CNEP: Applications in neuroscience
Millions of North Americans are affected by at least one neurological diseases such as neurodegenerative diseases (e.g., dementia-type diseases, demyelinating diseases, Parkinsonism-type diseases, etc), brain cancer, epilepsy, and traumatic brain injuries. According to Alzheimer's Association, approximately 6 million American individuals suffer from Alzheimer's, which is anticipated to rise to 13 million by 2050. The global clinic neurology market size was estimated at USD 42.5 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 5.56% from 2023 to 2030, attributed to the increasing prevalence of neurological diseases.
Measuring neuronal activities in response to stimulus is a basic requirement in neuroscience research and clinic diagnosis. Such measurement can be done at levels of molecular, cellular, neuronal group, circuits and pathways, and systems. Neuroelectrophysiology has been the oldest and most effective practice at molecular and cellular levels, including the classical patch-clamp techniques that directly isolate and measure voltage or current changes in a small area (patch) of a neuron’s membrane, and more recent technologies such as recombinant DNA, optogenetics, and structure biology. Patch clamp techniques are invasive and can take intracellular signals in vivo or in vitro whereas the other techniques are best for in vitro measurement. All of these techniques have the advantages of being quantitative and precise to the resolution of single neuron or even single ionic channels (proteins). Yet, they all share a limitation of being difficult for simultaneous recording on a large number of cells.
In contrast, system level measurement and recording solutions, such as CT, fMRI, EEG, etc., are noninvasive, cortical area level, and on conscious subjects. Their limitations are also obvious: Low spatial resolution with little information about cellular or subcellular level details, and mostly extracellular and so can only provide indirect indication of neuronal activity.
At Abinitio laboratories, we develop a CNEP-enabled, AI-enhanced, super high resolution functional measurement and diagnosis solution for neurology and psychiatry research and clinic applications. Such a CNEP-enabled diagnosis system is anticipated to be cloud-based with a set of engines (algorithms) running in the background, including a CNEP Engine that computes single neurons’ membrane potentials, a Reflex Arc Engine that establishes reflex arc for every stimulus for purpose of spatial and temporal correspondences, an Activation Function Engine that generates and applies structured stimulus signals to selectively trigger, isolate, locate, and enhance the responses at wanted pyramidal neurons, and an Alignment Engine that establishes a match between the neurons in subject cortex and the neurons in CNEP test report. Assistance from fMRI of human perception pathway is necessary in early versions of the system to provide a coarse location of active cortical areas corresponding to a specific perception task. Such CNEP-enabled solution is expected to have features as depicted below:
