Exploration and modulation of brain network interactions with noninvasive brain stimulation in combination with neuroimaging.
- Authors
- Shafi, Mouhsin M; Westover, M Brandon; Fox, Michael D; Pascual-Leone, Alvaro
- Year
- 2012
- Journal
- The European journal of neuroscience
- PMID
- 22429242
- DOI
- 10.1111/j.1460-9568.2012.08035.x
- PMCID
- PMC3313459
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.
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.
LLM interpretation
This figure consists of three network diagrams (A) and a line graph (B). Panel A illustrates the structural transition from a regular network (left) to a small-world network (center) and finally a random network (right). Panel B plots global efficiency ($E_{global}$, solid line) and local efficiency ($E_{local}$, dashed line) against the probability of random connections ($p$) on a logarithmic x-axis, showing that as $p$ increases, global efficiency rises significantly while local efficiency remains relatively stable before declining.
Changes in covariation between brain regions after rTMS treatment for auditory hallucinations in schizophrenic patientsLow-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).
LLM interpretation
This figure consists of brain mapping diagrams showing the positive (black) and negative (gray) covariation of mean FDG uptake in the left superior temporal cortex before (A) and after (B) rTMS treatment. The visualizations include sagittal, coronal, and axial views for both conditions. A comparison between the two rows shows a visible reduction in the size and extent of both positive and negative covariation clusters following the treatment.
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).
LLM interpretation
This figure presents EEG responses to TMS stimulation comparing schizophrenic patients (red) and healthy controls (blue). Panel A shows a line graph of global mean field power ($\mu$V vs. ms), where patients exhibit decreased power relative to controls between 12 and 100 ms (pink shaded area), peaking at 22 and 55 ms. Panel B uses topographic maps to highlight electrodes with significant differences (blue dots) at these two peaks, with a color scale indicating p-values. Panel C displays grand average waveforms for one significant electrode (Ch 19) and one non-significant electrode (Ch 8).
Changes in EEG synchronization as a function of task state and tDCS in different frequency bandsShows 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 β rest before stimulation; (2) Task after stimulation β rest before stimulation; (3) Rest after stimulation β rest before stimulation; and (4) Task after stimulation β task before stimulation. (Modified with permission from Polania et al, 2010a).
LLM interpretation
This figure consists of a grid of connectivity maps showing EEG synchronization changes across five frequency bands (Theta, Alpha, Beta, Low-Gamma, and High-Gamma) and four experimental comparisons. Red lines indicate significantly increased synchronization and blue lines indicate significantly decreased synchronization between EEG channels. The columns compare task and rest states before and after tDCS stimulation, with the most dense synchronization patterns appearing in the "Task (before tDCS) - Rest (before tDCS)" and "Task (after tDCS) - Rest (before tDCS)" columns.
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).
LLM interpretation
This figure consists of five network diagrams (AβE) illustrating theoretical mechanisms of network pathology. Panel A shows a baseline network with three densely connected local clusters and sparse long-range connections. Panels B through E depict various structural alterations, including the loss of nodes (B), loss of connections (C), increased local connectivity (D), and a combination of increased local connectivity and loss of long-distance connections (E).
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).
LLM interpretation
This figure illustrates the generation of resting-state correlation maps. It consists of a brain scan showing a yellow seed region in the left somatomotor cortex (A), a line graph plotting the % BOLD change over 300 seconds (B), and a series of axial brain slices (C) displaying Z-score correlation values. The correlation maps highlight significant activity in the right somatomotor cortex (RSMC), secondary somatosensory association cortex (S2), putamen (P), thalamus (Th), and cerebellum (Cer), with a color scale ranging from -20 to 20.
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).
LLM interpretation
This figure consists of PET scan brain images showing cerebral blood flow (CBF) responses to rTMS. Panel A displays a local CBF response in the left frontal eye field (FEF), while Panel B shows a distal CBF response in the ipsilateral parieto-occipital (PO) region. A color scale at the bottom indicates t-values ranging from 3 to 5, with colored clusters overlaid on the anatomical scans to mark areas of significant correlation.
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.)
LLM interpretation
Figure A consists of six transverse BOLD fMRI sections showing areas of increased activity (highlighted in orange/yellow) following rTMS of the left dorsal premotor cortex, with activity visible in the cingulate gyrus, ventral premotor cortex, auditory cortex, caudate nucleus, left posterior temporal lobe, medial geniculate, and cerebellum. Figure B displays EEG responses to single-pulse stimulation of the left sensorimotor cortex, featuring top-panel scalp potential contour maps (red for positive, blue for negative) and bottom-panel current-density distributions. The current-density maps show activation spreading from the coil center to frontal and parietal cortices at 11 ms, with contralateral activation emerging at 22 ms and peaking at 24 ms.
Spatiotemporal TMS-evoked current maps during wakefulness and NREM sleep in two subjectsThe 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.)
LLM interpretation
This figure presents spatiotemporal TMS-evoked current maps for two subjects during wakefulness and NREM sleep. It consists of time-series plots of global mean field power (black lines) relative to a significance threshold (yellow line) and corresponding cortical surface maps showing the location and latency of maximum current sources (color-coded from light blue to red). In both subjects, wakefulness shows prolonged and widespread cortical activation above the threshold, whereas NREM sleep shows a brief, localized initial response that quickly drops below the significance threshold.
Connectivity of left M1 hand region, based on structural equation modeling of PET data after TMSTMS 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 βsignalβ 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)
LLM interpretation
This figure is a structural equation modeling diagram illustrating the connectivity of the left M1 hand region (LMI) following TMS stimulation. Directed arrows represent the propagation of activity, color-coded by order: pink for first-order paths, green for second-order, and blue for third-order. The network connects LMI to various brain regions, including the thalamus (LTHvl, LTHvpl, RTHvl), parietal cortex (LPPC), premotor area (LPMv), and cerebellum (RCer).
Compensatory activation increases in the action selection network after left dorsal premotor cortex rTMS1Hz (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 OβShea et al, 2007).
LLM interpretation
This figure consists of three fMRI brain slices showing areas of activation and six bar charts representing the mean percent BOLD signal change (% BSC) across different brain regions (rM1, lSMA, rPMd, lCMA, and rCMA). The bar charts compare "Execute" (white bars) and "Select" (black bars) tasks before (Pre TMS) and after (Post TMS) inhibitory rTMS of the left dorsal premotor cortex. In regions such as rPMd, rCMA, and lSMA, there is a visible increase in % BSC for the "Select" task post-TMS compared to pre-TMS, while the "Execute" task remains relatively stable.
Changes in cerebral blood flow after rTMS for treatment of depressionThe 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 redβ orangeβyellow 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)βposterior 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).
LLM interpretation
This figure presents a statistical parametric map (SPM) consisting of multiple axial, coronal, and sagittal brain slices showing changes in regional cerebral blood flow (rCBF) after rTMS treatment. A red-orange-yellow color scale indicates significant increases in rCBF, with the color intensity corresponding to raw 2-tailed p-values ranging from <.05 to <.0001. Widespread increases are visible across various regions, including the prefrontal cortex, cingulate gyrus, basal ganglia, and cerebellum.
| # | Section | Preview |
|---|---|---|
| 40 | TRANSCRANIAL BRAIN STIMULATION AND NETWORK ANALYSIS | Such combined-modality studies permit analysis of precisely how different regions interact. Because⦠|
| 41 | TRANSCRANIAL BRAIN STIMULATION AND NETWORK ANALYSIS | Combined-modality studies involving TMS can also be used to assess how neural functional⦠|
| 42 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE | There has been an explosion of recent research suggesting that the pathophysiology underlying a⦠|
| 43 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE | identify have not been validated in experiments that directly manipulate neural activity.β¦ |
| 44 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE | The integration of brain stimulation techniques with traditional neuroimaging network analysis⦠|
| 45 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE | Because transcranial brain stimulation techniques provide a means to modulate cortical activity in a⦠|
| 46 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | Stroke, once the prime example of how a focal brain lesion can lead to a neurological deficit, isβ¦ |
| 47 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | Experiments utilizing TMS have provided insights into the network mechanisms of stroke recovery, asβ¦ |
| 48 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | also demonstrate an increase in the number of cortical sites from where an MEP of the paretic handβ¦ |
| 49 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | and superior parietal lobule all produced significant decreases in performance of motor tasks by theβ¦ |
| 50 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | TMS in combination with neuroimaging techniques can be used to study the dynamic mechanisms that theβ¦ |
| 51 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | recovered to baseline, demonstrated increased activation in the right premotor cortex, leftβ¦ |
| 52 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | Similarly, another important TMS/PET study (Chouinard et al., 2006) explored the effects of physicalβ¦ |
| 53 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | Another clinically significant study assessed the impact of interhemispheric inhibition from theβ¦ |
| 54 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | These and other studies have motivated research investigating the therapeutic potential ofβ¦ |
| 55 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | In a particularly intriguing recent study, Grefkes et al (2010) utilized fMRI and functionalβ¦ |
| 56 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Motor recovery after stroke | the endogenous coupling of ipsilesional SMA and M1, and with a significant decrease of theβ¦ |
| 57 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Depression | Similar to stroke, psychiatric diseases including depression and schizophrenia are beingβ¦ |
| 58 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Depression | focused on the subgenual cingulate cortex (Mayberg et al., 2005), dorsolateral prefrontal cortexβ¦ |
| 59 | BRAIN STIMULATION TECHNIQUES AND NETWORK ANALYSIS IN NEUROPSYCHIATRIC DISEASE β Depression | controls (Leistedt et al., 2009). Most intriguingly, a recent analysis applying graph theoreticβ¦ |
| Name | Type |
|---|---|
| 1-Hz rTMS local | drug |
| 20-Hz rTMS local | drug |
| action selection task local | phenotype |
| Affected hemisphere local | anatomy |
| Alzheimer's disease | phenotype |
| amygdala | anatomy |
| amygdala-hippocampal network local | anatomy |
| anodal stimulation local | drug |
| anodal tDCS local | drug |
| anterior cingulate cortex | anatomy |
| Area MT local | anatomy |
| Area V5 local | anatomy |
| area V5/MT local | anatomy |
| auditory hallucinations | phenotype |
| auditory network local | anatomy |
| autism | phenotype |
| basal ganglia | anatomy |
| behavior | phenotype |
| beta power | phenotype |
| beta rhythm local | anatomy |
| beta rhythm | phenotype |
| bilateral anterior cingulate local | anatomy |
| Bilateral anterior cingulate local | anatomy |
| bilateral cingulate motor areas local | anatomy |
| Bilateral hippocampal formations local | anatomy |
| bilateral middle frontal gyrus local | anatomy |
| bilateral temporal cortices local | anatomy |
| Blood flow changes local | phenotype |
| brain | anatomy |
| brain activity | phenotype |
| brain circuits | anatomy |
| brain networks | anatomy |
| Broca's area | anatomy |
| cathodal stimulation local | drug |
| cathodal tDCS local | drug |
| Cats | cohort |
| caudate nucleus | anatomy |
| cerebellum | anatomy |
| cerebral blood flow | phenotype |
| cerebral hemispheres | anatomy |
| chronic pain | phenotype |
| cingulate cortex | anatomy |
| Cingulate motor area | anatomy |
| cognition | phenotype |
| continuous theta-burst rTMS local | drug |
| contralateral cortex local | anatomy |
| Contralateral inferior parietal lobule local | anatomy |
| contralateral motor cortex local | anatomy |
| Contralateral motor cortex local | anatomy |
| contralateral orbit local | anatomy |
| contralesional cortex local | anatomy |
| contralesional dorsal premotor cortex local | anatomy |
| contralesional hemisphere local | anatomy |
| Contralesional hemisphere local | anatomy |
| contralesional M1 local | anatomy |
| contralesional M1 to ipsilesional M1 inhibition local | phenotype |
| contralesional premotor cortex local | anatomy |
| control subjects | cohort |
| corpus callosum | anatomy |
| cortex | anatomy |
| cortical excitability local | anatomy |
| cortical function | phenotype |
| cortical motor systems local | anatomy |
| cortical neurons | anatomy |
| Cortical region A local | anatomy |
| Cortical region B local | anatomy |
| cortical silent period local | phenotype |
| cortical stroke local | phenotype |
| cortical surface | anatomy |
| corticothalamic network local | anatomy |
| default mode network | anatomy |
| default-mode network | anatomy |
| default-mode network local | phenotype |
| delta power | phenotype |
| depressed patients | cohort |
| depression | phenotype |
| disease | phenotype |
| disease states local | phenotype |
| dopamine | drug |
| dorsal anterior cingulate local | anatomy |
| dorsal attention network | anatomy |
| dorsolateral prefrontal cortex | anatomy |
| EEG | phenotype |
| effective connectivity local | phenotype |
| Electroencephalography local | drug |
| epilepsy | phenotype |
| Epileptic spikes local | phenotype |
| excitability changes local | phenotype |
| Face Discrimination Task local | phenotype |
| facilitation local | phenotype |
| fcEEG local | drug |
| Figure-8 coil local | drug |
| Finger-tapping task local | phenotype |
| First seizure local | phenotype |
| first seizure patients local | cohort |
| Fitzgerald2007_controls local | cohort |
| Fitzgerald2007_patients local | cohort |
| fluoxetine | drug |
| fMRI | drug |
| frontal cortex | anatomy |
| frontal eye fields | anatomy |
| fronto-central region | anatomy |
| frontocingulate network local | anatomy |
| functional connectivity | phenotype |
| functional connectivity networks local | anatomy |
| Functional Connectivity Networks local | anatomy |
| Fusiform Face Area local | anatomy |
| gamma activity | phenotype |
| gamma oscillations | phenotype |
| gamma rhythm local | anatomy |
| global baseline hypoperfusion local | phenotype |
| Hallucination severity local | phenotype |
| Head injury | phenotype |
| healthy controls | cohort |
| Hemiparesis local | phenotype |
| high-frequency rTMS | drug |
| hippocampus | anatomy |
| Horacek et al. 2007 cohort local | cohort |
| human brain | anatomy |
| human somatomotor system local | anatomy |
| hyperperfusion local | phenotype |
| inferior parietal lobule | anatomy |
| inhibitory rTMS local | drug |
| insula | anatomy |
| intelligence (IQ) | phenotype |
| interhemispheric desynchronization local | phenotype |
| interhemispheric functional connectivity local | phenotype |
| interhemispheric inhibition local | phenotype |
| Interhemispheric inhibition local | phenotype |
| intermittent theta-burst rTMS local | drug |
| intracortical cortex local | anatomy |
| intracortical facilitation local | phenotype |
| ipsilateral motor cortex local | anatomy |
| ipsilesional cortex local | anatomy |
| ipsilesional dorsal premotor cortex local | anatomy |
| Ipsilesional hemisphere local | anatomy |
| ipsilesional M1 local | anatomy |
| ipsilesional SMA local | anatomy |
| ipsilesional SMA-M1 coupling local | phenotype |
| language network local | anatomy |
| lateral temporal cortices local | anatomy |
| left dlPFC | anatomy |
| left dorsal prefrontal cortex local | anatomy |
| left dorsal premotor cortex local | anatomy |
| left dorsal premotor region local | anatomy |
| Left frontal-precentral cortex local | anatomy |
| Left frontal-precentral gyrus local | anatomy |
| Left fronto-temporal regions local | anatomy |
| left-hemisphere dominant premotor-parietal network local | anatomy |
| left inferior frontal gyrus | anatomy |
| left inferior parietal lobule | anatomy |
| left medial parieto-occipital cortex local | anatomy |
| left motor hand region local | anatomy |
| left premotor cortex local | anatomy |
| Left premotor cortex local | anatomy |
| left premotor region local | anatomy |
| left primary motor cortex local | anatomy |
| left sensorimotor cortex local | anatomy |
| Left sensorimotor cortex local | anatomy |
| left somatomotor cortex local | anatomy |
| left superior temporal gyrus | anatomy |
| left supplementary motor area local | anatomy |
| left temporal cortex | anatomy |
| left temporo-parietal junction local | anatomy |
| left temporoparietal junction local | anatomy |
| Left temporo-parietal junction local | anatomy |
| Left temporoparietal junction local | anatomy |
| left temporoparietal region local | anatomy |
| left ventral nucleus of the thalamus local | anatomy |
| Lesioned cortex local | anatomy |
| lesioned hemisphere local | anatomy |
| Lesioned hemisphere local | anatomy |
| limbic regions | anatomy |
| loss of consciousness local | phenotype |
| loss of small-worldliness local | phenotype |
| low-frequency rTMS | drug |
| Low-frequency stimulation (1 Hz) local | drug |
| major depressive disorder | phenotype |
| medial prefrontal cortex | anatomy |
| medication-resistant depression local | phenotype |
| MEP amplitude local | phenotype |
| MEP size local | phenotype |
| mesial temporal lobe local | anatomy |
| Mesial temporal lobe local | anatomy |
| Mesial temporal lobe epilepsy local | phenotype |
| midazolam anesthesia local | drug |
| midline | anatomy |
| monoaminergic transmission local | drug |
| mood improvement local | phenotype |
| mood worsening local | phenotype |
| Motion Discrimination Task local | phenotype |
| motor activation after stroke local | phenotype |
| motor areas | anatomy |
| motor cortex | anatomy |
| motor evoked potential local | phenotype |
| motor evoked potential (MEP) local | phenotype |
| Motor-evoked potentials local | phenotype |
| Motor performance | phenotype |
| motor performance improvement local | phenotype |
| Motor recovery local | phenotype |
| Motor recovery after stroke local | phenotype |
| multiple sclerosis | phenotype |
| negative symptoms | phenotype |
| neglect | phenotype |
| network components local | anatomy |
| network dysfunction | phenotype |
| neural activity local | drug |
| neural network | anatomy |
| neuroimaging methods local | drug |
| neurological syndromes local | phenotype |
| neuronal activity | phenotype |
| neuronal excitability | phenotype |
| Neuropsychiatric disease states local | phenotype |
| neuropsychiatric disorders | phenotype |
| NMDA receptor | drug |
| non-eloquent area local | anatomy |
| noninvasive brain stimulation techniques local | drug |
| non-primary motor cortices local | anatomy |
| non-REM sleep local | phenotype |
| Non-REM Sleep local | phenotype |
| normal aging local | cohort |
| normal aging | phenotype |
| normal controls | cohort |
| number of cortical sites with MEP local | phenotype |
| occipital cortex | anatomy |
| occipital pole local | anatomy |
| Paired-pulse TMS local | drug |
| paretic hand local | phenotype |
| paretic hand motor performance local | phenotype |
| parietal cortex | anatomy |
| Parkinson's disease | phenotype |
| path length local | anatomy |
| patients | cohort |
| Patients presenting after a first seizure local | cohort |
| patients recovered fully from subcortical strokes local | cohort |
| Patients with mesial temporal lobe epilepsy local | cohort |
| PET | drug |
| phosphene threshold local | phenotype |
| Polania2010 local | cohort |
| positive symptoms | phenotype |
| posterior cingulate cortex | anatomy |
| posterior superior temporal cortex local | anatomy |
| precision grasping task local | phenotype |
| precuneus | anatomy |
| prefrontal cortex | anatomy |
| premotor cortex | anatomy |
| premotor-parietal network local | anatomy |
| primary visual cortex | anatomy |
| random graphs local | anatomy |
| reaction time delay local | phenotype |
| real rTMS local | drug |
| repetitive transcranial magnetic stimulation | drug |
| resting state | phenotype |
| right angular gyrus local | anatomy |
| right caudate nucleus local | anatomy |
| right dorsolateral prefrontal cortex | anatomy |
| right homotope of Broca local | anatomy |
| Right middle occipital gyrus local | anatomy |
| Right Parieto-Occipital Region local | anatomy |
| right prefrontal cortex | anatomy |
| right secondary somatosensory cortex local | anatomy |
| right sensorimotor cortex local | anatomy |
| Right sensorimotor cortex local | anatomy |
| right supplementary eye field local | anatomy |
| right temporal lobe local | anatomy |
| right temporo-occipital cortex local | anatomy |
| rTMS | drug |
| schizophrenia | phenotype |
| Seizure onset zone local | anatomy |
| sensorimotor cortex | anatomy |
| sensorimotor region | anatomy |
| sensorimotor regions local | anatomy |
| serotonin | drug |
| sham rTMS local | drug |
| sham stimulation local | drug |
| short-interval intracortical inhibition local | phenotype |
| small-world networks local | anatomy |
| somatomotor network local | anatomy |
| somatomotor system local | anatomy |
| spatial attention local | phenotype |
| Speer 2000 cohort local | cohort |
| Speer 2009 cohort local | cohort |
| spinal cord | anatomy |
| Spontaneous Activity local | phenotype |
| stroke | phenotype |
| stroke patients local | cohort |
| Stroke patients local | cohort |
| stroke patients undergoing rehabilitation local | cohort |
| Stroke recovery local | phenotype |
| Stroke Recovery local | phenotype |
| subcortical motor systems local | anatomy |
| subcortical stroke local | phenotype |
| superior parietal cortex | anatomy |
| supplementary motor area | anatomy |
| task performance | phenotype |
| tDCS | drug |
| temporal cortex | anatomy |
| Thalamocortical System local | anatomy |
| thalamus | anatomy |
| Therapeutic intervention local | drug |
| Theta band functional connectivity local | phenotype |
| theta-burst rTMS local | drug |
| theta-burst stimulation local | drug |
| TMS | drug |
| TMS-evoked response local | phenotype |
| Traditional pharmaceutical measure local | drug |
| Transcranial brain stimulation techniques local | drug |
| Unaffected hemisphere local | anatomy |
| ventral attention network | anatomy |
| ventral premotor cortex local | anatomy |
| Visual-evoked Responses local | phenotype |
| Visual-evoked Spiking Activity local | phenotype |
| Visual motion perception local | phenotype |
| visual network | anatomy |
| visual perception of a letter local | phenotype |
| voltage-sensitive cation channels local | drug |
| Wakefulness | phenotype |
| white matter | anatomy |
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Advances in Electrophysiological Research. | 2015 | 26259089 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Connectome-guided resection of deep-seated brain tumors using tubular retractors: matched cohort outcomes and exploratory quantitative tractometry. | Mittelman L et al. | β | 2026 | β |
| Exploring the capabilities of repetitive transcranial magnetic stimulation in major depressive disorder: Dynamic causal modeling of the neural network. | Kita A et al. | β | 2025 | β |
| The efficacy and safety of dual-target rTMS over dorsolateral prefrontal cortex (DLPFC) and cerebellum in the treatment of negative symptoms in first-episode schizophrenia: Protocol for a multicenter, randomized, double-blind, sham-controlled study. | Wang J et al. | β | 2025 | β |
| Tms-evoked potentials: Neurophysiological biomarkers for diagnosis and prediction of response to ventriculoperitoneal shunt in normal pressure hydrocephalus. | Davidy T et al. | β | 2025 | β |
| Transcranial Magnetic Stimulation-Induced Modulation of Functional Connectivity in Healthy Controls: A TMS-EEG Graph Study. | FernΓ‘ndez-Linsenbarth I et al. | β | 2025 | β |
| Brain network topological changes in inflammatory bowel disease: an exploratory study. | Polverino A et al. | β | 2024 | β |
| [Comparative analysis of the impact of repetitive transcranial magnetic stimulation and burst transcranial magnetic stimulation at different frequencies on memory function and neuronal excitability of mice]. | Fu R et al. | β | 2024 | β |
| Natural Image Reconstruction from fMRI Based on Node-Edge Interaction and Multi-Scale Constraint. | Kuang M et al. | β | 2024 | β |
| Non-invasive brain stimulation for functional recovery in animal models of stroke: A systematic review. | RodrΓguez A et al. | β | 2024 | β |
| Reproducible routes: reliably navigating the connectome to enrich personalized brain stimulation strategies. | Liu Y et al. | β | 2024 | β |
| The brain network hub degeneration in Alzheimer's disease. | Jin S et al. | β | 2024 | β |
| The Therapeutic Role of Intermittent Theta Burst Stimulation in Schizophrenia: A Systematic Review and Meta-analysis. | Salabat D et al. | β | 2024 | β |
| Toward Precision Noninvasive Brain Stimulation. | Cappon DB et al. | β | 2024 | β |
| Additive effect of transcranial direct current stimulation (tDCS) in combination with multicomponent training on elderly physical function capacity: a randomized, triple blind, controlled trial. | CorrΓͺa FI et al. | β | 2023 | β |
| Assessing the mechanisms of brain plasticity by transcranial magnetic stimulation. | Jannati A et al. | β | 2023 | β |
| Brain Connectivity Signature Extractions from TMS Invoked EEGs. | Gupta D et al. | β | 2023 | β |
| Can the Ability to Recognize Facial Emotions in Individuals With Neurodegenerative Disease be Improved? A Systematic Review and Meta-analysis. | Mirzai N et al. | β | 2023 | β |
| Effect of high-definition transcranial direct current stimulation on improving depression and modulating functional activity in emotion-related cortical-subcortical regions in bipolar depression. | Zhang L et al. | β | 2023 | β |
| Functional Brain Connectivity Prior to the COVID-19 Outbreak Moderates the Effects of Coping and Perceived Stress on Mental Health Changes: A First Year of COVID-19 Pandemic Follow-up Study. | Cabello-Toscano M et al. | β | 2023 | β |
| Multi-networks connectivity at baseline predicts the clinical efficacy of left angular gyrus-navigated rTMS in the spectrum of Alzheimer's disease: A sham-controlled study. | Chen HF et al. | β | 2023 | β |
| Noise improves the association between effects of local stimulation and structural degree of brain networks. | Zheng Y et al. | β | 2023 | β |
| Repetitive transcranial magnetic stimulation can improve the fixation of eyes rather than the fixation preference in children with autism spectrum disorder. | Tian L et al. | β | 2023 | β |
| Cognitive Improvement via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Amnesic Mild Cognitive Impairment Patients. | Yang Z et al. | β | 2022 | β |
| High-Performance Magnetic-core Coils for Targeted Rodent Brain Stimulations. | Bagherzadeh H et al. | β | 2022 | β |
| Narrative Review of Noninvasive Brain Stimulation in Stroke Rehabilitation. | Shen QR et al. | β | 2022 | β |
| Online closed-loop real-time tES-fMRI for brain modulation: A technical report. | Mulyana B et al. | β | 2022 | β |
| Preconditioning prefrontal connectivity using transcranial direct current stimulation and transcranial magnetic stimulation. | Alkhasli I et al. | β | 2022 | β |
| Transcranial magnetic stimulation (TMS) for geriatric depression. | Cappon D et al. | β | 2022 | β |
| Efficacy and safety of transcranial direct current stimulation as an add-on treatment for obsessive-compulsive disorder: a randomized, sham-controlled trial. | Silva RMFD et al. | β | 2021 | β |
| Intermittent theta burst stimulation of cerebellar vermis enhances fronto-cerebellar resting state functional connectivity in schizophrenia with predominant negative symptoms: A randomized controlled trial. | Basavaraju R et al. | β | 2021 | β |
| Phase-Dependent Deep Brain Stimulation: A Review. | Kumari LS et al. | β | 2021 | β |
| Precise Modulation Strategies for Transcranial Magnetic Stimulation: Advances and Future Directions. | Zhong G et al. | β | 2021 | β |
| Systemic Review on Transcranial Electrical Stimulation Parameters and EEG/fNIRS Features for Brain Diseases. | Yang D et al. | β | 2021 | β |
| The Sensory Abnormality Mediated Partially the Efficacy of Repetitive Transcranial Magnetic Stimulation on Treating Comorbid Sleep Disorder in Autism Spectrum Disorder Children. | Gao L et al. | β | 2021 | β |
| TMS-EEG Research to Elucidate the Pathophysiological Neural Bases in Patients with Schizophrenia: A Systematic Review. | Li X et al. | β | 2021 | β |
| Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression. | Cash RFH et al. | β | 2021 | β |
| Analyzing the advantages of subcutaneous over transcutaneous electrical stimulation for activating brainwaves. | Kang W et al. | β | 2020 | β |
| Converging Resting State Networks Unravels Potential Remote Effects of Transcranial Magnetic Stimulation for Major Depression. | Ishida T et al. | β | 2020 | β |
| Does non-invasive brain stimulation modulate emotional stress reactivity? | Smits FM et al. | β | 2020 | β |
| Effects of a combined transcranial magnetic stimulation (TMS) and cognitive training intervention in patients with Alzheimer's disease. | Sabbagh M et al. | β | 2020 | β |
| Effects of Transcranial Direct Current Stimulation on Episodic Memory in Amnestic Mild Cognitive Impairment: A Pilot Study. | Manenti R et al. | β | 2020 | β |
| Enhancing spatial reasoning by anodal transcranial direct current stimulation over the right posterior parietal cortex. | Wertheim J et al. | β | 2020 | β |
| Evaluation of White Matter Integrity Utilizing the DELPHI (TMS-EEG) System. | Levy-Lamdan O et al. | β | 2020 | β |
| Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition. | Ozdemir RA et al. | β | 2020 | β |
| Multi-day rTMS exerts site-specific effects on functional connectivity but does not influence associative memory performance. | Hendrikse J et al. | β | 2020 | β |
| Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state. | Papadopoulos L et al. | β | 2020 | β |
| Resting-state and task-based centrality of dorsolateral prefrontal cortex predict resilience to 1 Hz repetitive transcranial magnetic stimulation. | Fitzsimmons SMDD et al. | β | 2020 | β |
| The safety and efficacy of transcranial direct current stimulation as add-on therapy to fluoxetine in obsessive-compulsive disorder: a randomized, double-blind, sham-controlled, clinical trial. | Yoosefee S et al. | β | 2020 | β |
| The study of noninvasive brain stimulation using molecular brain imaging: A systematic review. | Tremblay S et al. | β | 2020 | β |
| Age-related differences in default-mode network connectivity in response to intermittent theta-burst stimulation and its relationships with maintained cognition and brain integrity in healthy aging. | Abellaneda-PΓ©rez K et al. | β | 2019 | β |
| Brain Stimulation in Obsessive-Compulsive Disorder (OCD): A Systematic Review. | Rapinesi C et al. | β | 2019 | β |
| Effects of transcranial direct current stimulation on the rehabilitation of painful shoulder following a stroke: protocol for a randomized, controlled, double-blind, clinical trial. | de Souza JA et al. | β | 2019 | β |
| Effects of transcranial direct current stimulation over the posterior parietal cortex on episodic memory reconsolidation. | Crossman M et al. | β | 2019 | β |
| High-Frequency Repetitive Transcranial Magnetic Stimulation Applied to the Parietal Cortex for Low-Functioning Children With Autism Spectrum Disorder: A Case Series. | Yang Y et al. | β | 2019 | β |
| How Can Transcranial Magnetic Stimulation Be Used to Modulate Episodic Memory?: A Systematic Review and Meta-Analysis. | Yeh N et al. | β | 2019 | β |
| Intramuscular electrical stimulus potentiates motor cortex modulation effects on pain and descending inhibitory systems in knee osteoarthritis: a randomized, factorial, sham-controlled study. | da Graca-TarragΓ³ M et al. | β | 2019 | β |
| Introducing a Novel Approach for Evaluation and Monitoring of Brain Health Across Life Span Using Direct Non-invasive Brain Network Electrophysiology. | Zifman N et al. | β | 2019 | β |
| Modulating Emotional Experience Using Electrical Stimulation of the Medial-Prefrontal Cortex: A Preliminary tDCS-fMRI Study. | Abend R et al. | β | 2019 | β |
| Repetitive Transcranial Magnetic Stimulation Induced Hypoconnectivity Within the Default Mode Network Yields Cognitive Improvements in Amnestic Mild Cognitive Impairment: A Randomized Controlled Study. | Cui H et al. | β | 2019 | β |
| Resting-state and task-based centrality of dorsolateral prefrontal cortex predict resilience to inhibitory repetitive transcranial magnetic stimulation | Fitzsimmons SM et al. | β | 2019 | β |
| Transcranial direct current stimulation applied after encoding facilitates episodic memory consolidation in older adults. | Sandrini M et al. | β | 2019 | β |
| Transcranial direct current stimulation over the sensory-motor regions inhibits gamma synchrony. | Pellegrino G et al. | β | 2019 | β |
| Transcranial magnetic stimulation: Neurophysiological and clinical applications. | Burke MJ et al. | β | 2019 | β |
| Attenuating anger and aggression with neuromodulation of the vmPFC: A simultaneous tDCS-fMRI study. | Gilam G et al. | β | 2018 | β |
| Autism-relevant traits interact with temporoparietal junction stimulation effects on social cognition: a high-definition transcranial direct current stimulation and electroencephalography study. | Donaldson PH et al. | β | 2018 | β |
| Changing Brain Networks Through Non-invasive Neuromodulation. | To WT et al. | β | 2018 | β |
| Effects of repeated transcranial direct current stimulation on smoking, craving and brain reactivity to smoking cues. | Mondino M et al. | β | 2018 | β |
| Effects of single versus dual-site High-Definition transcranial direct current stimulation (HD-tDCS) on cortical reactivity and working memory performance in healthy subjects. | Hill AT et al. | β | 2018 | β |
| Noninvasive Brain Stimulation to Enhance Functional Recovery After Stroke: Studies in Animal Models. | Boonzaier J et al. | β | 2018 | β |
| Repetitive transcranial magnetic stimulation of the right parietal cortex for comorbid generalized anxiety disorder and insomnia: A randomized, double-blind, sham-controlled pilot study. | Huang Z et al. | β | 2018 | β |
| tDCS potentiation provides no evidence for a link between right dorsal-lateral prefrontal cortical activity and empathic responding. | Snowdon ME et al. | β | 2018 | β |
| The effect of bilateral low-frequency rTMS over dorsolateral prefrontal cortex on serum brain-derived neurotropic factor and serotonin in patients with generalized anxiety disorder. | Lu R et al. | β | 2018 | β |
| Altered functional connectivity of interoception in illness anxiety disorder. | Grossi D et al. | β | 2017 | β |
| Disrupting dorsolateral prefrontal cortex by rTMS reduces the P300 based marker of deception. | Karton I et al. | β | 2017 | β |
| High-definition tDCS of the temporo-parietal cortex enhances access to newly learned words. | Perceval G et al. | β | 2017 | β |
| Predicting tDCS treatment outcomes of patients with major depressive disorder using automated EEG classification. | Al-Kaysi AM et al. | β | 2017 | β |
| Primary motor cortex functionally contributes to language comprehension: An online rTMS study. | Vukovic N et al. | β | 2017 | β |
| Remodeling Functional Connectivity in Multiple Sclerosis: A Challenging Therapeutic Approach. | Stampanoni Bassi M et al. | β | 2017 | β |
| Repetitive transcranial magnetic stimulation of the right dorsal lateral prefrontal cortex in the treatment of generalized anxiety disorder: A randomized, double-blind sham controlled clinical trial. | Dilkov D et al. | β | 2017 | β |
| Strengthening of Existing Episodic Memories Through Non-invasive Stimulation of Prefrontal Cortex in Older Adults with Subjective Memory Complaints. | Manenti R et al. | β | 2017 | β |
| Transcranial Electric Stimulation for Precision Medicine: A Spatiomechanistic Framework. | Yavari F et al. | β | 2017 | β |
| A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy. | Shafi MM et al. | β | 2016 | β |
| Effects of Fronto-Temporal Transcranial Direct Current Stimulation on Auditory Verbal Hallucinations and Resting-State Functional Connectivity of the Left Temporo-Parietal Junction in Patients With Schizophrenia. | Mondino M et al. | β | 2016 | β |
| Effects of transcranial direct current stimulation on the functional coupling of the sensorimotor cortical network. | Vecchio F et al. | β | 2016 | β |
| From Mild Cognitive Impairment to Alzheimer's Disease: A New Perspective in the "Land" of Human Brain Reactivity and Connectivity. | Rossini PM et al. | β | 2016 | β |
| Modulation of fear extinction processes using transcranial electrical stimulation. | Abend R et al. | β | 2016 | β |
| Neuroscience of drug craving for addiction medicine: From circuits to therapies. | Ekhtiari H et al. | β | 2016 | β |
| Older adults get episodic memory boosting from noninvasive stimulation of prefrontal cortex during learning. | Sandrini M et al. | β | 2016 | β |
| Predicting brain stimulation treatment outcomes of depressed patients through the classification of EEG oscillations. | Al-Kaysi AM et al. | β | 2016 | β |
| The stimulated social brain: effects of transcranial direct current stimulation on social cognition. | Sellaro R et al. | β | 2016 | β |
| Transcranial direct current stimulation for obsessive-compulsive disorder: A randomized, controlled, partial crossover trial. | D'Urso G et al. | β | 2016 | β |
| Advances in Electrophysiological Research. | Kamarajan C et al. | β | 2015 | β |
| Does non-invasive brain stimulation applied over the dorsolateral prefrontal cortex non-specifically influence mood and emotional processing in healthy individuals? | Mondino M et al. | β | 2015 | β |
| Increasing the role of belief information in moral judgments by stimulating the right temporoparietal junction. | Sellaro R et al. | β | 2015 | β |
| Is the human mirror neuron system plastic? Evidence from a transcranial magnetic stimulation study. | Mehta UM et al. | β | 2015 | β |
| Modulating reconsolidation: a link to causal systems-level dynamics of human memories. | Sandrini M et al. | β | 2015 | β |
| Personalizing the Electrode to Neuromodulate an Extended Cortical Region. | Cancelli A et al. | β | 2015 | β |
| The contribution of TMS-EEG coregistration in the exploration of the human cortical connectome. | Bortoletto M et al. | β | 2015 | β |
| TMS as a Tool for Examining Cognitive Processing. | Nevler N et al. | β | 2015 | β |
| Applications of transcranial direct current stimulation for understanding brain function. | Filmer HL et al. | β | 2014 | β |
| Best of both worlds: promise of combining brain stimulation and brain connectome. | Luft CD et al. | β | 2014 | β |
| Effective connectivity maps in the swine somatosensory cortex estimated from electrocorticography and validated with intracortical local field potential measurements. | Tanosaki M et al. | β | 2014 | β |
| Emergence of deglutology: a transdisciplinary field. | Babaei A et al. | β | 2014 | β |
| Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest. | Clemens B et al. | β | 2014 | β |
| Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation. | Shafi MM et al. | β | 2014 | β |
| Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields. | Ruffini G et al. | β | 2014 | β |
| Post-stroke balance rehabilitation under multi-level electrotherapy: a conceptual review. | Dutta A et al. | β | 2014 | β |
| The default mode network and social understanding of others: what do brain connectivity studies tell us. | Li W et al. | β | 2014 | β |
| Tracing the evolution of multi-scale functional networks in a mouse model of depression using persistent brain network homology. | Khalid A et al. | β | 2014 | β |
| Assessing brain plasticity across the lifespan with transcranial magnetic stimulation: why, how, and what is the ultimate goal? | Freitas C et al. | β | 2013 | β |
| Cerebral network disorders after stroke: evidence from imaging-based connectivity analyses of active and resting brain states in humans. | Rehme AK et al. | β | 2013 | β |
| Changes in plasticity across the lifespan: cause of disease and target for intervention. | Oberman L et al. | β | 2013 | β |
| Inferring evoked brain connectivity through adaptive perturbation. | Lepage KQ et al. | β | 2013 | β |
| In vivo assessment of human brain oscillations during application of transcranial electric currents. | Soekadar SR et al. | β | 2013 | β |
| Modulation of human corticospinal excitability by paired associative stimulation. | Carson RG et al. | β | 2013 | β |
| Network mechanisms of responsiveness to continuous theta-burst stimulation. | Rizk S et al. | β | 2013 | β |
| Noninvasive brain stimulation: from physiology to network dynamics and back. | Dayan E et al. | β | 2013 | β |
| Regional personalized electrodes to select transcranial current stimulation target. | Tecchio F et al. | β | 2013 | β |
| Simultaneous EEG monitoring during transcranial direct current stimulation. | Schestatsky P et al. | β | 2013 | β |
| The relationship between brain oscillatory activity and therapeutic effectiveness of transcranial magnetic stimulation in the treatment of major depressive disorder. | Leuchter AF et al. | β | 2013 | β |
| Transcranial magnetic stimulation (TMS) for major depression: a multisite, naturalistic, observational study of quality of life outcome measures in clinical practice. | Janicak PG et al. | β | 2013 | β |
| Anterior disconnection syndrome revisited using modern technologies. | Pereira AC et al. | β | 2012 | β |