Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates.

نویسندگان

  • Karlo A Malaga
  • Karen E Schroeder
  • Paras R Patel
  • Zachary T Irwin
  • David E Thompson
  • J Nicole Bentley
  • Scott F Lempka
  • Cynthia A Chestek
  • Parag G Patil
چکیده

OBJECTIVE We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. APPROACH A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. MAIN RESULTS From week 1-3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. SIGNIFICANCE This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the recording site-tissue interface rather than elimination of the glial scar.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Proposing A Distributed Model For Intrusion Detection In Mobile Ad-Hoc Network Using Neural Fuzzy Interface

Security term in mobile ad hoc networks has several aspects because of the special specification of these networks. In this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. Fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy Ratiocination of fuzzy system as...

متن کامل

Proposing A Distributed Model For Intrusion Detection In Mobile Ad-Hoc Network Using Neural Fuzzy Interface

Security term in mobile ad hoc networks has several aspects because of the special specification of these networks. In this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. Fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy Ratiocination of fuzzy system as...

متن کامل

Acute and chronic effects of lithium on BDNF and GDNF mRNA and protein levels in rat primary neuronal, astroglial and neuroastroglia cultures

Objective(s):Theneuroprotective effect of lithium has been attributed to its therapeutic action. However, the role of glial cells particularly astrocytes, and the possible interactions between neurons and astrocytes in neuroprotective effects of lithium have been disregarded. Thus, the aim of this study was to evaluate the direct effects of lithium on brain derived neurotrophic factor (BDNF) an...

متن کامل

Forecasting Ozone Density in Tehran Air Using a Smart Data-Driven Approach

Introduction: As a metropolitan area in Iran, Tehran is exposed to damage from air pollution due to its large population and pollutants from various sources. Accordingly, research on damage induced by air pollution in this city seems necessary. The main purpose of this study was to forecast ozone in the city of Tehran. Considering the hazards of ozone (O3) gas on human health and the environmen...

متن کامل

EVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS

In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of neural engineering

دوره 13 1  شماره 

صفحات  -

تاریخ انتشار 2016