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

Advances in Electrophysiological Research

Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders.These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment.

The contribution of TMS-EEG coregistration in the exploration of the human cortical connectome

Recent developments in neuroscience have emphasised the importance of integrated distributed networks of brain areas for successful cognitive functioning. Our current understanding is that the brain has a modular organisation in which segregated networks supporting specialised processing are linked through a few long-range connections, ensuring processing integration. Although such architecture is structurally stable, it appears to be flexible in its functioning, enabling long-range connections to regulate the information flow and facilitate communication among the relevant modules, depending on the contingent cognitive demands. Here we show how insights brought by the coregistration of transcranial magnetic stimulation and electroencephalography (TMS-EEG) integrate and support recent models of functional brain architecture. Moreover, we will highlight the types of data that can be obtained through TMS-EEG, such as the timing of signal propagation, the excitatory/inhibitory nature of connections and causality. Last, we will discuss recent emerging applications of TMS-EEG in the study of brain disorders.

Effective connectivity maps in the swine somatosensory cortex estimated from electrocorticography and validated with intracortical local field potential measurements

Macroscopic techniques are increasingly being used to estimate functional connectivity in the brain, which provides valuable information about brain networks. In any such endeavors it is important to understand capabilities and limitations of each technique through direct validation, which is often lacking. This study evaluated a multiple dipole source analysis technique based on electrocorticography (ECOG) data in estimating effective connectivity maps and validated the technique with intracortical local field potential (LFP) recordings. The study was carried out in an animal model (swine) with a large brain to avoid complications caused by spreading of the volume current. The evaluation was carried out for the cortical projections from the trigeminal nerve and corticocortical connectivity from the first rostrum area (R1) in the primary somatosensory cortex. Stimulation of the snout and layer IV of the R1 did not activate all projection areas in each animal, although whenever an area was activated in a given animal, its location was consistent with the intracortical LFP. The two types of connectivity maps based on ECOG analysis were consistent with each other and also with those estimated from the intracortical LFP, although there were small discrepancies. The discrepancies in mean latency based on ECOG and LFP were all very small and nonsignificant: snout stimulation, -1.1-2.0 msec (contralateral hemisphere) and 3.9-8.5 msec (ipsilateral hemisphere); R1 stimulation, -1.4-2.2 msec for the ipsilateral and 0.6-1.4 msec for the contralateral hemisphere. Dipole source analysis based on ECOG appears to be quite useful for estimating effective connectivity maps in the brain.

Changes in plasticity across the lifespan: cause of disease and target for intervention

We conceptualize brain plasticity as an intrinsic property of the nervous system enabling rapid adaptation in response to changes in an organism's internal and external environment. In prenatal and early postnatal development, plasticity allows for the formation of organized nervous system circuitry and the establishment of functional networks. As the individual is exposed to various sensory stimuli in the environment, brain plasticity allows for functional and structural adaptation and underlies learning and memory. We argue that the mechanisms of plasticity change over the lifespan with different slopes of change in different individuals. These changes play a key role in the clinical phenotype of neurodevelopmental disorders like autism and schizophrenia and neurodegenerative disorders such as Alzheimer's disease. Altered plasticity not only can trigger maladaptive cascades and can be the cause of deficits and disability but also offers opportunities for novel therapeutic interventions. In this chapter, we discuss the importance of brain plasticity across the lifespan and how neuroplasticity-based therapies offer promise for disorders with otherwise limited effective treatment.

Best of both worlds: promise of combining brain stimulation and brain connectome

Transcranial current brain stimulation (tCS) is becoming increasingly popular as a non-pharmacological non-invasive neuromodulatory method that alters cortical excitability by applying weak electrical currents to the scalp via a pair of electrodes. Most applications of this technique have focused on enhancing motor and learning skills, as well as a therapeutic agent in neurological and psychiatric disorders. In these applications, similarly to lesion studies, tCS was used to provide a causal link between a function or behavior and a specific brain region (e.g., primary motor cortex). Nonetheless, complex cognitive functions are known to rely on functionally connected multitude of brain regions with dynamically changing patterns of information flow rather than on isolated areas, which are most commonly targeted in typical tCS experiments. In this review article, we argue in favor of combining tCS method with other neuroimaging techniques (e.g., fMRI, EEG) and by employing state-of-the-art connectivity data analysis techniques (e.g., graph theory) to obtain a deeper understanding of the underlying spatiotemporal dynamics of functional connectivity patterns and cognitive performance. Finally, we discuss the possibilities of using these combined techniques to investigate the neural correlates of human creativity and to enhance creativity.

Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest

Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site.

Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields

Recently, multifocal transcranial current stimulation (tCS) devices using several relatively small electrodes have been used to achieve more focal stimulation of specific cortical targets. However, it is becoming increasingly recognized that many behavioral manifestations of neurological and psychiatric disease are not solely the result of abnormality in one isolated brain region but represent alterations in brain networks. In this paper we describe a method for optimizing the configuration of multifocal tCS for stimulation of brain networks, represented by spatially extended cortical targets. We show how, based on fMRI, PET, EEG or other data specifying a target map on the cortical surface for excitatory, inhibitory or neutral stimulation and a constraint on the maximal number of electrodes, a solution can be produced with the optimal currents and locations of the electrodes. The method described here relies on a fast calculation of multifocal tCS electric fields (including components normal and tangential to the cortical boundaries) using a five layer finite element model of a realistic head. Based on the hypothesis that the effects of current stimulation are to first order due to the interaction of electric fields with populations of elongated cortical neurons, it is argued that the optimization problem for tCS stimulation can be defined in terms of the component of the electric field normal to the cortical surface. Solutions are found using constrained least squares to optimize current intensities, while electrode number and their locations are selected using a genetic algorithm. For direct current tCS (tDCS) applications, we provide some examples of this technique using an available tCS system providing 8 small Ag/AgCl stimulation electrodes. We demonstrate the approach both for localized and spatially extended targets defined using rs-fcMRI and PET data, with clinical applications in stroke and depression. Finally, we extend these ideas to more general stimulation protocols, such as alternating current tCS (tACS).

The default mode network and social understanding of others: what do brain connectivity studies tell us

The Default Mode Network (DMN) has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common results show that the medial prefrontal cortex (MPFC) plays a key role in the social understanding of others, and the subregions of the MPFC contribute differently to this function according to their roles in different subsystems of the DMN. At the bottom, the ventral MPFC in the medial temporal lobe (MTL) subsystem and its connections with emotion regions are mainly associated with emotion engagement during social interactions. Above, the anterior MPFC (aMPFC) in the cortical midline structures (CMS) and its connections with posterior and anterior cingulate cortex contribute mostly to making self-other distinctions. At the top, the dorsal MPFC (dMPFC) in the dMPFC subsystem and its connection with the temporo-parietal junction (TPJ) are primarily related to the understanding of other's mental states. As behaviors become more complex, the related regions in frontal cortex are located higher. This reflects the transfer of information processing from automatic to cognitive processes with the increase of the complexity of social interaction. Besides the MPFC and TPJ, the connectivities of posterior cingulate cortex (PCC) also show some changes during tasks from the four social fields. These results indicate that the DMN is indispensable in the social understanding of others.

In vivo assessment of human brain oscillations during application of transcranial electric currents

Brain oscillations reflect pattern formation of cell assemblies’ activity, which is often disturbed in neurological and psychiatric diseases like depression, schizophrenia and stroke. In the neurobiological analysis and treatment of these conditions, transcranial electric currents applied to the brain proved beneficial. However, the direct effects of these currents on brain oscillations have remained an enigma because of the inability to record them simultaneously. Here we report a novel strategy that resolves this problem. We describe accurate reconstructed localization of dipolar sources and changes of brain oscillatory activity associated with motor actions in primary cortical brain regions undergoing transcranial electric stimulation. This new method allows for the first time direct measurement of the effects of non-invasive electrical brain stimulation on brain oscillatory activity and behavior.

Modulation of human corticospinal excitability by paired associative stimulation

Paired Associative Stimulation (PAS) has come to prominence as a potential therapeutic intervention for the treatment of brain injury/disease, and as an experimental method with which to investigate Hebbian principles of neural plasticity in humans. Prototypically, a single electrical stimulus is directed to a peripheral nerve in advance of transcranial magnetic stimulation (TMS) delivered to the contralateral primary motor cortex (M1). Repeated pairing of the stimuli (i.e., association) over an extended period may increase or decrease the excitability of corticospinal projections from M1, in manner that depends on the interstimulus interval (ISI). It has been suggested that these effects represent a form of associative long-term potentiation (LTP) and depression (LTD) that bears resemblance to spike-timing dependent plasticity (STDP) as it has been elaborated in animal models. With a large body of empirical evidence having emerged since the cardinal features of PAS were first described, and in light of the variations from the original protocols that have been implemented, it is opportune to consider whether the phenomenology of PAS remains consistent with the characteristic features that were initially disclosed. This assessment necessarily has bearing upon interpretation of the effects of PAS in relation to the specific cellular pathways that are putatively engaged, including those that adhere to the rules of STDP. The balance of evidence suggests that the mechanisms that contribute to the LTP- and LTD-type responses to PAS differ depending on the precise nature of the induction protocol that is used. In addition to emphasizing the requirement for additional explanatory models, in the present analysis we highlight the key features of the PAS phenomenology that require interpretation.

Transcranial magnetic stimulation (TMS) for major depression: a multisite, naturalistic, observational study of quality of life outcome measures in clinical practice

BACKGROUND

Transcranial magnetic stimulation (TMS) is an effective and safe therapy for major depressive disorder (MDD). This study assessed quality of life (QOL) and functional status outcomes for depressed patients after an acute course of TMS.

METHODS

Forty-two, U.S.-based, clinical TMS practice sites treated 307 outpatients with a primary diagnosis of MDD and persistent symptoms despite prior adequate antidepressant pharmacotherapy. Treatment parameters were based on individual clinical considerations and followed the labeled procedures for use of the approved TMS device. Patient self-reported QOL outcomes included change in the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) and the EuroQol 5-Dimensions (EQ-5D) ratings from baseline to end of the acute treatment phase.

RESULTS

Statistically significant improvement in functional status on a broad range of mental health and physical health domains was observed on the SF-36 following acute TMS treatment. Similarly, statistically significant improvement in patient-reported QOL was observed on all domains of the EQ-5D and on the General Health Perception and Health Index scores. Improvement on these measures was observed across the entire range of baseline depression symptom severity.

CONCLUSION

These data confirm that TMS is effective in the acute treatment of MDD in routine clinical practice settings. This symptom benefit is accompanied by statistically and clinically meaningful improvements in patient-reported QOL and functional status outcomes.

Noninvasive brain stimulation: from physiology to network dynamics and back

Noninvasive brain stimulation techniques have been widely used for studying the physiology of the CNS, identifying the functional role of specific brain structures and, more recently, exploring large-scale network dynamics. Here we review key findings that contribute to our understanding of the mechanisms underlying the physiological and behavioral effects of these techniques. We highlight recent innovations using noninvasive stimulation to investigate global brain network dynamics and organization. New combinations of these techniques, in conjunction with neuroimaging, will further advance the utility of their application.

Simultaneous EEG monitoring during transcranial direct current stimulation

Transcranial direct current stimulation (tDCS) is a technique that delivers weak electric currents through the scalp. This constant electric current induces shifts in neuronal membrane excitability, resulting in secondary changes in cortical activity. Although tDCS has most of its neuromodulatory effects on the underlying cortex, tDCS effects can also be observed in distant neural networks. Therefore, concomitant EEG monitoring of the effects of tDCS can provide valuable information on the mechanisms of tDCS. In addition, EEG findings can be an important surrogate marker for the effects of tDCS and thus can be used to optimize its parameters. This combined EEG-tDCS system can also be used for preventive treatment of neurological conditions characterized by abnormal peaks of cortical excitability, such as seizures. Such a system would be the basis of a non-invasive closed-loop device. In this article, we present a novel device that is capable of utilizing tDCS and EEG simultaneously. For that, we describe in a step-by-step fashion the main procedures of the application of this device using schematic figures, tables and video demonstrations. Additionally, we provide a literature review on clinical uses of tDCS and its cortical effects measured by EEG techniques.

Regional personalized electrodes to select transcranial current stimulation target

Rationale: Personalizing transcranial stimulations promises to enhance beneficial effects for individual patients.

Objective: To stimulate specific cortical regions by developing a procedure to bend and position custom shaped electrodes; to probe the effects on cortical excitability produced when the properly customized electrode is targeting different cortical areas.

Method: An ad hoc neuronavigation procedure was developed to accurately shape and place the personalized electrodes on the basis of individual brain magnetic resonance images (MRI) on bilateral primary motor (M1) and somatosensory (S1) cortices. The transcranial alternating current stimulation (tACS) protocol published by Feurra et al. (2011b) was used to test the effects on cortical excitability of the personalized electrode when targeting S1 or M1.

Results: Neuronal excitability as evaluated by tACS was different when targeting M1 or S1, with the General Estimating Equation model indicating a clear tCS Effect (p < 0.001), and post hoc comparisons showing solely M1 20 Hz tACS to reduce M1 excitability with respect to baseline and other tACS conditions.

Conclusions: The present work indicates that specific cortical regions can be targeted by tCS properly shaping and positioning the stimulating electrode.

Significance: Through multimodal brain investigations continuous efforts in understanding the neuronal changes related to specific neurological or psychiatric diseases become more relevant as our ability to build the compensating interventions improves. An important step forward on this path is the ability to target the specific cortical area of interest, as shown in the present pilot work.

Assessing brain plasticity across the lifespan with transcranial magnetic stimulation: why, how, and what is the ultimate goal?

Sustaining brain and cognitive function across the lifespan must be one of the main biomedical goals of the twenty-first century. We need to aim to prevent neuropsychiatric diseases and, thus, to identify and remediate brain and cognitive dysfunction before clinical symptoms manifest and disability develops. The brain undergoes a complex array of changes from developmental years into old age, putatively the underpinnings of changes in cognition and behavior throughout life. A functionally “normal” brain is a changing brain, a brain whose capacity and mechanisms of change are shifting appropriately from one time-point to another in a given individual's life. Therefore, assessing the mechanisms of brain plasticity across the lifespan is critical to gain insight into an individual's brain health. Indexing brain plasticity in humans is possible with transcranial magnetic stimulation (TMS), which, in combination with neuroimaging, provides a powerful tool for exploring local cortical and brain network plasticity. Here, we review investigations to date, summarize findings, and discuss some of the challenges that need to be solved to enhance the use of TMS measures of brain plasticity across all ages. Ultimately, TMS measures of plasticity can become the foundation for a brain health index (BHI) to enable objective correlates of an individual's brain health over time, assessment across diseases and disorders, and reliable evaluation of indicators of efficacy of future preventive and therapeutic interventions.

Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique that utilizes magnetic fluxes to alter cortical activity. Continuous theta-burst repetitive TMS (cTBS) results in long-lasting decreases in indices of cortical excitability, and alterations in performance of behavioral tasks. We investigated the effects of cTBS on cortical function via functional connectivity and graph theoretical analysis of EEG data. Thirty-one channel resting-state EEG recordings were obtained before and after 40 s of cTBS stimulation to the left primary motor cortex. Functional connectivity between nodes was assessed in multiple frequency bands using lagged max-covariance, and subsequently thresholded to construct undirected graphs. After cTBS, we find widespread decreases in functional connectivity in the alpha band. There are also simultaneous increases in functional connectivity in the high-beta bands, especially amongst anterior and interhemispheric connections. The analysis of the undirected graphs reveals that interhemispheric and interregional connections are more likely to be modulated after cTBS than local connections. There is also a shift in the topology of network connectivity, with an increase in the clustering coefficient after cTBS in the beta bands, and a decrease in clustering and increase in path length in the alpha band, with the alpha-band connectivity primarily decreased near the site of stimulation. cTBS produces widespread alterations in cortical functional connectivity, with resulting shifts in cortical network topology.

The relationship between brain oscillatory activity and therapeutic effectiveness of transcranial magnetic stimulation in the treatment of major depressive disorder

Major depressive disorder (MDD) is marked by disturbances in brain functional connectivity. This connectivity is modulated by rhythmic oscillations of brain electrical activity, which enable coordinated functions across brain regions. Oscillatory activity plays a central role in regulating thinking and memory, mood, cerebral blood flow, and neurotransmitter levels, and restoration of normal oscillatory patterns is associated with effective treatment of MDD. Repetitive transcranial magnetic stimulation (rTMS) is a robust treatment for MDD, but the mechanism of action (MOA) of its benefits for mood disorders remains incompletely understood. Benefits of rTMS have been tied to enhanced neuroplasticity in specific brain pathways. We summarize here the evidence that rTMS entrains and resets thalamocortical oscillators, normalizes regulation and facilitates reemergence of intrinsic cerebral rhythms, and through this mechanism restores normal brain function. This entrainment and resetting may be a critical step in engendering neuroplastic changes and the antidepressant effects of rTMS. It may be possible to modify the method of rTMS administration to enhance this MOA and achieve better antidepressant effectiveness. We propose that rTMS can be administered: (1) synchronized to a patient's individual alpha frequency (IAF), or synchronized rTMS (sTMS); (2) as a low magnetic field strength sinusoidal waveform; and, (3) broadly to multiple brain areas simultaneously. We present here the theory and evidence indicating that these modifications could enhance the therapeutic effectiveness of rTMS for the treatment of MDD.

Using transcranial electrical stimulation to enhance cognitive functions in the typical and atypical brain

Transcranial electrical stimulation (TES) includes methods such as transcranial direct current stimulation, transcranial random noise stimulation, and transcranial alternating current stimulation. These methods provide novel ways of enhancing human cognitive abilities for restorative purposes, or for general cognitive enhancement, by modulating neuronal activity. I discuss here the basic principles behind these methods and provide some illustrations of their efficacy in cognitive enhancement in those with typical and atypical brain function. Next, I outline some future directions for research that are have been largely neglected, such as the issue of individual differences, cognitive side effects, the efficacy of TES for use with healthy elderly populations, children with atypical development, and sports. The results observed thus far with TES as well as its future possibilities have significant implications for both basic and translational neuroscience.

Cerebral network disorders after stroke: evidence from imaging-based connectivity analyses of active and resting brain states in humans

Stroke causes a sudden disruption of physiological brain function which leads to impairments of functional brain networks involved in voluntary movements. In some cases, the brain has the intrinsic capacity to reorganize itself, thereby compensating for the disruption of motor networks. In humans, such reorganization can be investigated in vivo using neuroimaging. Recent developments in connectivity analyses based on functional neuroimaging data have provided new insights into the network pathophysiology underlying neurological symptoms. Here we review recent neuroimaging studies using functional resting-state correlations, effective connectivity models or graph theoretical analyses to investigate changes in neural motor networks and recovery after stroke. The data demonstrate that network disturbances after stroke occur not only in the vicinity of the lesion but also between remote cortical areas in the affected and unaffected hemisphere. The reorganization of motor networks encompasses a restoration of interhemispheric functional coherence in the resting state, particularly between the primary motor cortices. Furthermore, reorganized neural networks feature strong excitatory interactions between fronto-parietal areas and primary motor cortex in the affected hemisphere, suggesting that greater top-down control over primary motor areas facilitates motor execution in the lesioned brain. In addition, there is evidence that motor recovery is accompanied by a more random network topology with reduced local information processing. In conclusion, Stroke induces changes in functional and effective connectivity within and across hemispheres which relate to motor impairments and recovery thereof. Connectivity analyses may hence provide new insights into the pathophysiology underlying neurological deficits and may be further used to develop novel, neurobiologically informed treatment strategies.

Inferring evoked brain connectivity through adaptive perturbation

Inference of functional networks-representing the statistical associations between time series recorded from multiple sensors-has found important applications in neuroscience. However, networksexhibiting time-locked activity between physically independent elements can bias functional connectivity estimates employing passive measurements. Here, a perturbative and adaptive method of inferring network connectivity based on measurement and stimulation-so called "evoked network connectivity" is introduced. This procedure, employing a recursive Bayesian update scheme, allows principled network stimulation given a current network estimate inferred from all previous stimulations and recordings. The method decouples stimulus and detector design from network inference and can be suitably applied to a wide range of clinical and basic neuroscience related problems. The proposed method demonstrates improved accuracy compared to network inference based on passive observation of node dynamics and an increased rate of convergence relative to network estimation employing a naïve stimulation strategy.