The brain's gray matter is arranged into a series of six layers, each of which exhibits a characteristic morphology reflective of its cognitive properties. For over a hundred years, we have known that the architecture of a cortical layer can hold important insights into its function. Our analyses of cortical layers, however, remained extremely limited, in large part due to the highly invasive techniques that were required in order to map them. Recently, our lab has developed a new acquisition and analysis pipeline that enables the precise capture of neural layer architectural features using non-invasive techniques. Cortical Layer Imaging (CortiCode) provides detailed measurements, or corticograms, of cortical morphology at a subject-specific level. We are currently developing bioinformatic methods capable of analyzing corticograms across large cohorts of subjects, potentially providing a revolutionary advancement in the field of gray matter research.
The structural connectome
The connectome, or the massive array of neural connections in our brain, controls not only information transfer, but also brain function, cognition, and behavior. Recently, the use of Diffusion Tensor Imaging (DTI) has yielded groundbreaking insights in the field of brain tractotraphy. DTI has allowed researchers to map the human brain connectome, in vivo and non-invasively, for the first time. However, DTI-based tractography, which is prone to error and fails to provide information about signal transfer efficiency, still provides only a limited assessment of the connectome. In collaboration with Professor Peter Basser of the NIH, our lab has developed two new Magnetic Resonance Imagine (MRI)-based methods, AxCaliber and CHARMED, which are capable of estimating axonal density and diameter for each fiber path in the brain. In combination with graph theory analyses, these methods allow for new, highly accurate measurements of the connectome. With these techniques in hand, we are currently investigating how the structure of the connectome, as weighted by axonal diameter properties, differs between healthy and diseased brains (e.g. multiple sclerosis).
The mammalian brain is one the most complex and important biological systems, but its evolution has largely remained a mystery. For many years, researchers have attempted to describe the overall brain’s evolution in relationship to the evolution of the anatomy of its gray matter, using characteristics such as neuron number, neuron density, brain volume, or gyrification as possible indicators of evolutionary change. Recently,in collaboration with Professor Yossi Yovel from the school of Zoology, we have explored the connectome patterns of over 100 different mammalian brains. Our data indicate that connectome efficiency is a highly conserved property in the class. Currently, we are exploring the mechanisms by which these brain connectomes remain so similar in their efficiencies despite the great variation of cognitive functionality across species.
Connectivity and Plasticity
The brain is highly dynamic, adapting its functions and structures in response to both transient events and long-term experiences. Using diffusion MRI, we have found that the brain microarchitecture undergoes a significant level of structural remodeling within minutes following cognitive experiences. Previous studies in the lab have suggested that the origin of microstructural remodeling stems from the glial cells’ reactions to neuronal activity. Using MRIs, we are currently investigating the mechanisms by which glial cell-mediated plasticity occurs and whether they reveal new insights into brain organization. More specifically, we are examining whether the organization of spatial memory domains relies upon neuroplasticity. Concurrently, we are analyzing whether MRIs can be used to identify and understand cognition-driven remodeling processes at a system-wide level.