The time-elapsed model for neural assemblies is a nonlinear age-structured equation where the renewal term describes the network activity and influences the discharge rate, possibly with a delay due to the length of connections. We first solve a long...
Relevant prospective moments arise intermittently, while most of the time is filled with irrelevant events, or noise, that constantly bombard our sensory systems. Thus, anticipating a few key moments necessitates disregarding what lies between the pr...
BACKGROUNDBlood donation increases the risk of iron deficiency, but its effect on brain iron, myelination, and neurocognition remains unclear.METHODSThis ancillary study enrolled 67 iron-deficient blood donors, 19-73 years of age, participating in a ...
Artificial and biological agents are unable to learn given completely random and unstructured data. The structure of data is encoded in the distance or similarity relationships between data points. In the context of neural networks, the neuronal acti...
The inherently constrained regenerative capacity of neuronal tissue poses a major obstacle to repairing traumatic brain injury. While neural stem cell transplantation holds promise, its efficacy is constrained by slow and inefficient neuronal differe...
Continuous bump attractor networks (CBANs) are a prevailing model for how neural circuits represent continuous variables. CBANs maintain these representations by temporally integrating inputs that encode differential (i.e., incremental) changes to a ...
Brains evolve within specific sensory and physical environments, yet neuroscience has traditionally focused on studying neural circuits in isolation. Understanding of their function requires integrative brain-body testing in realistic contexts. To in...
To improve the computational efficiency of olfactory neural network, this paper proposes a multithreading-based parallel computing method. Firstly, focusing on the olfactory neural network and its neuronal equations, this paper analyzes and compares ...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Oct 8, 2025
The integration of multiple sensory inputs is essential for human perception and action in uncertain environments. This process includes reference frame transformations as different sensory signals are encoded in different coordinate systems. Studies...
Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain's information coding via discrete voltage spikes. However, it remains unclear how both art...
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