The structure of the axon-dendrite connections of neurons of the brain creates a rich spatial structure in which provided various combinations of signals surrounding neurons. Structure of dendritic trees and shape of dendritic spines allow repeatedly increase combinatorial component through cross synapses influence neighboring neurons. In this paper it is shown that the diffuse spreading of neurotransmitters allows neurons to detect and remember significant set of environmental activity patterns. As a core element fixation described extrasynaptic metabotropic receptive clusters. The described mechanism leads to the appearance of wave processes, based on the propagation of the front-line areas of spontaneous activity. In the proposed model, any compact pattern of neural activity is seen as a source emitting a diverging wave endogenous spikes. It is shown that the spike pattern of the wave front is strictly unique and uniquely defined pattern that started the wave. The propagation of waves with a unique pattern allows anywhere in nature undergoing brain wave patterns there to judge the whole brain processes information. In these assumptions naturally described mechanism of projection information between regions of the cortex. Performed computer simulations show the high effectiveness of such information model.
Brain-like Functional Organization within Large Language Models
School of Automation, Northwestern Polytechnical University（西北工业大学自动化学院）；School of Computing, University of Georgia（佐治亚大学计算学院）；School of Computer and Cyber Sciences, Augusta University（奥古斯塔大学计算机与网络科学学院）
Department of Electrical and Computer Engineering（电气与计算机工程系）
Neurons are individually translated into simple gates to plan a brain based on human psychology and intelligence. State machines, assumed previously learned in subconscious associative memory are shown to enable equation solving and rudimentary thinking using nanoprocessing within short term memory.
Fifty years ago, John von Neumann compared the architecture of the brain with that of computers that he invented and which is still in use today. In those days, the organisation of computers was based on concepts of brain organisation. Here, we give an update on current results on the global organisation of neural systems. For neural systems, we outline how the spatial and topological architecture of neuronal and cortical networks facilitates robustness against failures, fast processing, and balanced network activation. Finally, we discuss mechanisms of self-organization for such architectures…
There is no agreed definition of intelligence, so it is problematic to simply ask whether brains, swarms, computers, or other systems are intelligent or not. To compare the potential intelligence exhibited by different cognitive systems, I use the common approach used by artificial intelligence and artificial life: Instead of studying the substrate of systems, let us focus on their organization. This organization can be measured with information. Thus, I apply an informationist epistemology to describe cognitive systems, including brains and computers. This allows me to frame the usefulness an…
Shared representations in brains and models reveal a two-route cortical organization during scene perception
Department of Cognition, Development and Education Psychology, Faculty of Psychology, University of Barcelona（认知、发展与教育心理学系，心理学学院，巴塞罗那大学）；Institute of Neurosciences, University of Barcelona（神经科学研究所，巴塞罗那大学）；Bellvitge Institute for Biomedical Research（Bellvitge生物医学研究 institute）
The algorithm of brain learning and memory is still undetermined. The backpropagation algorithm of artificial neural networks was thought not suitable for brain cortex, and there is a lack of algorithm for memory engram. We designed a brain version of backpropagation algorithm, which are biologically plausible and could be implemented with virtual neurons to complete image classification task. An encoding algorithm that can automatically allocate engram cells is proposed, which is an algorithm implementation for memory engram theory, and could simulate how hippocampus achieve fast associative …
Working memory is a cognitive process that is responsible for temporarily holding and manipulating information. Most of the empirical neuroscience research on working memory has focused on measuring sustained activity in prefrontal cortex (PFC) and/or parietal cortex during simple delayed-response tasks, and most of the models of working memory have been based on neural integrators. But working memory means much more than just holding a piece of information online. We describe a new theory of working memory, based on a recurrent neural circuit that we call ORGaNICs (Oscillatory Recurrent GAted…
A Miniature Brain Transformer: Thalamic Gating, Hippocampal Lateralization, Amygdaloid Salience, and Prefrontal Working Memory in Attention-Coupled Latent Memory
Department of Computer Information Engineering（计算机信息工程系）
Rate-Coding Bundle Memory: A Unified Model of Memory and Control for Symbolic Computation in the Brain
Max Planck Institute for Psycholinguistics（马克斯·普朗克心理语言学研究所）；Donders Institute for Brain, Cognition and Behaviour（唐德斯大脑、认知与行为研究所）；Radboud University（拉德堡德大学）
ETIS Lab, UMR8051, CY Cergy Paris University, ENSEA, CNRS（ETIS实验室，UMR8051，塞尔吉巴黎大学，ENSEA，法国国家科学研究中心）
In order to keep trace of information and grow up, the infant brain has to resolve the problem about where old information is located and how to index new ones. We propose that the immature prefrontal cortex (PFC) use its primary functionality of detecting hierarchical patterns in temporal signals as a second purpose to organize the spatial ordering of the cortical networks in the developing brain itself. Our hypothesis is that the PFC detects the hierarchical structure in temporal sequences in the form of ordinal patterns and use them to index information hierarchically in different parts of …
Unveiling and Steering Connectome Organization with Interpretable Latent Variables
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University（国家多媒体信息处理重点实验室，计算机科学学院，北京大学）；School of Computer Science and Engineering, University of Electronic Science and Technology of China（计算机科学与工程学院，电子科学与技术大学）
Hierarchical Memory Organization for Wikipedia Generation
School of Computer Science, Peking University（北京大学计算机科学学院）；National Key Laboratory for Multimedia Information Processing, Peking University（北京大学多媒体信息处理国家重点实验室）；Huawei Noah’s Ark Lab（华为诺亚实验室）
Brain science and artificial intelligence have made great progress toward the understanding and engineering of the human mind. The progress has accelerated significantly since the turn of the century thanks to new methods for probing the brain (both structure and function), and rapid development in deep learning research. However, despite these new developments, there are still many open questions, such as how to understand the brain at the system level, and various robustness issues and limitations of deep learning. In this informal essay, I will talk about some of the concepts that are centr…
We consider the problem of finding good finite-horizon policies for POMDPs under the expected reward metric. The policies considered are {em free finite-memory policies with limited memory}; a policy is a mapping from the space of observation-memory pairs to the space of action-memeory pairs (the policy updates the memory as it goes), and the number of possible memory states is a parameter of the input to the policy-finding algorithms. The algorithms considered here are preliminary implementations of three search heuristics: local search, simulated annealing, and genetic algorithms. We compare…
Filesystem-Based Memory for LLM Agents: Organization, Evolution, and Sustainability
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of California, San Diego（加利福尼亚大学圣迭戈分校）；University of California, Merced（加利福尼亚大学默塞德分校）；Adobe Research（奥多比研究院）；Texas A&M University（德克萨斯农工大学）
Ludwig Maximilian University of Munich（路德维希·马克西米利安慕尼黑大学）；Siemens（西门子）
We analyse perception and memory, using mathematical models for knowledge graphs and tensors, to gain insights into the corresponding functionalities of the human mind. Our discussion is based on the concept of propositional sentences consisting of \textit{subject-predicate-object} (SPO) triples for expressing elementary facts. SPO sentences are the basis for most natural languages but might also be important for explicit perception and declarative memories, as well as intra-brain communication and the ability to argue and reason. A set of SPO sentences can be described as a knowledge graph, w…
The New School for Social Research（社会研究新学院）；University of Canterbury（坎特伯雷大学）
Within the scientific research community, memory information in the brain is commonly believed to be stored in the synapse - a hypothesis famously attributed to psychologist Donald Hebb. However, there is a growing minority who postulate that memory is stored inside the neuron at the molecular (RNA or DNA) level - an alternative postulation known as the cell-intrinsic hypothesis, coined by psychologist Randy Gallistel. In this paper, we review a selection of key experimental evidence from both sides of the argument. We begin with Eric Kandel's studies on sea slugs, which provided the first evi…
We present a unified computational theory of an agent's perception and memory. In our model, perception, episodic memory, and semantic memory are realized by different operational modes of the oscillating interactions between a symbolic index layer and a subsymbolic representation layer. The two layers form a bilayer tensor network (BTN). Although memory appears to be about the past, its main purpose is to support the agent in the present and the future. Recent episodic memory provides the agent with a sense of the here and now. Remote episodic memory retrieves relevant past experiences to pro…
Self-Clustering Graph Transformer Approach to Model Resting-State Functional Brain Activity
Georgia State University（佐治亚州立大学）；Tri-Institutional Center for Translational Research in Neuroimaging and Data Science（三方神经成像与数据科学转化研究中心）；Georgia Institute of Technology（佐治亚理工学院）
VoiceMem: Streaming Dual-Brain Memory for Real-Time Interaction
Nanyang Technological University（南洋理工大学）；National University of Singapore（新加坡国立大学）；Tsinghua University（清华大学）；The Chinese University of Hong Kong（香港中文大学）
A remarkable capacity of the brain is its ability to autonomously reorganize memories during offline periods. Memory replay, a mechanism hypothesized to underlie biological offline learning, has inspired offline methods for reducing forgetting in artificial neural networks in continual learning settings. A memory-efficient and neurally-plausible method is generative replay, which achieves state of the art performance on continual learning benchmarks. However, unlike the brain, standard generative replay does not self-reorganize memories when trained offline on its own replay samples. We propos…
