Background: Accompanied by a rapid and effective antidepressant effect, electroconvulsive shock (ECS) can also induce learning and memory impairment. Our previous research reported that metaplasticity is involved in this process. However, the mechanisms still remain unclear. This study investigated the role of current in the metaplastic changes and learning and memory impairment induced by ECS in depressive rats.
Methods: Depressive rats received ECS after modelling using chronic unpredictable. ZD7288, a type of current inhibitor was used to verify the effect of current. The sucrose preference test and Morris water maze were used for behavior testing. Changes in metaplasticity was assessed with the LTD/LTP threshold by stimulation at different frequencies. Spontaneous and evoked action potentials (APs) were measured to confirm difference of neuronal excitability. Additionally, the amplitude of current was analyzed.
Results: ECS exerts antidepressant effect, but also induce spatial learning and memory dysfunction. ECS up-regulates the LTD/LTP threshold. In rats treated with ECS, the frequency of spontaneous and evoked APs is significantly reduced. In addition, ECS induces changes in the intrinsic properties of AP, including a decrease of AP-half width and peak amplitude, and an increase in AP time to peak and post-hyperpolarization potential amplitude. In particular, ECS increases both instantaneous and steady-state currents. However, Inhibition of current with ZD7288 results in a relief of learning and memory impairment and a decrease in threshold, as well as a significant reversal of whole-cell electrophysiological changes.
Conclusion: ECS-induced learning and memory impairment is caused by neuronal hypoexcitability mediated metaplasticity, and upregulation of LTD/LTP threshold by an increase in current.
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http://dx.doi.org/10.3389/fpsyt.2024.1365119 | DOI Listing |
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental questions in robotics concerns this characteristic: How can linguistic compositionality be developed concomitantly with sensorimotor skills through associative learning, particularly when individuals only learn partial linguistic compositions and their corresponding sensorimotor patterns? To address this question, we propose a brain-inspired neural network model that integrates vision, proprioception, and language into a framework of predictive coding and active inference on the basis of the free-energy principle.
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Technical Center for Multifunctional Magneto-Optical Spectroscopy (Shanghai), Engineering Research Center of Nanophotonics & Advanced Instrument (Ministry of Education), Department of Physics, School of Physics and Electronic Science, East China Normal University, Shanghai, 200241, China.
Controlling polarization states of ferroelectrics can enrich optoelectronic properties and functions, offering a new avenue for designing advanced electronic and optoelectronic devices. Here, ferroelectric semiconductor-based field-effect transistors (FeSFETs) are fabricated, where the channel is a ferroelectric semiconductor (e.g.
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Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands.
Introduction: Physical exercise has repeatedly been reported to have advantageous effects on brain functions, including learning and memory formation. However, objective tools to measure such effects are often lacking. Eyeblink conditioning is a well-characterized method for studying the neural basis of associative learning.
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