Does the brain behave like a (complex) network? I. Dynamics
D Papo, JM Buldú - Physics of Life Reviews, 2023 - Elsevier
Graph theory is now becoming a standard tool in system-level neuroscience. However,
endowing observed brain anatomy and dynamics with a complex network structure does not …
endowing observed brain anatomy and dynamics with a complex network structure does not …
Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity
Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity.
Variation of intrinsic timescales across the neocortex reflects functional specialization of …
Variation of intrinsic timescales across the neocortex reflects functional specialization of …
Machine learning at the mesoscale: a computation-dissipation bottleneck
A Ingrosso, E Panizon - Physical Review E, 2024 - APS
The cost of information processing in physical systems calls for a trade-off between
performance and energetic expenditure. Here we formulate and study a computation …
performance and energetic expenditure. Here we formulate and study a computation …
Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks
Recurrent neural networks (RNNs) in the brain and in silico excel at solving tasks with
intricate temporal dependencies. Long timescales required for solving such tasks can arise …
intricate temporal dependencies. Long timescales required for solving such tasks can arise …
Lattice physics approaches for neural networks
Modern neuroscience has evolved into a frontier field that draws on numerous disciplines,
resulting in the flourishing of novel conceptual frames primarily inspired by physics and …
resulting in the flourishing of novel conceptual frames primarily inspired by physics and …
Effect of Synaptic Heterogeneity on Neuronal Coordination
Recent advancements in measurement techniques have resulted in an increasing amount of
data on neural activities recorded in parallel, revealing largely heterogeneous correlation …
data on neural activities recorded in parallel, revealing largely heterogeneous correlation …
Collective behaviors of neural network regulated by the spatially distributed stimuli
Y Xie, W Huang, Y Jia, Z Ye, Y Wu - Physica A: Statistical Mechanics and its …, 2024 - Elsevier
Most external stimuli, including sound, temperature, and illumination, exhibit spatially
heterogeneous, and different amplitudes of the same signal are received by neurons at …
heterogeneous, and different amplitudes of the same signal are received by neurons at …
[HTML][HTML] Neural activity in quarks language: Lattice Field Theory for a network of real neurons
Brain–computer interfaces have seen extraordinary surges in developments in recent years,
and a significant discrepancy now exists between the abundance of available data and the …
and a significant discrepancy now exists between the abundance of available data and the …
Spatio-temporal transformers for decoding neural movement control
Deep learning tools applied to high-resolution neurophysiological data have significantly
progressed, offering enhanced decoding, real-time processing, and readability for practical …
progressed, offering enhanced decoding, real-time processing, and readability for practical …
Modular Growth of Hierarchical Networks: Efficient, General, and Robust Curriculum Learning
M Hamidi, S Khajehabdollahi, E Giannakakis… - … 2024: Proceedings of …, 2024 - direct.mit.edu
Structural modularity is a pervasive feature of biological neural networks, which have been
linked to several functional and computational advantages. Yet, the use of modular …
linked to several functional and computational advantages. Yet, the use of modular …