An extended SHESN with leaky integrator neuron and inhibitory connection for Mackey-Glass prediction

2011 ◽  
Author(s):  
Bo Yang ◽  
Zhidong Deng
Keyword(s):  
Inhibitory Connection ◽  
Leaky Integrator

scholarly journals Diagnostic Task Specific Activations in Functional MRI and Aberrant Connectivity of Insula with Middle Frontal Gyrus Can Inform the Differential Diagnosis of Psychosis

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 95
Author(s):  
Drozdstoy Stoyanov ◽  
Katrin Aryutova ◽  
Sevdalina Kandilarova ◽  
Rositsa Paunova ◽  
Zlatoslav Arabadzhiev ◽  
...  
Keyword(s):  
Effective Connectivity ◽  
Paranoid Schizophrenia ◽  
Indirect Evidence ◽  
Inhibitory Effect ◽  
Posterior Cingulate Cortex ◽  
Anterior Insula ◽  
Middle Frontal Gyrus ◽  
Angular Gyrus ◽  
Inhibitory Connection ◽  
Significant Difference

We constructed a novel design integrating the administration of a clinical self-assessment scale with simultaneous acquisition of functional Magnetic Resonance Imaging (fMRI), aiming at cross-validation between psychopathology evaluation and neuroimaging techniques. We hypothesized that areas demonstrating differential activation in two groups of patients (the first group exhibiting paranoid delusions in the context of paranoid schizophrenia—SCH—and second group with a depressive episode in the context of major depressive disorder or bipolar disorder—DEP) will have distinct connectivity patterns and structural differences. Fifty-one patients with SCH (n = 25) or DEP (n = 26) were scanned with three different MRI sequences: a structural and two functional sequences—resting-state and task-related fMRI (the stimuli represent items from a paranoid-depressive self-evaluation scale). While no significant differences were found in gray matter volumes, we were able to discriminate between the two clinical entities by identifying two significant clusters of activations in the SCH group—the left Precuneus (PreCu) extending to the left Posterior Cingulate Cortex (PCC) and the right Angular Gyrus (AG). Additionally, the effective connectivity of the middle frontal gyrus (MFG), a part of the Dorsolateral Prefrontal Cortex (DLPFC) to the Anterior Insula (AI), demonstrated a significant difference between the two groups with inhibitory connection demonstrated only in SCH. The observed activations of PreCu, PCC, and AG (involved in the Default Mode Network DMN) might be indirect evidence of the inhibitory connection from the DLPFC to AI, interfering with the balancing function of the insula as the dynamic switch in the DMN. The findings of our current study might suggest that the connectivity from DLPFC to the anterior insula can be interpreted as evidence for the presence of an aberrant network that leads to behavioral abnormalities, the manifestation of which depends on the direction of influence. The reduced effective connectivity from the AI to the DLPFC is manifested as depressive symptoms, and the inhibitory effect from the DLPFC to the AI is reflected in the paranoid symptoms of schizophrenia.

PHASE DEPENDENT TRANSITION BETWEEN MULTISTABLE STATES IN A NEURAL NETWORK WITH RECIPROCAL INHIBITION

2004 ◽  
Vol 14 (05) ◽  
pp. 1559-1575 ◽  
Author(s):  
KATSUMI TATENO ◽  
HIDEYUKI TOMONARI ◽  
HATSUO HAYASHI ◽  
SATORU ISHIZUKA
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Synaptic Input ◽  
Reciprocal Inhibition ◽  
Conduction Delay ◽  
Inhibitory Connection ◽  
Pacemaker Neurons ◽  
Excitatory Synaptic Input ◽  
Multistable State

We studied multistable oscillatory states of a small neural network model and switching of an oscillatory mode. In the present neural network model, two pacemaker neurons are reciprocally inhibited with conduction delay; one pacemaker neuron inhibits the other via an inhibitory nonpacemaker interneuron, and vice versa. The small network model shows bifurcations from quasi-periodic oscillation to chaos via period 3 with increase in the synaptic weight of the reciprocal inhibition. The route to chaos in the network model is different from that in the single pacemaker neuron. The network model exhibits several multistable states. In a regime of a weak inhibitory connection, in-phase beat, out-of-phase beat (period 3), and chaotic oscillation coexist at the multistable state. We can switch an oscillatory mode by an excitatory synaptic input to one of the pacemaker neurons through an afferent path. In a strong inhibitory connection regime, in-phase beat and out-of-phase beat (period 4) coexist at the multistable state. An excitatory synaptic input through the afferent path leads to the transition from the in-phase beat to the out-of-phase beat. The transition from the out-of-phase beat to the in-phase beat is induced by an inhibitory synaptic input via interneurons. A conduction delay, furthermore, causes the spontaneous transition from the in-phase beat to the out-of-phase beat. These transitions can be explained by phase response curves.

scholarly journals Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator

2019 ◽  
Author(s):  
Mariam Ordyan ◽  
Tom Bartol ◽  
Mary Kennedy ◽  
Padmini Rangamani ◽  
Terrence Sejnowski
Keyword(s):  
Long Term Potentiation ◽  
Time Averaging ◽  
Calcium Signals ◽  
Term Potentiation ◽  
High Calcium ◽  
Leaky Integrator ◽  
Voltage Dependent ◽  
High Calcium Concentration ◽  
Voltage Dependent Calcium Channels

AbstractCalmodulin-dependent kinase II (CaMKII) has long been known to play an important role in learning and memory as well as long term potentiation (LTP). More recently it has been suggested that it might be involved in the time averaging of synaptic signals, which can then lead to the high precision of information stored at a single synapse. However, the role of the scaffolding molecule, neurogranin (Ng), in governing the dynamics of CaMKII is not yet fully understood. In this work, we adopt a rule-based modeling approach through the Monte Carlo method to study the effect of Ca2+ signals on the dynamics of CaMKII phosphorylation in the postsynaptic density (PSD). Calcium surges are observed in synaptic spines during an EPSP and back-propagating action potential due to the opening of NMDA receptors and voltage dependent calcium channels. We study the differences between the dynamics of phosphorylation of CaMKII monomers and dodecameric holoenzymes. The scaffolding molecule Ng, when present in significant concentration, limits the availability of free calmodulin (CaM), the protein which activates CaMKII in the presence of calcium. We show that it plays an important modulatory role in CaMKII phosphorylation following a surge of high calcium concentration. We find a non-intuitive dependence of this effect on CaM concentration that results from the different affinities of CaM for CaMKII depending on the number of calcium ions bound to the former. It has been shown previously that in the absence of phosphatase CaMKII monomers integrate over Ca2+ signals of certain frequencies through autophosphorylation (Pepke et al, Plos Comp. Bio., 2010). We also study the effect of multiple calcium spikes on CaMKII holoenzyme autophosphorylation, and show that in the presence of phosphatase CaMKII behaves as a leaky integrator of calcium signals, a result that has been recently observed in vivo. Our models predict that the parameters of this leaky integrator are finely tuned through the interactions of Ng, CaM, CaMKII, and PP1. This is a possible mechanism to precisely control the sensitivity of synapses to calcium signals.

scholarly journals A sensory integration account for time perception

2020 ◽  
Author(s):  
Alessandro Toso ◽  
Arash Fassihi ◽  
Luciano Paz ◽  
Francesca Pulecchi ◽  
Mathew E. Diamond
Keyword(s):  
Time Perception ◽  
Time Constant ◽  
Sensory Integration ◽  
Neuronal Firing ◽  
Elapsed Time ◽  
Leaky Integrator ◽  
Long Time ◽  
Integrator Model ◽  
Short Time ◽  
Sense Of Touch

ABSTRACTThe connection between stimulus perception and time perception remains unknown. The present study combines human and rat psychophysics with sensory cortical neuronal firing to construct a computational model for the percept of elapsed time embedded within sense of touch. When subjects judged the duration of a vibration applied to the fingertip (human) or whiskers (rat), increasing stimulus mean speed led to increasing perceived duration. Symmetrically, increasing vibration duration led to increasing perceived intensity. We modeled spike trains from vibrissal somatosensory cortex as input to dual leaky integrators – an intensity integrator with short time constant and a duration integrator with long time constant – generating neurometric functions that replicated the actual psychophysical functions of rats. Returning to human psychophysics, we then confirmed specific predictions of the dual leaky integrator model. This study offers a framework, based on sensory coding and subsequent accumulation of sensory drive, to account for how a feeling of the passage of time accompanies the tactile sensory experience.

scholarly journals Sodium Channels Implement a Molecular Leaky Integrator to Sense Spiking Frequency and Regulate Neuronal Firing

2019 ◽  
Vol 116 (3) ◽  
pp. 388a
Author(s):  
Marco A. Navarro ◽  
Jenna Lin ◽  
Autoosa Salari ◽  
Mirela Milescu ◽  
Lorin S. Milescu
Keyword(s):  
Sodium Channels ◽  
Neuronal Firing ◽  
Leaky Integrator

An Evolutionary Ecological Approach to the Study of Learning Behavior Using a Robot-Based Model

2002 ◽  
Vol 10 (3-4) ◽  
pp. 201-221 ◽  
Author(s):  
Elio Tuci ◽  
Matt Quinn ◽  
Inman Harvey
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Behavioral Responses ◽  
Evolutionary Robotics ◽  
Ecological Models ◽  
Autonomous Learning ◽  
Ecological Approach ◽  
Learning Behavior ◽  
Leaky Integrator

We are interested in the construction of ecological models of the evolution of learning behavior using methodological tools developed in the field of evolutionary robotics. In this article, we explore the applicability of integrated (i.e., nonmodular) neural networks with fixed connection weights and simple 'leaky-integrator' neurons as controllers for autonomous learning robots. In contrast to Yamauchi and Beer (1994a), we show that such a control system is capable of integrating reactive and learned behaviour without explicitly needing hand-designed modules, dedicated to a particular behavior, or an externally introduced reinforcement signal. In our model, evolutionary and ecological contingencies structure the controller and the behavioral responses of the robot. This allows us to concentrate on examining the conditions under which learning behavior evolves.

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