MAPPING BRAIN CIRCUITS IN HEALTH AND DISEASE
Intricate neural circuits underlie all brain functions. However, these neural circuits are highly dynamic. The ability to change, or the plasticity, of the brain has long been demonstrated at the level of isolated single synapses under artificial conditions. Circuit organization and brain function has been extensively studied by correlating neuronal activity with information input. The primary visual cortex has become an important model brain region for the study of sensory processing, in large part due to the ease of manipulating visual stimuli. Much has been learned from studies of visual cortex focused on understanding the signal-processing of visual inputs within neural circuits. Many of these findings are generalizable to other sensory systems and other regions of cortex. However, few studies have directly demonstrated the orchestrated neural-circuit plasticity occurring during behavioral experience.
It is vital to measure the precise circuit connectivity and to quantitatively characterize experience-dependent circuit plasticity to understand the processes of learning and memory formation. Moreover, it is important to study how circuit connectivity and plasticity in neurological and psychiatric disease states deviates from that in healthy brains. By understanding the impact of disease on circuit plasticity, it may be possible to develop therapeutic interventions to alleviate significant neurological and psychiatric morbidity. In the case of neural trauma or ischemic injury, where neurons and their connections are lost, functional recovery relies on neural-circuit repair. Evaluating whether neurons are reconnected into the local circuitry to re-establish the lost connectivity is crucial for guiding therapeutic development.
There are several major technical hurdles for studies aiming to quantify circuit connectivity. First, the lack of high-specificity circuit stimulation methods and second, the low throughput of the gold-standard patch-clamp technique for measuring synaptic events have limited progress in this area. To address these problems, we first engineered the patch-clamp experimental system to automate the patching process, increasing the throughput and consistency of patch-clamp electrophysiology while retaining compatibility of the system for experiments in ex vivo brain slices. We also took advantage of optogenetics, the technology that enables control of neural activity with light through ectopic expression of genetically encoded photo-sensitive channels in targeted neuronal populations. Combining optogenetic stimulation of pre-synaptic axonal terminals and whole-cell patch-clamp recording of post-synaptic currents, we mapped the distribution and strength of synaptic connections from a specific group of neurons onto a single cell. With the improved patch-clamp efficiency using our automated system, we efficiently mapped a significant number of neurons in different experimental conditions/treatments. This approach yielded large datasets, with sufficient power to make meaningful comparisons between groups.
Using this method, we first studied visual experience-dependent circuit plasticity in the primary visual cortex. We measured the connectivity of local feedback and recurrent neural projections in a Fragile X syndrome mouse model and their healthy counterparts, with or without a specific visual experience. We found that repeated visual experience led to increased excitatory drive onto inhibitory interneurons and intrinsically bursting neurons in healthy animals. Potentiation at these synapses was absent or abnormal in Fragile X animals. Furthermore, recurrent excitatory input onto regular spiking neurons within the same layer remained stable in healthy animals but was depressed in Fragile X animals following repeated visual experience. These results support the hypothesis that visual experience leads to selective circuit plasticity which may underlie the mechanism of visual learning. This circuit plasticity process is impaired in a mouse model of Fragile X syndrome.
In a separate study, in collaboration with the laboratory of Dr. Gong Chen, we applied the circuit-mapping method to measure the effect of a novel brain-repair therapy on functional circuit recovery following ischemic injury, which locally kills neurons and creates a glial scar. By directly reprogramming astrocytes into neurons within the region of the glial scar, this gene-therapy technology aims to restore the local circuit and thereby dramatically improve behavioral function after devastating neurological injury. We found that direct reprogramming converted astrocytes into neurons, and importantly, we found that these newly reprogrammed neurons integrated appropriately into the local circuit. The reprogramming also improved connections between surviving endogenous neurons at the injury site toward normal healthy levels of connectivity. Connections formed onto the newly reprogrammed neurons spontaneously remodeled, the process of which resembled neural development. By directly demonstrating functional connectivity of newly reprogrammed neurons, our results suggest that this direct reprogramming gene-therapy technology holds significant promise for future clinical application to restore circuit connectivity and neurological function following brain injury.
Synaptic and Circuit Mechanisms of Reward Timing in the Mouse Visual Cortex Whitehall Foundation
Neural Mechanisms of Predictive Impairments in Autism
National Institute of Mental HealthFind out more...
- Doctor of Philosophy
- Biological Sciences
- West Lafayette