scholarly journals Mental Arithmetic Leads to Multiple Discrete Changes From Baseline in the Firing Patterns of Human Thalamic Neurons

2009 ◽  
Vol 101 (4) ◽  
pp. 2107-2119 ◽  
Author(s):  
J. H. Kim ◽  
S. Ohara ◽  
F. A. Lenz
Keyword(s):  
Mental Arithmetic ◽  
Spike Trains ◽  
Aminobutyric Acid ◽  
Type B ◽  
Interspike Intervals ◽  
Condition Versus ◽  
Inhibitory Postsynaptic Potentials ◽  
Low Threshold ◽  
Neuronal Spike Trains ◽  
Counting Condition

Primate thalamic action potential bursts associated with low-threshold spikes (LTS) occur during waking sensory and motor activity. We now test the hypothesis that different firing and LTS burst characteristics occur during quiet wakefulness (spontaneous condition) versus mental arithmetic (counting condition). This hypothesis was tested by thalamic recordings during the surgical treatment of tremor. Across all neurons and epochs, preburst interspike intervals (ISIs) were bimodal at median values, consistent with the duration of type A and type B γ-aminobutyric acid inhibitory postsynaptic potentials. Neuronal spike trains (117 neurons) were categorized by joint ISI distributions into those firing as LTS bursts (G, grouped), firing as single spikes (NG, nongrouped), or firing as single spikes with sporadic LTS bursting (I, intermediate). During the spontaneous condition (46 neurons) only I spike trains changed category. Overall, burst rates (BRs) were lower and firing rates (FRs) were higher during the counting versus the spontaneous condition. Spike trains in the G category sometimes changed to I and NG categories at the transition from the spontaneous to the counting condition, whereas those in the I category often changed to NG. Among spike trains that did not change category by condition, G spike trains had lower BRs during counting, whereas NG spike trains had higher FRs. BRs were significantly greater than zero for G and I categories during wakefulness (both conditions). The changes between the spontaneous and counting conditions are most pronounced for the I category, which may be a transitional firing pattern between the bursting (G) and relay modes of thalamic firing (NG).

scholarly journals Cellular and Network Models for Intrathalamic Augmenting Responses During 10-Hz Stimulation

1998 ◽  
Vol 79 (5) ◽  
pp. 2730-2748 ◽  
Author(s):  
Maxim Bazhenov ◽  
Igor Timofeev ◽  
Mircea Steriade ◽  
Terrence J. Sejnowski
Keyword(s):  
Network Model ◽  
Network Models ◽  
Ionic Currents ◽  
Repetitive Stimulation ◽  
Aminobutyric Acid ◽  
Single Pair ◽  
Inhibitory Postsynaptic Potentials ◽  
Low Threshold ◽  
Stimulation Of

Bazhenov, Maxim, Igor Timofeev, Mircea Steriade, and Terrence J. Sejnowski. Cellular and network models for intrathalamic augmenting responses during 10-Hz stimulation. J. Neurophysiol. 79: 2730–2748, 1998. Repetitive stimulation of the thalamus at7–14 Hz evokes responses of increasing amplitude in the thalamus and the areas of the neocortex to which the stimulated foci project. Possible mechanisms underlying the thalamic augmenting responses during repetitive stimulation were investigated with computer models of interacting thalamocortical (TC) and thalamic reticular (RE) cells. The ionic currents in these cells were modeled with Hodgkin-Huxley type of kinetics, and the results of the model were compared with in vivo thalamic recordings from decorticated cats. The simplest network model demonstrating an augmenting response was a single pair of coupled RE and TC cells, in which RE-induced inhibitory postsynaptic potentials (IPSPs) in the TC cell led to progressive deinactivation of a low-threshold Ca2+ current. The augmenting responses in two reciprocally interacting chains of RE and TC cells depended also on γ-aminobutyric acid-B (GABAB) IPSPs. Lateral GABAA inhibition between identical RE cells, which weakened bursts in these cells, diminished GABAB IPSPs and delayed the augmenting response in TC cells. The results of these simulations show that the interplay between existing mechanisms in the thalamus explains the basic properties of the intrathalamic augmenting responses.

Synthesis and Pharmacological Evaluation of Novel γ-Aminobutyric Acid Type B (GABAB) Receptor Agonists as Gastroesophageal Reflux Inhibitors

2008 ◽  
Vol 51 (14) ◽  
pp. 4315-4320 ◽  
Author(s):  
Christer Alstermark ◽  
Kosrat Amin ◽  
Sean R. Dinn ◽  
Thomas Elebring ◽  
Ola Fjellström ◽  
...  
Keyword(s):  
Gastroesophageal Reflux ◽  
Gabab Receptor ◽  
Aminobutyric Acid ◽  
Type B ◽  
Receptor Agonists ◽  
Pharmacological Evaluation ◽  
Acid Type

scholarly journals A convolutional neural network for estimating synaptic connectivity from spike trains

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daisuke Endo ◽  
Ryota Kobayashi ◽  
Ramon Bartolo ◽  
Bruno B. Averbeck ◽  
Yasuko Sugase-Miyamoto ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Generalized Linear Model ◽  
Simulated Data ◽  
Spike Trains ◽  
Synaptic Connectivity ◽  
Neuronal Circuits ◽  
Cortical Areas ◽  
Neuronal Spike Trains ◽  
Individual Dataset

AbstractThe recent increase in reliable, simultaneous high channel count extracellular recordings is exciting for physiologists and theoreticians because it offers the possibility of reconstructing the underlying neuronal circuits. We recently presented a method of inferring this circuit connectivity from neuronal spike trains by applying the generalized linear model to cross-correlograms. Although the algorithm can do a good job of circuit reconstruction, the parameters need to be carefully tuned for each individual dataset. Here we present another method using a Convolutional Neural Network for Estimating synaptic Connectivity from spike trains. After adaptation to huge amounts of simulated data, this method robustly captures the specific feature of monosynaptic impact in a noisy cross-correlogram. There are no user-adjustable parameters. With this new method, we have constructed diagrams of neuronal circuits recorded in several cortical areas of monkeys.

A Computational Model as Neurodecoder Based on Synchronous Oscillation in the Visual Cortex

2003 ◽  
Vol 15 (10) ◽  
pp. 2399-2418 ◽  
Author(s):  
Zhao Songnian ◽  
Xiong Xiaoyun ◽  
Yao Guozheng ◽  
Fu Zhi
Keyword(s):  
Visual Cortex ◽  
Computational Model ◽  
Visual Information ◽  
Spike Trains ◽  
Spike Timing ◽  
Contour Detection ◽  
System Level ◽  
Neuronal Spike ◽  
Neuronal Spike Trains ◽  
External Stimuli

Based on synchronized responses of neuronal populations in the visual cortex to external stimuli, we proposed a computational model consisting primarily of a neuronal phase-locked loop (NPLL) and multiscaled operator. The former reveals the function of synchronous oscillations in the visual cortex. Regardless of which of these patterns of the spike trains may be an average firing-rate code, a spike-timing code, or a rate-time code, the NPLL can decode original visual information from neuronal spike trains modulated with patterns of external stimuli, because a voltage-controlled oscillator (VCO), which is included in the NPLL, can precisely track neuronal spike trains and instantaneous variations, that is, VCO can make a copy of an external stimulus pattern. The latter, however, describes multi-scaled properties of visual information processing, but not merely edge and contour detection. In this study, in which we combined NPLL with a multiscaled operator and maximum likelihood estimation, we proved that the model, as a neurodecoder, implements optimum algorithm decoding visual information from neuronal spike trains at the system level. At the same time, the model also obtains increasingly important supports, which come from a series of experimental results of neurobiology on stimulus-specific neuronal oscillations or synchronized responses of the neuronal population in the visual cortex. In addition, the problem of how to describe visual acuity and multiresolution of vision by wavelet transform is also discussed. The results indicate that the model provides a deeper understanding of the role of synchronized responses in decoding visual information.

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