Representation of objects in space by two classes of hippocampal pyramidal cells

Humans can recognize and navigate in a room when its contents have been rearranged. Rats also adapt rapidly to movements of objects in a familiar environment. We therefore set out to investigate the neural machinery that underlies this capacity by further investigating the place cell-based map of the surroundings found in the rat hippocampus. We recorded from single CA1 pyramidal cells as rats foraged for food in a cylindrical arena (the room) containing a tall barrier (the furniture). Our main finding is a new class of cells that signal proximity to the barrier. If the barrier is fixed in position, these cells appear to be ordinary place cells. When, however, the barrier is moved, their activity moves equally and thereby conveys information about the barrier's position relative to the arena. When the barrier is removed, such cells stop firing, further suggesting they represent the barrier. Finally, if the barrier is put into a different arena where place cell activity is changed beyond recognition ("remapping"), these cells continue to discharge at the barrier. We also saw, in addition to barrier cells and place cells, a small number of cells whose activity seemed to require the barrier to be in a specific place in the environment. We conclude that barrier cells represent the location of the barrier in an environment-specific, place cell framework. The combined place + barrier cell activity thus mimics the current arrangement of the environment in an unexpectedly realistic fashion.     

海马位置细胞对空间信息的处理

海马位置细胞接收各种来源的空间信息后,可对这些信息进行加工处理,在海马内形成认知地图或加强联合皮层内细胞集群的突触联系以形成对空间位置的永久记忆。海马内的空间信息输出后,在伏核（nucleus accumbens,NAC）。内与其它来源的信息进行整合,最终通过运动环路形成目标指向性行为。     

Hippocampal Theta-Gamma Coupling Reflects State-Dependent Information Processing in Decision Making

1. Download high-res image (205KB)
2. Download full-size image

     

Vasoactive Intestinal Polypeptide-Expressing Interneurons in the Hippocampus Support Goal-Oriented Spatial Learning

Download video (115MB)Help with mp4 files     

The development of spatial behaviour and the hippocampal neural representation of space

The role of the hippocampal formation in spatial cognition is thought to be supported by distinct classes of neurons whose firing is tuned to an organism''s position and orientation in space. In this article, we review recent research focused on how and when this neural representation of space emerges during development: each class of spatially tuned neurons appears at a different age, and matures at a different rate, but all the main spatial responses tested so far are present by three weeks of age in the rat. We also summarize the development of spatial behaviour in the rat, describing how active exploration of space emerges during the third week of life, the first evidence of learning in formal tests of hippocampus-dependent spatial cognition is observed in the fourth week, whereas fully adult-like spatial cognitive abilities require another few weeks to be achieved. We argue that the development of spatially tuned neurons needs to be considered within the context of the development of spatial behaviour in order to achieve an integrated understanding of the emergence of hippocampal function and spatial cognition.     

Refinement and Reactivation of a Taste-Responsive Hippocampal Network

1. Download : Download high-res image (124KB)
2. Download : Download full-size image

     

Temporal Sequence Compression by an Integrate-and-Fire Model of Hippocampal Area CA3

Cells in the rat hippocampus fire as a function of the animal's location in space. Thus, a rat moving through the world produces a statistically reproducible sequence of place cell firings. With this perspective, spatial navigation can be viewed as a sequence learning problem for the hippocampus. That is, learning entails associating the relationships among a sequence of places that are represented by a sequence of place cell firing. Recent experiments by McNaughton and colleagues suggest the hippocampus can recall a sequence of place cell firings at a faster rate than it was experienced. This speedup, which occurs during slow-wave sleep, is called temporal compression. Here, we show that a simplified model of hippocampal area CA3, based on integrate-and-fire cells and unsupervised Hebbian learning, reproduces this temporal compression. The amount of compression is proportional to the activity level during recall and to the relative timespan of associativity during learning. Compression seems to arise from an alteration of network dynamics between learning and recall. During learning, the dynamics are paced by external input and slowed by a low overall level of activity. During recall, however, external input is absent, and the dynamics are controlled by intrinsic network properties. Raising the activity level by lowering inhibition increases the rate at which the network can transition between previously learned states and thereby produces temporal compression. The tendency for speeding up future activations, however, is limited by the temporal range of associations that were present during learning.     

Spatial inference without a cognitive map: the role of higher-order path integration

The cognitive map has been taken as the standard model for how agents infer the most efficient route to a goal location. Alternatively, path integration – maintaining a homing vector during navigation – constitutes a primitive and presumably less-flexible strategy than cognitive mapping because path integration relies primarily on vestibular stimuli and pace counting. The historical debate as to whether complex spatial navigation is ruled by associative learning or cognitive map mechanisms has been challenged by experimental difficulties in successfully neutralizing path integration. To our knowledge, there are only three studies that have succeeded in resolving this issue, all showing clear evidence of novel route taking, a behaviour outside the scope of traditional associative learning accounts. Nevertheless, there is no mechanistic explanation as to how animals perform novel route taking. We propose here a new model of spatial learning that combines path integration with higher-order associative learning, and demonstrate how it can account for novel route taking without a cognitive map, thus resolving this long-standing debate. We show how our higher-order path integration (HOPI) model can explain spatial inferences, such as novel detours and shortcuts. Our analysis suggests that a phylogenetically ancient, vector-based navigational strategy utilizing associative processes is powerful enough to support complex spatial inferences.     

Different encoding of reward location in dorsal and intermediate hippocampus

1. Download : Download high-res image (205KB)
2. Download : Download full-size image

     

Rapid synaptic plasticity contributes to a learned conjunctive code of position and choice-related information in the hippocampus

1. Download : Download high-res image (169KB)
2. Download : Download full-size image