ReviewNeuron2026
Neural population activity for memory: Properties, computations, and codes.
Review in Neuron, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Design principles for cost functions in optimal sensory coding.Frontiers in computational neuroscience · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The brain's memory function involves patterns of neural population spiking activity, shaped by experience and recurring over time. These neural population patterns are typically studied with respect to the three stages of acquisition, retention, and retrieval. Despite intensive investigation, the relationship between the features of population activity and the properties, computations, and codes for memory remains elusive. In this perspective, we synthesize recent advances in the study of memory from the viewpoint of brain network physiology, aiming for a comprehensive mapping between the properties and computations of memory and the features of population-activity codes. We propose that brain memory circuits implement trade-offs between conflicting demands on population codes. We anticipate that an important challenge for both discovery and translational neuroscience of memory is to study these trade-offs, delineating a safe zone in the population-activity space where neuronal circuits operate efficiently.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.