified with permission from Speer et al, 2000).

Figure 10. Changes in covariation between brain regions after rTMS treatment for auditory hallucinations in schizophrenic patients

Low-frequency (0.9 Hz) rTMS was applied to the left temporoparietal region. The figure shows the positive (black) and negative (gray) covariation between mean FDG uptake in the left superior temporal cortex before (A) and after (B) rTMS treatment. Before rTMS, there was positive covariation with a large cluster consisting of the bilateral inferior, middle, and superior temporal gyri, parahippocampal gyrus, uncus, insula, anterior cingulate and left fusiform gyrus. Negative covariation was seen with the right inferior parietal lobule, precuneus, postcentral and precentral gyrus, and left precentral gyrus, superior frontal gyrus and precuneus. After rTMS, the regions of both positive and negative covariation were diminished in size. (Modified with permission from Horacek et al, 2007).

Figure 11. EEG response to TMS stimulation in schizophrenic patients and healthy controls

(A). The global mean field power derived from all 60 electrodes. Relative to controls (blue), the global mean field power was decreased in schizophrenic patients (red) between 12 and 100 ms following TMS (pink area). The decrease peaked at 22 and 55ms. (B) The electrode topography of the two peaks, demonstrating the electrodes with significantly different TMS-induced activity between healthy subjects and controls (blue electrodes). There are four centrally located electrodes with differential activity at 22ms, and 6 electrodes (3 central, 3 frontal) with differential activity at 55 ms. (C) Grand averages for a significant electrode (blue diamond) and nonsignificant electrode (gray diamond) in schizophrenic patients (red) and controls (blue). (Modified with permission from Ferrarelli et al, 2008).

Figure 12. Changes in EEG synchronization as a function of task state and tDCS in different frequency bands

Shows EEG channels that become significantly more synchronized (red) or desynchronized (blue) in different frequency bands. Columns from left to right demonstrate the following comparisons: (1) Task before stimulation – rest before stimulation; (2) Task after stimulation – rest before stimulation; (3) Rest after stimulation – rest before stimulation; and (4) Task after stimulation – task before stimulation. (Modified with permission from Polania et al, 2010a).