Should stimulation parameters be individualized to stop seizures: Evidence in support of this approach.

OBJECTIVE: Deep-brain electrical stimulation (DBS) is a treatment modality being explored for many neurologic diseases and is a potentially potent means of disrupting the aberrant rhythms that arise during the epileptic seizures that afflict >1% of the population. However, current DBS protocols typically employed are formulated a priori and do not reflect the electrophysiologic dynamics within the brain as seizures arise, which may underlie their limited efficacy. This study investigates how the efficacy of DBS could be improved using endogenous dynamics to inform stimulation protocols. METHODS: Multisite brain dynamics within the circuit of Papez were calculated in a chronic rat limbic epilepsy model induced via lithium chloride/pilocarpine intraperitoneal injections. Stimulation/recording electrodes were placed in the CA3 region of the left and right hippocampi and the anteromedial nucleus of the left thalamus. Deconvolution of local field potentials using empirical mode decomposition (EMD) and phase synchrony analysis revealed multisite coherence as seizures approached natural termination that could not be detected with Fourier analysis. Multisite stimulation used charge-neutral biphasic square waves at frequencies observed during natural termination. RESULTS: Synchronization of electrical activity across sites occurred as both spontaneous and evoked seizures naturally terminated. Furthermore, the location and frequency of the synchrony varied between subjects but was stable in time within each animal. DBS protocols were significantly more effective at rapidly stopping seizures when the frequency and location of multisite stimulation reflected the endogenous synchrony dynamics observed in each subject as seizures naturally terminated. SIGNIFICANCE: These results strongly support the approach of tailoring DBS protocols to individual endogenous rhythms that may represent how brains naturally resolve epileptic seizures. This approach may significantly improve the overall efficacy of this potentially important therapy.

Electrical control of epilepsy.

Epilepsy afflicts approximately 1-2% of the world's population. The mainstay therapy for treating the chronic recurrent seizures that are emblematic of epilepsy are drugs that manipulate levels of neuronal excitability in the brain. However, approximately one-third of all epilepsy patients get little to no clinical relief from this therapeutic regimen. The use of electrical stimulation in many forms to treat drug-refractory epilepsy has grown markedly over the past few decades, with some devices and protocols being increasingly used as standard clinical treatment. This article seeks to review the fundamental modes of applying electrical stimulation-from the noninvasive to the nominally invasive to deep brain stimulation-for the control of seizures in epileptic patients. Therapeutic practices from the commonly deployed clinically to the experimental are discussed to provide an overview of the innovative neural engineering approaches being explored to treat this difficult disease.

Design of optimal multi-site brain stimulation protocols via neuro-inspired epilepsy models for abatement of interictal discharges.

Objective. Electrical brain stimulation is recognized as a promising therapeutic approach for treating brain disorders such as epilepsy. However, the use of this technique is still largely empirical, since stimulation parameters and targets are chosen using a trial-and-error approach. Therefore, there is a pressing need to design optimal, rationale-based multi-site brain stimulation protocols to control epileptiform activity.Approach. Here, we developed biologically-inspired models of brain activity receiving stimulation at two levels of description (single- and multi-population epileptogenic networks). First, we used bifurcation analysis to determine optimal parameters able to abort epileptiform patterns. Second, we present a graph-theory based method to classify network populations in an epileptogenic network based on their contribution to seizure generation and propagation. Main results. The best therapeutic effects (i.e. reduction of epileptiform discharges duration and occurrence rate) were obtained by the specific targeting of populations with the highest eigenvector centrality values. The timing of stimulation was also found to be critical in seizure abortion impact.Significance. Overall, our results provide a proof-of-concept that using network neuroscience combined with physiology-based computational models of brain activity can provide an effective method for the rational design of brain stimulation protocols in epilepsy.

Stimulating Solutions for Intractable Epilepsy.

Implantable devices for controlling medically intractable seizures nondestructively are rapidly advancing. These offer reversible, potentially, restorative options beyond traditional, surgical procedures, which rely, largely on resection or ablation of selected brain sites. Several lines of, investigation aimed at improving efficacy of these devices are discussed, ranging from identifying novel subcortical, white matter, or cell-type specific targets to engineering advances for adaptive techniques based- on continuous, dynamic system analysis.

Reconstruction of post-synaptic potentials by reverse modeling of local field potentials.

OBJECTIVE: Among electrophysiological signals, local field potentials (LFPs) are extensively used to study brain activity, either in vivo or in vitro. LFPs are recorded with extracellular electrodes implanted in brain tissue. They reflect intermingled excitatory and inhibitory processes in neuronal assemblies. In cortical structures, LFPs mainly originate from the summation of post-synaptic potentials (PSPs), either excitatory (ePSPs) or inhibitory (iPSPs) generated at the level of pyramidal cells. The challenging issue, addressed in this paper, is to estimate, from a single extracellularly-recorded signal, both ePSP and iPSP components of the LFP. APPROACH: The proposed method is based on a model-based reverse engineering approach in which the measured LFP is fed into a physiologically-grounded neural mass model (mesoscopic level) to estimate the synaptic activity of a sub-population of pyramidal cells interacting with local GABAergic interneurons. MAIN RESULTS: The method was first validated using simulated LFPs for which excitatory and inhibitory components are known a priori and can thus serve as a ground truth. It was then evaluated on in vivo data (PTZ-induced seizures, rat; PTZ-induced excitability increase, mouse; epileptiform discharges, mouse) and on in clinico data (human seizures recorded with depth-EEG electrodes). SIGNIFICANCE: Under these various conditions, results showed that the proposed reverse engineering method provides a reliable estimation of the average excitatory and inhibitory post-synaptic potentials originating of the measured LFPs. They also indicated that the method allows for monitoring of the excitation/inhibition ratio. The method has potential for multiple applications in neuroscience, typically when a dynamical tracking of local excitability changes is required.

Neuronal desynchronization as a trigger for seizure generation.

Experimental reports have appeared which challenge the dogma that epileptic seizures arise as a consequence of neuronal hypersynchronization. We sought to explore what mechanisms that desynchronize neuronal firing could induce epileptic seizures. A computer model of connections in a mammalian hippocampal slice preparation was constructed including two recently-reported distinct inhibitory feedback circuits. When inhibition by interneurons that synapse on pyramidal dendrites was decreased, highly localized seizure-like bursting was observed in the CA3 region similar to that which occurs experimentally under GABAergic blockade. In contrast, when inhibition by interneurons that synapse in the axosomatic region was similarly decreased, no such bursting was observed. However, when this transient inhibition was increased, normal coordinated spread of excitation was interrupted by high-frequency localized seizure-like bursting. The increase of this inhibitory input resulted in decreased cell coupling of pyramidal neurons. A decrease in phase coherence was initially observed until seizure-like activity initiated causing a net increase in coherence as has been observed in epileptic patients. These results provide a possible pathway in which a decrease in synchronization could provide the trigger for inducing epileptiform activity.

Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients.

Spatiotemporal evolution of synchrony dynamics among neuronal populations plays an important role in decoding complicated brain function in normal cognitive processing as well as during pathological conditions such as epileptic seizures. In this paper, a non-linear analytical methodology is proposed to quantitatively evaluate the phase-synchrony dynamics in epilepsy patients. A set of finite neuronal oscillators was adaptively extracted from a multi-channel electrocorticographic (ECoG) dataset utilizing noise-assisted multivariate empirical mode de-composition (NA-MEMD). Next, the instantaneous phases of the oscillatory functions were extracted using the Hilbert transform in order to be utilized in the mean-phase coherence analysis. The phase-synchrony dynamics were then assessed using eigenvalue decomposition. The extracted neuronal oscillators were grouped with respect to their frequency range into wideband (1-600 Hz), ripple (80-250 Hz), and fast-ripple (250-600 Hz) bands in order to investigate the dynamics of ECoG activity in these frequency ranges as seizures evolve. Drug-refractory patients with frontal and temporal lobe epilepsy demonstrated a reduction in phase-synchrony around seizure onset. However, the network phase-synchrony started to increase toward seizure end and achieved its maximum level at seizure offset for both types of epilepsy. This result suggests that hyper-synchronization of the epileptic network may be an essential self-regulatory mechanism by which the brain terminates seizures.

Using Interictal HFOs to Improve the Identification of Epileptogenic Zones in Preparation for Epilepsy Surgery.

For the more than 15 million patients who have drug-resistant epilepsy, surgical resection of the region where seizure arise is often the only alternative therapy. However, the identification of this epileptogenic zone (EZ) is often imprecise. Generally, insufficient EZ identification and resection may cause seizures to continue and too much resection may lead to unnecessary neurological deficits. In this paper, an automatic high frequency oscillations (HFOs) detection method based on noise-assisted multivariate EMD (NA-MEMD) is proposed to improve the localization of the EZ for epilepsy patients. In this method, different detected HFO types such as fast-ripple (FR), ripple (R), and fast-ripple concurrent with ripple (FRandR) are utilized to investigate their clinical relevance in identifying EZ. The proposed method may significantly improve the precision by which pathological brain tissue can be identified.

EMD-Based, Mean-Phase Coherence Analysis to Assess Instantaneous Phase-Synchrony Dynamics in Epilepsy Patients.

In this paper, an adaptive, non-linear, analytical methodology is proposed in order to quantitatively evaluate the instantaneous phase-synchrony dynamics in epilepsy patients. A group of finite neuronal oscillators is extracted from a multichannel electrocorticographic (ECoG) data, using the empirical mode decomposition (EMD). The instantaneous phases of the extracted oscillators are measured using the Hilbert transform in order to be utilized in the mean-phase coherence analysis. Finally, the dynamical evolution of phase-synchrony among the extracted neuronal oscillators within 1-600 Hz frequency range is assessed using eigenvalue decomposition. A different phasesynchrony dynamics was observed in two patients with frontal vs. temporal lobe epilepsy, as their seizures evolve. However, experimental results demonstrated a hypersynchrony level at seizure offset for both types of epilepsy during the ictal periods. This result suggests that hypersynchronization of the epileptic network may be a crucial, self-regulatory mechanism by which the brain terminate seizures.

Electrical control of epileptic seizures.

SUMMARY: Epilepsy is among the most common neurologic disorders, yet it is estimated that about one third of patients do not respond favorably to currently available drug treatments and up to 50% experience major side effects of these treatments. Although surgical resection of seizure foci can provide reduction or cessation of seizure incidents, a significant fraction of pharmacologically intractable seizure patients are not considered viable candidates for such procedures. Research advances in applying electrical stimulation as an alternative treatment for intractable epilepsy have been reported. The primary focus of these studies has been the search for optimized stimulation protocols by which to electrically suppress, revert or prevent seizures. In this review, the authors discuss some of the promising results that have been achieved. These results are organized in three broad categories based on how such protocols are generated. They focus on how information of the electrical activity in the brain is incorporated in the control schemes, namely: open loop, semiclosed loop, and closed loop protocols. Benefits, potential promises, and challenges of these different control techniques are discussed.

Computer-assisted intraaneurysmal thrombus visualization.

OBJECTIVE: Improved visualization of intraaneurysmal thrombi can contribute to understanding their impact on clinical courses and treatments. Digital subtraction angiography (DSA) demonstrates the hemodynamic portion of aneurysm domes and vasculature structures and has been considered by many to be the principal technique used for aneurysm diagnosis. An intraaneurysmal thrombus may be visualized as a filling defect on DSA, but DSA does not reliably indicate the presence of an intraaneurysmal thrombus or its details. Computerized tomography (CT) and magnetic resonance (MR) imaging may have advantages over DSA, particularly because of their capacity to visualize soft tissue. Hence, we investigated the reconstruction of MR and CT images and compared it to DSA for assessment of intraaneurysmal thrombi. METHODS: Thirty-one patients with 34 aneurysms were enrolled. The entire group was examined with DSA. Sixteen cases were also examined with MR imaging; the remaining 15 were examined with CT imaging. Images of intraaneurysmal thrombi were rendered from corresponding MRI and soft tissue scans using CT. Intracranial vessels and aneurysms were defined from MR and CT angiography. Whole images were linked via imaging software for the reconstruction of vasculature structures. Images were superimposed to produce visualizations of thrombi situated in aneurysmal bodies. RESULTS: Reconstruction of the MR and CT images clearly demonstrated the presence and details of intraaneurysmal thrombi in 9 (26.4 %) of 34 aneurysms. DSA detected only 4 (11.7 %) of the cases as a filling defect. Significant differences in thrombus visualization were observed between DSA used alone or in conjunction with either MRA (P = .02) or CTA (P = .04) images. Mean volume of thrombosed aneurysms was 3.2 +/- 0.84 mL (mean +/- SEM) and thrombosis volume was 0.9 +/- 0.31 mL. Aneurysm and nested thrombus volumes were highly correlated (r = 0.987; P < .001). CONCLUSION: Intraaneurysmal thrombi were clearly visualized by computerized MR and CT image reconstruction. MR and CT were superior to DSA alone in demonstrating the presence of intra-aneurysmal thrombi. Computer-assisted 3-D visualization can be invaluable in understanding the shape and volume of intraaneurysmal thrombi, which may contribute to more accurate assessment and effective treatment of aneurysms cases.

Computational and experimental analysis of TMS-induced electric field vectors critical to neuronal activation.

OBJECTIVE: Transcranial magnetic stimulation (TMS) represents a powerful technique to noninvasively modulate cortical neurophysiology in the brain. However, the relationship between the magnetic fields created by TMS coils and neuronal activation in the cortex is still not well-understood, making predictable cortical activation by TMS difficult to achieve. Our goal in this study was to investigate the relationship between induced electric fields and cortical activation measured by blood flow response. Particularly, we sought to discover the E-field characteristics that lead to cortical activation. APPROACH: Subject-specific finite element models (FEMs) of the head and brain were constructed for each of six subjects using magnetic resonance image scans. Positron emission tomography (PET) measured each subject's cortical response to image-guided robotically-positioned TMS to the primary motor cortex. FEM models that employed the given coil position, orientation, and stimulus intensity in experimental applications of TMS were used to calculate the electric field (E-field) vectors within a region of interest for each subject. TMS-induced E-fields were analyzed to better understand what vector components led to regional cerebral blood flow (CBF) responses recorded by PET. MAIN RESULTS: This study found that decomposing the E-field into orthogonal vector components based on the cortical surface geometry (and hence, cortical neuron directions) led to significant differences between the regions of cortex that were active and nonactive. Specifically, active regions had significantly higher E-field components in the normal inward direction (i.e., parallel to pyramidal neurons in the dendrite-to-axon orientation) and in the tangential direction (i.e., parallel to interneurons) at high gradient. In contrast, nonactive regions had higher E-field vectors in the outward normal direction suggesting inhibitory responses. SIGNIFICANCE: These results provide critical new understanding of the factors by which TMS induces cortical activation necessary for predictive and repeatable use of this noninvasive stimulation modality.

Evaluation of Cortical Thickness after Traumatic Brain Injury in Military Veterans.

Military service members frequently sustain traumatic brain injuries (TBI) while on active duty, a majority of which are related to explosive blasts and are mild in severity. Studies evaluating the cortical gray matter in persons with injuries of this nature remain scarce. The purpose of this study was to assess cortical thickness in a sample of military veterans with chronic blast-related TBI. Thirty-eight veterans with mild TBI and 17 veterans with moderate TBI were compared with 58 demographically matched healthy civilians. All veterans with TBI sustained injuries related to a blast and were between 5 and 120 months post-injury (M = 62.08). Measures of post-traumatic stress disorder (PTSD) and depression were administered, along with a battery of neuropsychological tests to assess cognition. The Freesurfer software package was used to calculate cortical thickness of the participants. Results demonstrated significant clusters of cortical thinning in the right hemispheric insula and inferior portions of the temporal and frontal lobe in both mild and moderate TBI participants. The TBI sample from this study demonstrated a high incidence of comorbid PTSD and depression symptoms, which is consistent with the previous literature. Cortical thickness values correlated with measures of PTSD, depression, and post-concussive symptoms. This study provides evidence of cortical thinning in the context of chronic blast-related mild and moderate TBI in military veterans who have comorbid psychiatric symptoms. Our findings provide important insight into the natural progression of long-term cortical change in this population and may have implications for future clinical evaluation and treatment.

Identification of determinism in noisy neuronal systems.

Most neuronal ensembles are nonlinear excitable systems. Thus it is becoming common to apply principles derived from nonlinear dynamics to characterize neuronal systems. One important characterization is whether such systems contain deterministic behavior or are purely stochastic. Unfortunately, many methods used to make this distinction do not perform well when both determinism and high-amplitude noise are present which is often the case in physiological systems. Therefore, we propose two novel techniques for identifying determinism in experimental systems. The first, called short-time expansion analysis, examines the expansion rate of small groups of points in state space. The second, called state point forcing, derives from the technique of chaos control. The system state is forced onto a fixed point, and the subsequent behavior is analyzed. This technique can be used to verify the presence of fixed points (or unstable periodic orbits) and to assess stationarity. If these are present, it implies that the system contains determinism. We demonstrate the use and possible limitations of these two techniques in two systems: the Hénon map, a classic example of a chaotic system, and spontaneous epileptiform bursting in the rat hippocampal slice. Identifying the presence of determinism in a physiological system assists in the understanding of the system's dynamics and provides a mechanism for manipulating this behavior.

Manipulating epileptiform bursting in the rat hippocampus using chaos control and adaptive techniques.

Epilepsy is a relatively common disease, afflicting 1%-2% of the population, yet many epileptic patients are not sufficiently helped by current pharmacological therapies. Recent reports have suggested that chaos control techniques may be useful for electrically manipulating epileptiform bursting behavior in vitro and could possibly lead to an alternative method for preventing seizures. We implemented chaos control of spontaneous bursting in the rat hippocampal slice using robust control techniques: stable manifold placement (SMP) and an adaptive tracking (AT) algorithm designed to overcome nonstationarity. We examined the effect of several factors, including control radius size and synaptic plasticity, on control efficacy. AT improved control efficacy over basic SMP control, but relatively frequent stimulation was still necessary and very tight control was only achieved for brief stretches. A novel technique was developed for validating period-1 orbit detection in noisy systems by forcing the system directly onto the period-1 orbit. This forcing analysis suggested that period-1 orbits were indeed present but that control would be difficult because of high noise levels and nonstationarity. Noise might actually be lower in vivo, where regulatory inputs to the hippocampus are still intact. Thus, it may still be feasible to use chaos control algorithms for preventing epileptic seizures.

Rapid onset of a kainate-induced mirror focus in rat hippocampus is mediated by contralateral AMPA receptors.

The development of an epileptic "mirror" focus in an area of the brain contralateral to the primary epileptic focus typically evolves over days in the experimental setting after status epilepticus or electrical kindling of the primary focal region. In contrast, we observed the rapid development of an apparent mirror focus in the contralateral hippocampus following microinjection of kainic acid (KA) in the ipsilateral hippocampus in rats. Using multisite intracranial recordings, local field potentials were recorded in anesthetized adult male rats using electrodes implanted in the CA3 region of both hippocampi and in the anteromedial nucleus of the thalamus. Epileptogenesis was induced by microinjection of KA in the ipsilateral CA3 region. Development of seizures was followed under three experimental perturbations to the contralateral hippocampus: (A) no treatment, (B) pre-treatment with microinjection of the AMPA/Kainate receptor antagonist CNQX, and (C) pre-treatment with microinjection of the selective kainate receptor antagonist UBP 301. Both control and UBP 301 groups had seizures preferentially originate in the contralateral hippocampus appearing within ten minutes of KA injection. In contrast, the CNQX group had seizures preferentially originate in the ipsilateral hippocampus. By tracking the order of seizure onset, the probability that a hippocampal seizure would propagate across commissural fibers prior to any thalamic seizure activity was significantly reduced in the CNQX group compared to control and UBP groups suggesting that the AMPA receptor mediated component responsible for mirror focus development was also necessary for the spread of ictal activity via the commissural fibers. Understanding how a complex circuit in the brain develops may be critical to uncovering ways of either disrupting its development or treating its effects. The rapid appearance of a contralateral mirror focus via AMPA receptors in a limbic epilepsy model might be the mechanism by which a putative long-term mirror focus is established in vivo and may also underlie how secondary generalization progresses in some cases.

Synchrony dynamics across brain structures in limbic epilepsy vary between initiation and termination phases of seizures.

Neuronal populations in the brain achieve levels of synchronous electrophysiological activity during both normal brain function and pathological states such as epileptic seizures. Understanding how the dynamics of neuronal oscillators in the brain evolve from normal to diseased states is a critical component toward decoding such complex behaviors. In this study, we sought to develop a more in-depth understanding of multisite dynamics underlying seizure evolution in limbic epilepsy by analyzing oscillators in recordings of local field potentials from three brain structures (bilateral hippocampi and anteromedial thalamus) in a kainic acid in vivo rat model of temporal lobe epilepsy extracted using the empirical mode decomposition (EMD) technique. EMD provides an adaptive nonlinear decomposition into a set of finite oscillatory components. Oscillator frequencies, power, and phase synchrony were assessed within and between sites as seizures evolved. Consistent patterns of low-frequency (~35 Hz) synchrony occurred transiently during early-stage ictogenesis between thalamus and both hippocampi; in contrast, higher frequency (~120 Hz) synchrony appeared between thalamus and focal hippocampus as seizures naturally terminated. These multi-site synchrony events may provide a key insight into how synchrony disruption via stimulation could be targeted as well as contribute to a better understanding of how brain synchrony evolves in epilepsy.

PET-based confirmation of orientation sensitivity of TMS-induced cortical activation in humans.

BACKGROUND: Currently, it is difficult to predict precise regions of cortical activation in response to transcranial magnetic stimulation (TMS). Most analytical approaches focus on applied magnetic field strength in the target region as the primary factor, placing activation on the gyral crowns. However, imaging studies support M1 targets being typically located in the sulcal banks. OBJECTIVE/HYPOTHESIS: To more thoroughly investigate this inconsistency, we sought to determine whether neocortical surface orientation was a critical determinant of regional activation. METHODS: MR images were used to construct cortical and scalp surfaces for 18 subjects. The angle (θ) between the cortical surface normal and its nearest scalp normal for ~50,000 cortical points per subject was used to quantify cortical location (i.e., gyral vs. sulcal). TMS-induced activations of primary motor cortex (M1) were compared to brain activations recorded during a finger-tapping task using concurrent positron emission tomographic (PET) imaging. RESULTS: Brain activations were primarily sulcal for both the TMS and task activations (P < 0.001 for both) compared to the overall cortical surface orientation. Also, the location of maximal blood flow in response to either TMS or finger-tapping correlated well using the cortical surface orientation angle or distance to scalp (P < 0.001 for both) as criteria for comparison between different neocortical activation modalities. CONCLUSION: This study provides further evidence that a major factor in cortical activation using TMS is the orientation of the cortical surface with respect to the induced electric field. The results show that, despite the gyral crown of the cortex being subjected to a larger magnetic field magnitude, the sulcal bank of M1 had larger cerebral blood flow (CBF) responses during TMS.

A study of multi-site brain dynamics during limbic seizures.

Neuronal populations in the brain achieve levels of synchronous electrophysiological activity as a consequence of both normal brain functions as well as during pathological states such as in epileptic seizures. Understanding the nature of this synchrony and the dynamics of neuronal oscillators in the brain is a critical component towards decoding such complex behaviors. We have sought to achieve a more in-depth understanding of the dynamics underlying the evolution of seizures in limbic epilepsy by analyzing recordings of local field potentials from three subcortical nuclei that are part of the circuit of Papez in a kainic acid rat model of temporal lobe epilepsy using the empirical mode decomposition technique. The empirical mode decomposition allows for an adaptive and nonlinear decomposition of the local field potentials into a series of finite oscillatory components. We calculated the frequencies, power, and measures of phase synchrony of these oscillatory components as seizures evolve in the brain and discovered patterns of phase synchrony that varies between the different stages of the seizures.

Using increased structural detail of the cortex to improve the accuracy of modeling the effects of transcranial magnetic stimulation on neocortical activation.

Transcranial magnetic stimulation (TMS) is a noninvasive technique that can alter brain activation by inducing electrical current in neurons using dynamic magnetic fields. Because of its painless nature, clinical usage has expanded to diagnostic purposes and therapeutic treatments. However, several issues and challenges still exist for TMS. A very limited understanding of the interaction between magnetic fields, cortical structure, and consequent brain excitation is currently available. Most previously published models lack key anatomical details that are essential elements in calculating induced electric fields critical to brain activation. In this study, gross human brain and head structures were derived using multiple modality images and a finite-element model was constructed. Furthermore, microstructural detail was incorporated using neocortical columnar structures. Using this detailed model, we investigated the influence of TMS coil position, distance and orientation on induced electric fields, and neocortical activation. Several activation standards and conductivity values were tested for their impact on the distribution of neocortical activation. Optimized activation patterns agreed well with published clinical experiments, under similar coil configurations. A structurally detailed finite-element model capable of accurately predicting neocortical activation for a given coil/magnetic field profile may provide a critical resource for understanding the electrophysiological consequences of TMS and for further refinement of this important technique.