神经元与认知
Temperature is one of the most relevant parameters for the regulation of intracellular processes. Measuring localized subcellular temperature gradients is fundamental for a deeper understanding of cell function, such as the genesis of…
In a recent article, Guo et al. [arXiv:2206.11228] report that adversarially trained neural representations in deep networks may already be as robust as corresponding primate IT neural representations. While we find the paper's primary…
Neuroimaging studies are often limited by the number of subjects and cognitive processes that can be feasibly interrogated. However, a rapidly growing number of neuroscientific studies have collectively accumulated an extensive wealth of…
In the domain of face recognition, there exists a puzzling timing discrepancy between results from macaque neurophysiology on the one hand and human electrophysiology on the other. Single unit recordings in macaques have demonstrated face…
Our ability to track multiple objects in a dynamic environment enables us to perform everyday tasks such as driving, playing team sports, and walking in a crowded mall. Despite more than three decades of literature on multiple object…
Artificial intelligence (AI) is a fast-growing field focused on modeling and machine implementation of various cognitive functions with an increasing number of applications in computer vision, text processing, robotics, neurotechnology,…
We show that the action potential signals generated inside axons are reaction-diffusion solitons or reaction-diffusion waves, refuting the Hodgkin and Huxley hypothesis that action potentials propagate along axons with an elastic wave…
This paper discusses a simple and explicit toy-model example of the categorical Hopfield equations introduced in previous work of Manin and the author. These describe dynamical assignments of resources to networks, where resources are…
Bayesian theories of biological and brain function speculate that Markov blankets (a conditional independence separating a system from external states) play a key role for facilitating inference-like behaviour in living systems. Although it…
The inverse Ising model is used in computational neuroscience to infer probability distributions of the synchronous activity of large neuronal populations. This method allows for finding the Boltzmann distribution with single neuron biases…
Neurons in the brain are wired into adaptive networks that exhibit a range of collective dynamics. Oscillations, for example, are paradigmatic synchronous patterns of neural activity with a defined temporal scale. Neuronal avalanches, in…
This article introduces a new methodology for reconstructing the white matter fiber pathways of brain in diffusion MRI. Usually, the signal intensity values will be lesser in the direction of higher diffusivity. The proposed approach picks…
Human brains lie at the core of complex neurobiological systems, where the neurons, circuits, and subsystems interact in enigmatic ways. Understanding the structural and functional mechanisms of the brain has long been an intriguing pursuit…
Brain Age (BA) estimation via Deep Learning has become a strong and reliable bio-marker for brain health, but the black-box nature of Neural Networks does not easily allow insight into the features of brain ageing.We trained a ResNet model…
The Reward Prediction Error hypothesis proposes that phasic activity in the midbrain dopaminergic system reflects prediction errors needed for learning in reinforcement learning. Besides the well-documented association between dopamine and…
Exploring and establishing artificial neural networks with electrophysiological characteristics and high computational efficiency is a popular topic in the field of computer vision. Inspired by the working mechanism of primary visual…
The purpose of this study is to develop a new methodology for designing stimulus sequences for cVEP BCI based on experimental studies regarding the behavior and the properties of the actual EEG responses of the visual system to coded visual…
Bibian et al. show in their recent paper (Bibi\'an et al. 2021) that eye and head movements can affect the EEG-based classification in a reaching motor task. These movements can generate artefacts that can cause an overoptimistic estimation…
Morphogenesis in the central nervous system has received intensive attention as elucidating fundamental mechanisms of morphogenesis will shed light on the physiology and pathophysiology of the developing central nervous system.…
The perspective-taking in social cognition is an ability that makes third-person judgments about the intentions, beliefs and thoughts of others. We aimed to investigate gender differences in the neural structure differences in (non)…