Introduction to living cortical networks and multielectrode array technology

The brain is perhaps one of the most powerful and robust computing machines in existance. It can recognize vastly different patterns, store a lifetime worth of information, and yet is more fault tolerant than any computer today. How does the brain do this? To answer that question you would need to study how neurons, which are the major computing component in the brain, processes and encodes information. In the past we we were limited to examining just a few neurons at a time using single electrode "patch" style recordings and from that we learned, and still learn, a great deal about the inner workings of single neurons. But we also know that much of the computational properties of neurons occurs at the neural ensemble or "population" levels (thousands to millions of neurons in concert). Multielectrode arrays (MEA) were created to bridge the gap between recordings of single neuron to and population levels recordings by creating a system in which a large grid of electrodes could be employed to collectively sample the activity across a a small population of cells and yet maintain the resolution to measure individual cells.

Figure 1 shows and example of a microelectrode array. These MEAs were developed in the late 1970's by Jerry Pine , Gunter Gross. The MEA is essentially a large grid of electrodes spread across the surface of a dish in which neurons can be grown (cultured). These arrays permit researchers to both study and stimulate patterns of activity of neurons grown across the surface of the MEA. For example, we can input various stimulation patterns into the cortical network and examine the response (output) of the network to learn more about how these networks compute or store information.

In our lab, rat cortex obtained from Brain Bits (, is mechanicly dissociated and digested using the Papain Dissociation Kit from Worthington Biochemical ( The papain digestion dissolves the connective tissue surrounding the neurons leaving a suspension of neuron cell bodies (called soma) which are then dropped onto the surface of the MEA and its electrodes which have coated with polyethelyneamine and laminin to improve adhesion and promote growth. (see link for detailed protocols under the technology section of this website).

Neurons that are cultured in this matter will rapidly begin to reconnect and form a dense neural network. In other words, a living neural network that we can study in detail. Figure 2 shows a time-lapse movie of the growth and emergence of connectivity of neurons over the course of the first 8 hours after being placed into the MEA. As you can see, many of the neurons (which appear as small dark spheres) send out "filaments" or processes to nearby neurons. The movement that you are seeing are the neurons in the process of forming a new neural network of cells. As the network emerges, the neurons will begin spontaneously send messages (action potentials) down these processes to other neurons in the net. These action potentials are electrical events which can be detected by the electrodes on the MEA as large deviations or "spikes" in the voltage. For example, during the first few days scattered individual action potentials (spikes) begin to be detected by the MEA. However after 10 days the network will begin to produce one of the primary forms of network activity seen in these networks in which neurons will begin to fire in synchronous coordinated bursts of activity.
Figure 3 is a movie showing the raw electrical activity recorded by an 8x8 grid of electrodes on an MEA. Each window displays 200 milliseconds of raw electrical activity including ambient electrical noise (blue fuzzy line at the center of each window) and spikes which appear as deviations from the noise. Note how spontaneous spikes appear throughout the culture followed by periods/bursts of activity. These bursts are semi-periodic occurring every 1 to 15 seconds, dependent on the culture measured.
Figure 4 illustrates the fine spatial and temporal structure to these bursts. In this movie, the grid of electrodes are depicted flat along the bottom of the plot and the colorized waves represent integrated activity (leaky integrator) over time. The move is 10x slower than realtime and shows the burst activity seen in Figure 3 as wells as some of the patterns that occur during a burst. For example, the spikes can be seen to propagate across the surface. In fact there is a great deal of variability within each burst illustrate the potentially rich amount of information that may be present in the both the timing and location of spikes.
With this system we can measure this rich dynamical system of neurons in realtime as well as stimulate patterns of our own to understand how information is processed and encoding in living neural networks.

A sample of areas of research using MEA technology:

neural plasticity
cardiac myocytes
circadian rythem
biosensor applications