Schizophrenia is a debilitating neuropsychiatric disorder that ranks among the top 10 health burdens worldwide, yet current treatment options are not effective for many patients. In order to develop new therapies, we must gain a better understanding of how the physiology of the brain is altered in the disease. This will require links to be established between pathophysiological processes that occur at the levels of synaptic transmission, neuronal activity patterns, circuit dynamics, information processing, and finally cognitive performance. Our current body of knowledge is based on the two extremes of this spectrum: genetic defects that lead to dysfunction in cellular function on one end, changes in global brain activation patterns and cognitive performance on the other. What we are missing is an intermediate link at the level of neural circuits, or more specifically, an understanding of how distortions of the spatial and temporal patterns of neural activity in schizophrenia ultimately derail the computations performed by the networks, leading to cognitive failure. A widely-accepted theoretical model of schizophrenia called the disconnection hypothesis posits that the disease results from disordered functional connectivity between brain regions. While some functional imaging evidence supports this theory, it has never been tested at the neuronal circuit level and thus a mechanistic framework has not been developed. Here we propose to test the central hypothesis that schizophrenia is a disease in which aberrant action potential timing in prefrontal circuits leads to weakening of synaptic connections over time, through established mechanisms of spike-timing-dependent plasticity. In the Specific Aim 1, we propose to analyze a previously collected dataset of neuronal activity obtained from nonhuman primates performing a working memory task after receiving a drug that mimics features of schizophrenia. Preliminary analysis of this data suggests that spiking activity is disordered such that cells in the same local circuits are desynchronized and functional connectivity between cell pairs is reduced; these findings are consistent with our hypothesis that spike timing disruption leads to functional disconnection in schizophrenia. We will further develop these analyses and relate them to the disruptions in cognitive processing that parallel those seen in human schizophrenic patients.
In Specific Aim 2, we propose to conduct large-scale neural recordings in transgenic mice in order to investigate how a mutation that increases risk for schizophrenia changes the properties of neuronal interactions. We will apply similar analytical techniques to the neural data from Aims 1 and 2 in order to maximize the translational power of both animal models. Lastly, in Specific Aim 3, we propose to perform computational neural network simulations in order to establish a theoretical framework that causally links disordered spike timing to functional disconnection. The information gained through these studies will form a basis for a new theoretical framework of the pathogenesis of schizophrenia which can be used to guide a rational search for new treatments.
Schizophrenia is a devastating disorder which affects approximately 1% of the global population, including 3 million Americans, yet current treatments are not effective because we have an insufficient understanding of the pathological mechanisms of the disease. We propose to investigate how aberrant electrical activity leads to changes in local network dynamics and ultimately a breakdown in cognitive processing, using a unique approach that involves analysis of neural data from two animal models of the disease in addition to computational simulations of neuronal networks. This research will provide a new understanding of the pathophysiological mechanisms that underlie cognitive dysfunction in schizophrenia which could be used to identify new targets and strategies for intervention.
| Zick, Jennifer L; Blackman, Rachael K; Crowe, David A et al. (2018) Blocking NMDAR Disrupts Spike Timing and Decouples Monkey Prefrontal Circuits: Implications for Activity-Dependent Disconnection in Schizophrenia. Neuron 98:1243-1255.e5 |
