Differential ripple propagation along the hippocampal longitudinal axis
Abstract
Hippocampal ripples are highly synchronous neural events critical for memory consolidation and retrieval. A minority of strong ripples has been shown to be of particular importance in situations of increased memory demands. The propagation dynamics of strong ripples inside the hippocampal formation are, however, still opaque. We analyzed ripple propagation within the hippocampal formation in a large open access dataset comprising 267 Neuropixel recordings in 49 awake, head-fixed mice. Surprisingly, strong ripples (top 10% in ripple strength) propagate differentially depending on their generation point along the hippocampal longitudinal axis. The septal hippocampal pole is able to generate longer ripples that engage more neurons and elicit spiking activity for an extended time even at considerable distances. Accordingly, a substantial portion of the variance in strong ripple duration (R² = 0.463) is explained by the ripple generation location on the longitudinal axis, in agreement with a possible distinctive role of the hippocampal septal pole in conditions of high memory demand. Moreover, we observed that the location of the ripple generation has a significant impact on the spiking rate modulation of different hippocampal subfields, even before the onset of the ripple. This finding suggests that ripple generation location plays a crucial role in shaping the neural activity across the hippocampus.
Data availability
All the code used to process the dataset is available at https://github.com/RobertoDF/De-Filippo-et-al-2022, pre-computed data structures can be downloaded at 10.6084/m9.figshare.20209913. All figures and text can be reproduced using code present in this repository, each number present in the text is directly linked to a python data structure. The original dataset is provided by the Allen Institute and available at https://allensdk.readthedocs.io/en/latest/visual_coding_neuropixels.html.
-
Visual Coding - Neuropixelshttps://knowledge.brain-map.org/data/4YYLRZZGK82FQ85NIH8/summary.
Article and author information
Author details
Funding
Deutsche Forschungsgemeinschaft (184695641 - SFB 958)
- Dietmar Schmitz
Deutsche Forschungsgemeinschaft (327654276 - SFB 1315)
- Dietmar Schmitz
European Research Council (810580)
- Roberto de Filippo
NeuroCure Exzellenzcluster (Exc-2049-390688087)
- Dietmar Schmitz
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, de Filippo & Schmitz
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,398
- views
-
- 210
- downloads
-
- 10
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons. Neurons in the parietal and prefrontal cortex are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound. Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time. Here, we elucidate this drift-diffusion signal on individual decisions. We recorded simultaneously from hundreds of neurons in the lateral intraparietal cortex of monkeys while they made decisions about the direction of random dot motion. We show that a single scalar quantity, derived from the weighted sum of the population activity, represents a combination of deterministic drift and stochastic diffusion. Moreover, we provide direct support for the hypothesis that this drift-diffusion signal approximates the quantity responsible for the variability in choice and reaction times. The population-derived signals rely on a small subset of neurons with response fields that overlap the choice targets. These neurons represent the integral of noisy evidence. Another subset of direction-selective neurons with response fields that overlap the motion stimulus appear to represent the integrand. This parsimonious architecture would escape detection by state-space analyses, absent a clear hypothesis.
-
- Developmental Biology
- Neuroscience
Exposure to ketone bodies in early development can reduce neurological impairments in a strain of the nematode C. elegans with PTEN defects.