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Raise Your Hand if You Know How Complex Raising Your Hand Is


What school teacher has not asked a question in class that half a dozen children want to answer? Kids shoot their hands skyward, waving them for emphasis, hoping to get called on. Suppose the question was our title. Would many students, at any level of education, be able to answer it correctly? Likely not. They might even think it a silly question. “I do that every day. What’s so impressive about raising my hand?” Let us count the ways.

The motor cortex controls motor behaviors by generating movement-specific signals and transmitting them through spinal cord circuits and motoneurons to the muscles. Precise and well-coordinated muscle activation patterns are necessary for accurate movement execution. Therefore, the activity of cortical neurons should correlate with movement parameters. To investigate the specifics of such correlations among activities of the motor cortex, spinal cord network and muscles, we developed a model for neural control of goal-directed reaching movements that simulates the entire pathway from the motor cortex through spinal cord circuits to the muscles controlling arm movements. In this model, the arm consists of two joints (shoulder and elbow), whose movements are actuated by six muscles (4 single-joint and 2 double-joint flexors and extensors). The muscles provide afferent feedback to the spinal cord circuits. Cortical neurons are defined as cortical “controllers” that solve an inverse problem based on a proposed straight-line trajectory to a target position and a predefined bell-shaped velocity profile. Thus, the controller generates a motor program that produces a task-specific activation of low-level spinal circuits that in turn induce the muscle activation realizing the intended reaching movement…. [Emphasis added.]

Those are the opening words in a paper on PLOS ONE by seven physiologists primarily from Drexel University School of Medicine in Philadelphia. Don’t worry, it won’t be on the test.

The scientists are doing their best to simplify what goes on in a simple “goal-directed reaching movement” of the arm. Models in science are simplifications of reality, focusing on certain aspects of a problem to the exclusion of details considered irrelevant. That’s why they zero in on just two joints and six muscles. By trying to model arm movements under brain control, they hope they can learn things that will help designers of robotic arms that amputees can move with their thoughts.

That makes our day and age very special. For the first time in human history, we can revisit questions of human anatomy and physiology from the viewpoint of design requirements, without omitting anything from brain to limb and back again. We’re no longer limited to Galen’s external observations of motion, or to the dissections of Vesalius. Valuable as those were for their time, they could not have known what neurons are, or the firing patterns of brain signals to muscles, or the molecular bases for muscle contractions. Our burgeoning era of robotics brings together a more comprehensive view of the whole gamut of requirements to enable a brain to raise a hand.

These scientists know what they are up against: “Even simple arm movements such as reaching require complex interactions among the central and peripheral nervous systems, and skeletal muscles to generate the intended arm movements,” they say. So leave aside piano playing or tennis; they would just like to understand a simple arm reach: moving one arm from an existing position to a target position.

In experiments, unperturbed reaching movement usually occurs along a straight-line trajectory with a bell-shaped velocity profile. Dynamically, reaching movements result from complex concurrent or sequential activation patterns of multiple muscles used to accelerate and then, slow down and stop the arm along the intended trajectory. To generate the required muscle activation patterns, the motor cortex needs to solve a corresponding “inverse problem” and, based on this solution, provide the appropriate dynamical inputs to the spinal circuits.

Speed up, move arm, slow down, stop. It sounds simple, but the brain has to plan everything in advance, after the mind has decided what it wants the arm to do (we won’t get into the vexing mind-body problem of how the mind initiates and communicates orders to the motor cortex). Just a simple arm reach requires coordination of, at a minimum, these physical parameters: distance, direction, velocity, friction, stretch, leverage, acceleration, force, torque, and gravity. To operate the arm in that physical parameter space, the brain needs to send appropriate signals down neurons.

When you think about this interaction (neurons to motion), there’s very little obvious connection between the two. What does the opening of a potassium channel in a neuron have to do with raising a hand? Yet the motor cortex has to know which signals to send down which neurons to make the signal activate the correct muscle. Additionally, the firing rate has to be tuned to prevent chaotic or spasmodic movements. Along the way, the neurons have to send feedback signals to the brain to indicate whether the desired motion is working properly, so that the brain can make adjustments. This is getting very complicated already! How does the brain, hidden in the dark inside the skull, know all this?

Although many movement parameters correlate with cortical activity, the cause of these correlations is still not clear. For example, it has been suggested that the directional sensitivity of cortical neurons is the result of a specific organization of inhibitory interactions within and between neuronal columns in the motor cortex. A competing viewpoint is that cortical activity is related to the activity of corresponding muscles that have anisotropic properties and thus, form cortical directional tuning. Moreover, the contribution of the spinal cord circuitry to directional modulation is not well understood.

To try to get a grasp on this highly complex set of interactions, the team created a simplified mathematical model: a conceptual arm with only two joints and six muscles, operated by control circuitry that tries to move it along the horizontal plane. Even so, coordinating the six muscles presents a challenge. Their model “motor cortex” sends signals to a model “spinal cord” with a feedback circuit back to the cortex. The signals travel from the spinal cord to the muscles. “Using our mathematical model,” they say, “we simulated center-out reaching tasks in 8 different directions” to see if it corresponds with real muscle reaching movements. By amplifying the feedback circuit, for instance, they could learn how important feedback is to the circuit. They could learn about shoulder dependence, elbow dependence, muscle lengths, firing rates and preferred directions by adjusting the signals. Without getting too deep into the weeds, this excerpt from their findings gives a taste of the complexity of the interactions:

The changes in muscle lengths during the movement largely depend on the relative direction to the shoulder joint because of the rotational symmetry of the arm geometry. Hence, in our model the directional modulation manifests as dependence on the angle between the direction of movement and the direction from the initial position to the shoulder joint. This is consistent with an idea that the motor cortex encodes direction based on the shoulder reference frame, suggested in other experimental and modeling studies.

Interesting ID word there: “encodes.” The authors discuss competing theories for what information the cortical neurons encode: Is it for static parameters? Dynamic parameters? Directional tuning as muscles do their thing autonomously? Since 1982,

directional tuning has been ubiquitously considered as a key property of neural activity in the motor cortex. However, it remains controversial whether directional preference is the fundamental property of cortical neurons or a side effect of muscle activity or other movement features.

Either way, the brain has to know what signals are going to accomplish the work the mind wants to do. So when Johnny thinks he knows the answer to the teacher’s question and shoots his hand into the air, the brain is figuring out a lot of math!

For extra credit, we remind readers that the brain is simultaneously operating blood vessels in the arm, controlling the immune system, maintaining the bones, responding to sensations from the skin, delivering nutrients from food and eliminating waste, and more. On another scale entirely, think of all the activity taking place simultaneously at the cellular and molecular levels!

If you’re not impressed enough already, listen to Steve Laufmann discuss living systems on ID the Future (here and here). Coming from the field of enterprise architecture, where integrated systems need to work in demanding environments, Mr. Laufmann has a real gut feel for the complexity of life as an engineer would look at it. Taking inspiration from Dr. Howard Glicksman’s 81-part series here at Evolution News, “The Designed Body,” Laufmann shares with host Todd Butterfield his absolute conviction that the overlapping system requirements in life are far, far beyond the capabilities of random variations or gradual evolution.

Photo credit: © JackF —