Results 51 to 60 of about 1,594,291 (128)

Study of a New Neuron [PDF]

arXiv, 1994
We study a modular neuron alternative to the McCulloch-Pitts neuron that arises naturally in analog devices in which the neuron inputs are represented as coherent oscillatory wave signals. Although the modular neuron can compute $XOR$ at the one neuron level, it is still characterized by the same Vapnik-Chervonenkis dimension as the standard neuron. We
arxiv  

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator [PDF]

arXiv, 2019
The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer allocations that individually measure in the millions of core hours. Supercomputer centers are transitioning to next generation
arxiv  

Excitation Dropout: Encouraging Plasticity in Deep Neural Networks

, 2019
We propose a guided dropout regularizer for deep networks based on the evidence of a network prediction defined as the firing of neurons in specific paths.
Bargal, Sarah Adel, Morerio, Pietro, Murino, Vittorio, Sclaroff, Stan, Zhang, Jianming, Zunino, Andrea   +5 more
core  

Precision microfluidic control of neuronal ensembles in cultured cortical networks [PDF]

arXiv
In vitro neuronal culture is an important research platform in cellular and network neuroscience. However, neurons cultured on a homogeneous scaffold form dense, randomly connected networks and display excessively synchronized activity; this phenomenon has limited their applications in network-level studies, such as studies of neuronal ensembles, or ...
arxiv  

Deciphering Functions of Neurons in Vision-Language Models [PDF]

arXiv
The burgeoning growth of open-sourced vision-language models (VLMs) has catalyzed a plethora of applications across diverse domains. Ensuring the transparency and interpretability of these models is critical for fostering trustworthy and responsible AI systems.
arxiv  

Using Single-Neuron Representations for Hierarchical Concepts as Abstractions of Multi-Neuron Representations [PDF]

arXiv
Brain networks exhibit complications such as noise, neuron failures, and partial synaptic connectivity. These can make it difficult to model and analyze their behavior. This paper describes a way to address this difficulty, namely, breaking down the models and analysis using levels of abstraction. We describe the approach for the problem of recognizing
arxiv  

Embodied Biocomputing Sequential Circuits with Data Processing and Storage for Neurons-on-a-chip [PDF]

arXiv
With conventional silicon-based computing approaching its physical and efficiency limits, biocomputing emerges as a promising alternative. This approach utilises biomaterials such as DNA and neurons as an interesting alternative to data processing and storage. This study explores the potential of neuronal biocomputing to rival silicon-based systems. We
arxiv  

On Relation-Specific Neurons in Large Language Models [PDF]

arXiv
In large language models (LLMs), certain neurons can store distinct pieces of knowledge learned during pretraining. While knowledge typically appears as a combination of relations and entities, it remains unclear whether some neurons focus on a relation itself -- independent of any entity. We hypothesize such neurons detect a relation in the input text
arxiv  

The Hypothalamic Medial Preoptic Area-Paraventricular Nucleus Circuit Modulates Depressive-Like Behaviors in a Mouse Model of Postpartum Depression. [PDF]

Research (Wash D C)
Fu P, Liu CP, Liu CY, Zhang YC, Xu JP, Mao RT, Ding XY, Li F, Zhang YL, Yang HL, Zhu JN, Zhang G, Jing J.   +12 more
europepmc   +1 more source

Functional Diversity of Serotonin Neurons in the Dorsal and Median Raphe Nuclei in Emotional Responses. [PDF]

Neuropsychopharmacol Rep
Ohmura Y, Nagayasu K.
europepmc   +1 more source