Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks

Short-term synaptic plasticity is modulated by long-term synaptic changes. There is, however, no general agreement on the computational role of this interaction. Here, we derive a learning rule for the release probability and the maximal synaptic conductance in a circuit model with combined recurrent and feedforward connections that allows learning to discriminate among natural inputs. Short-term synaptic plasticity thereby provides a nonlinear expansion of the input space of a linear classifier, whereas the random recurrent network serves to decorrelate the expanded input space. Computer simulations reveal that the twofold increase in the number of input dimensions through short-term synaptic plasticity improves the performance of a standard perceptron up to 100%. The distributions of release probabilities and maximal synaptic conductances at the capacity limit strongly depend on the balance between excitation and inhibition. The model also suggests a new computational interpretation of spikes evoked by stimuli outside the classical receptive field. These neuronal activities may reflect decorrelation of the expanded stimulus space by intracortical synaptic connections.

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Acute Exercise and Sustained Attention on Memory Function

American Journal of Health Behavior ◽

10.5993/ajhb.44.3.5 ◽

2020 ◽

Vol 44 (3) ◽

pp. 326-332

Author(s):

Audreaiona Waters ◽

Liye Zou ◽

Myungjin Jung ◽

Qian Yu ◽

Jingyuan Lin ◽

...

Keyword(s):

Neural Networks ◽

Sustained Attention ◽

Acute Exercise ◽

Short Term Memory ◽

Memory Function ◽

Long Term Memory ◽

Short Term ◽

Attention Task ◽

Term Memory

Objective: Sustained attention is critical for various activities of daily living, including engaging in health-enhancing behaviors and inhibition of health compromising behaviors. Sustained attention activates neural networks involved in episodic memory function, a critical cognition for healthy living. Acute exercise has been shown to activate these same neural networks. Thus, it is plausible that engaging in a sustained attention task and engaging in a bout of acute exercise may have an additive effect in enhancing memory function, which was the purpose of this experiment. Methods: 23 young adults (Mage = 20.7 years) completed 2 visits, with each visit occurring approximately 24 hours apart, in a counterbalanced order, including: (1) acute exercise with sustained attention, and (2) sustained attention only. Memory was assessed using a word-list paradigm and included a short- and long-term memory assessment. Sustained attention was induced via a sustained attention to response task (SART). Acute exercise involved a 15-minute bout of moderate-intensity exercise. Results: Short-term memory performance was significantly greater than long-term memory, Mdiff = 1.86, p < .001, and short-term memory for Exercise with Sustained Attention was significantly greater than short-term memory for Sustained Attention Only, Mdiff = 1.50, p = .01. Conclusion: Engaging in an acute bout of exercise before a sustained attention task additively influenced short-term memory function.

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Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i04.5831 ◽

2020 ◽

Vol 34 (04) ◽

pp. 4115-4122

Author(s):

Kyle Helfrich ◽

Qiang Ye

Keyword(s):

Neural Networks ◽

Unit Circle ◽

Recurrent Neural Networks ◽

Unit Disc ◽

Gradient Descent ◽

Short Term Memory ◽

Short Term ◽

Term Memory ◽

Gradient Descent Algorithm

Several variants of recurrent neural networks (RNNs) with orthogonal or unitary recurrent matrices have recently been developed to mitigate the vanishing/exploding gradient problem and to model long-term dependencies of sequences. However, with the eigenvalues of the recurrent matrix on the unit circle, the recurrent state retains all input information which may unnecessarily consume model capacity. In this paper, we address this issue by proposing an architecture that expands upon an orthogonal/unitary RNN with a state that is generated by a recurrent matrix with eigenvalues in the unit disc. Any input to this state dissipates in time and is replaced with new inputs, simulating short-term memory. A gradient descent algorithm is derived for learning such a recurrent matrix. The resulting method, called the Eigenvalue Normalized RNN (ENRNN), is shown to be highly competitive in several experiments.

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JNK1 contributes to metabotropic glutamate receptor-dependent long-term depression and short-term synaptic plasticity in the mice area hippocampal CA1

European Journal of Neuroscience ◽

10.1111/j.1460-9568.2006.05300.x ◽

2007 ◽

Vol 25 (2) ◽

pp. 391-396 ◽

Cited By ~ 45

Author(s):

Xin-Mei Li ◽

Chen-Chen Li ◽

Shan-Shan Yu ◽

Ju-Tao Chen ◽

Kanaga Sabapathy ◽

...

Keyword(s):

Synaptic Plasticity ◽

Glutamate Receptor ◽

Metabotropic Glutamate Receptor ◽

Short Term ◽

Long Term Depression ◽

Metabotropic Glutamate ◽

Hippocampal Ca1

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Towards simulations of long-term behavior of neural networks: Modeling synaptic plasticity of connections within and between human brain regions

Neurocomputing ◽

10.1016/j.neucom.2020.01.050 ◽

2020 ◽

Vol 416 ◽

pp. 38-44

Author(s):

Emmanouil Giannakakis ◽

Cheol E. Han ◽

Bernd Weber ◽

Frances Hutchings ◽

Marcus Kaiser

Keyword(s):

Neural Networks ◽

Synaptic Plasticity ◽

Human Brain ◽

Brain Regions ◽

Long Term Behavior

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Long-term depression of Aplysia sensorimotor synapses in cell culture: inductive role of a rise in postsynaptic calcium

Journal of Neurophysiology ◽

10.1152/jn.1996.76.3.2111 ◽

1996 ◽

Vol 76 (3) ◽

pp. 2111-2114 ◽

Cited By ~ 9

Author(s):

X. Y. Lin ◽

D. L. Glanzman

Keyword(s):

Cell Culture ◽

Synaptic Plasticity ◽

Sensory Neurons ◽

Tetraacetic Acid ◽

Short Term ◽

Long Term Depression ◽

Central Synapses ◽

Postsynaptic Calcium

1. Activation of sensory neurons at 2 Hz for 15 min induces long-term depression (LTD) of isolated Aplysia sensorimotor synapses in cell culture. 2. Prior infusion of the Ca2+ chelator 1,2-bis-(2-aminophenoxy)-ethane-N,N,N',N'-tetraacetic acid (BAPTA) into the postsynaptic motor neuron blocks the induction of LTD, but not short-term synaptic depression. 3. Invertebrate central synapses possess the capacity for LTD. This form of long-term synaptic plasticity may play an important role in learning in Aplysia.

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Physiological framework for adaptation of stomata to CO 2 from glacial to future concentrations

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2011.0270 ◽

2012 ◽

Vol 367 (1588) ◽

pp. 537-546 ◽

Cited By ~ 65

Author(s):

Peter J. Franks ◽

Ilia J. Leitch ◽

Elizabeth M. Ruszala ◽

Alistair M. Hetherington ◽

David J. Beerling

Keyword(s):

Leaf Surface ◽

Unit Area ◽

Leaf Gas Exchange ◽

Feedback Regulation ◽

Cell Nuclei ◽

Short Term ◽

Dna Amount ◽

Taxonomic Range ◽

Operational Range

In response to short-term fluctuations in atmospheric CO 2 concentration, c a , plants adjust leaf diffusive conductance to CO 2 , g c , via feedback regulation of stomatal aperture as part of a mechanism for optimizing CO 2 uptake with respect to water loss. The operational range of this elaborate control mechanism is determined by the maximum diffusive conductance to CO 2 , g c(max) , which is set by the size ( S ) and density (number per unit area, D ) of stomata on the leaf surface. Here, we show that, in response to long-term exposure to elevated or subambient c a , plants alter g c(max) in the direction of the short-term feedback response of g c to c a via adjustment of S and D . This adaptive feedback response to c a , consistent with long-term optimization of leaf gas exchange, was observed in four species spanning a diverse taxonomic range (the lycophyte Selaginella uncinata , the fern Osmunda regalis and the angiosperms Commelina communis and Vicia faba ). Furthermore, using direct observation as well as flow cytometry, we observed correlated increases in S , guard cell nucleus size and average apparent 1C DNA amount in epidermal cell nuclei with increasing c a , suggesting that stomatal and leaf adaptation to c a is linked to genome scaling.

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