On how correlations between excitatory and inhibitory synaptic inputs maximize the information rate of neuronal firing

Cortical neurons receive barrages of excitatory and inhibitory inputs which are not independent, as network structure and synaptic kinetics impose statistical correlations. Experiments in vitro and in vivo have demonstrated correlations between inhibitory and excitatory synaptic inputs in which inhibition lags behind excitation in cortical neurons. This delay arises in feed-forward inhibition circuits and ensures that coincident excitation and inhibition do not preclude neuronal firing. Conversely, inhibition that is too delayed broadens neuronal integration times, thereby diminishing spike-time precision and increasing the firing frequency. This led us to hypothesize that the correlation between excitatory and inhibitory synaptic inputs modulates the encoding of information of neural spike trains. We tested this hypothesis by investigating the effect of such correlations on the information rate (IR) of spike trains using the Hodgkin-Huxley model in which both synaptic and membrane conductances are stochastic. We investigated two different synaptic input regimes: balanced synaptic conductances and balanced currents. Our results show that correlations arising from the synaptic kinetics, tau, and millisecond lags, delta, of inhibition relative to excitation strongly affect the IR of spike trains. In the regime of balanced synaptic currents, for short time lags (delta ~ 1 ms) there is an optimal tau that maximizes the IR of the postsynaptic spike train. Given the short time scales for monosynaptic inhibitory lags and synaptic decay kinetics reported in cortical neurons under physiological contexts, we propose that feed-forward inhibition in cortical circuits is poised to maximize the rate of information transfer between cortical neurons. Our results also provide a possible explanation for how certain drugs and genetic mutations affecting the synaptic kinetics can deteriorate information processing in the brain

The Role Of The Nmda Receptor In Shaping Cortical Activity During Development

Currently, it is estimated that neuropsychiatric disorders will affect 20-25% of humans in their lifetime. These disorders are a major cause of mortality, suffering, and economic cost to society. Within this broad class, neurodevelopmental disorders (NDDs), including intellectual disability, autism spectrum disorder, and schizophrenia, are estimated to affect 2-5% percent of the world population. Devastatingly, we lack fundamental treatments for NDDs, which have proved some of the most imposing disorders to understand scientifically. The challenge is twofold: first, NDDs affect the most complex aspects of human cognition; second, pathogenesis begins early in neural circuit development, but we lack predictive biomarkers before overt behavioral deficits are apparent. Although we have identified many genes associated with these disorders, how underlying genetic disruptions lead to pathological neural network development and function remains unclear. The overarching framework of this dissertation is that all NPDs are disorders of distributed neural networks, and pathophysiology must be understood at this level to effectively intervene clinically. The cerebral cortex is necessary for complex human capacities, and cortical dysfunction is hypothesized to be central to the pathophysiology of NDDs. NMDA glutamate receptors (NMDARs) are important for the development of local circuit features in the cortex, for normal neurocognitive function, and are strongly implicated in NDDs. However, the role of NMDARs in the development of the large-scale cortical network dynamics that underly higher cognition has not been well examined. Understanding the role of NMDARs at this network level is critical because large-scale “functional connectivity” patterns are thought to be hallmarks of normal cortical function, are hypothesized to be disrupted in NDDs, and may be detectable in humans using non-invasive neuroimaging or electrophysiology. In the studies presented in this dissertation, I (in collaboration and with the support of my colleagues) tested the role of the NMDAR in shaping large-scale cortical network organization using in vivo widefield imaging of whole cortex spontaneous activity in developing mice. I found that NMDAR function in the lineage that includes cortical excitatory neurons and glia, specifically, was critical for the elaboration of normal cortical activity patterns and dynamic network organization. In the first set of experiments, NMDARs were deleted in glutamatergic excitatory neurons (Emx1-cre+/WT/Grin1f/f ; referred to as EX-NMDAR KO mice) or GABAergic inhibitory neurons (Nkx2.1+/WT/Grin1f/f; referred to as IN-NMDAR KO mice). The developing cortex normally exhibits a diverse range of spatio-temporal patterns, reflecting the emergence of functionally associated sub-networks. In EX-NMDAR KO mice, normal patterns of spontaneous activity were severely disrupted and reduced to a nearly one-dimensional dynamic space dominated by large, cortex-wide events. Interestingly, in IN-NMDAR KO mice, the structure and complexity of spontaneous activity was largely normal. In the next set of experiments, I tested the role of extrinsic thalamic neurotransmission on cortical activity during development. Deleting the vesicular glutamate transporter from thalamic neurons while leaving cortical NMDARs intact (Sert-Cre+/−,vglut1−/−,vglut2fl/fl; referred to as TH-VG KO mice) led to a shift in cortical activity patterns towards large domains of activity, reminiscent of patterns observed in EX-NMDAR KO mice. This manipulation also reduced the dimensionality of cortical activity, though not as severally as in EX-NMDAR KO mice. In a final set of experiments, I tested cortical activity in three established mouse models of mono-genetic causes of NDDs in humans: the FMR1-KO mouse based on Fragile X Syndrome, the CNTNAP2-KO mouse, and the TS2-neo mouse based on Timothy Syndrome. In all three of these mouse models, I found that large-scale cortical activity patterns were largely normal, but there was a statistically significant shift towards reduced cortex-wide synchrony and increased dimensionality of spontaneous activity, which may be consistent with the disconnectivity hypothesis of autism. In a final set of experiments, we tested our hypothesis, based on past literature and our results in EX-NMDAR KO and TH-VG KO mice, that the disruptions in cortical activity was predominantly due to the developmental loss of activity-dependent wiring of circuits. To test the developmental versus acute role of NMDAR function in shaping cortical activity, I blocked NMDAR pharmacologically in wild-type mice. I found that acute NMDAR blockade shifted cortical activity to a restricted dynamic space similar to that observed in EX-NMDAR KO mice and more extreme than that observed in TH-VG KO mice. These results strongly reinforce the critical role of NMDAR in shaping cortical activity during development, and suggest that a substantial component of that may be through NMDAR’s role in synaptic transmission and moment to moment cortex-wide circuit function. Overall, these results provide critical insight into the role of NMDARs and the glutamatergic system in cortical network functional organization during development. Specifically, they highlight the essential role of NMDARs in excitatory neurons on the functional connectivity and dynamic repertoire of the cortical network during development. These results make novel contribution to our understanding of how NMDARs may contribute to the pathophysiology of NDDs. Specifically, they contribute powerful new insight into to a critical mechanistic question about the cell-specific role of NMDARs in the pathophysiology of schizophrenia and the mechanisms of NMDAR antagonists, which have transformed psychiatry recently due to their rapid-acting anti-depressant and anti-suicidal properties. Furthermore, they identify a patterns of large-scale network dysfunction that might be detectable in humans using noninvasive functional imaging or electrophysiology