ABSTRACT The functional and cognitive effects of traumatic brain injury (TBI) are poorly understood, as even mild injuries (concussion) can lead to long-lasting, untreatable symptoms. Simplified brain dynamics models may help researchers better understand the relationship between brain injury patterns and functional outcomes. Properly developed, these computational models provide an approach to investigate the effects of both computational and in vivo injury on simulated dynamics and cognitive function, respectively, for model organisms. In this study, we apply the Kuramoto model and an existing mesoscale mouse brain structural network to develop a simplified computational model of mouse brain dynamics. We explore how to optimize our initial model to predict existing mouse brain functional connectivity collected from mice under various anesthetic protocols. Finally, to determine how strongly the changes in our optimized models’ dynamics can predict the extent of a brain injury, we investigate how our simulations respond to varying levels of structural network damage. Results predict a mixture of hypo- and hyperconnectivity after experimental TBI, similar to results in TBI survivors, and also suggest a compensatory remodeling of connections that may have an impact on functional outcomes after TBI. AUTHOR SUMMARY Recent research has investigated the consequences of traumatic brain injuries by combining computational models of human brain activity and structural models of the whole human brain or cortex. As experimental injury research can only be conducted using animal models, we apply a simplified computational model of whole-brain dynamics, the Kuramoto model, to a mouse brain structural network. We tune our model to best predict measurements of functional connectivity recorded from 58 fMRI scans of mice and lesion the network model to explore the effects of injury. Our findings predict that functional connectivity may increase or decrease in various regions of the brain, even at a high injury level, which may aid in future predictions of cognitive impairments after brain injury.

Author Summary Astrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. We constructed a multilayer network model of neuron-astrocyte connectivity based on calcium activity in mixed cortical cultures, and used this model to evaluate the effect of glutamatergic inhibition and mechanical injury on network topology. We found that injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in injured networks pretreated with a glutamate receptor antagonist. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations. Abstract Astrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. Despite recent advances in understanding neuron-astrocyte signaling, little is known about astrocytic modulation of neuronal activity at the population level, particularly in disease or following injury. We used high-speed calcium imaging of mixed cortical cultures in vitro to determine how population activity changes after disruption of glutamatergic signaling and mechanical injury. We constructed a multilayer network model of neuron-astrocyte connectivity, which captured distinct topology and response behavior from single-cell-type networks. mGluR 5 inhibition decreased neuronal activity, but did not on its own disrupt functional connectivity or network topology. In contrast, injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in networks pretreated with mGluR 5 inhibition. Comparison of spatial and functional connectivity revealed that functional connectivity is largely independent of spatial proximity at the microscale, but mechanical injury increased the spatial-functional correlation. Finally, we found that astrocyte segments of the same cell often belong to separate functional communities based on neuronal connectivity, suggesting that astrocyte segments function as independent entities. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations.

Cytosolic PSD-95 interactor (cypin) regulates many aspects of neuronal development and function, ranging from dendritogenesis to synaptic protein localization. While it is known that removal of postsynaptic density protein-95 (PSD-95) from the postsynaptic density decreases synaptic N-methyl-D-aspartate (NMDA) receptors and that cypin overexpression protects neurons from NMDA-induced toxicity, little is known about cypin’s role in AMPA receptor clustering and function. Experimental work shows that cypin overexpression decreases PSD-95 levels in synaptosomes and the PSD, decreases PSD-95 clusters/μm 2 , and increases mEPSC frequency. Analysis of microelectrode array (MEA) data demonstrates that cypin or cypinΔPDZ overexpression increases sensitivity to CNQX (cyanquixaline) and AMPA receptor-mediated decreases in spike waveform properties. Network-level analysis of MEA data reveals that cypinΔPDZ overexpression causes networks to be resilient to CNQX-induced changes in local efficiency. Incorporating these findings into a computational model of a neural circuit demonstrates a role for AMPA receptors in cypin-promoted changes to networks and shows that cypin increases firing rate while changing network functional organization, suggesting cypin overexpression facilitates information relay but modifies how information is encoded among brain regions. Our data show that cypin promotes changes to AMPA receptor signaling independent of PSD-95 binding, shaping neural circuits and output to regions beyond the hippocampus. Author Summary We used lentivirus to overexpress cytosolic PSD-95 interactor (cypin) and a cypin mutant that cannot bind PSD-95 (cypinΔPDZ) to understand how cypin regulates synaptic signaling. Using biochemical and electrophysiological approaches, we show that cypin, but not the cypin mutant, regulates synaptic PSD-95 content. Surprisingly, cypin overexpression increases AMPA receptor function independent of its role in PSD-95 localization, while cypinΔPDZ overexpression causes networks to be resistant to CNQX-mediated changes to local efficiency. We then developed a computational model to account for the effects of cypin overexpression, finding that our simulated model also demonstrates a role for AMPA receptors in cypin-promoted changes to neural circuits. These results support a role for cypin in controlling synaptic function at synapses that is distinct from regulation of PSD-95 function.