Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility

The Unique Determination of Neuronal Currents in the Brain via Magnetoencephalography

The problem of determining the neuronal current inside the brain from measurements of the induced magnetic field outside the head is discussed under the assumption that the space occupied by the brain is approximately spherical. By inverting the Geselowitz equation, the part of the current which can be reconstructed from the measurements is precisely determined. This actually consists of only certain moments of one of the two functions specifying the tangential part of the current. The other function specifying the tangential part of the current as well as the radial part of the current are completely arbitrary. However, it is also shown that with the assumption of energy minimization, the current can be reconstructed uniquely. A numerical implementation of this unique reconstruction is also presented

Vector-Based Approach for the Detection of Initial Dips Using Functional Near-Infrared Spectroscopy

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method for the detection of local brain activity using changes in the local levels of oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb). Simultaneous measurement of the levels of oxyHb and deoxyHb is an advantage of fNIRS over other modalities. This review provides a historical description of the physiological problems involved in the accurate identification of local brain activity using fNIRS. The need for improved spatial and temporal identification of local brain activity is described in terms of the physiological challenges of task selection and placement of probes. In addition, this review discusses challenges with data analysis based on a single index, advantages of the simultaneous analysis of multiple indicators, and recently established composite indicators. The vector-based approach provides quantitative imaging of the phase and intensity contrast for oxygen exchange responses in a time series and may detect initial dips related to neuronal activity in the skull. The vector plane model consists of orthogonal vectors of oxyHb and deoxyHb. Initial dips are hemodynamic reactions of oxyHb and deoxyHb induced by increased oxygen consumption in the early tasks of approximately 2–3 seconds. The new analytical concept of fNIRS, able to effectively detect initial dips, may extend further the clinical and social applications of fNIRS

신경전자기 신호원의 고유특성을 고려한 신호원 복원 알고리즘

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 계산과학전공, 2013. 2. 정현교.뇌전도 및 뇌자도를 이용한 신경전자기 신호원 영상법은 분포전류원 모델의 경우, 추가적인 정보와 제한조건이 주어져야만 유일한 신호원을 복원할 수 있는 역문제이다. 본 학위 논문에서는 뇌전도 및 뇌자도를 이용한 신호원 영상법의 정확도를 향상시키기 위한 새로운 방법을 제안한다. 뇌자도는 대뇌피질상에 존재하는 반지름 방향의 신호원에 둔감한 반면 뇌전도는 뇌자도에 비해 상대적으로 방향성에 큰 영향을 받지 않는 것으로 알려져 있다. 이러한 신호원 고유의 방향 특성은 현재까지 분포전류원 모델의 신호원 추정에 적용되지 않았다. 본 학위 논문에서는 뇌전도와 뇌자도를 동시 측정한 경우에 대해 신호원의 방향성을 고려해 대뇌피질 상에 존재하는 신호원을 복원하는 방법을 제안하였다. 기존의 뇌전도/뇌자도 신호원 영상법을 통해 복원된 신호원은 실제 신호원과 비교했을 때 한점에 집중되거나 넓은 영역에 퍼져 있다. 따라서 다양한 분포 형태를 가진 신호원의 경우 기존 복원법을 통해서는 신호원의 분포 형태를 추정하기 힘들다는 단점이 있었다. 본 학위 논문에서는 신호원의 최대값을 추정해 이러한 한계를 극복하여 신호원의 분포를 복원할 수 있는 새로운 신호원 영상법을 제안하였다. 제안된 방법들을 다양한 상황의 시뮬레이션을 통해 정확도를 평가했으며 간질환자의 데이터에 적용해 수술로 제거된 뇌부위와 뇌자도를 이용해 복원된 신호원의 위치와 분포영역을 비교하였다. 그 결과, 본 논문에서 제안한 방법들은 기존 방법에 비해 뇌자도 및 뇌전도의 국지화 정확도를 향상시켰 수 있었으며 앞으로 뇌영역 활성부위를 추정하는 의학 분야 및 역문제 연구에서 널리 사용될 것으로 기대된다.The functional imaging of neuroelectromagnetic sources of electroencephalographic (EEG) and magnetoencephalographic (MEG) based on distributed source models requires additional information and constraints on the source in order to overcome the ill-posedness and to obtain a plausible solution. In this dissertation, we present two methods to enhance accuracy of MEG and EEG source reconstruction. We propose a new cortical source imaging algorithm for integrating simultaneously recorded EEG and MEG, which takes into account the different sensitivity characteristics of the two modalities with respect to cortical source orientations. It is well known that MEG cannot reliably detect neuronal sources with radial orientation, whereas EEG is relatively less dependent on the source orientations than MEG. However, this intrinsic difference has not previously been taken into account in the integrative cortical source imaging using simultaneously recorded EEG and MEG data. On the other hands, most imaging algorithms explicitly favor either spatially more focal or diffuse current source patterns. Naturally, in a situation where both focal and extended sources are present or the source is arbitrary distributed, such reconstruction algorithms may yield inaccurate estimate. The other algorithm proposed in this dissertation improves accuracy of bio-electromagnetic source estimation regardless the extension of source distribution. The additional maximum amplitude constraint does successively enhance the localization accuracy in EEG/MEG source imaging. The proposed approaches are validated through numerical simulations and applied to practical epilepsy measurements and compared to the resection region. From the extensive analysis, it will be shown that the proposed approaches can enhance the source localization accuracy considerably, compared to the conventional approaches. Therefore the proposed methods in this dissertation are expected to be a promising approach on the research of inverse problem and many clinical applications of EEG and MEG.Abstracts 1 Contents 3 List of Tables 5 List of Figures 6 List of Symbols 8 1. Introduction 9 1.1 Motivation and Aim 9 1.2 Overview of Chapters 14 2. Basics of Functional Neuroimaging 16 2.1 Functional Neuroimaging 16 2.2 Measurment of EEG and MEG 19 2.2.1 EEG 19 2.2.2 MEG 22 2.3 Anatomy of Human Brain 24 2.4 Generation of Neuroelectromagnetic Fields 29 3. Forward and Inverse Problems 31 3.1 Neuroelectromagnetic Forward Problem 31 3.1.1 Quasi-Static Approximation 31 3.1.2 Analytic Formulation 32 3.1.3 Numerical Approach 35 3.1.4 Linearization of Forward Problem 38 3.2 Neuroelectromagnetic Inverse Problem 39 3.2.1 Distributed Source Model 39 3.2.2 L2 Norm Mminimization Approach 40 3.2.3 L1 Norm Minimization Approach 42 4. Preprocessing and Quantitative Evalution Metrics 43 4.1 Preprosessing 43 4.2 Techniques of Quantification of Distributed Source 46 5. Algorithm Considering Directional Characteristics 56 5.1 Proposed Algorithm 56 5.2 Numerical Experiment of Proposed Method 63 6. Algorithm Considering the Maximum Current Density 70 6.1 Proposed Algorithm 70 6.2 Numerical Experiment of Proposed Method 72 6.3 Application to Localization of Epileptic Zone 84 7. Conclsion 89 References 92 Appendix A. Derivation of L2 Norm Minimization Problem 100 Appendix B. Derivation of Directional Inverse Operators 105 Appendix C. Derivation of L1 Norm Minimization Problem 107 Abstract (in Korean) 110Docto