Feature or a bug? Could insect brains replace silicon in next-gen robotics?

As odd as it may sound, the Defense Advanced Research Projects Agency (DARPA) has been expressing significant interest in insects lately. Even the most humble insect has capabilities that far exceed today’s most sophisticated technology. Consider a wasp, for example. It can fly at high speeds and is far more maneuverable than any drone or RC aircraft. Furthermore, drones and aircraft are limited by their fuel or battery capacity. While a wasp (or other insect types) also has a limited amount of energy, its range is truly impressive for its size. As such, DARPA has been seeking grant proposals for new technologies that are based on flying insects.

Among the concepts that are being studied is whether insects brains might be able to take the place of an onboard computer. After all, bug brains are tiny (with some only consisting of a few hundred neurons), and yet they can perform cognitive functions that could be compared on some levels to AI.

So is it really possible to harness the power of an insect’s brain? I’m not a fan of animal experiments, so I’m not about to start dissecting bugs to find out. Even so, I find the concept of mixing biological and electronic systems to be fascinating from a technology standpoint. So let’s consider whether or not a brain (insect or human) could ever be used to control an electronic circuit.

Let’s start with the interface

insect brains

The first thing that would be needed to control an electronic circuit using a brain would be some sort of interface between the biological material (the brain) and the electronics. This would likely mean tying the brain to a microprocessor. The brain’s neurological output could serve as microprocessor input. Code running on the microprocessor might then control the device based on the input that is received.

As implausible as this may seem, it could actually work (at least in theory). Microprocessors use electrical signals as input. The neurons in the brain also communicate by way of electrical impulses. In fact, there is a formula for calculating the electrical potential of a neuron.

The formula that I am about to show you provides you with the Nernst Potential (which is essentially the electrical potential) across the nerve cell’s membrane for a specific ion. This is the point at which electrostatic forces and diffusive forces balance one another out. Here is the formula:

E(ion) = ((R*T)/(Z*F)) * ln (extracellular concentration / intracellular concentration)

So to put this into perspective, let’s pretend that we have a nerve cell in a petri dish and we want to find the Nernst potential for a positive Potassium ion (K+). Let’s also assume that the extracellular concentration is 55 and that the intracellular concentration is 140 and that the cell’s temperature is 37 degrees Celsius. Here are the values that are used in the calculation:

Eion = The Nernst Potential in volts for the K+ ion
R (the Universal Gas Constant) = 8.3144598 J⋅mol ^−1 ⋅ K ^−1
F (Faraday’s Constant) = 96485.33289 C mol ^ −1
Z (the Valence Electron Count) = +1
T (temperature in Kelvin, which is the Celsius temperature plus 273.15) = 310.15
Ln refers to the natural logarithm operator

Here is how the math breaks down:

EK+ = ((8.3144598 * 310.15) / (1 * 96485.33289)) * ln (44 / 140)
EK+= -0.02497 volts

If I multiply this value by 1,000, I can convert the answer to approximately -25 millivolts.

The point behind all of this is to prove that nerve cells do carry an electrical potential and that it is possible to mathematically calculate that potential.

Interacting with digital electronics

insects brains

A microprocessor’s pins carry input and output signals into and out of the microprocessor. An in-depth discussion of the inner workings of a microprocessor is beyond the scope of this article. Even so, I do want to spend a bit of time talking about how a transistor works, because transistors form the basis of the logic circuits within a microprocessor.

As you no doubt know, microprocessors process binary code. Binary code is represented as a series of ones and zeros, but in reality, a binary value of one represents the presence of an electrical signal, while a value of zero represents the absence of such a signal.

Transistors can either function as an amplifier or as a switch, but in the case of a logic circuit, a transistor acts as a switch, turning current on and off in response to the presence or absence of a signal.

Transistors have three wires, which act as a base, a collector, and an emitter. Current flows between the collector and the emitter, but only when a small current is applied to the base. In other words, if voltage is applied to the base then the electronic switch is closed and current is allowed to flow between the collector and the emitter. If no voltage is applied to the base, then the switch is open, and current is prevented from flowing between the collector and the emitter.

Now here is the really important part. The level of current that is applied to a transistor’s base does not necessarily have to match the level of current flowing between the collector and the emitter. In many cases, only a tiny amount of current is applied to the base, and a larger current flows between the collector and the emitter.

So think about this in the terms of a nerve cell. When a nerve fires, it generates a tiny amount of current, usually in the magnitude of millivolts. If this current can be directed to a transistor’s base (through an input pin on a microprocessor), it can act as binary input for a logic circuit.

What else has to happen?

insect brains

In order to use a brain to control a robot, there are a couple of other things that have to happen. First, the brain’s neurons have to be mapped. Otherwise, there is no way of knowing what causes a particular neuron to fire.

Work is already being done on this type of mapping. For example, grasshoppers tend to jump when they are approached by a potential predator. Scientists have traced the path from the optic nerve, through the brain, to the leg muscles.

The biggest challenge to mapping a brain is that brains are not exactly alike from one organism to the next. Each neuron can have thousands of connections to other neurons (at least that’s the case in humans, I don’t know about bugs). These connections, which are called synapses, are dynamic. Synaptic connections change over time as a result of things like learning, aging, or even in response to certain injuries. What this means is that a generic brain map probably is not going to be adequate.

The other thing that would be needed if robotics were to be controlled by a brain is connectivity to other biological systems. The brain cannot survive without the aid of the body. The brain needs oxygen and nutrients. Oxygen is supplied by the blood, which means that a circulatory system is required. Of course, the circulatory system cannot simply manufacture oxygen. Oxygen is supplied by the lungs and then transferred to the blood through alveoli. Hence a respiratory system is also required. Several other critical systems, such as a digestive system, would also be required if the brain were to be kept alive.

In addition, the body supplies sensory input to the brain through various organs. Just as a computer cannot function unless it receives input, neither can the brain. In the case of a biological robot, some of this input would likely be provided by biological organs. It would be far easier from an engineering standpoint, for example, to send visual input to a bug’s brain through the bug’s own eyes than to try to translate a digital video signal into something that the brain can understand.

This is not to say that all of the brain’s input would be purely biological. Digital signals would most likely have to be the basis for feedback loops. Let me give you an example.

If you were to jump off of a chair, the nerves throughout your body would tell your brain that you have made contact with the floor. These same nerves also convey information such as how hard you landed, and in what position. A flying insect would presumably have a similar degree of self-awareness. Nerves in the bug’s legs probably tell it when it has landed.

If a bug’s brain were to be used as the basis for a flying robot, then that brain is going to be expecting certain sensory input, such as information about whether or not the bug’s legs are touching the ground. This type of input information would have to be created synthetically by electronic sensors, and then the digital signal would need to be converted into something that the bug’s brain could understand.

Actually, it would not be enough for the bug’s brain to simply understand the signals. The digitally created signals would have to mimic the electrical signals that are produced by the bug’s own body. Remember, the bug knows how to fly. If unfamiliar information is fed into the bug’s brain, the bug probably wouldn’t be able to fly very well (or at all).

Insect brains: Tremendous potential

Although I have serious ethical issues with the idea of turning insects into cyborgs, I think that the technology holds tremendous potential as a way of helping those who are paralyzed or who rely on prosthetics.

Featured image: Wikimedia

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