scholarly journals The Enhanced Rise and Delayed Fall of Memory in a Model of Synaptic Integration: Extension to Discrete State Synapses

2016 ◽  
Vol 28 (9) ◽  
pp. 1927-1984 ◽  
Author(s):  
Terry Elliott
Keyword(s):  
Synaptic Plasticity ◽  
Signal To Noise Ratio ◽  
Memory Systems ◽  
Discrete State ◽  
Developmental Models ◽  
Initial Rise ◽  
Filter Size ◽  
Low Pass ◽  
Synaptic Parameters ◽  
Low Pass Filters

Integrate-and-express models of synaptic plasticity propose that synapses may act as low-pass filters, integrating synaptic plasticity induction signals in order to discern trends before expressing synaptic plasticity. We have previously shown that synaptic filtering strongly controls destabilizing fluctuations in developmental models. When applied to palimpsest memory systems that learn new memories by forgetting old ones, we have also shown that with binary-strength synapses, integrative synapses lead to an initial memory signal rise before its fall back to equilibrium. Such an initial rise is in dramatic contrast to nonintegrative synapses, in which the memory signal falls monotonically. We now extend our earlier analysis of palimpsest memories with synaptic filters to consider the more general case of discrete state, multilevel synapses. We derive exact results for the memory signal dynamics and then consider various simplifying approximations. We show that multilevel synapses enhance the initial rise in the memory signal and then delay its subsequent fall by inducing a plateau-like region in the memory signal. Such dynamics significantly increase memory lifetimes, defined by a signal-to-noise ratio (SNR). We derive expressions for optimal choices of synaptic parameters (filter size, number of strength states, number of synapses) that maximize SNR memory lifetimes. However, we find that with memory lifetimes defined via mean-first-passage times, such optimality conditions do not exist, suggesting that optimality may be an artifact of SNRs.

Stability Against Fluctuations: Scaling, Bifurcations, and Spontaneous Symmetry Breaking in Stochastic Models of Synaptic Plasticity

2011 ◽  
Vol 23 (3) ◽  
pp. 674-734 ◽  
Author(s):  
Terry Elliott
Keyword(s):  
Synaptic Plasticity ◽  
Symmetry Breaking ◽  
Spontaneous Symmetry Breaking ◽  
Stochastic Models ◽  
Synaptic Connectivity ◽  
Stable States ◽  
Step Size ◽  
Low Pass ◽  
Temperature Parameter ◽  
Low Pass Filters

In stochastic models of synaptic plasticity based on a random walk, the control of fluctuations is imperative. We have argued that synapses could act as low-pass filters, filtering plasticity induction steps before expressing a step change in synaptic strength. Earlier work showed, in simulation, that such a synaptic filter tames fluctuations very well, leading to patterns of synaptic connectivity that are stable for long periods of time. Here, we approach this problem analytically. We explicitly calculate the lifetime of meta-stable states of synaptic connectivity using a Fokker-Planck formalism in order to understand the dependence of this lifetime on both the plasticity step size and the filtering mechanism. We find that our analytical results agree very well with simulation results, despite having to make two approximations. Our analysis reveals, however, a deeper significance to the filtering mechanism and the plasticity step size. We show that a filter scales the step size into a smaller, effective step size. This scaling suggests that the step size may itself play the role of a temperature parameter, so that a filter cools the dynamics, thereby reducing the influence of fluctuations. Using the master equation, we explicitly demonstrate a bifurcation at a critical step size, confirming this interpretation. At this critical point, spontaneous symmetry breaking occurs in the class of stochastic models of synaptic plasticity that we consider.

scholarly journals Mean First Passage Memory Lifetimes by Reducing Complex Synapses to Simple Synapses

2017 ◽  
Vol 29 (6) ◽  
pp. 1468-1527 ◽  
Author(s):  
Terry Elliott
Keyword(s):  
Synaptic Plasticity ◽  
First Passage Time ◽  
Passage Time ◽  
Memory Models ◽  
Memory Storage ◽  
First Passage ◽  
Internal States ◽  
Low Pass ◽  
Complex Models ◽  
Low Pass Filters

Memory models that store new memories by forgetting old ones have memory lifetimes that are rather short and grow only logarithmically in the number of synapses. Attempts to overcome these deficits include “complex” models of synaptic plasticity in which synapses possess internal states governing the expression of synaptic plasticity. Integrate-and-express, filter-based models of synaptic plasticity propose that synapses act as low-pass filters, integrating plasticity induction signals before expressing synaptic plasticity. Such mechanisms enhance memory lifetimes, leading to an initial rise in the memory signal that is in radical contrast to other related, but nonintegrative, memory models. Because of the complexity of models with internal synaptic states, however, their dynamics can be more difficult to extract compared to “simple” models that lack internal states. Here, we show that by focusing only on processes that lead to changes in synaptic strength, we can integrate out internal synaptic states and effectively reduce complex synapses to simple synapses. For binary-strength synapses, these simplified dynamics then allow us to work directly in the transitions in perceptron activation induced by memory storage rather than in the underlying transitions in synaptic configurations. This permits us to write down master and Fokker-Planck equations that may be simplified under certain, well-defined approximations. These methods allow us to see that memory based on synaptic filters can be viewed as an initial transient that leads to memory signal rise, followed by the emergence of Ornstein-Uhlenbeck-like dynamics that return the system to equilibrium. We may use this approach to compute mean first passage time–defined memory lifetimes for complex models of memory storage.

Ku/Ka-band Compact Orthomode Junction with Low Pass Filters for High Power Applications

2015 ◽  
Vol E98.C (2) ◽  
pp. 156-161
Author(s):  
Hidenori YUKAWA ◽  
Koji YOSHIDA ◽  
Tomohiro MIZUNO ◽  
Tetsu OWADA ◽  
Moriyasu MIYAZAKI
Keyword(s):  
High Power ◽  
Ka Band ◽  
Low Pass ◽  
Low Pass Filters

Mathematical Model of Low-Pass Filters

2011 ◽  
Vol 5 (2) ◽  
pp. 155-162
Author(s):  
Jose de Jesus Rubio ◽  
Diana M. Vazquez ◽  
Jaime Pacheco ◽  
Vicente Garcia
Keyword(s):  
Mathematical Model ◽  
Low Pass ◽  
Low Pass Filters

scholarly journals Delay Equivalences in Tuning PID Control for the Double Integrator Plus Dead-Time

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 328
Author(s):  
Mikulas Huba ◽  
Damir Vrancic
Keyword(s):  
Dead Time ◽  
Pid Controllers ◽  
Noisy Environment ◽  
Advantages And Disadvantages ◽  
Implementation Problem ◽  
Low Pass ◽  
Excellent Control ◽  
Low Pass Filters ◽  
Double Integrator

The paper investigates and explains a new simple analytical tuning of proportional-integrative-derivative (PID) controllers. In combination with nth order series binomial low-pass filters, they are to be applied to the double-integrator-plus-dead-time (DIPDT) plant models. With respect to the use of derivatives, it should be understood that the design of appropriate filters is not only an implementation problem. Rather, it is also critical for the resulting performance, robustness and noise attenuation. To simplify controller commissioning, integrated tuning procedures (ITPs) based on three different concepts of filter delay equivalences are presented. For simultaneous determination of controller + filter parameters, the design uses the multiple real dominant poles method. The excellent control loop performance in a noisy environment and the specific advantages and disadvantages of the resulting equivalences are discussed. The results show that none of them is globally optimal. Each of them is advantageous only for certain noise levels and the desired degree of their filtering.

scholarly journals 1.0 V-0.18 µm CMOS Tunable Low Pass Filters with 73 dB DR for On-Chip Sensing Acquisition Systems

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 563
Author(s):  
Jorge Pérez-Bailón ◽  
Belén Calvo ◽  
Nicolás Medrano
Keyword(s):  
Power Consumption ◽  
Dynamic Range ◽  
Low Voltage ◽  
Cutoff Frequency ◽  
Cmos Technology ◽  
Active Area ◽  
Current Steering ◽  
Low Pass ◽  
On Chip ◽  
Low Pass Filters

This paper presents a new approach based on the use of a Current Steering (CS) technique for the design of fully integrated Gm–C Low Pass Filters (LPF) with sub-Hz to kHz tunable cut-off frequencies and an enhanced power-area-dynamic range trade-off. The proposed approach has been experimentally validated by two different first-order single-ended LPFs designed in a 0.18 µm CMOS technology powered by a 1.0 V single supply: a folded-OTA based LPF and a mirrored-OTA based LPF. The first one exhibits a constant power consumption of 180 nW at 100 nA bias current with an active area of 0.00135 mm2 and a tunable cutoff frequency that spans over 4 orders of magnitude (~100 mHz–152 Hz @ CL = 50 pF) preserving dynamic figures greater than 78 dB. The second one exhibits a power consumption of 1.75 µW at 500 nA with an active area of 0.0137 mm2 and a tunable cutoff frequency that spans over 5 orders of magnitude (~80 mHz–~1.2 kHz @ CL = 50 pF) preserving a dynamic range greater than 73 dB. Compared with previously reported filters, this proposal is a competitive solution while satisfying the low-voltage low-power on-chip constraints, becoming a preferable choice for general-purpose reconfigurable front-end sensor interfaces.

scholarly journals ECG Signal Denoising and Reconstruction Based on Basis Pursuit

2021 ◽  
Vol 11 (4) ◽  
pp. 1591
Author(s):  
Ruixia Liu ◽  
Minglei Shu ◽  
Changfang Chen
Keyword(s):  
Signal To Noise Ratio ◽  
Heart Diseases ◽  
Gaussian White Noise ◽  
Basis Pursuit ◽  
Signal Denoising ◽  
Ecg Signal ◽  
Penalty Term ◽  
Ecg Signals ◽  
Alternating Direction ◽  
Low Pass

The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However, ECG signals are easily contaminated by different noises. This paper presents efficient denoising and compressed sensing (CS) schemes for ECG signals based on basis pursuit (BP). In the process of signal denoising and reconstruction, the low-pass filtering method and alternating direction method of multipliers (ADMM) optimization algorithm are used. This method introduces dual variables, adds a secondary penalty term, and reduces constraint conditions through alternate optimization to optimize the original variable and the dual variable at the same time. This algorithm is able to remove both baseline wander and Gaussian white noise. The effectiveness of the algorithm is validated through the records of the MIT-BIH arrhythmia database. The simulations show that the proposed ADMM-based method performs better in ECG denoising. Furthermore, this algorithm keeps the details of the ECG signal in reconstruction and achieves higher signal-to-noise ratio (SNR) and smaller mean square error (MSE).

scholarly journals Imbalanced post- and extrasynaptic SHANK2A functions during development affect social behavior in SHANK2-mediated neuropsychiatric disorders

2021 ◽  
Author(s):  
Ahmed Eltokhi ◽  
Miguel A. Gonzalez-Lozano ◽  
Lars-Lennart Oettl ◽  
Andrey Rozov ◽  
Claudia Pitzer ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Social Interaction ◽  
Social Behavior ◽  
Ampa Receptors ◽  
Signal To Noise Ratio ◽  
Signal Transmission ◽  
Neuropsychiatric Disorders ◽  
Autism Spectrum ◽  
Strong Impact ◽  
Odor Processing

AbstractMutations in SHANK genes play an undisputed role in neuropsychiatric disorders. Until now, research has focused on the postsynaptic function of SHANKs, and prominent postsynaptic alterations in glutamatergic signal transmission have been reported in Shank KO mouse models. Recent studies have also suggested a possible presynaptic function of SHANK proteins, but these remain poorly defined. In this study, we examined how SHANK2 can mediate electrophysiological, molecular, and behavioral effects by conditionally overexpressing either wild-type SHANK2A or the extrasynaptic SHANK2A(R462X) variant. SHANK2A overexpression affected pre- and postsynaptic targets and revealed a reversible, development-dependent autism spectrum disorder-like behavior. SHANK2A also mediated redistribution of Ca2+-permeable AMPA receptors between apical and basal hippocampal CA1 dendrites, leading to impaired synaptic plasticity in the basal dendrites. Moreover, SHANK2A overexpression reduced social interaction and increased the excitatory noise in the olfactory cortex during odor processing. In contrast, overexpression of the extrasynaptic SHANK2A(R462X) variant did not impair hippocampal synaptic plasticity, but still altered the expression of presynaptic/axonal signaling proteins. We also observed an attention-deficit/hyperactivity-like behavior and improved social interaction along with enhanced signal-to-noise ratio in cortical odor processing. Our results suggest that the disruption of pre- and postsynaptic SHANK2 functions caused by SHANK2 mutations has a strong impact on social behavior. These findings indicate that pre- and postsynaptic SHANK2 actions cooperate for normal neuronal function, and that an imbalance between these functions may lead to different neuropsychiatric disorders.

scholarly journals Frequency-preference response in covalent modification cycles under substrate sequestration conditions

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Juliana Reves Szemere ◽  
Horacio G. Rotstein ◽  
Alejandra C. Ventura
Keyword(s):  
Frequency Response ◽  
Covalent Modification ◽  
Protein Abundance ◽  
Dynamic Features ◽  
Signaling Systems ◽  
Low Pass ◽  
Low Pass Filters ◽  
Periodic Inputs ◽  
Preferred Frequency Response

AbstractCovalent modification cycles (CMCs) are basic units of signaling systems and their properties are well understood. However, their behavior has been mostly characterized in situations where the substrate is in excess over the modifying enzymes. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations, leading to substrate sequestration by the enzymes. In this enzyme-in-excess regime, CMCs have been shown to exhibit signal termination, the ability of the product to return to a stationary value lower than its peak in response to constant stimulation, while this stimulation is still active, with possible implications for the ability of systems to adapt to environmental inputs. We characterize the conditions leading to signal termination in CMCs in the enzyme-in-excess regime. We also demonstrate that this behavior leads to a preferred frequency response (band-pass filters) when the cycle is subjected to periodic stimulation, whereas the literature reports that CMCs investigated so far behave as low-pass filters. We characterize the relationship between signal termination and the preferred frequency response to periodic inputs and we explore the dynamic mechanism underlying these phenomena. Finally, we describe how the behavior of CMCs is reflected in similar types of responses in the cascades of which they are part. Evidence of protein abundance in vivo shows that enzymes and substrates are present in comparable concentrations, thus suggesting that signal termination and frequency-preference response to periodic inputs are also important dynamic features of cell signaling systems, which have been overlooked.

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