Techniques for imaging small impedance changes in the human head due to neuronal depolarisation

A new imaging modality is being developed, which may be capable of imaging small impedance changes in the human head due to neuronal depolarization. One way to do this would be by imaging the impedance changes associated with ion channels opening in neuronal membranes in the brain during activity. The results of previous modelling and experimental studies indicated that impedance changes between 0.6%and 1.7% locally in brain grey matter when recorded at DC. This reduces by a further of 10% if measured at the surface of the head, due to distance and the effect of the resistive skull. In principle, this could be measured using Electrical Impedance Tomography (ElT) but it is close to its threshold of detectability. With the inherent limitation in the use of electrodes, this work proposed two new schemes. The first is a magnetic measurement scheme based on recording the magnetic field with Superconducting Quantum Interference Devices (SQUIDs), used in Magnetoencephalography (MEG) as a result of a non-invasive injection of current into the head. This scheme assumes that the skull does not attenuate the magnetic field. The second scheme takes into consideration that the human skull is irregular in shape, with less and varying conductivity as compared to other head tissues. Therefore, a key issue is to know through which electrodes current can be injected in order to obtain high percentage changes in surface potential when there is local conductivity change in the head. This model will enable the prediction of the current density distribution at specific regions in the brain with respect to the varying skull and local conductivities. In the magnetic study, the head was modelled as concentric spheres, and realistic head shapes to mimic the scalp, skull, Cerebrospinal Auid (CSF) and brain using the Finite Element Method (FEM). An impedance change of 1 % in a 2cm-radius spherical volume depicting the physiological change in the brain was modelled as the region of depolarisation. The magnetic field, 1 cm away from the scalp, was estimated on injecting a constant current of 100 µA into the head from diametrically opposed electrodes. However, in the second scheme, only the realistic FEM of the head was used, which included a specific region of interest; the primary visual cortex (V1). The simulated physiological change was the variation in conductivity of V1 when neurons were assumed to be firing during a visual evoked response. A near DC current of 100 µA was driven through possible pairs of 31 electrodes using ElT techniques. For a fixed skull conductivity, the resulting surface potentials were calculated when the whole head remained unperturbed, or when the conductivity of V1 changed by 0.6%, 1 %, and 1.6%. The results of the magnetic measurement predicted that standing magnetic field was about 10pT and the field changed by about 3fT (0.03%) on depolarization. For the second scheme, the greatest mean current density through V1 was 0.020 ± 0.005 µAmm-2, and occurred with injection through two electrodes positioned near the occipital cortex. The corresponding maximum change in potential from baseline was 0.02%. Saline tank experiments confirmed the accuracy of the estimated standing potentials. As the noise density in a typical MEG system in the frequency band is about 7fT/√Hz, it places the change at the limit of detectability due to low signal to noise ratio. This is therefore similar to electrical recording, as in conventional ElT systems, but there may be advantages to MEG in that the magnetic field direcdy traverses the skull and instrumentation errors from the electrode-skin interface will be obviated. This has enabled the estimation of electrode positions most likely to permit recording of changes in human experiments and suggests that the changes, although tiny, may just be discernible from noise

Models and image: reconstruction in electrical impedance tomography of human brain function

Electrical Impedance Tomography (EIT) of brain function has the potential to provide a rapid portable bedside neuroimaging device. Recently, our group published the first ever EIT images of evoked activity recorded with scalp electrodes. While the raw data showed encouraging, reproducible changes of a few per cent, the images were noisy. The poor image quality was due, in part, to the use of a simplified reconstruction algorithm which modelled the head as a homogeneous sphere. The purpose of this work has been to develop new algorithms in which the model incorporates extracerebral layers and realistic geometry, and to assess their effect on image quality. An algorithm was suggested which allowed fair comparison between reconstructions assuming analytical and numerical (Finite Element Method - FEM) models of the head as a homogeneous sphere and as concentric spheres representing the brain, CSF, skull and scalp. Comparison was also made between these and numerical models of the head as a homogeneous, head-shaped volume and as a head-shaped volume with internal compartments of contrasting resistivity. The models were tested on computer simulations, on spherical and head-shaped, saline-filled tanks and on data collected during human evoked response studies. EIT also has the potential to image resistance changes which occur during neuronal depolarization in the cortex and last tens of milliseconds. Also presented in this thesis is an estimate of their magnitude made using a mathematical model, based on cable theory, of resistance changes at DC during depolarization in the cerebral cortex. Published values were used for the electrical properties and geometry of cell processes (Rail, 1975). The study was performed in order to estimate the resultant scalp signal that might be obtained and to assess the ability of EIT to produce images of neuronal depolarization

The Surface Laplacian Technique in EEG: Theory and Methods

This paper reviews the method of surface Laplacian differentiation to study EEG. We focus on topics that are helpful for a clear understanding of the underlying concepts and its efficient implementation, which is especially important for EEG researchers unfamiliar with the technique. The popular methods of finite difference and splines are reviewed in detail. The former has the advantage of simplicity and low computational cost, but its estimates are prone to a variety of errors due to discretization. The latter eliminates all issues related to discretization and incorporates a regularization mechanism to reduce spatial noise, but at the cost of increasing mathematical and computational complexity. These and several others issues deserving further development are highlighted, some of which we address to the extent possible. Here we develop a set of discrete approximations for Laplacian estimates at peripheral electrodes and a possible solution to the problem of multiple-frame regularization. We also provide the mathematical details of finite difference approximations that are missing in the literature, and discuss the problem of computational performance, which is particularly important in the context of EEG splines where data sets can be very large. Along this line, the matrix representation of the surface Laplacian operator is carefully discussed and some figures are given illustrating the advantages of this approach. In the final remarks, we briefly sketch a possible way to incorporate finite-size electrodes into Laplacian estimates that could guide further developments.Comment: 43 pages, 8 figure

Functional Electrical Impedance Tomography of adult and neonatal brain function.

Electrical Impedance Tomography (EIT) is a fast, portable imaging technique that produces tomographic images of the internal impedance of an object from surface electrode measurements. This thesis reports the first use of EIT to image evoked brain activity in adults and neonates and determines whether accurate EIT images could be obtained from the adult and neonatal brain. In addition, a realistic head-tank phantom was developed to test the performance of EIT with known impedance changes placed within a real human skull. Two EIT systems were used. Images were obtained using 31 or 21 Ag/AgCl EEG scalp electrodes in adults and neonates, respectively, with either 256 or 187 individual impedance measurements from different electrode combinations: 2 applied a safe, alternating current and 2 measured the resultant scalp voltage. Imaging was performed using a block design with 6-15 stimulation periods of between 10-75s during either: 1) Visual, 2) Somatosensory or 3) Motor stimuli. Impedance changes were detected in 38/39 adults and 9/9 neonates within 0.6-5.8s after stimulus onset, and returned to baseline 7.6-36s after stimulus cessation. Reconstructed images were noisy: -20-70% images showed correct localisation to the expected area of cortex stimulated by the visual, motor or somatosensory paradigms. As EIT images from the head-tank localised changes within 10% of the impedance perturbation, this indicated that poor localisation in humans was not due to the head-shape or the skull, but may be related to unknown physiological factors. An improved EIT reconstruction algorithm, using a computerised finite-element model of the head, showed improved localisation for the adult images. This is the first demonstration that EIT can detect and image impedance changes in the head, probably due to increased regional cerebral blood volume in the activated cortex. Improvements may enable more accurate neuroimaging of the adult and neonatal brain for use in clinical practice

An assessment of some possible neurological applications of electrical impedance tomography

Electrical impedance tomography (EIT) is a recently developed technique which produces reconstructed images of the internal distribution of the impedance of an object from measurement with external electrodes. It was assessed for its possible application in imaging intra-cranial disorders non- invasively with the use of scalp electrodes. Cerebral impedance increases of 12-55% were measured by a four electrode method at 50 kHz during global cerebral ischaemia or cortical spreading depression (CSD) in anaesthetized rats. Measured with scalp electrodes in two pairs 2-26 mm apart, impedance increased by 1.8-5.9% during global cerebral ischaemia for 5 or 15 min; the changes correlated in duration with cortical impedance changes, but increased more gradually. Increases of about 2% still were observed when the effects of variations in temperature and local scalp impedance were excluded. A finite element model was used to predict the attenuation of a signal due to cerebral anoxic depolarization by the extracerebral layers. These residual impedance changes were compatible with this, but their cause by other mechanisms related to the method of production of cerebral ischaemia could not be ruled out. An unexpected decrease of 0.8% was observed during CSD with electrodes 0.5mm apart on the scalp. This became undetectable when scalp temperature was kept constant. The model predicted that impedance changes of about 1% could be measured during CSD with scalp electrodes spaced further apart. Images were then collected using a prototype EIT system operating at 51 kHz during the same model of cerebral ischaemia. Test objects in a medium of constant resistivity could be accurately localized, but spatial resolution of intracranial impedance changes was substantially degraded when recorded with scalp electrodes. EIT has the potential for imaging various cerebral physiological or pathological changes, but improvements to the reconstruction algorithm are needed if regional intracerebral changes are to be discriminated during recording with scalp electrodes

Preliminary studies in imaging neuronal depolarization in the brain with electrical or magnetic detection impedance tomography.

Electrical impedance Tomography (EIT) is a novel medical imaging method which has the potential to provide the revolutionary advance of a method to image fast neural activity non-invasively. by imaging electrical impedance changes over milliseconds which occur when neuronal ion channels open during activity. These changes have been estimated to be c.1% locally in cerebral cortex, if measured with applied current below 100Hz. The purpose of this work was to determine if such changes could be reproducibly recorded in humans non invasive First, a novel recessed electrode was designed and tested to determine to enable a maximal current of 1mA to be applied to the scalp without causing painful skin sensation. Modelling indicated that this produced a peak current density of 0.3A/m2 in underlying cortex, which was below the threshold for stimulation. Next, the signal-to-noise ratio of impedance changes during evoked visual activity was investigated in healthy volunteers with current injected with scalp electrodes and recording of potential by scalp electrodes (Low Frequency EIT) or magnetic field by magnetoencephalography (Magnetic Detection EIT). Numerical FEM simulations predicted that resistivity changes of 1% in the primary7 visual cortex translate into scalp voltage changes of IjiV (0.004%) and external magnetic field changes of 30fT (0.2%) and were independently validated in saline filled tanks. In vivo, similar changes with a signal-to-noise ratio of 3 after averaging for 10 minutes were recorded for both methods the main noise sources were background brain activity and the current source. These studies with non-invasive scalp recording have, for the first time, demonstrated the existence of such changes when measured non-invasively. These are unfortunately too low to enable reliable imaging within a realistic recording time but support the view that such imaging could be possible in animal or human epileptic studies with electrodes placed on the brain or non-invasively following technological improvements this further work is currently in progress

Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media

The resistive or non-resistive nature of the extracellular space in the brain is still debated, and is an important issue for correctly modeling extracellular potentials. Here, we first show theoretically that if the medium is resistive, the frequency scaling should be the same for electroencephalogram (EEG) and magnetoencephalogram (MEG) signals at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. The frequency scaling of EEG displays coherent variations across the brain, in general between 1/f and 1/f^2, and tends to be smaller in parietal/temporal regions. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. In conclusion, there is a significant difference in frequency scaling between EEG and MEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive.Comment: Submitted to Journal of Computational Neuroscienc