Topic: hippocampal formation

The predictive map hypothesis provides a promising framework to model representations in the hippocampal formation. I will introduce a tractable implementation of a predictive map called the successor representation (SR), before presenting data showing that rats and humans display SR-like navigational choices on a novel open-field maze. Next, I will show how such a predictive map could be implemented using spatial representations found in the hippocampal formation, before finally presenting how such learning might be well approximated by phenomena that exist in the spatial memory system - name

In human and non-human animals, conceptual knowledge is partially organized according to low-dimensional geometries that rely on brain structures and computations involved in spatial representations. Recently, two separate lines of research have investigated cognitive maps, that are associated with the hippocampal formation and are similar to world-centered representations of the environment, and image spaces, that are associated with the parietal cortex and are similar to self-centered spatial relationships. I will suggest that cognitive maps and image spaces may be two manifestations of a m

There is a long-standing tension between the notion that the hippocampal formation is essentially a spatial mapping system, and the notion that it plays an essential role in the establishment of episodic memory and the consolidation of such memory into structured knowledge about the world. One theory that resolves this tension is the notion that the hippocampus generates rather arbitrary 'index' codes that serve initially to link attributes of episodic memories that are stored in widely dispersed and only weakly connected neocortical modules. I will show how an essentially 'spatial' coding mec

There has been a long-lasting debate on whether the function of the hippocampal formation is to store and retrieve episodic memory, supported by experiments in humans, or to code for space, suggested by spatially tuned cells (place cells, grid cells, etc.) recorded in nonhuman animals. In an attempt to reconcile the two views, we use a memory-augmented neural network in a reinforcement learning setup to solve a navigation task in a simulated maze. The key feature of the model is that it learns autonomously what and when to store into, and retrieve from, an external memory buffer. Once the mode

The hippocampal formation plays a key role in learning and memory, with CA3 thought to be the substrate of pattern completion [1]. However, its underlying computational and synaptic mechanisms are not yet understood. Here we analyze the mechanisms behind sequence replay through simulations of spiking neurons and a time-discrete model of moving membrane potential distributions. First, we simulated spiking networks of excitatory leaky integrate-and-fire cells forming a sequence of assemblies. The sequence contains both recurrent and feedforward connections (within and across assemblies, respect

Sharp wave-ripples (SPW-Rs) are widely studied oscillatory patterns observed during sleep and awake immobility in the hippocampal formation of most mammals [Buzsáki, 2015]. During SPW-Rs behavioral sequences are replayed compressed in time [Wilson & McNaughton, 1994; Diba & Buzsáki, 2007], which led to the hypothesis that they are mediating memory transfer from the hippocampus to the neocortex [Buzsáki, 1989]. SPW-Rs can be internally generated in the highly recurrent CA3 network [Maier et al., 2003], but their incidence during sleep is affected by slow oscillations in the cortex [Sirota et al

Navigation and memory are vital for survival, with organisms relying on landmarks and objects for orientation and foraging. The hippocampal formation constructs a spatial cognitive map using spatial cells like Place, Grid, and Head Direction cells. Sensory processing guides this map's construction, with the Medial Entorhinal Cortex (MEC) encoding self-motion cues (Path Integration) analogous to the 'where' pathway, while the Lateral Entorhinal Cortex (LEC) integrates sensory inputs analogous to the 'what' pathway. Object-dependent spatial cells, including Object Vector cells, Object Sensitive