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The hippocampal formation is thought to learn spatial maps of environments, and in many models this learning process consists of forming a sensory association for each location in the environment. This is inefficient, akin to learning a…

人工智能 · 计算机科学 2021-07-02 Marcus Lewis

Electroencephalography (EEG) foundation models hold significant promise for universal Brain-Computer Interfaces (BCIs). However, existing approaches often rely on end-to-end fine-tuning and exhibit limited efficacy under frozen-probing…

机器学习 · 计算机科学 2026-03-20 Jiquan Wang , Sha Zhao , Yangxuan Zhou , Yiming Kang , Shijian Li , Gang Pan

High-dimensional neural activity often reside in a low-dimensional subspace, referred to as neural manifolds. Grid cells in the medial entorhinal cortex provide a periodic spatial code that are organized near a toroidal manifold,…

神经元与认知 · 定量生物学 2025-10-22 Yuxing Jared Yao , Iris H. R. Yoon

Several problems in neuroimaging and beyond require inference on the parameters of multi-task sparse hierarchical regression models. Examples include M/EEG inverse problems, neural encoding models for task-based fMRI analyses, and climate…

The hippocampus supports spatial navigation by encoding cognitive maps through collective place cell activity. We model the place cell population as non-negative spatial embeddings derived from the spectral decomposition of multi-step…

神经元与认知 · 定量生物学 2025-10-28 Minglu Zhao , Dehong Xu , Deqian Kong , Wen-Hao Zhang , Ying Nian Wu

Occupancy grids encode for hot spots on a map that is represented by a two dimensional grid of disjoint cells. The problem is to recursively update the probability that each cell in the grid is occupied, based on a sequence of sensor…

信号处理 · 电气工程与系统科学 2020-07-13 Christopher Robbiano , Edwin K. P. Chong , Mahmood R. Azimi-Sadjadi , Louis L. Scharf , Ali Pezeshki

Space is represented in the mammalian brain by the activity of hippocampal place cells as well as in their spike-timing correlations. Here we propose a theory how this temporal code is transformed to spatial firing rate patterns via…

神经元与认知 · 定量生物学 2017-08-02 Mauro M. Monsalve-Mercado , Christian Leibold

Hippocampal cognitive map---a neuronal representation of the spatial environment---is broadly discussed in the computational neuroscience literature for decades. More recent studies point out that hippocampus plays a major role in producing…

神经元与认知 · 定量生物学 2017-10-18 Andrey Babichev , Yuri Dabaghian

Cognitive maps are a proposed concept on how the brain efficiently organizes memories and retrieves context out of them. The entorhinal-hippocampal complex is heavily involved in episodic and relational memory processing, as well as spatial…

神经元与认知 · 定量生物学 2024-01-04 Paul Stoewer , Achim Schilling , Andreas Maier , Patrick Krauss

Grid cells in the dorsolateral band of the medial entorhinal cortex(dMEC) display strikingly regular periodic firing patterns on a lattice of positions in 2-D space. This helps animals to encode relative spatial location without reference…

神经元与认知 · 定量生物学 2021-11-10 Yuduo Zhi , Daniel L. Cox

Behavioral flexibility is learning from previous experiences and planning appropriate actions in a changing or novel environment. Successful behavioral adaptation depends on internal models the brain builds to represent the relational…

神经元与认知 · 定量生物学 2021-07-01 Linda Q. Yu , Seongmin A. Park , Sarah C. Sweigart , Erie D. Boorman , Matthew R. Nassar

About a decade ago grid cells were discovered in the medial entorhinal cortex of rat. Their peculiar firing patterns, which correlate with periodic locations in the environment, led to early hypothesis that grid cells may provide some form…

神经元与认知 · 定量生物学 2018-10-18 Jochen Kerdels , Gabriele Peters

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of "grid fields" in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values…

神经元与认知 · 定量生物学 2019-03-13 Louis Kang , Vijay Balasubramanian

The paper describes a program which computes the best possible Bayesian model of 3D space from vision (in bees) or echo location (in bats), at Marrs [1982] Level 2. The model exploits the strong Bayesian prior probability that most other…

神经元与认知 · 定量生物学 2024-05-16 Robert Worden

A central question in multimodal neuroimaging analysis is to understand the association between two imaging modalities and to identify brain regions where such an association is statistically significant. In this article, we propose a…

统计方法学 · 统计学 2024-11-28 Moyan Li , Lexin Li , Jian Kang

Traditional methods for spatial inference estimate smooth interpolating fields based on features measured at well-located points. When the spatial locations of some observations are missing, joint inference of the fields and locations is…

Grid cells in medial entorhinal cortex are believed to play a key role in path integration. However, the relation between path integration and the grid-like arrangement of their firing field remains unclear. We provide theoretical evidence…

神经与进化计算 · 计算机科学 2016-06-06 Reza Moazzezi

The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space---a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long…

神经元与认知 · 定量生物学 2017-10-10 Andrey Babichev , Dmitriy Morozov , Yuri Dabaghian

We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces…

We develop a new methodology for determining the location and dynamics of brain activity from combined magnetoencephalography (MEG) and electroencephalography (EEG) data. The resulting inverse problem is ill-posed and is one of the most…

应用统计 · 统计学 2019-07-23 Yin Song , Farouk S. Nathoo , Arif Babul