scholarly journals Modeling of human reaction selection following the arrival of an event in the brain

2021 ◽  
Author(s):  
hind ZAARAOUI
Keyword(s):  
Motor Neurons ◽  
Action Potentials ◽  
Path Integrals ◽  
Total Deformation ◽  
Incoming Information ◽  
Excitatory Neurotransmitters ◽  
Information Event ◽  
Receptor Neurons ◽  
Temporal And Spatial ◽  
The Brain

This work proposes a mathematical model about how a reaction is created in the human brain in responseto a particular incoming Information/Event using quantum mechanics and more precisely path integrals theory.The set of action potentials created in a particular neuron N2 is a result of temporal and spatial summationof the signals coming from different neighboring neurons Nx with different dendrite-paths. Each dendritepathof N2 is assumed to be determined by its respective synapse with its neurotransmitters and therefore tohave its particular action S due to its respective neurotransmitters types (excitatory or inhibitory) and etc. Anexternal incoming signal information being initially modulated by recepetor neurons (in eyes, ears...) travelsthrough the neighboring neurons that are linked to the excited receptor neurons. A potential reaction responsesare subsequently created thanks to a final deformed signal in the motor neurons by all the correlated neuralpaths. The total deformation at each neuron is created by different incoming dendrite-paths and their structures(inhibitory or excitatory neurotransmitters and their type), and of course the existence or not of the signal andits frequency coming from each path. Using path Integrals theory, we compute the probability of existence ofthe signal-Information or the potential reaction to the incoming information at each neuron. In this paper wecompute how much the signal-Information has been distorted between two neighboring linked neural pointsincluding if it arrives or not to the neigboring neurons. We propose an Information entropy similar to Shannonone and we demonstrate that this entropy is equivalent to timespace curvature in the Brain.

scholarly journals The equivalence Spacetime curvature - Information wave function Entropy: a link between quantum mechanics and general relativity in Universe and Brain

2021 ◽  
Author(s):  
hind ZAARAOUI
Keyword(s):  
Field Theory ◽  
Quantum Physics ◽  
Path Integrals ◽  
Quantum Field ◽  
Spacetime Curvature ◽  
Incoming Information ◽  
Information Wave Function ◽  
Curvature Information ◽  
The Brain ◽  
The Universe

Our work consists on showing that the Spacetime curvature introduced by Einstein in the Universe and also in the Brain is a result of the Information Entropy of different quantum Paths of elementary particles (leptons, bosons…) of path integrals model. We started by seeing the structure of how the incoming information is processed and then propagated in the brain and how the latter is deformed in each neuron to thus create a potential reaction response distorted or not. In quantum physics, and particularly in quantum field theory (QFT), the paths in path integrals have an equivalent role to paths between two neighboring linked neurons (synapses + neurotransmitters + dendrites). Using this modeling, we prove mathematically that the entropy of the Information coming from the paths could be equivalent to the Spacetime curvature in Universe as in Brain

Sol-Gel Optical Sensors for Glutamate

2000 ◽  
Vol 662 ◽  
Author(s):  
Jenna L. Rickus ◽  
Esther Lan ◽  
Allan J. Tobin ◽  
Jeffery I. Zink ◽  
Bruce Dunn
Keyword(s):  
Optical Sensors ◽  
Sol Gel ◽  
Kinetic Studies ◽  
Excitatory Neurotransmitter ◽  
Nadh Fluorescence ◽  
Millisecond Time Scale ◽  
Temporal And Spatial ◽  
Sensor Detection ◽  
The Brain ◽  
Amino Acid Glutamate

AbstractThe amino acid glutamate is the major excitatory neurotransmitter used in the nervous system for interneuronal communication. It is used throughout the brain by various neuronal pathways including those involved in learning and memory, locomotion, and sensory perception. Because glutamate is released from neurons on a millisecond time scale into sub-micrometer spaces, the development of a glutamate biosensor with high temporal and spatial resolution is of great interest for the study of neurological function and disease. Here, we demonstrate the feasibility of an optical glutamate sensor based on the sol-gel encapsulation of the enzyme glutamate dehydrogenase (GDH). GDH catalyses the oxidative deamination of glutamate and the reduction of NAD+ to NADH. NADH fluorescence is the basis of the sensor detection. Thermodynamic and kinetic studies show that GDH remains active in the sol-gel matrix and that the reaction rate is correlated to the glutamate concentration.

scholarly journals Müllerian inhibiting substance contributes to sex-linked biases in the brain and behavior

2009 ◽  
Vol 106 (17) ◽  
pp. 7203-7208 ◽  
Author(s):  
Pei-Yu Wang ◽  
Anna Protheroe ◽  
Andrew N. Clarkson ◽  
Floriane Imhoff ◽  
Kyoko Koishi ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Reproductive Tract ◽  
Behavioral Traits ◽  
Spinal Motor Neurons ◽  
Müllerian Inhibiting Substance ◽  
Males And Females ◽  
Brain And Behavior ◽  
And Behavior ◽  
The Brain ◽  
Mullerian Inhibiting Substance

Many behavioral traits and most brain disorders are common to males and females but are more evident in one sex than the other. The control of these subtle sex-linked biases is largely unstudied and has been presumed to mirror that of the highly dimorphic reproductive nuclei. Sexual dimorphism in the reproductive tract is a product of Müllerian inhibiting substance (MIS), as well as the sex steroids. Males with a genetic deficiency in MIS signaling are sexually males, leading to the presumption that MIS is not a neural regulator. We challenge this presumption by reporting that most immature neurons in mice express the MIS-specific receptor (MISRII) and that male Mis−/− and Misrii−/− mice exhibit subtle feminization of their spinal motor neurons and of their exploratory behavior. Consequently, MIS may be a broad regulator of the subtle sex-linked biases in the nervous system.

Ephaptic Coupling in Hybrid Neuronal Model

2021 ◽  
Author(s):  
Gabriel Moreno Cunha ◽  
Gilberto Corso ◽  
José Garcia Vivas Miranda ◽  
Gustavo Zampier Dos Santos Lima
Keyword(s):  
Electric Fields ◽  
Action Potentials ◽  
Population Vector ◽  
Input Stimulus ◽  
Circular Statistic ◽  
Coupling Behavior ◽  
The Impact ◽  
The Brain ◽  
Ephaptic Coupling ◽  
Phase Differences

Abstract In recent decades, there has been growing interest in the impact of electric fields generated in the brain. Transmembrane ionic currents originate electric fields in the extracellular space and are capable of affecting nearby neurons, a phenomenon called ephaptic neuronal communication. In the present work, the Quadratic Integrate-and-Trigger model (QIF-E) underwent an adjustment/improvement to include the ephaptic coupling behavior between neurons and their results are compared to the empirical results. In this way, the analysis tools are employed according to the neuronal activity regime: (i) for the subthreshold regime, the circular statistic is used to describe the phase differences between the input stimulus signal and the modeled membrane response; (ii) in the suprathreshold regime, the Population Vector and the Spike Field Coherence are employed to estimate phase preferences and the coupling intensity between the input stimulus and the Action Potentials. The results observed are i) in the subthreshold regime the values of the phase differences change with distinct frequencies of an input stimulus; ii) in the supra-threshold regime the preferential phase of Action Potentials changes for different frequencies. In addition, we explore other parameters of the model, such as noise and membrane characteristic-time, in order to understand different types of neurons and extracellular environment related to ephaptic communication. Such results are consistent with results observed in empirical experiments based on ephaptic coupling behavior. In addition, the QIF-E model allows further studies on the physiological importance of ephaptic coupling in the brain, and its simplicity can open a door to simulating ephaptic coupling in neuron networks and evaluating the impact of ephaptic communication in such scenarios.

scholarly journals Apical length governs computational diversity of L5 pyramidal neurons

2019 ◽  
Author(s):  
Alessandro R. Galloni ◽  
Aeron Laffere ◽  
Ede Rancz
Keyword(s):  
Action Potentials ◽  
Pyramidal Neurons ◽  
Apical Dendrite ◽  
Common Assumption ◽  
Dendritic Excitability ◽  
Visual Cortices ◽  
The Common ◽  
Channel Dependent ◽  
Apical Dendrites ◽  
The Brain

AbstractAnatomical similarity across the neocortex has led to the common assumption that the circuitry is modular and performs stereotyped computations. Layer 5 pyramidal neurons (L5PNs) in particular are thought to be central to cortical computation because of their extensive arborisation and nonlinear dendritic operations. Here, we demonstrate that computations associated with dendritic Ca2+ plateaus in L5PNs vary substantially between the primary and secondary visual cortices. L5PNs in the secondary visual cortex show reduced dendritic excitability and smaller propensity for burst firing. This reduced excitability is correlated with shorter apical dendrites. Using numerical modelling, we uncover a universal principle underlying the influence of apical length on dendritic backpropagation and excitability, based on a Na+ channel-dependent broadening of backpropagating action potentials. In summary, we provide new insights into the modulation of dendritic excitability by apical dendrite length and show that the operational repertoire of L5 neurons is not universal throughout the brain.

scholarly journals The current state of electrocorticography-based brain–computer interfaces

2020 ◽  
Vol 49 (1) ◽  
pp. E2 ◽  
Author(s):  
Kai J. Miller ◽  
Dora Hermes ◽  
Nathan P. Staff
Keyword(s):  
Functional Limitations ◽  
Brain Computer Interfaces ◽  
Brain Surface ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Current State ◽  
Temporal And Spatial ◽  
Direct Feedback ◽  
The Brain ◽  
Lateral Sclerosis

Brain–computer interfaces (BCIs) provide a way for the brain to interface directly with a computer. Many different brain signals can be used to control a device, varying in ease of recording, reliability, stability, temporal and spatial resolution, and noise. Electrocorticography (ECoG) electrodes provide a highly reliable signal from the human brain surface, and these signals have been used to decode movements, vision, and speech. ECoG-based BCIs are being developed to provide increased options for treatment and assistive devices for patients who have functional limitations. Decoding ECoG signals in real time provides direct feedback to the patient and can be used to control a cursor on a computer or an exoskeleton. In this review, the authors describe the current state of ECoG-based BCIs that are approaching clinical viability for restoring lost communication and motor function in patients with amyotrophic lateral sclerosis or tetraplegia. These studies provide a proof of principle and the possibility that ECoG-based BCI technology may also be useful in the future for assisting in the cortical rehabilitation of patients who have suffered a stroke.

scholarly journals Identification and Research of Adhd and Healthy Controls using Fmri

2019 ◽  
Vol 8 (6S) ◽  
pp. 370-372
Keyword(s):  
Brain Regions ◽  
Healthy Controls ◽  
Hyperactivity Disorder ◽  
Network Activation ◽  
Healthy Control ◽  
Temporal And Spatial ◽  
The Individual ◽  
The Brain ◽  
Coronal View

Analyzing the brain regions for different activations corresponding to the activation input for an experimental setup of task functional MRI or a resting state functional Magnetic Resonance Imaging(fMRI) for a diagnosed or healthy control is a challenging issue as the processing data is voluminous 4D data with nearly 1,51,552 voxels for a single volume of 261 scans fMRI. The data considered for analysis consists of 10 healthy controls and 10 Attention Deficit Hyperactivity Disorder(ADHD) fMRI. The workflow starts with preprocessing the individual scan for realignment, coregistration and Normalisation to Montreal Neurological Institute (MNI) space. Single site scan visit consists of 64x64x37 voxels. Seventy independent components are obtained from processed data by data reduction, Independent Component Analysis (ICA) calculation, Back reconstruction and Component Calibration. ICA performs satisfactorily well on temporal and spatial localization. Visual medial network activation is pronounced in ADHD Controls than in healthy people. Sagittal, Axial and Coronal view of ADHD controls is obtained as component number 42.The analysis is further used for the automatic classification of healthy controls and ADHD people.

Forward Dendritic Spikes

2011 ◽  
pp. 42-59
Author(s):  
Oscar Herreras ◽  
Julia Makarova ◽  
José Manuel Ibarz
Keyword(s):  
Action Potentials ◽  
Remarkable Property ◽  
Synaptic Inputs ◽  
Brain Circuits ◽  
Voltage Dependent ◽  
Dendritic Spikes ◽  
Underlying Mechanisms ◽  
The Brain ◽  
Made In

Neurons send trains of action potentials to communicate each other. Different messages are issued according to varying inputs, but they can also mix them up in a multiplexed language transmitted through a single cable, the axon. This remarkable property arises from the capability of dendritic domains to work semi autonomously and even decide output. We review the underlying mechanisms and theoretical implications of the role of voltage-dependent dendritic currents on the forward transmission of synaptic inputs, with special emphasis in the initiation, integration and forward conduction of dendritic spikes. When these spikes reach the axon, output decision was made in one of many parallel dendritic substations. When failed, they still serve as an internal language to transfer information between dendritic domains. This notion brakes with the classic view of neurons as the elementary units of the brain and attributes them computational/storage capabilities earlier billed to complex brain circuits.

scholarly journals Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth

2019 ◽  
Vol 16 (157) ◽  
pp. 20190246 ◽  
Author(s):  
Marie Levakova ◽  
Lubomir Kostal ◽  
Christelle Monsempès ◽  
Philippe Lucas ◽  
Ryota Kobayashi
Keyword(s):  
Olfactory Receptor ◽  
Time Course ◽  
Olfactory Receptor Neuron ◽  
Receptor Activation ◽  
Olfactory Receptor Neurons ◽  
Response Dynamics ◽  
Spike Threshold ◽  
Olfactory Stimuli ◽  
Receptor Neurons ◽  
The Brain

In order to understand how olfactory stimuli are encoded and processed in the brain, it is important to build a computational model for olfactory receptor neurons (ORNs). Here, we present a simple and reliable mathematical model of a moth ORN generating spikes. The model incorporates a simplified description of the chemical kinetics leading to olfactory receptor activation and action potential generation. We show that an adaptive spike threshold regulated by prior spike history is an effective mechanism for reproducing the typical phasic–tonic time course of ORN responses. Our model reproduces the response dynamics of individual neurons to a fluctuating stimulus that approximates odorant fluctuations in nature. The parameters of the spike threshold are essential for reproducing the response heterogeneity in ORNs. The model provides a valuable tool for efficient simulations of olfactory circuits.

scholarly journals Diabetes Mellitus-Related Dysfunction of the Motor System

2020 ◽  
Vol 21 (20) ◽  
pp. 7485
Author(s):  
Ken Muramatsu
Keyword(s):  
Motor Control ◽  
Motor Neurons ◽  
Motor System ◽  
Corticospinal Tract ◽  
Experimental Studies ◽  
Sensory System ◽  
Treatment Strategies ◽  
Motor Deficits ◽  
New Perspective ◽  
The Brain

Although motor deficits in humans with diabetic neuropathy have been extensively researched, its effect on the motor system is thought to be lesser than that on the sensory system. Therefore, motor deficits are considered to be only due to sensory and muscle impairment. However, recent clinical and experimental studies have revealed that the brain and spinal cord, which are involved in the motor control of voluntary movement, are also affected by diabetes. This review focuses on the most important systems for voluntary motor control, mainly the cortico-muscular pathways, such as corticospinal tract and spinal motor neuron abnormalities. Specifically, axonal damage characterized by the proximodistal phenotype occurs in the corticospinal tract and motor neurons with long axons, and the transmission of motor commands from the brain to the muscles is impaired. These findings provide a new perspective to explain motor deficits in humans with diabetes. Finally, pharmacological and non-pharmacological treatment strategies for these disorders are presented.

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