Evidence map›Paper›PMID 29855432›Full record

ArticleJournal of neural engineering2018

Assessing functional connectivity across 3D tissue engineered axonal tracts using calcium fluorescence imaging.

Anjali Vijay Dhobale, Dayo O Adewole, Andy Ho Wing Chan, Toma Marinov, Mijail D Serruya, Reuben H Kraft, D Kacy Cullen

Abstract read
In one paragraph

Article in Journal of neural engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
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  8. Bioactive Neuroelectronic Interfaces.Frontiers in neuroscience · 2019
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Anjali Vijay DhobaleThe Penn State Computational Biomechanics Group, The Pennsylvania State University, University Park, PA, United States of America.
Dayo O AdewoleCenter for Brain Injury and Repair, Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
Andy Ho Wing ChanDepartment of Neurology and Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States of America.
Toma MarinovThe Penn State Computational Biomechanics Group, The Pennsylvania State University, University Park, PA, United States of America.
Mijail D SerruyaCenter for Neurotrauma, Neurodegeneration and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, United States of America.
Reuben H KraftThe Penn State Computational Biomechanics Group, The Pennsylvania State University, University Park, PA, United States of America.ORCID 0000-0001-8211-0681
D Kacy CullenCenter for Brain Injury and Repair, Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.

Funding

Biological 'Living Electrodes' Using Tissue Engineered Axonal Tracts to Probe and Modulate the Nervous SystemU01NS094340 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI CULLEN, DANIEL KACY · 2015 to 2017
$2.0M
BLRD VA I01 BX003748NINDS NIH HHS U01 NS094340
6 · The paper itself

Abstract

objectiveMicro-tissue engineered neural networks (micro-TENNs) are anatomically-inspired constructs designed to structurally and functionally emulate white matter pathways in the brain. These 3D neural networks feature long axonal tracts spanning discrete neuronal populations contained within a tubular hydrogel, and are being developed to reconstruct damaged axonal pathways in the brain as well as to serve as physiologically-relevant in vitro experimental platforms. The goal of the current study was to characterize the functional properties of these neuronal and axonal networks. APPROACH: Bidirectional micro-TENNs were transduced to express genetically-encoded calcium indicators, and spontaneous fluorescence activity was recorded using real-time microscopy at 20 Hz from specific regions-of-interest in the neuronal populations. Network activity patterns and functional connectivity across the axonal tracts were then assessed using various techniques from statistics and information theory including Pearson cross-correlation, phase synchronization matrices, power spectral analysis, directed transfer function, and transfer entropy. MAIN

resultsPearson cross-correlation, phase synchronization matrices, and power spectral analysis revealed high values of correlation and synchronicity between the spatially segregated neuronal clusters connected by axonal tracts. Specifically, phase synchronization revealed high synchronicity of  >0.8 between micro-TENN regions of interest. Normalized directed transfer function and transfer entropy matrices suggested robust information flow between the neuronal populations. Time varying power spectrum analysis revealed the strength of information propagation at various frequencies. Signal power strength was visible at elevated peak levels for dominant delta (1-4 Hz) and theta (4-8 Hz) frequency bands and progressively weakened at higher frequencies. These signal power strength results closely matched normalized directed transfer function analysis where near synchronous information flow was detected between frequencies of 2-5 Hz. SIGNIFICANCE: To our knowledge, this is the first report using directed transfer function and transfer entropy methods based on fluorescent calcium activity to estimate functional connectivity of distinct neuronal populations via long-projecting, 3D axonal tracts in vitro. These functional data will further improve the design and optimization of implantable neural networks that could ultimately be deployed to reconstruct the nervous system to treat neurological disease and injury.

Indexed as

Neural Networks, ComputerAnimalsAxonsCalciumCerebral CortexDelta RhythmEntropyFemaleFluorescenceNeural PathwaysNeuroimagingNeuronsPregnancyRatsTheta RhythmTissue EngineeringCalcium

Identifiers

PMID29855432
PMCPMC6999858

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Registered trials

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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.