Properties of spontaneous and miniature excitatory postsynaptic currents in neurons of the rat prefrontal cortex

Malkin, Sergey L.; Kim, K. Kh.; Tikhonov, Denis B.; Zaitsev, Aleksey V.

doi:10.1134/s0022093014060052

Cited by 9 publications

(8 citation statements)

References 26 publications

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“…However, the top gate TFT could also be used to realize similar synaptic behaviors. 8,9,[16][17][18] The IGZO transistor samples were fabricated using the following steps which are very common for lab study. The fabrication was based on a wafer with n-type Si as the bottom gate layer and a 100-nm thick SiO 2 as an insulating layer on top.…”

Section: Methodsmentioning

confidence: 99%

“…To investigate the effect of voltage stress on the device insulators, different voltage conditions were applied in order to obtain a transfer curve and the loops are compared. [14][15][16] As Figure 3 Overview of a voltage pulse profile and the corresponding discharge current in the TFTs with the IGZO channel in red (trapped electrons, mobile carriers trapped by interface between the IGZO and the SiO2 layer or defects). The number for the sub-images on the right correspond to each respective numbered region in the schematic on the left.…”

Section: Methodsmentioning

confidence: 99%

“…They have some attractive properties, including transparency, flexibility, and relatively low-cost fabrication mainly attributed to the low temperature processing at no higher than 200°C. [15][16][17][18][19] Most of AOS are n-type materials. This is because p-type AOS materials have carrier mobilities much lower than n-type AOS materials.…”

Section: Introductionmentioning

confidence: 99%

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<p>Implementation of PPI with Nano Amorphous Oxide Semiconductor Devices for Medical Applications</p>

Dai

et al. 2020

IJN

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Background: Electronic devices which mimic the functionality of biological synapses are a large step to replicate the human brain for neuromorphic computing and for numerous medical research investigations. One of the representative synaptic behaviors is paired-pulse facilitation (PPF). It has been widely investigated because it is regarded to be related to biological memory. However, plasticity behavior is only part of the human brain memory behavior.Methods: Here, we present a phenomenon which is opposite to PPF, i.e., paired-pulse inhibition (PPI), in nano oxide devices for the first time. The research here suggests that rather than being enhanced, the phenomena of memory loss would also be possessed by such electronic devices. The device physics mechanism behind memory loss behavior was investigated. This mechanism is sustained by historical memory and degradation manufactured by device trauma to regulate characteristically stimulated origins of artificial transmission behaviors.Results: Under the trauma of a memory device, both the signal amplitude and signal time stimulated by a pulse are lower than the first signal stimulated by a previous pulse in the PPF, representing a new scenario in the struggle for memory. In this way, more typical human brain behaviors could be simulated, including the effect of age on latency and error generation, cerebellar infarct, trauma and memory loss pharmacological actions (such as those caused by hyoscines and nitrazepam). Conclusion: Thus, this study developed a new approach for implementing the manner in which the brain works in semiconductor devices for improving medical research.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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<p>Implementation of PPI with Nano Amorphous Oxide Semiconductor Devices for Medical Applications</p>

Dai

et al. 2020

IJN

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“…4, G and H). Because mEPSC frequency primarily represents the probability of presynaptic release and mEPSC amplitude is largely associated with the conductance of postsynaptic receptors (25), the results suggest improved postsynaptic receptor function in MK0677/SKF81297-treated 5×FAD CA1 neurons. Together, these findings strongly suggest a role for dysfunctional GHSR1α regulation of DRD1 in AD hippocampal synaptic failure and also indicate that combined stimulation of GHSR1α and DRD1 can rescue Aβ-induced hippocampal synaptic deficits.…”

Section: Resultsmentioning

confidence: 97%

Disrupted hippocampal growth hormone secretagogue receptor 1α interaction with dopamine receptor D1 plays a role in Alzheimer′s disease

et al. 2019

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Hippocampal lesions are a defining pathology of Alzheimer’s disease (AD). However, the molecular mechanisms that underlie hippocampal synaptic injury in AD have not been fully elucidated. Current therapeutic efforts for AD treatment are not effective in correcting hippocampal synaptic deficits. Growth hormone secretagogue receptor 1α (GHSR1α) is critical for hippocampal synaptic physiology. Here, we report that GHSR1α interaction with β-amyloid (Aβ) suppresses GHSR1α activation, leading to compromised GHSR1α regulation of dopamine receptor D1 (DRD1) in the hippocampus from patients with AD. The simultaneous application of the selective GHSR1α agonist MK0677 with the selective DRD1 agonist SKF81297 rescued Ghsr1α function from Aβ inhibition, mitigating hippocampal synaptic injury and improving spatial memory in an AD mouse model. Our data reveal a mechanism of hippocampal vulnerability in AD and suggest that a combined activation of GHSR1α and DRD1 may be a promising approach for treating AD.

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“…The analysis of spontaneous (miniature) postsynaptic currents, i.e., postsynaptic responses to the neurotransmitter release from single presynaptic vesicles, reveals that the resolution of synaptic weights is indeed finite for chemical synapses. Malkin et al (2014), for example, show that the amplitudes of spontaneous excitatory postsynaptic currents recorded from different types of excitatory and inhibitory cortical neurons are unimodally distributed with a peak at about 20 pA and a lower bound at about 10 pA. Note that these results have been obtained despite a number of factors that may potentially wash out the discreteness of synaptic transmission, such as variability in vesicles sizes, variability in the position of vesicle fusion zones, quasirandomness in neurotransmitter diffusion across the synaptic cleft, and variability in postsynaptic receptor densities.…”

Section: Discussionmentioning

confidence: 99%

Dynamical Characteristics of Recurrent Neuronal Networks Are Robust Against Low Synaptic Weight Resolution

et al. 2021

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The representation of the natural-density, heterogeneous connectivity of neuronal network models at relevant spatial scales remains a challenge for Computational Neuroscience and Neuromorphic Computing. In particular, the memory demands imposed by the vast number of synapses in brain-scale network simulations constitute a major obstacle. Limiting the number resolution of synaptic weights appears to be a natural strategy to reduce memory and compute load. In this study, we investigate the effects of a limited synaptic-weight resolution on the dynamics of recurrent spiking neuronal networks resembling local cortical circuits and develop strategies for minimizing deviations from the dynamics of networks with high-resolution synaptic weights. We mimic the effect of a limited synaptic weight resolution by replacing normally distributed synaptic weights with weights drawn from a discrete distribution, and compare the resulting statistics characterizing firing rates, spike-train irregularity, and correlation coefficients with the reference solution. We show that a naive discretization of synaptic weights generally leads to a distortion of the spike-train statistics. If the weights are discretized such that the mean and the variance of the total synaptic input currents are preserved, the firing statistics remain unaffected for the types of networks considered in this study. For networks with sufficiently heterogeneous in-degrees, the firing statistics can be preserved even if all synaptic weights are replaced by the mean of the weight distribution. We conclude that even for simple networks with non-plastic neurons and synapses, a discretization of synaptic weights can lead to substantial deviations in the firing statistics unless the discretization is performed with care and guided by a rigorous validation process. For the network model used in this study, the synaptic weights can be replaced by low-resolution weights without affecting its macroscopic dynamical characteristics, thereby saving substantial amounts of memory.

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Properties of spontaneous and miniature excitatory postsynaptic currents in neurons of the rat prefrontal cortex

Cited by 9 publications

References 26 publications

<p>Implementation of PPI with Nano Amorphous Oxide Semiconductor Devices for Medical Applications</p>

<p>Implementation of PPI with Nano Amorphous Oxide Semiconductor Devices for Medical Applications</p>

Disrupted hippocampal growth hormone secretagogue receptor 1α interaction with dopamine receptor D1 plays a role in Alzheimer′s disease

Dynamical Characteristics of Recurrent Neuronal Networks Are Robust Against Low Synaptic Weight Resolution

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