A key feature of complex systems is the existence of emergent properties, in which small causes can have very profound and sometimes astonishingly unexpected effects downstream. Because of this exquisite sensitivity to initial conditions, complex systems can both respond to their environments with a minimum of energy, as well as easily spiral out of control. Some familiar examples of complex systems are stock markets, terrorist networks, viral transmission, and the weather. Economic recessions, violent revolutions, pandemics, and tsunamis are what happen when their dynamics become uncontrollable, which illustrates the power of a complex system gone awry.
Our bodies and, in particular, our brains, are complex systems governed by nested control circuits, and here too, the precarious balance between order and chaos becomes crucial. The brain must be dynamically supple enough to efficiently respond to inputs, but also constrained enough to be able to maintain homeostasis. LCNeuro research starts from the working hypothesis that imbalance in either direction, caused by problems in network architecture or problems in information transfer, forms the basis for many of our most crippling psychiatric and neurological diseases.
At LCNeuro, we obtain human brain signals non-invasively through imaging: using functional magnetic resonance imaging (fMRI), near-infrared spectroscopy (NIRS), magnetoencephalography (MEG) and electroencephalography (EEG, ECOG). These are combined with computational modeling (control systems, Bayesian, dynamical systems) to better understand neural trajectories under healthy and disease states.
Our research has direct clinical applications, with a focus on development of neurobiologically-based diagnostic instruments. These are designed to:
detect exceptional stress resilience for screening of recruits to high-risk professions, such U.S. Special Forces,
identify pathological stress vulnerability in young children at risk for clinical anxiety and depression,
map neural signatures for schizophrenia that may indicate the drug to which a patient is likely to respond most effectively, and
markedly improve neurosurgical outcomes for patients with severe epilepsy, by more accurately identifying the focal points in their brains that trigger their debilitating seizures.
Our engineering work also includes complementary development of:
software and algorithm development for near-infrared spectroscopy, an emerging technology with portability, convenience, and low operating costs that make it ideally suited for diagnostics within clinical settings (emergency rooms, doctors’ offices, rural and military facilities) that cannot support fMRI,
chemosensory stimuli capable of activating the human limbic system without conscious perception (human alarm pheromones), and
dynamic phantoms for artifact removal in MRI (blood oxygen level dependent, diffusion tensor imaging, arterial spin labeling).