AIMC Topic: Nerve Net
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Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.
PLoS computational biology
Jan 23, 2023
How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary approaches to quantify the structure in connectivity. O...
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks.
Neuron
Jan 10, 2023
Neural activity is often described in terms of population-level factors extracted from the responses of many neurons. Factors provide a lower-dimensional description with the aim of shedding light on network computations. Yet, mechanistically, comput...
Evaluating the statistical similarity of neural network activity and connectivity via eigenvector angles.
Bio Systems
Nov 29, 2022
Neural systems are networks, and strategic comparisons between multiple networks are a prevalent task in many research scenarios. In this study, we construct a statistical test for the comparison of matrices representing pairwise aspects of neural ne...
Inferring Effective Connectivity Networks From fMRI Time Series With a Temporal Entropy-Score.
IEEE transactions on neural networks and learning systems
Oct 5, 2022
Inferring brain-effective connectivity networks from neuroimaging data has become a very hot topic in neuroinformatics and bioinformatics. In recent years, the search methods based on Bayesian network score have been greatly developed and become an e...
Maximum entropy models provide functional connectivity estimates in neural networks.
Scientific reports
Jun 10, 2022
Tools to estimate brain connectivity offer the potential to enhance our understanding of brain functioning. The behavior of neuronal networks, including functional connectivity and induced connectivity changes by external stimuli, can be studied usin...
How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase.
IEEE transactions on neural networks and learning systems
May 2, 2022
Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating biological functions of the human...
Binding events through the mutual synchronization of spintronic nano-neurons.
Nature communications
Feb 15, 2022
The brain naturally binds events from different sources in unique concepts. It is hypothesized that this process occurs through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented. ...
Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.
Nature communications
Feb 3, 2022
The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in "conjunction hu...
Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals.
PloS one
Jan 21, 2022
Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrat...
Percolation in networks with local homeostatic plasticity.
Nature communications
Jan 10, 2022
Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportati...
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