Modulation of functional network properties in major depressive disorder following electroconvulsive therapy (ECT): a resting-state EEG analysis

Electroconvulsive therapy (ECT) is a highly effective neuromodulatory intervention for treatment-resistant major depressive disorder (MDD). Presently, however, understanding of its neurophysiological effects remains incomplete. In the present study, we utilised resting-state electroencephalography (RS-EEG) to explore changes in functional connectivity, network topology, and spectral power elicited by an acute open-label course of ECT in a cohort of 23 patients with treatment-resistant MDD. RS-EEG was recorded prior to commencement of ECT and again within 48 h following each patient’s final treatment session. Our results show that ECT was able to enhance connectivity within lower (delta and theta) frequency bands across subnetworks largely confined to fronto-central channels, while, conversely, more widespread subnetworks of reduced connectivity emerged within faster (alpha and beta) bands following treatment. Graph-based topological analyses revealed changes in measures of functional segregation (clustering coefficient), integration (characteristic path length), and small-world architecture following ECT. Finally, post-treatment enhancement of delta and theta spectral power was observed, which showed a positive association with the number of ECT sessions received. Overall, our findings indicate that RS-EEG can provide a sensitive measure of dynamic neural activity following ECT and highlight network-based analyses as a promising avenue for furthering mechanistic understanding of the effects of convulsive therapies

A Computational Assessment of Target Engagement in the Treatment of Auditory Hallucinations with Transcranial Direct Current Stimulation

We use auditory verbal hallucinations (AVH) to illustrate the challenges in defining and assessing target engagement in the context of transcranial direct current stimulation (tDCS) for psychiatric disorders. We defined the target network as the cluster of regions of interest (ROIs) that are consistently implicated in AVH based on the conjunction of multimodal meta-analytic neuroimaging data. These were prescribed in the New York Head (a population derived model) and head models of four single individuals. We appraised two potential measures of target engagement, tDCS-induced peak electric field strength and tDCS-modulated volume defined as the percentage of the volume of the AVH network exposed to electric field magnitude stronger than the postulated threshold for neuronal excitability. We examined a left unilateral (LUL) montage targeting the prefrontal cortex (PFC) and temporoparietal junction (TPJ), a bilateral (BL) prefrontal montage, and a 2 × 1 montage targeting the left PFC and the TPJ bilaterally. Using computational modeling, we estimated the peak electric field strength and modulated volume induced by each montage for current amplitudes ranging 1–4 mA. We found that the LUL montage was inferior to both other montages in terms of peak electric field strength in right-sided AVH-ROIs. The BL montage was inferior to both other montages in terms of modulated volume of the left-sided AVH-ROIs. As the modulated volume is non-linear, its variability between montages reduced for current amplitudes above 3 mA. These findings illustrate how computational target engagement for tDCS can be tailored to specific networks and provide a principled approach for future study desig

Computational Model of Electroconvulsive Therapy Considering Electric Field Dependent Skin Conductivity

Improvements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patient’s head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. However, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. In this thesis, we develop a computational framework based on diverse clinical data sets. We developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These “adaptive” models simulate ECT both during therapeutic stimulation using high current and when dynamic impedance is measured, as well as prior to stimulation when low current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject-specific maximum, and a deep scalp layer with a subject-specific fixed conductivity. We demonstrated that variation in these scalp parameters may explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrated that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. Our predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and ECT current delivery to the brain, themselves depend on assumptions about tissue properties. Broadly, our novel modeling pipeline opens the door to explore how adaptive-scalp conductivity may impact transcutaneous electrical stimulation (tES). Lastly, we incorporate the (device specific) role of frequency with a single overall assumption allowing quasi-static stimulations of ECT: appropriately parametrizing effective resistivity at single representative frequency (e.g., at 1 kHz), including subject-specific and adaptive skin resistivities. We only stipulate that our functions for (adaptive) resistivity at 1 kHz explain local tissue resistivity as they impact the static and dynamic impedance measures by specific ECT devices (e.g., Thymatron)

A Comprehensive View of Electrosleep: The History, Finite Element Models and Future Directions

Transcranial Electrical Stimulation (tES) encompasses all methods of non-invasive current application to the brain used in research and clinical practice. We present the first comprehensive and technical review, explaining the evolution of tES in both terminology and dosage over the past 100 years of research to present day. Current transcranial Pulsed Current Stimulation (tPCS) approaches such as Cranial Electrotherapy Stimulation (CES) descended from Electrosleep (ES) through Cranial Electro-stimulation Therapy (CET), Transcerebral Electrotherapy (TCET), and NeuroElectric Therapy (NET) while others like Transcutaneous Cranial Electrical Stimulation (TCES) descended from Electroanesthesia (EA) through Limoge, and Interferential Stimulation. Prior to a contemporary resurgence in interest, variations of transcranial Direct Current Stimulation were explored intermittently, including Polarizing current, Galvanic Vestibular Stimulation (GVS), and Transcranial Micropolarization. The development of these approaches alongside Electroconvulsive Therapy (ECT) and pharmacological developments are considered. Both the roots and unique features of contemporary approaches such as transcranial Alternating Current Stimulation (tACS) and transcranial Random Noise Stimulation (tRNS) are discussed. Trends and incremental developments in electrode montage and waveform spanning decades are presented leading to the present day. Commercial devices, seminal conferences, and regulatory decisions are noted. This is concluded with six rules on how increasing medical and technological sophistication may now be leveraged for broader success and adoption of tES. Despite this history, questions regarding the efficacy of ES remain including optimal dose (electrode placement and waveform). An investigation into brain electric field and current density produced by various montages that are historically relevant to ES was done to evaluate how these montages effect the brain. MRI-derived head models that were segmented using an automated segmentation algorithm and manual corrections were solved for four different electrode montages. The montages that were used are as follows: Sponge electrode on left and right eyes (active), Sponge electrodes over left and right mastoids (return); Sponge electrodes above left and right eyes (active), Sponge electrodes over left and right mastoids (return); High-Definition (HD) electrodes on AF3 and AF4 (active), 5x7 cm sponge on neck (return); HD electrodes on AF3 and AF4 (active), 5x7 sponge electrode on Iz (return). A high concentration of electric field was found on the optic nerve, with levels lowered as the electrodes moved further away from the eyes. There was also a moderate current density on the amygdala, a center involved with anxiety, as well as high electric fields on the brain stem which are centers for sleep. Using the models that were run for the electrosleep inspired montages the montage that was selected for the proposed experiment was to use anodes on AF3 and AF4 with the cathode on Iz. The anodes will be HD electrodes while the cathode will be a 5x7 cm sponge. Subjects will be split into 4 groups of 8 people each and will receive two legs of stimulation spaced one week apart. One leg will have current of 2 mA, 1 mA, 0.5 mA or sham while the other leg is all sham and the order in which they receive it will be randomized. Subjects will be stimulated for 20 minutes at 100 Hz and will spend a total of 40 minutes during the experiment where they will have their eyes recorded with an IR sensitive camera and they will be required to perform an odd-tone response task. Subjects are expected to fall asleep faster with higher levels of current and there is no added effect from baseline expected for subjects who receive sham stimulatio

Human head temperature and electric field investigations under ECT

Electroconvulsive therapy (ECT) is a non-invasive technique used to treat psychiatric conditions. A high strength low frequency electrical stimulation is delivered through two electrodes. The aim of this work is to develop an ECT finite element human head model to investigate the electric field and the increase in temperature due to the electrical stimulation. The bio-heat transfer equation combined with Laplace equation and their initial and boundary conditions are used to define the physics of the models. Firstly, finite ele-ment spherical human head models are created in COMSOL Multiphysics and the behaviour of the thermal field due to ECT electrical stimulation is analysed. Hetero-geneity was considered and thermal anisotropy of the skull layer was applied to the finite element models. Secondly, a realistic human head model is created using magnetic resonance images (MRI). Similar physics is applied to define the thermal and electrical problems, and the anisotropic conductivity of the skull is considered. The realistic models contain anatomical features and realistic tissue conductive properties. Through these models we investigate the role of stimulation parameters such as: electrode montages, strength of stimulation, temperature behaviour, etc. Later on, another realistic human head model with a brain tumor is created and a diffusion tensor image is included. Based on this model the white matter anisotropy is considered and the effect on the electric field is analysed. The results show that high temperatures only occur on external areas of the head, such as scalp and fat. The thermal conductivity anisotropy is insignificant from a heat-transferring point of view. However, the electrical anisotropy does need to be included in order to get more accurate outcomes. If ECT was applied to a patient with a brain tumor, then factors such as tumor location, aggressiveness, electrode montage, etc would need to be considered. Further work can be undertaken through computational simulation to make personal ECT treatment feasible in clinical practice

Noninvasive Neuromodulation: Modeling and Analysis of Transcranial Brain Stimulation with Applications to Electric and Magnetic Seizure Therapy

Bridging the fields of engineering and psychiatry, this dissertation proposes a novel framework for the rational dosing of electric and magnetic seizure therapy, including electroconvulsive therapy (ECT) and magnetic seizure therapy (MST), for the treatment of psychiatric disorders such as medication resistant major depression and schizophrenia. The objective of this dissertation is to develop computational modeling tools that allow ECT and MST stimulation paradigms to be biophysically optimized ex vivo, prior to testing safety and efficacy in preclinical and clinical trials. Despite therapeutic advances, treatment resistant depression (TRD) remains a largely unmet clinical need. ECT is highly effective for TRD, but its side effects limit its real-world clinical utility. Modifications of treatment technique (e.g., electrode placement, stimulus parameters, novel paradigms such as MST) significantly improve the tolerability of convulsive therapy. However, we know relatively little about the distribution of the electric field (E-field) induced in the brain to inform spatial targeting of ECT and MST. Lacking an understanding of biophysical and physiological mechanisms, refinements in ECT/MST technique rely exclusively on time-consuming and costly clinical trials. Consequently, key questions remain unanswered about how to position the ECT electrodes or MST coil for targeted brain stimulation. Addressing this knowledge gap, this dissertation proposes a new platform that will inform an improved spatial targeting of ECT and MST through state-of-the-art computer simulations of the E-field distribution in human and nonhuman primate (NHP) brain. Part I of this dissertation aims to develop anatomically realistic finite element models of transcranial electric and magnetic stimulation in human and NHPs incorporating tissue heterogeneity and anisotropy derived from structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. The NHP models of ECT and MST are created alongside the human model since NHPs are used in preclinical studies on the mechanisms of seizure therapy. Part II of this dissertation aims to apply the model developed in Part I to electric and magnetic seizure therapy. We compute the strength and spatial distributions of the E-field induced in the brain by various ECT and MST paradigms. The relative E-field strength among various regions of interest (ROIs) is examined to select electrode/coil configurations that produce most focal stimulation of target ROIs that are considered to mediate the therapeutic action of ECT and MST. Since E-field alone is insufficient to account for individual differences in neurophysiological response, we calibrate the E-field maps relative to the neural activation threshold via in vivo measurements of the corticospinal tract response to single pulses (motor threshold, MT). We derive an empirical estimate of the neural activation threshold by coupling simulated E-field strength with individually measured MT. The E-field strength relative to an empirical neural activation threshold and corresponding volume of suprathreshold stimulation (focality) is examined to inform the selection of ECT and MST stimulus pulse amplitude that will result in focal ROI stimulation. We contrast the ECT/MST stimulation strength and focality with conventional fixed and individually titrated pulse amplitude necessary to induce a seizure (seizure threshold, ST) to study pulse amplitude adjustment as a novel means of controlling stimulation strength and focality. This work provides a basis for rational dosing of seizure therapies that could help improve their risk/benefit ratio and guide the development of safer alternatives for patients with severe psychiatric disorders

Precision non-implantable neuromodulation therapies : a perspective for the depressed brain

Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although nonimplantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more ‘‘precision-oriented’’ practice

Enhancing ECT technique: the influence of anaesthetic factors on ictal seizure quality in electroconvulsive therapy

Electroconvulsive therapy (ECT) is an effective treatment for severe psychiatric disorders, particularly major depression. ECT involves the induction of a generalised seizure, under general anaesthesia. Commonly used anaesthetic agents possess anticonvulsant properties, which may reduce the quality of the induced seizure and the efficacy of ECT treatment. Preliminary evidence suggests that the time interval between anaesthetic induction and ECT stimulus administration impacts ECT seizure quality. Previously, it was unclear to what degree this was a direct consequence of the time interval, as opposed to the ventilation provided during the time interval, as hyperventilation has been shown to impact seizure quality. This thesis aimed to clarify the influence of the time interval and ventilation technique on seizure quality. Further, the importance of seizure quality for the efficacy of ECT was examined. Study 1 is a systematic review of evidence addressing the clinical relevance of ictal EEG quality, the main outcome of interest in studies 2 and 3. The review explores the relationship between ictal seizure quality, treatment technique and treatment outcomes. This review confirmed that ictal EEG quality is an important clinical measure, with evidence to support ECT dosing decisions based on changes in EEG quality across the ECT treatment course. Study 2 is a retrospective study examining the influence of the anaesthetic to ECT stimulus time interval on seizure quality, with thiopentone anaesthetic. This study confirms previous preliminary findings with propofol anaesthetic, with longer time intervals showing better seizure quality, providing further evidence of the clinical importance of the anaesthetic to ECT stimulus time interval. Study 3 is a prospective randomised trial examining the relative impact of the anaesthetic to ECT stimulus time interval, and the pre-treatment ventilation approach, on ictal seizure quality utilising a 2 x 2 factorial, crossover study design. Results confirm the significant effect of the anaesthetic to ECT stimulus time interval on seizure quality and argue strongly for the regular clinical monitoring, and potential optimisation, of this variable. By contrast, the effect of ventilation rate pre-treatment was not significant. In summary, this thesis provides new evidence demonstrating the impact of anaesthetic technique on ictal seizure quality and elucidates the clinical relevance of these novel findings

Numerical human head modelling and investigation for precise tDCS applications

As a non-invasive and sub-convulsive functional stimulation technique, transcranial direct current stimulation (tDCS) generates a relatively weak current intensity and applies the moderate current to the brain to modulate the level of cortical excitability. This neuromodulatory technique has been extensively used as a potential clinical treatment for various neuropsychiatric conditions, ranging from depression, addition to schizophrenia and Parkinson’s disease. Recently, tDCS has also been researched as a promising alternative treatment to alleviate neuropathic pain of cancer patients. The focus of this project is to numerically investigate the precise applications of tDCS based on a series of high resolution realistic human head model using finite element methods. Specifically, the influence of brain shift caused by gravity was firstly pre-validated using real shaped human head model. After that, this study focuses on the investigation of tDCS applications on the brain cancer patients in order to treat their neuropsychiatric conditions and neuropathic pain caused by the brain tumors. Thirdly, the role of blood vessels in shaping the induced current distributions within the cortex during tDCS was thoroughly investigated and addressed. The outcomes of this project highlight the importance of head orientation during the clinical application of tDCS. The results also clear the safety concern in applying tDCS to the patients with brain cancer. In addition, this project provides positive supports on the introduction of brain blood vessels during the precise human head modelling for tDCS though considerable workload will be involved