Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior
Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or
inputs from other brain regions. To avoid misinterpreting temporally structured inputs as …
inputs from other brain regions. To avoid misinterpreting temporally structured inputs as …
[HTML][HTML] Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling
Spatiotemporal properties of neuronal population activity in cortical motor areas have been
subjects of experimental and theoretical investigations, generating numerous interpretations …
subjects of experimental and theoretical investigations, generating numerous interpretations …
Causal connectivity measures for pulse-output network reconstruction: Analysis and applications
ZK Tian, K Chen, S Li… - Proceedings of the …, 2024 - National Acad Sciences
The causal connectivity of a network is often inferred to understand network function. It is
arguably acknowledged that the inferred causal connectivity relies on the causality measure …
arguably acknowledged that the inferred causal connectivity relies on the causality measure …
Dynamical Differential Covariance based Brain Network for Motor Intent Recognition
R Fu, Y Du, S Wang, G Wen, J Chen… - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
In the field of motor imagery (MI) recognition based on electroencephalogram (EEG),
complex network-based analysis of brain connectivity has gained significant attention …
complex network-based analysis of brain connectivity has gained significant attention …
Dynamic Brain Networks with Prescribed Functional Connectivity
In this paper, we consider stable stochastic linear systems modeling whole-brain resting-
state dynamics. We parametrize the state matrix of the system (effective connectivity) in …
state dynamics. We parametrize the state matrix of the system (effective connectivity) in …
Information-transfer characteristics in network motifs
Information processing in biological systems is realized by the appropriate transmission of
information flows over complex networks, such as gene regulatory, signal transduction, and …
information flows over complex networks, such as gene regulatory, signal transduction, and …
A General Framework for Characterizing Optimal Communication in Brain Networks
Communication in brain networks is the foundation of cognitive function and behavior. A
multitude of evolutionary pressures, including the minimization of metabolic costs while …
multitude of evolutionary pressures, including the minimization of metabolic costs while …
Estimating effective connectivity in neural networks: comparison of derivative-based and correlation-based methods
N Laasch, W Braun, L Knoff, J Bielecki, CC Hilgetag - bioRxiv, 2024 - biorxiv.org
Inferring and understanding the underlying connectivity structure of a system solely from the
observed activity of its constituent components is a challenge in many areas of science. In …
observed activity of its constituent components is a challenge in many areas of science. In …
On the Rotational Structure in Neural Data
Spatiotemporal properties of the activity of neuronal populations in cortical motor areas have
been the subject of many experimental and theoretical investigations, which generated …
been the subject of many experimental and theoretical investigations, which generated …
Scalable covariance-based connectivity inference for synchronous neuronal networks
We present a novel method for inferring connectivity from large-scale neuronal networks
with synchronous activity. Our approach leverages Dynamic Differential Covariance to …
with synchronous activity. Our approach leverages Dynamic Differential Covariance to …