Topic
Synapse part
About: Synapse part is a research topic. Over the lifetime, 13 publications have been published within this topic receiving 90 citations.
Papers
TL;DR: This work simulates the effects of their nonlinear conductance response on the training of a three-layer fully connected neural network and shows that the bidirectional programming of Al/Mo/PCMO can be used to implement high-density neuromorphic systems with a single conductance per synapse, at only a slight degradation to accuracy.
Abstract: Neuromorphic computing embraces the “device history” offered by many analog non-volatile memory (NVM) devices to implement the small weight changes computed by a gradient-descent learning algorithm such as backpropagation. Deterministic and stochastic imperfections in the conductance response of real NVM devices can be encapsulated for modeling within a pair of “jump-tables.” Such jump-tables describe the full cumulative distribution function of conductance-change at each device conductance value, for both weight potentiation (SET) and depression (RESET). First, using several types of artificially constructed jump-tables, we revisit the relative importance of deviations from an ideal NVM with perfectly linear conductance response. Then, using jump-tables measured on improved non-filamentary resistive RAM devices based on Pr0.7Ca0.3MnO3[see companion paper], we simulate the effects of their nonlinear conductance response on the training of a three-layer fully connected neural network. We find that, despite the relatively large conductance changes exhibited by any Pr0.7Ca0.3MnO3 device when either potentiating from its lowest conductance state or depressing from its highest conductance states, neural network training accuracies of >90% can be achieved. Highest accuracies are achieved by programming both conductances on each timestep (“fully bidirectional”), with the improved conductance on/off ratio of Al/Mo/PCMO resulting in marked improvements in training and test accuracy. Further accuracy improvements can be obtained by tuning the relative learning rate for potentiation (SET) by a factor of $1.66\times $ with respect to depression (RESET), to offset the slight asymmetry between the average size of the associated SET and RESET conductance changes. Finally, we show that the bidirectional programming of Al/Mo/PCMO can be used to implement high-density neuromorphic systems with a single conductance per synapse, at only a slight degradation to accuracy.
25 citations
TL;DR: Synapse dysfunction is tightly associated with the development and progression of neurodegenerative diseases like AD, and following synapse associated pathways to be most affected.
Abstract: Alzheimer’s disease (AD) is a common neurodegenerative disorder primarily affecting memory and thinking ability; caused by progressive degeneration and death of nerve cells. In this study, we integrated multiple dataset retrieved from the National Center for Biotechnology Information's Gene Expression Omnibus database, and took a systemsbiology approach to compare and distinguish the molecular network based synaptic dysregulation associated with AD in particular and neurodegenerative diseases in general. We first identified 832 differentially expressed genes using cut off P value 2, followed by gene ontology study to identify genes associated with synapse (n=95) [membrane associated guanylate kinase, 2, amyloid beta precursor protein, neurotrophic tyrosine kinase, receptor, type 2], synapse part [γ-aminobutyric acid A receptor, γ1], synaptic vesicle [glutamate receptor, ionotropic, α-amino-3-hydroxy-5- methyl-4-isoxazole propionic acid receptor 2, synaptoporin], pre- and post-synaptic density [neuronal calcium sensor 1, glutamate receptor, metabotropic 3]. We integrated these data with known pathways using Ingenuity Pathway Analysis tool and found following synapse associated pathways to be most affected; γ-aminobutyric acid receptor signaling, synaptic long term potentiation/depression, nuclear factor-erythroid 2-related factor 2-mediated oxidative stress response, huntington's disease signaling and Reelin signaling in neurons. In conclusion, synaptic dysfunction is tightly associated with the development and progression of neurodegenerative diseases like AD.
20 citations
TL;DR: Integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups and found the hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age.
Abstract: Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age‑induced differentially expressed genes (DEGs) and potential molecular mechanisms that contribute to the different outcomes of patients with OS. Microarray data (GSE39058 and GSE39040) obtained from the Gene Expression Omnibus database and used to analyze age‑induced DEGs to reveal molecular mechanism of OS among different age groups ( 20 years old). Differentially expressed mRNAs (DEMs) were divided into up and downregulated DEMs (according to the expression fold change), then Gene Ontology function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Furthermore, the interactions among proteins encoded by DEMs were integrated with prediction for microRNA‑mRNA interactions to construct a regulatory network. The key subnetwork was extracted and Kaplan‑Meier survival analysis for a key microRNA was performed. DEMs within the subnetwork were predominantly involved in 'ubiquitin protein ligase binding', 'response to growth factor', 'regulation of type I interferon production', 'response to decreased oxygen levels', 'voltage‑gated potassium channel complex', 'synapse part', 'regulation of stem cell proliferation'. In summary, integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups. The hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age and require further analysis.
13 citations
Patent•
2 Jun 1995
TL;DR: In this paper, a neural circuit element containing a weighting circuit and a threshold value processing circuit is used to compare a compared signal Y with a threshold signal Yth in regard to a neuron.
Abstract: PURPOSE:To perform the learning that introduces a time-series change corresponding to the relevant learning by changing the weight and the threshold value according to the receiving frequency and the receiving intensity of input signals and by approximating further the excitability and the suppressibility of the synapse part to an organism system. CONSTITUTION:In the neural circuit element containing a weighting circuit 11 which simulates the synapse connection to weight an input signal Xi (i=1-n), the circuit 11 increases and decreases the weight against the high and low receiving frequency of the signal Xi respectively. Meanwhile, a threshold value processing circuit 12 increases and decreases the threshold value theta against the high and low receiving frequency of a compared signal Y respectively in regard of a neural circuit element containing the circuit 12 which simulates a neuron to compare the signal Y with a threshold signal Yth.
8 citations
TL;DR: By integrating genetic, brain imaging, and behavioral data, this research initially revealed the neurogenetic underpinnings of neuroticism, which is helpful for understanding individual differences in neuroticism.
Abstract: Neuroticism is a robust personality trait associated with multiple mental disorders. Heretofore, research on the relationship among genes, brain, and behavior to explore individual differences in neuroticism is scarce. Hence, in this study (N = 630), genetic data, self-reported neuroticism, and brain structural data were combined to explore whether the cortical thickness (CT) of brain regions mediated the relationship between the polygenic risk score (PRS) of neuroticism and NEO neuroticism (NEO-N), and the enrichment analysis was performed to reveal the underlying mechanism of their relationship. Results showed that the PRSs were significantly associated with NEO-N scores (p < .05). The CT of left rostral middle frontal gyrus was negatively related to the best PRS in PRSice (PRSbest ) or the PRS at 0.05 threshold (PRS0.05 ) (corrected p < .05), which was also found to mediate the association between the PRS and NEO-N (PRSbest : ab = .012, p < .05; PRS0.05 : ab = .012, p < .05). Enrichment analysis revealed that these genes were mainly involved in biological adhesion, cell adhesion, neuron part, and synapse part, which were associated with the abnormal thickness of frontal cortex. By integrating genetic, brain imaging, and behavioral data, our research initially revealed the neurogenetic underpinnings of neuroticism, which is helpful for understanding individual differences in neuroticism.
8 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 3 |
| 2020 | 1 |
| 2019 | 1 |
| 2018 | 3 |
| 2014 | 1 |
| 2010 | 1 |