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Mohagheghi Nejad, M.

Publications and source records attributed to Mohagheghi Nejad, M..

2 recordsLinked to original sources

Navigation and the Efficiency of Spatial Coding: Insights from Closed-Loop Simulations

Spatial learning is critical for survival and its underlying neuronal mechanisms have been studied extensively. These studies have revealed a wealth of information about the neural representations of space, such as place cells and boundary cells. While many studies have focused on how these representations emerge in the brain, their functional role in driving spatial learning and navigation has received much less attention. We extended an existing computational modeling tool-chain to study the functional role of spatial representations using closed-loop simulations of spatial learning. At the heart of the model agent was a spiking neural network that formed a ring attractor. This network received inputs from place and boundary cells and the location of the activity bump in this network was the output. This output determined the movement directions of the agent. We found that the navigation performance depended on the parameters of the place cell input, such as their number, the place field sizes, and peak firing rate, as well as, unsurprisingly, the size of the goal zone. The dependence on the place cell parameters could be accounted for by just a single variable, the overlap index, but this dependence was nonmonotonic. By contrast, performance scaled monotonically with the Fisher information of the place cell population. Our results therefore demonstrate that efficiently encoding spatial information is critical for navigation performance.

neuroscience↗

Transmission of motor signals from the basal ganglia to the thalamus: effect of correlations, sensory responses, and excitation

Movement-related decreases in firing rate have been observed in basal ganglia output neurons. They may transmit motor signals to the thalamus, but the effect of these firing rate decreases on downstream neurons in the motor thalamus is not known. One possibility is that they lead to thalamic post-inhibitory rebound spikes. However, it has also been argued that the physiological conditions permitting rebound spiking are pathological, and primarily present in Parkinsons disease. As in Parkinsons disease neural activity becomes pathologically correlated, we investigated the impact of correlations in basal ganglia output on the transmission of motor signals using a Hodgkin-Huxley model of thalamocortical neurons. We found that such correlations disrupt the transmission of motor signals via rebound spikes by decreasing the signal-to-noise ratio and increasing the trial-to-trial variability. We further examined the role of sensory responses in basal ganglia output neurons and the effect of cortical excitation of motor thalamus in modulating rebound spiking. Interestingly, both could either promote or suppress the generation of rebound spikes depending on their timing relative to the motor signal. Finally, we determined parameter regimes, such as levels of excitation, under which rebound spiking is feasible in the model, and confirmed that the conditions for rebound spiking are primarily given in pathological regimes. However, we also identified specific conditions in the model that would allow rebound spiking to occur in healthy animals in a small subset of thalamic neurons. Overall, our model provides novel insights into differences between normal and pathological transmission of motor signals.

neuroscience↗