Abstract
Multiscale modeling of neuropsychiatric illness bridges scales of clinical importance: from the highest scales (presentation of behavioral signs and symptoms), through intermediate scales (clinical testing and surgical intervention), down to the molecular scale of pharmacotherapy. Modeling of brain disease is difficult compared to modeling of other organs, because dysfunction manifests at scales where measurements are rudimentary due both to inadequate access (memory and cognition) and to complexity (behavior). Nonetheless, we can begin to explore these aspects through the use of information-theoretic measures as stand-ins for meaning at the top scales. We here describe efforts across five disorders: Parkinson’s, Alzheimer’s, stroke, schizophrenia, and epilepsy. We look at the use of therapeutic brain stimulation to replace lost neural signals, a loss that produces diaschisis, defined as activity changes in other brain areas due to missing inputs. These changes may in some cases be compensatory, hence beneficial, but in many cases a primary pathology, whether itself static or dynamic, sets in motion a series of dynamic consequences that produce further pathology. The simulations presented here suggest how diaschisis can be reversed by using a neuroprosthetic signal. Despite having none of the information content of the lost physiological signal, the simplified neuroprosthetic signal can restore a diaschitic area to near-normal patterns of activity. Computer simulation thus begins to explain the remarkable success of stimulation technologies - deep brain stimulation, transcranial magnetic stimulation, ultrasound stimulation, transcranial direct current stimulation - across an extremely broad range of pathologies. Multiscale modeling can help us to optimize and integrate these neuroprosthetic therapies by taking into consideration effects of different stimulation protocols, combinations of stimulation with neuropharmacological therapy, and interplay of these therapeutic modalities with particular patterns of disease focality, dynamics, and prior therapies.
Highlights
Review Multiscale modeling provides a bridge across scales, from the microscopic to the macroscopic, from the invisible to the visible, from the pharmacological to clinical signs and symptoms
A major gap in our understanding of the brain activity is the difficulty of relating information theoretic measures, which measure statistical properties of signals, to the level of dysfunction in meaning and thought, a critical feature of schizophrenia and other disorders
In addition to demonstrating the flow of information, simulations can contribute to filling this gap as they are called upon to produce behaviors: converting a signal to a meaningful output or perception - interpreting complex stimulus sets by extracting meaning from a jumble of inputs [39,40,41,42,43]. This is the notion of embodiment, the idea that the functioning of the neural systems depends on the continuing feedback from the body and the world
Summary
A recurring theme in this set of studies has been that pathological dynamics, often involving initial abnormality in signal transmission, may lead to secondary compensatory signal abnormalities whose pathological impact may be as great or greater than the initial insult. In addition to demonstrating the flow of information, simulations can contribute to filling this gap as they are called upon to produce behaviors: converting a signal to a meaningful output or perception - interpreting complex stimulus sets by extracting meaning from a jumble of inputs [39,40,41,42,43]. This is the notion of embodiment, the idea that the functioning of the neural systems depends on the continuing feedback from the body and the world.
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