Plasticity impairment exposes CA3 vulnerability in a hippocampal network model of mild traumatic brain injury

Abstract

Proper function of the hippocampus is critical for executing cognitive tasks such as learning and memory. Traumatic brain injury (TBI) and other neurological disorders are commonly associated with cognitive deficits and hippocampal dysfunction.Although there are many existing models of individual subregions of the hippocampus, few models attempt to integrate the primary areas into one system. In this work, we developed a computational model of the hippocampus, including the dentate gyrus, CA3, and CA1. The subregions are represented as an interconnected neuronal network, incorporating well-characterized ex vivo slice electrophysiology into the functional neuron models and well-documented anatomical connections into the network structure. In addition, since plasticity is foundational to the role of the hippocampus in learning and memory as well as necessary for studying adaptation to injury, we implemented spike-timing-dependent plasticity among the synaptic connections. Our model mimics key features of hippocampal activity, including signal frequencies in the theta and gamma bands and phase-amplitude coupling in area CA1.We also studied the effects of spike-timing-dependent plasticity impairment, a potential consequence of TBI, in our model and found that impairment decreases broadband power in CA3 and CA1 and reduces phase coherence between these two subregions, yet phase-amplitude coupling in CA1 remains intact. Altogether, our work demonstrates characteristic hippocampal activity with a scaled network model of spiking neurons and reveals the sensitive balance of plasticity mechanisms in the circuit through one manifestation of mild traumatic injury.

Plasticity impairment alters community structure but permits successful pattern separation in a hippocampal network model

“…The areas follow a primarily feedforward topology with the DG sending projections to CA3 which terminates in CA1 (a summary of the modeling methods follows. See Schumm et al, 2022 for more information about the model parameters).…”

“…There are 10 different types of neurons represented in the model across the three anatomical subregions ( Schumm et al, 2022 ). The dentate consists of granule cells, mossy cells, basket cells, and interneurons.…”

“…The dimensionless parameters a, b, c, d, and k are adjusted to represent different subtypes of neurons. The current (I) aggregates receptor-based ionic currents, including AMPA, NMDA, and GABA-A receptors, and 1 Hz noise input that drives the network and follows a gamma distribution (k = 2, θ = 1 /2) (Izhikevich and Edelman, 2008;Gabrieli et al, 2020b;Schumm et al, 2020Schumm et al, , 2022. There are 10 different types of neurons represented in the model across the three anatomical subregions (Schumm et al, 2022).…”

“…Although TBI likely includes a plethora of mechanisms, we isolated the effects of impaired potentiation. We simulate one effect of mild TBI as STDP impairment by reducing potentiation in the circuit and establish that this deficit reduced activity and broadband power in the network ( Schumm et al, 2022 ). Here we extend those results by demonstrating how STDP impairment affects the structural network, focusing specifically on community organization.…”

Differential Neural Network-Based Nonparametric Identification of Eye Response to Enforced Head Motion

“…Izhikevich artificial mathematical models have been proven to be an efficient model of diverse neuron responses [9]. Therefore, an aggregation of several Izhikevich artificial neurons is named electrophysiology-inspired approximated DNN or spiking DNNs [10,11].…”