Journal of Computational Neuroscience 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.Analysis of hippocampal local field potentials by diffusion mapped delay coordinates
AbstractSpatial navigation through novel spaces and to known goal locations recruits multiple integrated structures in the mammalian brain. Within this extended network, the hippocampus enables formation and retrieval of cognitive spatial maps and contributes to decision making at choice points. Exploration and navigation to known goal locations produce synchronous activity of hippocampal neurons resulting in rhythmic oscillation events in local networks. Power of specific oscillatory frequencies and numbers of these events recorded in local field potentials correlate with distinct cognitive aspects of spatial navigation. ...
Source: Journal of Computational Neuroscience - April 6, 2024 Category: Neuroscience Source Type: research
A mean-field model of gamma-frequency oscillations in networks of excitatory and inhibitory neurons
AbstractGamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and a mean-field model. At the network level, we consider two different mechanisms to generate gamma oscillations and show that they are best seen if one takes into account the synaptic delay between neurons. At the mean-field level, we show that, by introducing delays, the mean-field can also produce gamma oscillations. The mean-field matches the mean...
Source: Journal of Computational Neuroscience - March 21, 2024 Category: Neuroscience Source Type: research
A voltage-based Event-Timing-Dependent Plasticity rule accounts for LTP subthreshold and suprathreshold for dendritic spikes in CA1 pyramidal neurons
AbstractLong-term potentiation (LTP) is a synaptic mechanism involved in learning and memory. Experiments have shown that dendritic sodium spikes (Na-dSpikes) are required for LTP in the distal apical dendrites of CA1 pyramidal cells. On the other hand, LTP in perisomatic dendrites can be induced by synaptic input patterns that can be both subthreshold and suprathreshold for Na-dSpikes. It is unclear whether these results can be explained by one unifying plasticity mechanism. Here, we show in biophysically and morphologically realistic compartmental models of the CA1 pyramidal cell that these forms of LTP can be fully acco...
Source: Journal of Computational Neuroscience - March 12, 2024 Category: Neuroscience Source Type: research
Neural waves and computation in a neural net model I: Convolutional hierarchies
AbstractThe computational resources of a neuromorphic network model introduced earlier are investigated in the context of such hierarchical systems as the mammalian visual cortex. It is argued that a form of ubiquitous spontaneous local convolution, driven by spontaneously arising wave-like activity —which itself promotes local Hebbian modulation—enables logical gate-like neural motifs to form into hierarchical feed-forward structures of the Hubel-Wiesel type. Extra-synaptic effects are shown to play a significant rôle in these processes. The type of logic that emerges is not Boolean, conf irming and extending earlier...
Source: Journal of Computational Neuroscience - February 21, 2024 Category: Neuroscience Source Type: research
Ion-concentration gradients induced by synaptic input increase the voltage depolarization in dendritic spines
AbstractThe vast majority of excitatory synaptic connections occur on dendritic spines. Due to their extremely small volume and spatial segregation from the dendrite, even moderate synaptic currents can significantly alter ionic concentrations. This results in chemical potential gradients between the dendrite and the spine head, leading to measurable electrical currents. In modeling electric signals in spines, different formalisms were previously used. While the cable equation is fundamental for understanding the electrical potential along dendrites, it only considers electrical currents as a result of gradients in elect...
Source: Journal of Computational Neuroscience - February 13, 2024 Category: Neuroscience Source Type: research
A biophysically comprehensive model of urothelial afferent neurons: implications for sensory signalling in urinary bladder
AbstractThe urothelium is the innermost layer of the bladder wall; it plays a pivotal role in bladder sensory transduction by responding to chemical and mechanical stimuli. The urothelium also acts as a physical barrier between urine and the outer layers of the bladder wall. There is intricate sensory communication between the layers of the bladder wall and the neurons that supply the bladder, which eventually translates into the regulation of mechanical activity. In response to natural stimuli, urothelial cells release substances such as ATP, nitric oxide (NO), substance P, acetylcholine (ACh), and adenosine. These act on...
Source: Journal of Computational Neuroscience - February 12, 2024 Category: Neuroscience Source Type: research
On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks
AbstractOverall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We...
Source: Journal of Computational Neuroscience - October 14, 2023 Category: Neuroscience Source Type: research
A fractional-order Wilson-Cowan formulation of cortical disinhibition
AbstractThis work presents a fractional-order Wilson-Cowan model derivation under Caputo ’s formalism, considering an order of\(0<\alpha \le 1\). To that end, we propose memory-dependent response functions and average neuronal excitation functions that permit us to naturally arrive at a fractional-order model that incorporates past dynamics into the description of synaptically coupled neuronal populations ’ activity. We then shift our focus on a particular example, aiming to analyze the fractional-order dynamics of the disinhibited cortex. This system mimics cortical activity observed during neurological disorders...
Source: Journal of Computational Neuroscience - October 3, 2023 Category: Neuroscience Source Type: research
Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification
AbstractSpiking neural networks (SNNs), as the third generation of neural networks, are based on biological models of human brain neurons. In this work, a shallow SNN plays the role of an explicit image decoder in the image classification. An LSTM-based EEG encoder is used to construct the EEG-based feature space, which is a discriminative space in viewpoint of classification accuracy by SVM. Then, the visual feature vectors extracted from SNN is mapped to the EEG-based discriminative features space by manifold transferring based on mutual k-Nearest Neighbors (Mk-NN MT). This proposed “Brain-guided system” improves the...
Source: Journal of Computational Neuroscience - September 18, 2023 Category: Neuroscience Source Type: research
Optimization of ictal aborting stimulation using the dynamotype taxonomy
AbstractElectrical stimulation is an increasingly popular method to terminate epileptic seizures, yet it is not always successful. A potential reason for inconsistent efficacy is that stimuli are applied empirically without considering the underlying dynamical properties of a given seizure. We use a computational model of seizure dynamics to show that different bursting classes have disparate responses to aborting stimulation. This model was previously validated in a large set of human seizures and led to a description of the Taxonomy of Seizure Dynamics and the dynamotype, which is the clinical analog of the bursting clas...
Source: Journal of Computational Neuroscience - September 5, 2023 Category: Neuroscience Source Type: research
A high-efficiency model indicating the role of inhibition in the resilience of neuronal networks to damage resulting from traumatic injury
AbstractRecent investigations of traumatic brain injuries have shown that these injuries can result in conformational changes at the level of individual neurons in the cerebral cortex. Focal axonal swelling is one consequence of such injuries and leads to a variable width along the cell axon. Simulations of the electrical properties of axons impacted in such a way show that this damage may have a nonlinear deleterious effect on spike-encoded signal transmission. The computational cost of these simulations complicates the investigation of the effects of such damage at a network level. We have developed an efficient algorith...
Source: Journal of Computational Neuroscience - August 26, 2023 Category: Neuroscience Source Type: research
The method for assessment of local permutations in the glomerular patterns of the rat olfactory bulb by aligning interindividual odor maps
AbstractThe comparison of odor functional maps in rodents demonstrates a high degree of inter-individual variability in glomerular activity patterns. There are substantial methodological difficulties in the interindividual assessment of local permutations in the glomerular patterns, since the position of anatomical extracranial landmarks, as well as the size, shape and angular orientation of olfactory bulbs can vary significantly. A new method for defining anatomical coordinates of active glomeruli in the rat olfactory bulb has been developed. The method compares the interindividual odor functional maps and calculates prob...
Source: Journal of Computational Neuroscience - August 25, 2023 Category: Neuroscience Source Type: research
Exploring weight initialization, diversity of solutions, and degradation in recurrent neural networks trained for temporal and decision-making tasks
AbstractRecurrent Neural Networks (RNNs) are frequently used to model aspects of brain function and structure. In this work, we trained small fully-connected RNNs to perform temporal and flow control tasks with time-varying stimuli. Our results show that different RNNs can solve the same task by converging to different underlying dynamics and also how the performance gracefully degrades as either network size is decreased, interval duration is increased, or connectivity damage is induced. For the considered tasks, we explored how robust the network obtained after training can be according to task parameterization. In the p...
Source: Journal of Computational Neuroscience - August 10, 2023 Category: Neuroscience Source Type: research
Homogeneous inhibition is optimal for the phase precession of place cells in the CA1 field
AbstractPlace cells are hippocampal neurons encoding the position of an animal in space. Studies of place cells are essential to understanding the processing of information by neural networks of the brain. An important characteristic of place cell spike trains is phase precession. When an animal is running through the place field, the discharges of the place cells shift from the ascending phase of the theta rhythm through the minimum to the descending phase. The role of excitatory inputs to pyramidal neurons along the Schaffer collaterals and the perforant pathway in phase precession is described, but the role of local int...
Source: Journal of Computational Neuroscience - July 5, 2023 Category: Neuroscience Source Type: research
Correction to: Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
(Source: Journal of Computational Neuroscience)
Source: Journal of Computational Neuroscience - June 26, 2023 Category: Neuroscience Source Type: research
