Alpha-synuclein oligomers alter the spontaneous firing discharge of cultured midbrain neurons

Tomagra, Giulia; Franchino, Claudio; Cesano, Federico; Chiarion, Giovanni; lure, Antonio de; Carbone, Emilio; Calabresi, Paolo; Mesin, Luca; Picconi, Barbara; Marcantoni, Andrea; Carabelli, Valentina

doi:10.3389/fncel.2023.1078550

Cited by 3 publications

(4 citation statements)

References 95 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 2 summarizes the possible neurotoxic mechanisms associated with exposure to α-SynOs. In neurons, α-SynOs induce perturbation of cellular and mitochondrial membranes, altering their structures and functions [ 71 , 105 , 127 , 128 , 129 , 130 ]. Specific receptor interactions have been proposed to explain α-synO toxicity, including prion protein [ 131 , 132 ], β spectrin [ 133 , 134 ], RLP1 receptor [ 135 ] and purinergic P2X7R receptor [ 136 , 137 ].…”

Section: Alpha-synuclein Oligomersmentioning

confidence: 99%

Alpha Synuclein: Neurodegeneration and Inflammation

Forloni

2023

IJMS

View full text Add to dashboard Cite

Alpha-Synuclein (α-Syn) is one of the most important molecules involved in the pathogenesis of Parkinson’s disease and related disorders, synucleinopathies, but also in several other neurodegenerative disorders with a more elusive role. This review analyzes the activities of α-Syn, in different conformational states, monomeric, oligomeric and fibrils, in relation to neuronal dysfunction. The neuronal damage induced by α-Syn in various conformers will be analyzed in relation to its capacity to spread the intracellular aggregation seeds with a prion-like mechanism. In view of the prominent role of inflammation in virtually all neurodegenerative disorders, the activity of α-Syn will also be illustrated considering its influence on glial reactivity. We and others have described the interaction between general inflammation and cerebral dysfunctional activity of α-Syn. Differences in microglia and astrocyte activation have also been observed when in vivo the presence of α-Syn oligomers has been combined with a lasting peripheral inflammatory effect. The reactivity of microglia was amplified, while astrocytes were damaged by the double stimulus, opening new perspectives for the control of inflammation in synucleinopathies. Starting from our studies in experimental models, we extended the perspective to find useful pointers to orient future research and potential therapeutic strategies in neurodegenerative disorders.

show abstract

Section: Alpha-synuclein Oligomersmentioning

confidence: 99%

Alpha Synuclein: Neurodegeneration and Inflammation

Forloni

2023

IJMS

View full text Add to dashboard Cite

show abstract

“… Network motifs, which are subgraphs showing patterns of local connectivity. Node and edge centrality, based on the idea that specific combinations of nodes and links can control information flow [ 249 , 258 , 259 , 260 , 261 ]. Network resilience, based on the evidence that anatomical connectivity influences the ability of neuropathological lesions to affect brain activity.…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

“…Node and edge centrality, based on the idea that specific combinations of nodes and links can control information flow [ 249 , 258 , 259 , 260 , 261 ].…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

“…Ultimately, complex network tools are particularly important in understanding connectivity, as they provide a mathematical framework for modeling and analyzing the network of connections between brain regions, and to better understand brain function and disorders, such as Alzheimer’s disease, autism, and schizophrenia, and their impacts on brain connectivity over time, which can help to track the progression of brain diseases and inform the development of new treatments [ 30 , 261 , 265 , 266 , 267 , 268 , 269 ].…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

et al. 2023

Self Cite

View full text Add to dashboard Cite

Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros–cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks.

show abstract

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

Lam,

Enright,

Cadena

et al. 2023

Front. Cell. Neurosci.

View full text Add to dashboard Cite

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo, functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a “bottom-up” 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

show abstract

Alpha-synuclein oligomers alter the spontaneous firing discharge of cultured midbrain neurons

Cited by 3 publications

References 95 publications

Alpha Synuclein: Neurodegeneration and Inflammation

Alpha Synuclein: Neurodegeneration and Inflammation

Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

Contact Info

Product

Resources

About