Fernando Gasca

Cellular effects of acute direct current stimulation: somatic and synaptic terminal effects

•  The diversity of cellular targets of direct current stimulation (DCS), including somas, dendrites and axon terminals, determine the modulation of synaptic efficacy. •  Axon terminals of cortical pyramidal neurons are two–three times more susceptible to polarization than somas. •  DCS in humans results in current flow dominantly parallel to the cortical surface, which in animal models of cortical stimulation results in synaptic pathway‐specific modulation of neuronal excitability. •  These results suggest that somatic polarization together with axon terminal polarization may be important for synaptic pathway‐specific modulation of DCS, which underlies modulation of neuronal excitability during transcranial DCS.

Transcranial electrical stimulation accelerates human sleep homeostasis.

The sleeping brain exhibits characteristic slow-wave activity which decays over the course of the night. This decay is thought to result from homeostatic synaptic downscaling. Transcranial electrical stimulation can entrain slow-wave oscillations (SWO) in the human electro-encephalogram (EEG). A computational model of the underlying mechanism predicts that firing rates are predominantly increased during stimulation. Assuming that synaptic homeostasis is driven by average firing rates, we expected an acceleration of synaptic downscaling during stimulation, which is compensated by a reduced drive after stimulation. We show that 25 minutes of transcranial electrical stimulation, as predicted, reduced the decay of SWO in the remainder of the night. Anatomically accurate simulations of the field intensities on human cortex precisely matched the effect size in different EEG electrodes. Together these results suggest a mechanistic link between electrical stimulation and accelerated synaptic homeostasis in human sleep.

Simulation of a conductive shield plate for the focalization of transcranial magnetic stimulation in the rat

Transcranial Magnetic Stimulation (TMS) in the rat is a powerful tool for investigating brain function. However, the state-of-the-art experiments are considerably limited because the stimulation usually affects undesired anatomical structures. A simulation of a conductive shield plate placed between the coil stimulator and the rat brain during TMS is presented. The Finite Element (FE) method is used to obtain the 3D electric field distribution on a four-layer rat head model. The simulations show that the shield plate with a circular window can improve the focalization of stimulation, as quantitatively seen by computing the three-dimensional half power region (HPR). Focalization with the shield plate showed a clear compromise with the attenuation of the induced field. The results suggest that the shield plate can work as a helpful tool for conducting TMS rat experiments on specific targets.

Finite element simulation of transcranial current stimulation in realistic rat head model

Transcranial current stimulation (tCS) is a method for modulating neural excitability and is used widely for studying brain function. Although tCS has been used on the rat, there is limited knowledge on the induced electric field distribution during stimulation. This work presents the finite element (FE) simulations of tCS in a realistic rat head model derived from MRI data. We simulated two electrode configurations and analyzed the spatial focality of the induced electric field for three implantation depth scenarios : (1) electrode implanted at the surface of the skull, (2) halfway through the skull and (3) in contact with cerebrospinal fluid. We quantitatively show the change in focality of stimulation with depth. This work emphasizes the importance of performing FE analysis in realistic models as a vital step in the design of tCS rat experiments. This can yield a better understanding of the location and intensity of stimulation, and its correlation to brain function.

MARS — Motor assisted robotic stereotaxy system

We report on the design, setup and first results of a robotized system for stereotactic neurosurgery. It features three translational and two rotational axes, as well as a motorized MicroDrive, thereby resembling the Zamorano-Duchovny (ZD) design of stereotactic frames (inomed Medizintechnik GmbH). Both rotational axes intersect in one point, the Center of the Arc, facilitating trajectory planning. We used carbon fiber-reinforced plastic to reduce the weight of the system. The robot can be mounted to standard operating tables side rails and can be transported on an operation theatre (OT) instrument table. We discuss the design paradigms, the resulting design and the actual robot. Kinematic calculations for the robot based on the Denavit-Hartenberg (DH) rules are presented. Positioning accuracy of our system is determined using two perpendicular cameras mounted on an industrial robot. The results are compared to a manual ZD system. We found that the robots mean position deviation is 0.231 mm with a standard deviation of 0.076 mm.

Automated segmentation of tissue structures in optical coherence tomography data

Segmentation of optical coherence tomography (OCT) images provides useful information, especially in medical imaging applications. Because OCT images are subject to speckle noise, the identification of structures is complicated. Addressing this issue, two methods for the automated segmentation of arbitrary structures in OCT images are proposed. The methods perform a seeded region growing, applying a model-based analysis of OCT A-scans for the seeds acquisition. The segmentation therefore avoids any user-intervention dependency. The first region-growing algorithm uses an adaptive neighborhood homogeneity criterion based on a model of an OCT intensity course in tissue and a model of speckle noise corruption. It can be applied to an unfiltered OCT image. The second performs region growing on a filtered OCT image applying the local median as a measure for homogeneity in the region. Performance is compared through the quantitative evaluation of artificial data, showing the capabilities of both in terms of structures detected and leakage. The proposed methods were tested on real OCT data in different scenarios and showed promising results for their application in OCT imaging.

3D printers may reduce animal numbers to train neuroengineering procedures

Neuroengineering related interventions to small animals always carry the high risk of missled procedures, frequently causing premature death of the animal. In this paper the manufacturing process to build a physical rat skull and brain model for educational use is presented. Out of MRI images a rat brain was segmented to build a negative mould. This form was used to cast an agarose rat brain. For an accompanying rat neurocranium model, CT images were rendered to a surface mesh and printed in 3D out of PLA. The presented workflow results in a high detailed rat skull and rat brain.

Model-Based Detection of White Matter in Optical Coherence Tomography Data

A method for white matter detection in Optical Coherence Tomography A-Scans is presented. The Kalman filter is used to obtain a slope change estimate of the intensity signal. The estimate is subsequently analyzed by a spike detection algorithm and then evaluated by a neural network binary classifier (Perceptron). The capability of the proposed method is shown through the quantitative evaluation of simulated A-Scans. The method was also applied to data obtained from a rats brain in vitro. Results show that the developed algorithm identifies less false positives than other two spike detection methods, thus, enhancing the robustness and quality of detection.