Multielectrode Arrays - Progress!

My graduate student extraordinare has been working on growing neurons in multielectrode array dishes. These are special petri dishes with electrodes built right in so that we can stimulate the neurons and record from them. We can use this preparation to learn about how neurons communicate with each other. Its pretty neat. The equipment necessary to run these studies is not cheap, but luckily we stumbled across an unused rig at the medical school which they graciously agreed to let us use. Even better, they gave us our own incubator, which is critical since the cells must be kept at a constant temperature and CO2 concentration otherwise they will rapidly perish.

We've recently presented an update on our research at the BMES 2013 conference in Seattle. We are also in the process of submitting our first peer-reviewed paper on this work. Our first innovation has been the implementation of a statistical technique known as the False Discovery Rate method to identify statistically significant connections between neurons. We then used the FDR method to track how those changes evolve over time. Our first experiment, which we performed as a retrospective study using data graciously donated us by Dr. Potter at Georgia Tech, studied changes that occur over the course of 40 days in vitro. We found that cell cultures go through three phases - an initial phase where the cells are unconnected and disorganized; a second phase in which synaptic connections increase in both number and distance; and and a third phase in which the cells either die or massively prune off synaptic connections.

We've also made a really interesting discovery that cell cultures derived from the same source neural tissue tend to evolve along very similar time courses, whereas cultures derived from different neural tissue tend to evolve with very different time courses. We have some hypotheses as to why this happens but we can't know for sure without running more experiments.

At present, we're working on two projects. The first is to assess to what extent electrical stimulation causes changes in neural cultures. We are doing this by selectively applying stimuli to different quadrants of each neural dish and studying how neural connectivity changes as a result. We expect to have results on this later this year or early next year. Our second project is especially interesting but we've decided to keep a lid on it for the time being! We'll talk about it publicly once the work has been peer reviewed and published.

Its Alive!

Its alive! Since June we have been working on a project to grow rat neurons in a multi-electrode array dish, which is like a petri dish but instrumented with electrodes so that you can record electrical activities from the cells. Over the summer we were pretty successful in growing the cells but we hadn't been able to make any good recordings.

Last week we scuttled the first batch of neurons and started a new batch, applying all of the hard earned knowledge from first time around. This time, victory! Just eight days after starting the neurons in the dish, we've made our first real recordings of neural activity. There are clear periods of spiking behavior and the spike waveforms are of the shape and amplitude that we expect. A real milestone for our lab!

Fluorescent Lights

Just learned the hard way that fluorescent lights operate at 25kHz. Our first attempt at neuronal recordings yielded a giant power spike at 25kHz which we discovered (by trial and error) was due to the lights in the lab. Thank goodness for the real-time FFT feature on the oscilloscope.

No sign of action potentials. I think we need to work out some grounding issues and try again tomorrow...

Multi-Electrode Arrays

This summer we've embarked on a new project. Based on some conversations that arose during my Neural Engineering graduate course, we've decided to try growing neurons in multi-electrode array (MEA) dishes to record from them. The dish where we grow the neurons is set up with a series of electrodes built right into the dish. We are growing rat neurons in the dish and they are doing quite well - they have spontaneously started growing axons to interact with each other and we expect they will be sufficiently  mature to record from within ten days.

The picture at right shows our neurons under the microscope in the MEA dish. The black traces are the wires and electrodes of the dish. The neurons are the dark spots and the little dark lines between neurons are the axons. This picture was taken on August 19, 2011.

Once we have this procedure established, we plan to explore whether these arrays of neurons can be 'trained' via stimulus protocols. In theory, repeated electrical stimuli can force the neurons to rearrange their connectivity in predictable patterns. In that sense the network can be said to "learn" the stimuli. This is effectively similar to creating a biological neural network.

In order to save money, we are developing our own in-house circuit for amplifying and digitizing the neural signals (as opposed to buying an off-the-shelf rig). The circuit is based off the amplifier I published in my dissertation (in 2004). We have designed a 10-channel PCB which we hope to send today to the fabrication facility.

More details to come as they emerge!

Lecture 12 - Neuron Modeling

In Week 12 we focussed on two papers. The first was "Quadratic Leaky Integrate-and-Fire Neural Network tuned with an Evolution-Strategy for a Simulated 3D Biped Walking Controller" (by Wiklendt) which can be found here. This paper developed a modified leaky integrate and fire neural network model to control a simulated biped. The model effectively used a three-layer neural model to control ten degrees of freedom in the simulated biped. Although the model was effectively an integrate and fire model, the authors made two nice simplifications that cleaned up the math enough that spike times could be calculated exactly, as opposed to being simulated numerically. The network learned using a (mu plus lambda) evolution strategy (ES) which was beyond the scope of our reading; I think next year this would make for a good reading. We were able to understand that essentially the evolution model is a cellular automaton that uses a fitness strategy to assess which neurons are weighted optimally for the desired outcome.

Overall the class seemed pretty down on this article since it used a virtual neural network to control a virtual biped: since neither the controller nor the network was "real", the class wondered what the practical application of this knowledge was.

The second article we read was the highly creative "Adaptive Flight Control with Living Neuronal Networks on Microelectrode Arrays" by DeMarse and Dockendorf at the University of Florida. The paper describes a setup in which a population of neurons is grown in a specially instrumented petri dish which can record electrical activity from the cells as they fire. The neural population is used to provide pitch and roll control for a virtual aircraft in a flight simulator game. Network training is achieved by providing the network with trains of high frequency pulses that force the network connectivity to change with respect to the stimulating electrode. What was neat about this paper was that the authors used the fact that the network could simultaneously encode two different control signals (pitch and roll) and that these could be assessed simultaneously by providing a single stimulus pulse to each of the control electrodes and then measuring the speed and extent of neural activations in response. The size and speed of the response was taken to encode the controls to the flight simulator. The class was generally positive on this paper (especially in comparison to the previous one, since the control signals were coming from a real source.

We also discussed whether this technology would make sense to bring to Temple University. There is some interest in my lab about growing neurons in vitro and measuring and manipulating their connectivity.

Multi-Electrode Arrays

We are considering learning to use cultures of neural cells in a multielectrode array (MEA) to simulate functional neural tissue including feedback and LTP/LTD. We were amazed to stumble across this site, which offers a complete open source solution for MEA recording and stimulation. This is courtesy of the Potter group at Georgia Tech.