A computational simulation of long-term synaptic potentiation inducing protocol processes with model of CA3 hippocampal microcircuit

Świetlik, Dariusz; Białowas, J; Kusiak, Aida; Cichońska, Dominika

doi:10.5603/fm.a2018.0042

Cited by 13 publications

(31 citation statements)

References 54 publications

(64 reference statements)

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“…The CA1 microcircuit is presented of Figure 1. Our simulations of the hippocampus are based on computational models from previous studies [53,54]. There are four pyramidal cells (P1, P2, P3, and P4), two basket (B1, B2), one O-LM cell (inhibitory interneurons), and 3 independently programmed theta rhythm generators.…”

Section: The Model Descriptionmentioning

confidence: 99%

“…We have used the theta oscillation in our previous studies [53,54], which were based on faster gamma-frequency oscillations [1,[57][58][59][60], spatial information [61][62][63], in-time locking cell activities [64], and regulation of learning facilities [1,[65][66][67].…”

Section: The Model Descriptionmentioning

confidence: 99%

“…The mathematical description of equations and parameters that we used in our simulations was based on our previous studies on single neuron model [53] and sparse CA3 network model [54]. All mathematical descriptions of CA1 model neurons are presented in Table 1.…”

Section: Art Of Workmentioning

confidence: 99%

“…The mathematical description of the glutamate receptors AMPA, NMDA, and the GABA receptor was based on our previous studies [53,54]. The real value of postsynaptic potential is estimated by using functions from Table 1.…”

Section: Synaptic Propertiesmentioning

confidence: 99%

“…During these studies all pyramidal cells had the same LSW parameter (0,2). However during our previous studies on CA3 microcircuit, the pyramidal cells used LSW ranging from 0,6 to 0,7 [53,54].…”

Section: Synaptic Propertiesmentioning

confidence: 99%

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Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus

Świetlik

2018

Complexity

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The aim of this paper is to present a computational model of the CA1 region of the hippocampus, whose properties include (a) attenuation of receptors for external stimuli, (b) delay and decay of postsynaptic potentials, (c) modification of internal weights due to propagation of postsynaptic potentials through the dendrite, and (d) modification of weights for the analog memory of each input due to a pattern of long-term synaptic potentiation (LTP) with regard to its decay. The computer simulations showed that CA1 model performs efficient LTP induction and high rate of sub-millisecond coincidence detection. We also discuss a possibility of hardware implementation of pyramidal cells of CA1 region of the hippocampus.

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Section: The Model Descriptionmentioning

confidence: 99%

Section: The Model Descriptionmentioning

confidence: 99%

Section: Art Of Workmentioning

confidence: 99%

Section: Synaptic Propertiesmentioning

confidence: 99%

Section: Synaptic Propertiesmentioning

confidence: 99%

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Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus

Świetlik

2018

Complexity

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Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review

Surdu,

Budala,

Luchian

et al. 2024

Diagnostics

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Artificial intelligence (AI) is revolutionizing the field of oral and dental healthcare by offering innovative tools and techniques for optimizing diagnosis, treatment planning, and patient management. This narrative review explores the current applications of AI in dentistry, focusing on its role in enhancing diagnostic accuracy and efficiency. AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.

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Computer Model of Synapse Loss During an Alzheimer’s Disease-Like Pathology in Hippocampal Subregions DG, CA3 and CA1—The Way to Chaos and Information Transfer

Świetlik

Białowas

Moryś

et al. 2019

Entropy

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The aim of the study was to compare the computer model of synaptic breakdown in an Alzheimer’s disease-like pathology in the dentate gyrus (DG), CA3 and CA1 regions of the hippocampus with a control model using neuronal parameters and methods describing the complexity of the system, such as the correlative dimension, Shannon entropy and positive maximal Lyapunov exponent. The model of synaptic breakdown (from 13% to 50%) in the hippocampus modeling the dynamics of an Alzheimer’s disease-like pathology was simulated. Modeling consisted in turning off one after the other EC2 connections and connections from the dentate gyrus on the CA3 pyramidal neurons. The pathological model of synaptic disintegration was compared to a control. The larger synaptic breakdown was associated with a statistically significant decrease in the number of spikes (R = −0.79, P < 0.001), spikes per burst (R = −0.76, P < 0.001) and burst duration (R = −0.83, P < 0.001) and an increase in the inter-burst interval (R = 0.85, P < 0.001) in DG-CA3-CA1. The positive maximal Lyapunov exponent in the control model was negative, but in the pathological model had a positive value of DG-CA3-CA1. A statistically significant decrease of Shannon entropy with the direction of information flow DG->CA3->CA1 (R = −0.79, P < 0.001) in the pathological model and a statistically significant increase with greater synaptic breakdown (R = 0.24, P < 0.05) of the CA3-CA1 region was obtained. The reduction of entropy transfer for DG->CA3 at the level of synaptic breakdown of 35% was 35%, compared with the control. Entropy transfer for CA3->CA1 at the level of synaptic breakdown of 35% increased to 95% relative to the control. The synaptic breakdown model in an Alzheimer’s disease-like pathology in DG-CA3-CA1 exhibits chaotic features as opposed to the control. Synaptic breakdown in which an increase of Shannon entropy is observed indicates an irreversible process of Alzheimer’s disease. The increase in synapse loss resulted in decreased information flow and entropy transfer in DG->CA3, and at the same time a strong increase in CA3->CA1.

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A computational simulation of long-term synaptic potentiation inducing protocol processes with model of CA3 hippocampal microcircuit

Cited by 13 publications

References 54 publications

Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus

Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus

Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review

Computer Model of Synapse Loss During an Alzheimer’s Disease-Like Pathology in Hippocampal Subregions DG, CA3 and CA1—The Way to Chaos and Information Transfer

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