In this paper we explain the strikingly regular activity of the 'grid' cells in rodent dorsal medial entorhinal cortex (dMEC) and the spatially localized activity of the hippocampal place cells in CA3 and CA1 by assuming that the hippocampal region is constructed to support an internal dynamical model of the sensory information. The functioning of the different areas of the hippocampal-entorhinal loop and their interaction are derived from a set of information theoretical principles. We demonstrate through simple transformations of the stimulus representations that the double form of space representation (i.e. place field and regular grid tiling) can be seen as a computational 'by-product' of the circuit. In contrast to other theoretical or computational models we can also explain how place and grid activity may emerge at the respective areas simultaneously. In accord with recent views, our results point toward a close relation between the formation of episodic memory and spatial navigation.
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 spike-timing-dependent synaptic plasticity. The resulting dynamics of synaptic weights resembles well-known pattern formation models in which a lateral inhibition mechanism gives rise to a Turing instability. We identify parameter regimes in which hexagonal firing patterns develop as they have been found in medial entorhinal cortex.
During sleep, the hippocampus recapitulates neuronal patterns corresponding to behavioral trajectories during previous experiences. This hippocampal replay supports the formation of long-term memories. Yet, whether replay originates within the hippocampal circuitry or is initiated by extrahippocampal inputs is unknown. Here, I review recent findings regarding the organization of neuronal activity upstream to the hippocampus, in the head-direction (HD) and grid cell networks. I argue that hippocampal activity is under the influence of primary spatial signals, which originate from subcortical st…
Fudan University（复旦大学）；Beijing Normal University（北京师范大学）
The entorhinal-hippocampal circuit plays a critical role in higher brain functions, especially spatial cognition. Grid cells in the medial entorhinal cortex (MEC) periodically fire with different grid spacing and orientation, which makes a contribution that place cells in the hippocampus can uniquely encode locations in an environment. But how sparse firing granule cells in the dentate gyrus are formed from grid cells in the MEC remains to be determined. Recently, the fruit fly olfactory circuit provides a variant algorithm (called locality-sensitive hashing) to solve this problem. To investig…
Fourier-like summation of several grid cell modules with different spatial frequencies in the medial entorhinal cortex (MEC) has long been proposed to form the contours of place firing fields. Recent experiments largely, but not completely, support this theory. Place fields are obviously expanded by inactivation of dorsal MEC, which fits the hypothesis. However, contrary to the prediction, inactivation of ventral MEC is also weakly broaden the spatial place firing patterns. In this study, we derive the model from grid spatial frequencies represented by Gaussian profiles to a 1D place field by …
University of Oxford（牛津大学）；Stanford University（斯坦福大学）；University College London（伦敦大学学院）
Many deep neural network architectures loosely based on brain networks have recently been shown to replicate neural firing patterns observed in the brain. One of the most exciting and promising novel architectures, the Transformer neural network, was developed without the brain in mind. In this work, we show that transformers, when equipped with recurrent position encodings, replicate the precisely tuned spatial representations of the hippocampal formation; most notably place and grid cells. Furthermore, we show that this result is no surprise since it is closely related to current hippocampal…
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 of metric for space. Subsequent research has since uncovered a wealth of new insights into the characteristics of grid cells and their neural neighborhood, the parahippocampal-hippocampal region, calling for a revision and refinement of earlier grid cell models. This survey paper aims to provide a comprehensive summary of grid cell research published in the …
Grid cells play a principal role in enabling mammalian cognitive representations of ambient environments. The key property of these cells -- the regular arrangement of their firing fields -- is commonly viewed as means for establishing spatial scales or encoding specific locations. However, using grid cells' spiking outputs for deducing spatial orderliness proves to be a strenuous task, due to fairly irregular activation patterns triggered by the animal's sporadic visits to the grid fields. The following discussion addresses statistical mechanisms enabling emergent regularity of grid cell firi…
University of Oxford（牛津大学）；University College London（伦敦大学学院）
A central problem to understanding intelligence is the concept of generalisation. This allows previously learnt structure to be exploited to solve tasks in novel situations differing in their particularities. We take inspiration from neuroscience, specifically the hippocampal-entorhinal system known to be important for generalisation. We propose that to generalise structural knowledge, the representations of the structure of the world, i.e. how entities in the world relate to each other, need to be separated from representations of the entities themselves. We show, under these principles, arti…
Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological perturbation on in vitro networks of hippocampal neurons that has been shown to increase synaptic str…
Research on network mechanisms and coding properties of grid cells assume that the firing rate of a grid cell in each of its fields is the same. Furthermore, proposed network models predict spatial regularities in the firing of inhibitory interneurons that are inconsistent with experimental data. In this paper, by analyzing the response of grid cells recorded from rats during free navigation, we first show that there are strong variations in the mean firing rate of the fields of individual grid cells and thus show that the data is inconsistent with the theoretical models that predict similar p…
Lattices abound in nature - from the crystal structure of minerals to the honey-comb organization of ommatidia in the compound eye of insects. Such regular arrangements provide solutions for optimally dense packings, efficient resource distribution and cryptographic schemes, highlighting the importance of lattice theory in mathematics and physics, biology and economics, and computer science and coding theory. Do lattices also play a role in how the brain represents information? To answer this question, we focus on higher-dimensional stimulus domains, with particular emphasis on neural represen…
The grid cells (GCs) of the medial entorhinal cortex (MEC) and place cells (PCs) of the hippocampus are key elements of the brain network for the metric representation of space. Currently, any of the existing theoretical models can explain all aspects of GC-specific spatially selective patterns of activity. It is also not clear how these patterns are formed during the network development. On the other hand, it was previously shown that the network that can learn to extract high principal components from the activity of the place cells could provide the basis for GC-like activity patterns devel…
University of Arizona（亚利桑那大学）；University of California, Berkeley（加州大学伯克利分校）
Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that form a periodic and hexagonal tiling of the environment. The joint activity of grid and place cell populations, as a function of location, forms a neural code for space. An ensemble of codes is generated by varying grid and place cell population parameters. For each code in this ensemble, codewords are generated by stimulating a network with a discrete set …
CANNs: A Toolkit for Research on Continuous Attractor Neural Networks
School of Psychological and Cognitive Sciences, Peking–Tsinghua Center for Life Sciences, PKU-IDG/McGovern Institute for Brain Research, Center of Quantitative Biology（心理与认知科学学院，北京清华大学生命科学中心，北京大学IDG/麦克戈文脑科学研究院，定量生物学中心）
