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Brain Sciences
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Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies:...
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Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Computational Neuroscience and Neuroinformatics".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 13099

Special Issue Editors

Dr. Michela Chiappalone

E-Mail Website
Guest Editor
Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
Interests: neuroengineering; neuroprosthetics; neurorehabilitation; pre-clinical studies
Special Issues, Collections and Topics in MDPI journals
Dr. Marianna Semprini

E-Mail Website
Guest Editor
Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
Interests: neuroengineering; neuroprosthetics; neurorehabilitation; clinical studies

Special Issue Information

Dear Colleagues, 

Neurological diseases causing motor/cognitive impairments are among the most common causes of adult-onset disability. More than one billion people worldwide are affected, and this number is likely to increase in the coming years, because of the rapidly aging population. In this context, to elucidate the mechanisms underlying the recovery of impaired neuronal functions, it is crucial to investigate the electrophysiological properties of the neural substrate in different conditions. For example, novel brain signal processing may provide biomarkers of the plastic changes induced by the pathological conditions and/or the therapeutic intervention, e.g., robotic rehabilitation, neuromodulation, neuroprosthetics.

Investigations into the neural mechanisms that underlie both healthy and pathological conditions are, thus, needed in systems at different levels of complexity, from in vitro, to in vivo, and up to entire humans, to provide a complete vocabulary of translational neural indicators.

This Special Issue will collect diverse contributions on mechanisms to investigate/modulate dynamics and/or plasticity both in the healthy and injured condition. Innovative experimental designs, software, and hardware algorithms for targeted signal processing, computational modeling, represent useful approaches to fulfill the aims of this Special Issue. We accept submissions of manuscripts as original articles, critical reviews, research notes, and short communications.

Dr. Michela Chiappalone
Dr. Marianna Semprini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computational modeling 
  • electrophysiology 
  • humans 
  • in vivo 
  • in vitro 
  • neural biomarkers 
  • neural signal processing 
  • neural disease 
  • neural interface 
  • neural plasticity 
  • neuromodulation 
  • neuroprosthetics 
  • translational studies

Published Papers (5 papers)

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Research

20 pages, 3421 KiB  
Article
Spontaneous and Perturbational Complexity in Cortical Cultures
by Ilaria Colombi, Thierry Nieus, Marcello Massimini and Michela Chiappalone
Brain Sci. 2021, 11(11), 1453; https://doi.org/10.3390/brainsci11111453 - 01 Nov 2021
Cited by 10 | Viewed by 2691
Abstract
Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while [...] Read more.
Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity. Full article
(This article belongs to the Special Issue Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments)
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12 pages, 2074 KiB  
Article
Experimental Platform to Study Spiking Pattern Propagation in Modular Networks In Vitro
by Yana Pigareva, Arseniy Gladkov, Vladimir Kolpakov, Irina Mukhina, Anton Bukatin, Victor B. Kazantsev and Alexey Pimashkin
Brain Sci. 2021, 11(6), 717; https://doi.org/10.3390/brainsci11060717 - 28 May 2021
Cited by 8 | Viewed by 3280
Abstract
The structured organization of connectivity in neural networks is associated with highly efficient information propagation and processing in the brain, in contrast with disordered homogeneous network architectures. Using microfluidic methods, we engineered modular networks of cultures using dissociated cells with unidirectional synaptic connections [...] Read more.
The structured organization of connectivity in neural networks is associated with highly efficient information propagation and processing in the brain, in contrast with disordered homogeneous network architectures. Using microfluidic methods, we engineered modular networks of cultures using dissociated cells with unidirectional synaptic connections formed by asymmetric microchannels. The complexity of the microchannel geometry defined the strength of the synaptic connectivity and the properties of spiking activity propagation. In this study, we developed an experimental platform to study the effects of synaptic plasticity on a network level with predefined locations of unidirectionally connected cellular assemblies using multisite extracellular electrophysiology. Full article
(This article belongs to the Special Issue Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments)
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12 pages, 2425 KiB  
Article
A Computational Model for Pain Processing in the Dorsal Horn Following Axonal Damage to Receptor Fibers
by Jennifer Crodelle and Pedro D. Maia
Brain Sci. 2021, 11(4), 505; https://doi.org/10.3390/brainsci11040505 - 16 Apr 2021
Cited by 2 | Viewed by 2252
Abstract
Computational modeling of the neural activity in the human spinal cord may help elucidate the underlying mechanisms involved in the complex processing of painful stimuli. In this study, we use a biologically-plausible model of the dorsal horn circuitry as a platform to simulate [...] Read more.
Computational modeling of the neural activity in the human spinal cord may help elucidate the underlying mechanisms involved in the complex processing of painful stimuli. In this study, we use a biologically-plausible model of the dorsal horn circuitry as a platform to simulate pain processing under healthy and pathological conditions. Specifically, we distort signals in the receptor fibers akin to what is observed in axonal damage and monitor the corresponding changes in five quantitative markers associated with the pain response. Axonal damage may lead to spike-train delays, evoked potentials, an increase in the refractoriness of the system, and intermittent blockage of spikes. We demonstrate how such effects applied to mechanoreceptor and nociceptor fibers in the pain processing circuit can give rise to dramatically distinct responses at the network/population level. The computational modeling of damaged neuronal assemblies may help unravel the myriad of responses observed in painful neuropathies and improve diagnostics and treatment protocols. Full article
(This article belongs to the Special Issue Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments)
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26 pages, 1703 KiB  
Article
Built to Last: Functional and Structural Mechanisms in the Moth Olfactory Network Mitigate Effects of Neural Injury
by Charles B. Delahunt, Pedro D. Maia and J. Nathan Kutz
Brain Sci. 2021, 11(4), 462; https://doi.org/10.3390/brainsci11040462 - 05 Apr 2021
Cited by 2 | Viewed by 2364
Abstract
Most organisms suffer neuronal damage throughout their lives, which can impair performance of core behaviors. Their neural circuits need to maintain function despite injury, which in particular requires preserving key system outputs. In this work, we explore whether and how certain structural and [...] Read more.
Most organisms suffer neuronal damage throughout their lives, which can impair performance of core behaviors. Their neural circuits need to maintain function despite injury, which in particular requires preserving key system outputs. In this work, we explore whether and how certain structural and functional neuronal network motifs act as injury mitigation mechanisms. Specifically, we examine how (i) Hebbian learning, (ii) high levels of noise, and (iii) parallel inhibitory and excitatory connections contribute to the robustness of the olfactory system in the Manduca sexta moth. We simulate injuries on a detailed computational model of the moth olfactory network calibrated to data. The injuries are modeled on focal axonal swellings, a ubiquitous form of axonal pathology observed in traumatic brain injuries and other brain disorders. Axonal swellings effectively compromise spike train propagation along the axon, reducing the effective neural firing rate delivered to downstream neurons. All three of the network motifs examined significantly mitigate the effects of injury on readout neurons, either by reducing injury’s impact on readout neuron responses or by restoring these responses to pre-injury levels. These motifs may thus be partially explained by their value as adaptive mechanisms to minimize the functional effects of neural injury. More generally, robustness to injury is a vital design principle to consider when analyzing neural systems. Full article
(This article belongs to the Special Issue Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments)
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10 pages, 1263 KiB  
Article
A R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots
by Robert Marschallinger, Carmen Tur, Hannes Marschallinger and Johann Sellner
Brain Sci. 2021, 11(1), 90; https://doi.org/10.3390/brainsci11010090 - 12 Jan 2021
Viewed by 1806
Abstract
One significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations [...] Read more.
One significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script LDPgenerator.r, a small sample data set and associated graphics for comparison. Full article
(This article belongs to the Special Issue Investigating Dynamics and Plasticity of Healthy and Injured Neuronal Assemblies: Algorithms, Modelling, and Experiments)
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