IEEE transactions on neural networks and learning systems
Oct 29, 2024
The brain's mystery for efficient and intelligent computation hides in the neuronal encoding, functional circuits, and plasticity principles in natural neural networks. However, many plasticity principles have not been fully incorporated into artific...
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image ...
Medical & biological engineering & computing
Oct 17, 2024
The counting and characterization of neurons in primary cultures have long been areas of significant scientific interest due to their multifaceted applications, ranging from neuronal viability assessment to the study of neuronal development. Traditio...
Advanced materials (Deerfield Beach, Fla.)
Oct 15, 2024
Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than the simple integrators commonly modeled in neuromorphic computing. A biological neuron can in fact efficiently perform Boolean algebra, including linea...
The development of biologically-inspired computational models has been the focus of study ever since the artificial neuron was introduced by McCulloch and Pitts in 1943. However, a scrutiny of literature reveals that most attempts to replicate the hi...
Mathematical neuroscience investigates how calcium distribution in nerve cells affects the neurological system. The interaction of numerous systems is necessary for the operation of several cellular processes in neuron cells, such as calcium, buffer,...
Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we ha...
Neural networks : the official journal of the International Neural Network Society
Sep 28, 2024
Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual syste...
Neural networks : the official journal of the International Neural Network Society
Sep 28, 2024
SNNs are gaining popularity in AI research as a low-power alternative in deep learning due to their sparse properties and biological interpretability. Using SNNs for dense prediction tasks is becoming an important research area. In this paper, we fir...
Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle su...