Geometry based dynamic modeling of the neuron-electrode interface

A dynamic model of the neuron-electrode interface is presented which is based on the interface geometry and the electrical properties of the neuronal membrane. The model is used to compute the potential at the electrode and the local membrane potentials. Extracellular as well as intracellular current stimulation can be simulated. The results demonstrate that extracellular recorded action potentials with several shapes and amplitudes can be produced, depending on the properties of the interface and the membrane. With homogeneous membrane properties, only small amplitudes are simulated, High amplitudes are produced with decreased concentration of voltage sensitive channels in the lower membrane. Resemblance of the shape of the intracellular potential is accomplished by decreasing the capacity of the lower membran

Trapping cortical rat neurons

Cortical rat neurons were trapped by dielectrophoresis (DEP). Experimental data were compared with theoretically deduced relationships. The neuron was represented by a single-shell model. A planar quadrupole electrode structure was used for the creation of a nonuniform field. The electrode structure was modeled as four point charges. The experimental data did almost completely fit the theoretical yield/time relationship. The theoretical yield/amplitude relationship, however, did only apply for a restricted amount of frequencies. The experimental frequency behaviour (i.e., the DEP-spectrum) did not apply to the theory. A difference in neuronal physiological state can produce different DEP-spectra. For two frequencies (10 kHz and 14 MHz) adhesion to the substrate and outgrowth of the neurons was investigate

Characterization of the behaviour of dissociated neurons exposed to dielectrophoretic forces

The behaviour of cortical rat neurons exposed to dielectrophoretic forces is investigated by varying the amplitude and frequency of the applied field. The number of neurons trapped in the center of a planar quadrupole micro-electrode structure is determined for two different amplitudes (3 V and 5 V) and six different frequencies in the range from 1 MHz to 18 MHz. A contradictory trend is found for the yield of trapped neurons for the two amplitudes as a function of the frequency

Cross-interval histogram analysis of neuronal activity on multi-electrode arrays

Cross-neuron-interval histogram (CNIH) analysis has been performed in order to study correlated activity and connectivity between pairs of neurons in a spontaneously active developing cultured network of rat cortical cells. Thirty-eight histograms could be analyzed using two parameters, one for the shape and one for the average number per interval bin. The histogram shape varied gradually between flat and clearly peaked around zero interval, indicating no/abundant connectivity and direct connection pathways, respectively

Finite element modeling of the neuron-electrode interface: stimulus transfer and geometry

The relation between stimulus transfer and the geometry of the neuron-electrode interface can not be determined properly using electrical equivalent circuits, since current that flows from the sealing gap through the neuronal membrane is difficult to model in these circuits. Therefore, finite element modeling is proposed as a tool for linking the electrical properties of the neuron-electrode interface to its geometr

The effect of training of culture neuronal networks, can they learn

Dissociated 1 or 2 days old postnatal rat cortical cells were cultured onto multi electrode arrays (MEA’s) with 61 electrode sites. They were trained with two protocols, i.e. the tetanic stimulation method from the report by Jimbo et al. (1998) and the selective adaptation protocol (report Shahaf and Marom, 2001). Tetanic stimulation training changed the net- work response significiantly. But training had no lasting effect, which means no learning result. The selective adaptation proto- col did also not lead to lasting learning effects