Attention - Wikipedia
In neuropsychology, attention is understood as a set of mechanisms by which sensory cues and internal goals modulate neuronal tuning and orient behavioral and cognitive processes.
Conscious Perception: Time for an Update?
Understanding the neural mechanism underlying subjective representation has become a central endeavor in cognitive-neuroscience. In theories of conscious perception, stimulus gaining conscious access is usually considered as a discrete neuronal event...
Linear Acceleration Is a Primary Risk Factor for Concussion
Rotational acceleration of the head has long been posited as the primary cause of concussion due to its ability to generate shear strains that disrupt neuronal structure and function [1,2]. Linear acceleration, by contrast, is considered less injurio...
NEURONAL Definition & Meaning - Merriam-Webster
: a grayish or reddish cell that is the basic working unit of the nervous system and has an axon and dendrites that carry nerve impulses.
NEURONAL Definition & Meaning - Merriam-Webster
: a grayish or reddish cell that is the basic working unit of the nervous system and has an axon and dendrites that carry nerve impulses.
NEURONAL Definition & Meaning - Merriam-Webster
: a grayish or reddish cell that is the basic working unit of the nervous system and has an axon and dendrites that carry nerve impulses.
Periodic Event-Triggered Boundary Control of Neuron Growth with Actuation at Soma
Exploring novel strategies for the regulation of axon growth, we introduce a periodic event-triggered control (PETC) to enhance the practical implementation of the associated PDE backstepping control law. Neurological injuries may impair neuronal fun...
Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb
The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system? Usin...
Chaotic and non-chaotic phases in experimental responses of a single neuron
Consistency and predictability of brain functionalities depend on reproducible activity of a single neuron. We identify a reproducible non-chaotic neuronal phase where deviations between concave response latency profiles of a single neuron do not inc...
Apuntes de Redes Neuronales Artificiales
These handouts are designed for people who is just starting involved with the topic artificial neural networks. We show how it works a single artificial neuron (McCulloch & Pitt model), mathematically and graphically. We do explain the delta rule, a...
Dynamics of Neural Networks with Continuous Attractors
We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stab...
Spontaneous Motion on Two-dimensional Continuous Attractors
Attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons. The firing rate profile, or the neuronal activity, is thought to carry information. Continuous attractor neural networks (CANNs) descri...
Criticality, stability, competition, and consolidation of new representations in brain net…
The brain forms and stores distributed representations from sparse external input that compete for neuronal resources with already stored memory traces. It is unclear what dynamical properties of neural systems allow formation and subsequent consolid...
Effects of a mixed reality headset on the delay of visually evoked potentials
Virtual and mixed reality (VR, MR) technologies offer a powerful solution for on-the-ground flight training curricula. While these technologies offer safer and cheaper instructional programs, it is still unclear how they impact neuronal brain dynamic...
A Quantitative Overview of Biophysical Forces Governing Neural Function
The Hodgkin-Huxley (HH) model is the currently accepted formalism of neuronal excitability. However, the HH model does not capture a number of biophysical behaviors associated with action potentials or propagating nerve impulses. Physical mechanisms...
Improving production process performance thanks to neuronal analysis
Product quality level is become a key factor for companies' competitiveness. A lot of time and money are required to ensure and guaranty it. Besides, motivated by the need of traceability, collecting production data is now commonplace in most compani...
Slow dynamics of neuronal excitability under pulse stimulation
Neurons fire irregularly on multiple timescales when stimulated with a periodic pulse train. This raises two questions: Does this irregularity imply significant intrinsic stochasticity? Can existing neuron models be readily extended to describe behav...
CAPE: Connectivity-Aware Path Enforcement Loss for Curvilinear Structure Delineation
Promoting the connectivity of curvilinear structures, such as neuronal processes in biomedical scans and blood vessels in CT images, remains a key challenge in semantic segmentation. Traditional pixel-wise loss functions, including cross-entropy and...
Three-dimensional alteration of neurites in schizophrenia
This paper reports nano-CT analysis of brain tissues of schizophrenia and control cases. The analysis revealed that: (1) neuronal structures vary between individuals, (2) the mean curvature of distal neurites of the schizophrenia cases was 1.5 times...
ModelDBRepository/257027
Circadian rhythmicity shapes astrocyte morphology and neuronal function in CA1 (McCauley et al 2020) (⭐ 1)
Complex transitions between spiking, bursting and silent regimes in a new memristive Rulko…
The Rulkov model, which simulates the behavior of biological neurons, is modified by replacing one of its control parameters with a memristive, sigmoid-type function of finite memory. This modification causes the parameter to vary according to the sy...
Neuronal Response Clamp
Since the first recordings made of evoked action potentials it has become apparent that the responses of individual neurons to ongoing physiologically relevant input, are highly variable. This variability is manifested in non-stationary behavior of p...
ShaoshiZ/PyHipp
Python code for analyzing neuronal data (⭐ 0)
mlech26l/ordinary_neural_circuits
Neuronal Circuit Policies (⭐ 41)
Neural development features: Spatio-temporal development of the Caenorhabditis elegans neu…
The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the...
NeuralEnsemble/neuroConstruct
neuroConstruct: biophysically detailed neuronal modelling in 3D (⭐ 52)
VMijangos/Redes_Neuronales
Repositorio del curso de Redes neuronales, en la Facultad de Ciencias, UNAM. (⭐ 31)
Neurodegenerative disease - Wikipedia
progressive loss of neurons, in the process known as neurodegeneration. Neuronal damage may also ultimately result in their death. Neurodegenerative diseases
Neuroplasticity - Wikipedia
1900s, the pioneering neuroscientist Santiago Ramón y Cajal used the term neuronal plasticity to describe nonpathological changes in the structure of adult
InoveAlumnos/redes_neuronales_python
Material de clase y ejercicios acerca de redes neuronales (⭐ 12)
NeuralEnsemble/PyNN
A Python package for simulator-independent specification of neuronal network models. (⭐ 301)
BlueBrain/NeuroM
Neuronal Morphology Analysis Tool (⭐ 108)
Healing the brain: hydrogels enable neuronal tissue growth
Points: 140 | Comments: 11 | Author: Tschayba
EPFL-LCN/neuronaldynamics-exercises
Python exercises accompanying the book "Neuronal Dynamics" (⭐ 277)
Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation
Spike sorting algorithms are used to separate extracellular recordings of neuronal populations into single-unit spike activities. The development of customized hardware implementing spike sorting algorithms is burgeoning. However, there is a lack of...
Inferring correlations associated to causal interactions in brain signals using autoregres…
The specific connectivity of a neuronal network is reflected in the dynamics of the signals recorded on its nodes. The analysis of how the activity in one node predicts the behaviour of another gives the directionality in their relationship. However,...
Control of seizure-like dynamics in neuronal populations with excitability adaptation rela…
We consider a heterogeneous, globally coupled population of excitatory quadratic integrate-and-fire neurons with excitability adaptation due to a metabolic feedback associated with ketogenic diet, a form of therapy for epilepsy. Bifurcation analysis...
A mathematical model of reward-mediated learning in drug addiction
Substances of abuse are known to activate and disrupt neuronal circuits in the brain reward system. We propose a simple and easily interpretable dynamical systems model to describe the neurobiology of drug addiction that incorporates the psychiatric...
Diversity and noise effects in a model of homeostatic regulation of the sleep-wake cycle
Recent advances in sleep neurobiology have allowed development of physiologically based mathematical models of sleep regulation that account for the neuronal dynamics responsible for the regulation of sleep-wake cycles and allow detailed examination...
A mathematical model of reward and executive circuitry in obsessive compulsive disorde
The neuronal circuit that controls obsessive and compulsive behaviors involves a complex network of brain regions (some with known involvement in reward processing). Among these are cortical regions, the striatum and the thalamus (which compose the C...