scholarly journals Dendritic processing in the trigeminal motoneurons

2013 ◽  
Vol 19 (2) ◽  
pp. 198-199
Author(s):  
Shiro Nakamura ◽  
Ayako Mochizuki ◽  
Kiyomi Nakayama ◽  
Tomio Inoue
Keyword(s):  
Dendritic Processing ◽  
Trigeminal Motoneurons

Dual-mode dendritic devices enhanced neural network based on electrolyte gated transistors

2021 ◽  
Author(s):  
Zhaokun Jing ◽  
Yuchao Yang ◽  
Ru Huang
Keyword(s):  
Neural Network ◽  
Multilayer Perceptron ◽  
Back Propagation ◽  
Input Voltage ◽  
High Signal ◽  
Neuron Models ◽  
Dual Mode ◽  
Dendritic Processing ◽  
The Neural Networks ◽  
Processing Block

Abstract As a fundamental component of biological neurons, dendrites have been proven to have crucial effects in neuronal activities. Single neurons with dendrite structures show high signal processing capability that is analogous to a multilayer perceptron, whereas oversimplified point neuron models are still prevalent in AI algorithms and neuromorphic systems and fundamentally limit their efficiency and functionality of the systems constructed. In this study, we propose a dual-mode dendritic device based on electrolyte gated transistor, which can be operated to generate both supralinear and sublinear current-voltage responses when receiving input voltage pulses. We propose and demonstrate that the dual-mode dendritic devices can be used as a dendritic processing block between weight matrices and output neurons so as to enhance the expression ability of the neural networks. A dual-mode dendrites-enhanced neural network is therefore constructed with only two trainable parameters in the second layer, thus achieving 1000× reduction in the amount of second layer parameter compared to multilayer perceptron. After training by back propagation, the network reaches 90.1% accuracy in MNIST handwritten digits classification, showing advantage of the present dual-mode dendritic devices in building highly efficient neuromorphic computing.

Dendritic processing

2001 ◽  
Vol 11 (4) ◽  
pp. 415-422 ◽  
Author(s):  
T Euler
Keyword(s):  
Dendritic Processing

scholarly journals Dendrites enable a robust mechanism for neuronal stimulus selectivity

2015 ◽  
Author(s):  
Romain D. Cazé ◽  
Sarah Jarvis ◽  
Amanda J. Foust ◽  
Simon R. Schultz
Keyword(s):  
Spatial Distribution ◽  
Information Processing ◽  
Linear Model ◽  
Cortical Neurons ◽  
General Mechanism ◽  
Starting Point ◽  
Dendritic Processing ◽  
Non Linear ◽  
Equivalent Linear Model ◽  
Preferred Stimulus

AbstractHearing, vision, touch-underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Non-linear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does not exceed that of non-preferred stimuli. Using a multi-subunit non-linear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses. We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of synapses or dendrites loss than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites, that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially non-selective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.

Nonlinear dendritic processing determines angular tuning of barrel cortex neurons in vivo

Nature ◽  
2012 ◽  
Vol 490 (7420) ◽  
pp. 397-401 ◽  
Author(s):  
Maria Lavzin ◽  
Sophia Rapoport ◽  
Alon Polsky ◽  
Liora Garion ◽  
Jackie Schiller
Keyword(s):  
Barrel Cortex ◽  
Dendritic Processing

Strychnine blockade of the non-reciprocal inhibition of trigeminal motoneurons induced by stimulation of the parvocellular reticular formation

1991 ◽  
Vol 567 (2) ◽  
pp. 346-349 ◽  
Author(s):  
Pablo Castillo ◽  
Cristina Pedroarena ◽  
Michael H. Chase ◽  
Francisco R. Morales
Keyword(s):  
Reticular Formation ◽  
Reciprocal Inhibition ◽  
Trigeminal Motoneurons ◽  
Stimulation Of

Trigeminal premotor neurons in the bulbar parvocellular reticular formation participating in induction of rhythmical activity of trigeminal motoneurons by repetitive stimulation of the cerebral cortex in the guinea pig

1993 ◽  
Vol 69 (2) ◽  
pp. 595-608 ◽  
Author(s):  
S. Nozaki ◽  
A. Iriki ◽  
Y. Nakamura
Keyword(s):  
Cerebral Cortex ◽  
Reticular Formation ◽  
Field Potential ◽  
Repetitive Stimulation ◽  
Motoneuron Pool ◽  
Postsynaptic Potential ◽  
Rhythmical Activity ◽  
Premotor Neurons ◽  
Trigeminal Motoneurons ◽  
Stimulation Of

1. Single-unit activity was recorded from neurons in the bulbar parvocellular reticular formation (PCRF) dorsal and dorsolateral to the gigantocellular reticular nucleus near its caudal boundary, and the roles of these reticular neurons in induction of rhythmical activity of trigeminal motoneurons by repetitive stimulation of the cerebral cortex (the cortical masticatory area, CMA) were studied in the paralyzed guinea pig anesthetized with urethan or with ketamine and chlorpromazine. 2. One hundred nine PCRF neurons were activated antidromically by microstimulation in either the masseter (MA) or anterior digastric (AD) motoneuron pool in the ipsilateral trigeminal motor nucleus, and orthodromically by stimulation in the contralateral CMA. Repetitive CMA stimulation induced rhythmical burst activity in these PCRF neurons in association with the rhythmical field potential in the contralateral AD motoneuron pool induced by the same CMA stimulation. The burst was synchronous with the rhythmical AD field potential in 81 neurons, 44 and 37 of which responded antidromically to stimulation in the MA and AD motoneuron pools, respectively. The remaining 28 neurons antidromically responded to stimulation in the MA motoneuron pool, and their burst corresponded in time with the period between successive AD field potentials. 3. Spike-triggered averaging of the intracellular potentials of MA and AD motoneurons (MNs) by simultaneously recorded spontaneous spikes of the PCRF neurons, which showed rhythmical burst responses during the jaw-opening phase to repetitive CMA stimulation, revealed a monosynaptic inhibitory postsynaptic potential in MA.MNs in 12 of 34 tested pairs and a monosynaptic excitatory postsynaptic potential (EPSP) in AD.MNs in 14 of 26 tested pairs. An EPSP was also found in MA.MNs after a monosynaptic latency from triggering spikes in 11 of 37 tested PCRF neurons that showed burst activity during the jaw-closing phase. 4. We conclude that both excitatory and inhibitory premotor neurons projecting to MA.MNs as well as excitatory premotor neurons projecting to AD.MNs are located in the PCRF, and that these premotor neurons relay the output of the central rhythm generator for rhythmical jaw movements in the medial bulbar reticular formation to trigeminal motoneurons, and thus participate in induction of rhythmical activities of trigeminal motoneurons by repetitive CMA stimulation.

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