A large number of neurological disorders (neurodegenerative, neurodevelopmental or trauma induced) are difficult to diagnose or assess, thus limiting treatment efficacy. Existing solutions and products attempting to fill this gap are costly, extremely slow, often invasive, and in many cases fail to definitively (and quantitatively) diagnose or assess treatment. Our innovative low-cost sensory testing device and accompanying software package can be used to non-invasively assess the central nervous system (CNS) health status in minutes for numerous patient populations. The somatosensory system is ideally suited for the design of a CNS diagnostic system. First, the organization of the system is such that adjacent skin regions project to adjacent cortical regions (i.e., it is somatotopic). Second, ambient environmental noise in the system can be easily controlled (i.e., it is less likely that a patient will be exposed to distracting tactile input than auditory or visual input). Third, the somatosensory system is the only sensory system that is highly integrated with the pain system, and this is often an important aspect of a patient's diagnosis. The diagnostic system delivers a battery of somatosensory-based tests that are conducted rapidly, much like an eye exam with verbal feedback. Neuro-adaptation, functional connectivity (e.g. cortical synchronization), and feed-forward inhibition are just a few of the cortical mechanisms that can be quantified using somatosensory testing protocols. Many of these protocols leverage tactile illusions which act as confounds on top of a basic somatosensory test, allowing each subject to serve as his or her own control. Design and validation of the perceptual metrics was/is accomplished via correlative studies that compare non-invasive observations of human sensory percepts with non-human primate neurophysiological studies. Additional validation has been demonstrated through the use of a magnet-compatible version of the device in both functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) studies. Based on pilot data (currently an ontological database of roughly 3000 subjects), the system can be used to enable clinicians to have a much better view of a patient's CNS health status.Doctor of Philosoph
