Sparse and distributed coding of episodic memory in neurons of the human hippocampus

Abstract

Neurocomputational models hold that sparse distributed coding is the most efficient way for hippocampal neurons to encode episodic memories rapidly. We investigated the representation of episodic memory in hippocampal neurons of nine epilepsy patients undergoing intracranial monitoring as they discriminated between recently studied words (targets) and new words (foils) on a recognition test. On average, single units and multiunits exhibited higher spike counts in response to targets relative to foils, and the size of this effect correlated with behavioral performance. Further analyses of the spike-count distributions revealed that (i) a small percentage of recorded neurons responded to any one target and (ii) a small percentage of targets elicited a strong response in any one neuron. These findings are consistent with the idea that in the human hippocampus episodic memory is supported by a sparse distributed neural code.recognition memory | intracranial recording | amygdala T he hippocampus is known to play a fundamental role in declarative memory (1-4), but it is not known how mnemonic information is coded by the activity of individual hippocampal neurons. At least three different coding schemes have been considered: a localist coding scheme, a fully distributed coding scheme, and a sparse distributed coding scheme (5). In a localist coding scheme, an individual neuron (sometimes referred to as a "grandmother cell") codes only one memory, and each memory is coded by the activity of only one neuron. In a fully distributed coding scheme, each memory is coded instead by a pattern of activity across many hippocampal neurons. Falling between these two extremes is a sparse distributed coding scheme in which each memory is coded by the activity of a small proportion of hippocampal neurons, and each neuron contributes to the representation of only a few memories. Sparse distributed coding has long been hypothesized to be the most efficient way for hippocampal neurons to encode episodic memories (remembering events) in rapid succession without overwriting previously stored memories (6-8).Most prior work concerned with the coding of declarative memory in the human hippocampus has focused on the neural representation of semantic memories (remembering facts), such as memory for famous people or landmarks (9, 10). The results of these studies suggest that long-established semantic memories may be represented by fewer than 1% of neurons in the hippocampus (11). However, neurocomputational theories are concerned with the representation of episodic memories. The purpose of our study was to test predictions of these neurocomputational theories about how episodic memories are represented by neurons of the hippocampus.The representation of episodic memory in the hippocampus typically has been investigated using recognition procedures. In recognition, the task is to discriminate between familiar items presented earlier in the experimental session (targets) and novel items not previously presented (foils). An episodic memory signal...

Fear Memory

“…Fear conditioning in particular relies on CS-US interactions in the DG and in the LA (295,328,350,448,574). After all, this fits better with the findings on humans with large bilateral temporal lobe lesions (493,589), specifically those with lesions restricted to the hippocampus (308,549,664,686), who have consistently been shown to have a general incapacity to retain new declarative memories of any kind, but to remember well memories acquired weeks or months before the lesion, and, importantly, do not show appreciable deficits in scene construction (of a picture they see) while consistently losing memory items relevant to that scene (308).…”

“…It has been estimated that Ͻ1% of all the units tested encode semantic rather than episodic information, but they do so for extremely long periods (652). The findings on the neurons dedicated to episodic memory fit with those from neurocomputational models indicating that "sparse distributed coding is the most efficient way to encode episodic memories rapidly" (664). The recordings made by Wixted et al (664) and Quián Quiroga and co-workers (652) were in epileptic patients undergoing intracranial monitoring as they underwent behavioral testing, in the style made famous by Wilder Penfield when he studied the retrieval of memories from the temporal lobe of awake patients submitted to epilepsy surgery for epileptic (491,492,494).…”

“…The work of Wixted, Squire and their collaborators (664) and Quián Quiroga and his collaborators (486,652) on hippocampal units in vivo has provided very strong evidence that this structure is primarily involved in the coding of episodic memory in neurons and that this coding is rapid, very sparse, and distributed. It has been estimated that Ͻ1% of all the units tested encode semantic rather than episodic information, but they do so for extremely long periods (652).…”

“…Nowadays LTP and LTD are viewed as intrinsic to the consolidation, but not necessarily the long-term maintenance or expression of many forms of learning: aversive, spatial, contextual, fear, etc., either by themselves (125,226) The more recent views on hippocampal function in memory point not only to a key role in cellular consolidation (265,272,401,664) but also to one in the integration of different recent learned information of various types and from various sources, through interactions between the LTP or LTD generated in one form of learning with those generated in others (16,43,115,116,428,561), even between learnings of opposite or at least very different behavioral characteristics like extinction and novelty recognition (115,116).…”

Antidepresan İlaçların Öğrenme ve Bellek Mekanizmasına Etkileri

“…Hipokampus, hareketlerin davranış biçimine dönüşmesinde önemli role sahip bulunan limbik sistemde yer alır. Epizodik hafızanın oluşumunda hipokampusda özellikle CA3 bölgesindeki bağlantılar önemli rol oynar 32 . Nöronlar sinaptik aralıklarında sinyalleri iletirken aynı zamanda bu sinyallerin yoğunluğuna göre geçici veya kalıcı yapısal değişiklikler oluşturarak sinyal etkisini uzun süre üzerlerinde tutabilirler.…”