Hold your arms outstretched , close your eyes, and then slowly and deliberately bring your index fingers together until they touch. Even though each fingertip is at the end of a long, multijointed appendage that operates freely in three dimensions, most people successfully touch their fingertips, with a positional error of 5 millimeters or less.
It's a really simple thing for most of us to do. Yet it is a compelling demonstration of how sophisticated the body's movement-control systems are. This natural motion control is made possible by an array of specialized sensory cells that are embedded in skin, muscles, ligaments, and tendons. These mechanoreceptors, as they are called by neuroscientists, convert mechanical phenomena -- such as touch, pressure, muscle stretch, tendon force, and joint angles -- into streams of nerve impulses that can be interpreted by the brain and spinal cord, which make up the central nervous system. Based on this rich flow of sensory data, muscles can be commanded to contract with the synchrony and precision to hit a curve ball or play the piano.
It is in many ways a classic feedback control system, similar to those that engineers design and use every day. But it is a controller largely hidden from us in the central nervous system, and we are rarely conscious of it. If you concentrate, however, you can definitely pick it up.
For example, try standing perfectly still. It's impossible to remain truly motionless like a mannequin; your body naturally sways. If you pay attention to the pressure on the soles of your feet, for instance, you will become aware of an ever-shifting center of pressure. As your body leans forward, the focus of pressure travels out to the toes. Lean backward and the pressure moves toward the heels. Your sensory-motor control system integrates this touch sense from the soles of your feet with other balance feedback to keep you from falling over.
Given the critical role that the mechanical senses play, any loss of function involving them can obviously impact your health and quality of life. Most people expect that their vision and hearing will degrade with age but don't fully grasp that the same holds true for their mechanical senses. For the elderly, the decline of the sense of touch in the feet and of proprioception -- the sense of what position their limbs are in -- is a strong contributor to the tendency to fall. In the United States, roughly one-third of people over age 65 fall each year, and many of these falls result in serious and debilitating injuries, such as broken hips.
Disease, too, can blunt the mechanical senses. Diabetes, for example, often leads to a generalized loss of nerve function, which in many cases manifests itself as a profound drop in mechanoreceptor performance. Lack of mechanical awareness, especially in the feet of people with diabetes, contributes to the occurrence of open sores that can be extremely difficult to heal and that all too often lead to the amputation of affected areas.
With literally millions of people around the world suffering from loss of sensitivity in mechanoreceptors, there is a huge opportunity for new technologies and therapies to improve the lives of these people and make a sizable dent in soaring health care costs. With those goals in mind, our research teams at Afferent Corp., in Providence, R.I., and Boston University have been collaborating to develop and test a new class of neurotherapy devices that have the promise of directly improving mechanical sensory function to help prevent falls in the elderly and foot injuries and amputations in people with diabetes.
These devices are based on the discovery, almost a decade ago, that certain forms of electrical or mechanical stimulation applied to mechanoreceptors increase their ability to detect sensory information. In effect, it is possible to turn up the volume on sensory signals from the extremities to increase input to the brain and improve sensory-motor control.
The starting point for understanding this means of sensory volume control is the fact that all sensory cells are so-called threshold-based units. That is, the stimulus from the environment must exceed a minimum threshold to cause the neuron to begin signaling with the rapid-fire voltage spikes it uses to communicate with the spinal cord and brain. One way to characterize the degradation of sensory function due to aging and disease is as an elevation in this threshold; stimulus levels that once were above the sensory threshold are now below it and cannot be felt.
The fundamental concept behind the new sensory enhancement technology is that it is possible to fill that subthreshold region with artificial activity, effectively providing a pedestal or bias of background activity to sensory neurons. This artificial stimulation does not itself cause the sensory neurons to fire -- you can't feel it, in other words. Rather, it puts the neurons in a state that predisposes them to fire when presented with a real stimulus from the environment -- pressure on the sole of your foot, for instance. The result is that the neuron's threshold of sensitivity is effectively pushed back down toward a normal, more sensitive level.
Interestingly, both mechanical and electrical forms of subthreshold stimulation improve sensitivity. This stems from the fact that each mechanoreceptor is a transducer that provides the interface between the mechanical environment we navigate through and our electrical-based nervous system. You can therefore push the neuron toward firing, either by presenting low-level mechanical energy in the form of slight vibrations or by inputting minute, submilliampere electrical currents.
But a counterintuitive finding has emerged from our research. The best type of stimulation signal is not a finely tuned frequency but rather noise -- specifically, white noise, a signal comprising all frequencies within a certain band, in this case, typically less than 1 kilohertz. Given that engineers are trained to remove noise from systems to improve their performance, it may seem strange indeed that this neurological system seems to work best when noise is present.
It is not that sensory neurons defy traditional notions of signal-to-noise ratios. Instead, the dead zone below the threshold of sensation provides an opportunity for certain levels of noise to improve performance [see illustration, "Feel the Noise"]. If the noise level is too high, the sensory neuron fires mainly in response to the applied noise instead of to the signal to be detected and, as with any sensor, the noise degrades its performance. But just the right amount of noise provides the pedestal upon which signals can ride over the threshold. The use of noise to improve the performance of nonlinear systems like this one is termed stochastic resonance.
Stochastic resonance gets its name from the stochastic, or random, signals involved and the fact that, as in a resonance phenomenon, you can get a bigger than expected impact from small-amplitude signals. Its origins lie about as far afield from both engineering and medicine as one can get. In the early 1980s, physicists at the Free University of Brussels and the University of Rome, La Sapienza, were trying to explain our planet's more-or-less regular ice ages, which occur about every 100 000 years. The frequency of those episodes matches a periodic elongation in Earth's orbit, but by itself the elongation is too small a factor to bury the world in glaciers.
The physicists figured that random climatic fluctuations -- atmospheric noise -- could combine with the periodic orbital force and push Earth's climate into or out of an ice age. In the following years, scientists found instances of stochastic resonance in phenomena as diverse as chemical reactions and the behavior of lasers.
Stochastic resonance remained largely the purview of physical systems until 1993, when Frank E. Moss, a physicist at the University of Missouri, St. Louis, found that sensory neurons connected to the fine hairs on crayfish tails appeared to use stochastic resonance. Crayfish use the tail hairs to detect disturbances in the water that might indicate a predator's presence. But these disturbances are so weak that you would expect roiling water in streams to hide the predator's signal and leave the crustacean open to attack.
But crayfish sensory neurons, Moss discovered, actually take advantage of the noisy signal of a stream's turbulence, using it to amplify the predator's prowlings. A few years following Moss's report, our lab at Boston University showed that stochastic resonance also works in the human nervous system. We showed that a person's sense of touch was better when a little random vibration was applied to the fingertips.
But why noise? Why wouldn't applying a constant light load or small dc electric current work? The answer lies in a basic feature of sensory neurons: they are excellent at adapting to constant or regular periodic input. When presented with such a stimulus over an extended period, the neuron adapts to the stimulus and ceases to respond. People become gradually unaware of, say, the touch of clothes on their skin. If the input signal is noisy and random, neurons are unable to adapt to it.