Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness
- Italian Institute of Technology, Italy
- KAUST, Saudi Arabia
- Istituto Italiano di tecnologia, Italy
Abstract
Imaging neuronal activity with high and homogeneous spatial resolution across the field-of-view (FOV) and limited invasiveness in deep brain regions is fundamental for the progress of neuroscience, yet is a major technical challenge. We achieved this goal by correcting optical aberrations in gradient index lens-based ultrathin (< 500 μm) microendoscopes using aspheric microlenses generated through 3D-microprinting. Corrected microendoscopes had extended FOV (eFOV) with homogeneous spatial resolution for two-photon fluorescence imaging and required no modification of the optical set-up. Synthetic calcium imaging data showed that, compared to uncorrected endoscopes, eFOV-microendoscopes led to improved signal-to-noise ratio and more precise evaluation of correlated neuronal activity. We experimentally validated these predictions in awake head-fixed mice. Moreover, using eFOV-microendoscopes we demonstrated cell-specific encoding of behavioral state-dependent information in distributed functional subnetworks in a primary somatosensory thalamic nucleus. eFOV-microendoscopes are, therefore, small-crosssection ready-to-use tools for deep two-photon functional imaging with unprecedentedly high and homogeneous spatial resolution.
Data availability
The datasets shown in Figures 4, 6, 7 and corresponding figure supplements are available at:https://data.mendeley.com/datasets/wm6c5wzs4c/draft?a=56f1660e-a036-40ee-83ef-458dc2457b6aThe software used in this paper to generate and analyze artificial t-series is available at: https://github.com/moni90/eFOV_microendoscopes_simNumerical data for graphs represented in figures 3-7, figure 2-figure supplement 2-4, figure 3-figure supplement 4, figure 4-figure supplement 1-2 are provided as source data.
Article and author information
Author details
Funding
European Research Council (NEURO-PATTERNS)
- Tommaso Fellin
IIT interdisciplinary grant
- Tommaso Fellin
IIT interdisciplinary grant
- Carlo Liberale
KAUST (BAS/1/1064-01-01)
- Carlo Liberale
NIH Brain Initiative (NS090576)
- Tommaso Fellin
NIH Brain Initiative (NS107464)
- Tommaso Fellin
NIH Brain Initiative (NS107464)
- Stefano Panzeri
NIH Brain Initiative (NS109961)
- Stefano Panzeri
FP7 (DESIRE)
- Tommaso Fellin
FIRB (RBAP11X42L)
- Tommaso Fellin
Flag-Era JTC Human Brain Project (SLOW-DYN)
- Tommaso Fellin
Flag-Era JTC Human Brain Project (SLOW-DYN)
- Stefano Panzeri
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: Experimental procedures involving animals have been approved by the Istituto Italiano di Tecnologia Animal Health Regulatory Committee, by the National Council on Animal Care of the Italian Ministry of Health (authorization # 1134/2015-PR, # 689/2018-PR) and carried out according to the National legislation (D.Lgs. 26/2014) and to the legislation of the European Communities Council Directive (European Directive 2010/63/EU).
Copyright
© 2020, Fellin et al.
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
-
- 3,802
- views
-
- 594
- downloads
-
- 39
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
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)
Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness
eLife 9:e58882.
https://doi.org/10.7554/eLife.58882
Further reading
-
- Neuroscience
Predicting an individual’s cognitive traits or clinical condition using brain signals is a central goal in modern neuroscience. This is commonly done using either structural aspects, such as structural connectivity or cortical thickness, or aggregated measures of brain activity that average over time. But these approaches are missing a central aspect of brain function: the unique ways in which an individual’s brain activity unfolds over time. One reason why these dynamic patterns are not usually considered is that they have to be described by complex, high-dimensional models; and it is unclear how best to use these models for prediction. We here propose an approach that describes dynamic functional connectivity and amplitude patterns using a Hidden Markov model (HMM) and combines it with the Fisher kernel, which can be used to predict individual traits. The Fisher kernel is constructed from the HMM in a mathematically principled manner, thereby preserving the structure of the underlying model. We show here, in fMRI data, that the HMM-Fisher kernel approach is accurate and reliable. We compare the Fisher kernel to other prediction methods, both time-varying and time-averaged functional connectivity-based models. Our approach leverages information about an individual’s time-varying amplitude and functional connectivity for prediction and has broad applications in cognitive neuroscience and personalised medicine.
-
- Neuroscience
Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain–behavior associations in unseen data, generalizability of the model was rather limited for all three latent components (r change from within- to out-of-sample statistics: LC1within = 0.36, LC1out = 0.03; LC2within = 0.34, LC2out = 0.05; LC3within = 0.35, LC3out = 0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.
