scholarly journals Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions

2020 ◽  
Author(s):  
Tanguy Fardet ◽  
Anna Levina
Keyword(s):  
Disease Progression ◽  
Neurological Disorders ◽  
Large Scale ◽  
Time Course ◽  
Neuronal Response ◽  
Activity Patterns ◽  
Complex Activity ◽  
Course Of Disease ◽  
New Models ◽  
Neuronal Disorders

AbstractIn this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.Author summaryNeurons, even “at rest”, require a constant supply of energy to function. They cannot sustain high-frequency activity over long periods because of regulatory mechanisms, such as adaptation or sodium channels inactivation, and metabolic limitations. These limitations are especially severe in many neuronal disorders, where energy can become insufficient and make the neuronal response change drastically, leading to increased burstiness, network oscillations, or seizures. Capturing such behaviors and impact of energy constraints on them is an essential prerequisite to study disorders such as Parkinson’s disease and epilepsy. However, energy and spiking constraints are not present in any of the standard neuronal models used in computational neuroscience. Here we introduce models that provide a simple and scalable way to account for these features, enabling large-scale theoretical and computational studies of neurological disorders and activity patterns that could not be captured by previously used models. These models provide a way to study energy-associated disorders over the whole time-course of disease progression, and they enable a better assessment of energy-centered approaches to improve therapies.

scholarly journals Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions

2020 ◽  
Vol 16 (12) ◽  
pp. e1008503
Author(s):  
Tanguy Fardet ◽  
Anna Levina
Keyword(s):  
Large Scale ◽  
Time Course ◽  
Supply And Demand ◽  
Activity Patterns ◽  
Complex Activity ◽  
Biologically Relevant ◽  
New Models ◽  
Low Dimensionality ◽  
Diseased State ◽  
Large Scale Simulations

In this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.

Disease progression and regression in sporadic small vessel disease–insights from neuroimaging

2017 ◽  
Vol 131 (12) ◽  
pp. 1191-1206 ◽  
Author(s):  
Esther M.C. van Leijsen ◽  
Frank-Erik de Leeuw ◽  
Anil M. Tuladhar
Keyword(s):  
Disease Progression ◽  
Time Course ◽  
Temporal Dynamics ◽  
Small Vessel Disease ◽  
Small Vessel ◽  
Course Of Disease ◽  
Vessel Disease ◽  
Clinical Consequences ◽  
Dynamic Time

Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of dementia. Comprehensive characterization of the time course of disease progression will result in better understanding of aetiology and clinical consequences of SVD. SVD progression has been studied extensively over the years, usually describing change in SVD markers over time using neuroimaging at two time points. As a consequence, SVD is usually seen as a rather linear, continuously progressive process. This assumption of continuous progression of SVD markers was recently challenged by several studies that showed regression of SVD markers. Here, we provide a review on disease progression in sporadic SVD, thereby taking into account both progression and regression of SVD markers with emphasis on white matter hyperintensities (WMH), lacunes and microbleeds. We will elaborate on temporal dynamics of SVD progression and discuss the view of SVD progression as a dynamic process, rather than the traditional view of SVD as a continuous progressive process, that might better fit evidence from longitudinal neuroimaging studies. We will discuss possible mechanisms and clinical implications of a dynamic time course of SVD, with both progression and regression of SVD markers.

scholarly journals Stable behavioral state-specific large scale activity patterns in the developing cortex of neonates

2021 ◽  
Author(s):  
Nima Mojtahedi ◽  
Yury Kovalchuk ◽  
Alexander Böttcher ◽  
Olga Garaschuk
Keyword(s):  
Large Scale ◽  
Specific Activity ◽  
Activity Patterns ◽  
Building Blocks ◽  
Retrosplenial Cortex ◽  
Behavioral State ◽  
Dorsal Cortex ◽  
Complex Activity ◽  
Cortical Areas ◽  
Exact Function

AbstractEndogenous neuronal activity is a hallmark of the developing brain. In rodents, a handful of such activities were described in different cortical areas but the unifying macroscopic perspective is still lacking. Here we combined large-scale in vivo Ca2+ imaging of the dorsal cortex in non-anesthetized neonatal mice with advanced mathematical analyses to reveal unique behavioral state-specific maps of endogenous activity. These maps were remarkably stable over time within and across experiments and used patches of correlated activity with little hemispheric symmetry as well as stationary and propagating waves as building blocks. Importantly, the maps recorded during motion and rest were almost inverse, with sensory-motor areas active during motion and posterior-lateral areas active at rest. The retrosplenial cortex engaged in both resting- and motion-related activities, building functional long-range connections with respective cortical areas. The data obtained bind different region-specific activity patterns described so far into a single consistent picture and set the stage for future inactivation studies, probing the exact function of this complex activity pattern for cortical wiring in neonates.

scholarly journals A transient postnatal quiescent period precedes emergence of mature cortical dynamics

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Soledad Dominguez ◽  
Liang Ma ◽  
Han Yu ◽  
Gabrielle Pouchelon ◽  
Christian Mayer ◽  
...  
Keyword(s):  
Neural Networks ◽  
Large Scale ◽  
Time Course ◽  
Transition Period ◽  
Activity Patterns ◽  
Developmental Trajectory ◽  
Spatiotemporal Resolution ◽  
Quiescent Period ◽  
Network Operation

Mature neural networks synchronize and integrate spatiotemporal activity patterns to support cognition. Emergence of these activity patterns and functions is believed to be developmentally regulated, but the postnatal time course for neural networks to perform complex computations remains unknown. We investigate the progression of large-scale synaptic and cellular activity patterns across development using high spatiotemporal resolution in vivo electrophysiology in immature mice. We reveal that mature cortical processes emerge rapidly and simultaneously after a discrete but volatile transition period at the beginning of the second postnatal week of rodent development. The transition is characterized by relative neural quiescence, after which spatially distributed, temporally precise, and internally organized activity occurs. We demonstrate a similar developmental trajectory in humans, suggesting an evolutionarily conserved mechanism that could facilitate a transition in network operation. We hypothesize that this transient quiescent period is a requisite for the subsequent emergence of coordinated cortical networks.

scholarly journals Time Course of Disease Progression of PRPF31-mediated Retinitis Pigmentosa

2019 ◽  
Vol 200 ◽  
pp. 76-84 ◽  
Author(s):  
Kelly Kiser ◽  
Kaylie D. Webb-Jones ◽  
Sara J. Bowne ◽  
Lori S. Sullivan ◽  
Stephen P. Daiger ◽  
...  
Keyword(s):  
Retinitis Pigmentosa ◽  
Disease Progression ◽  
Time Course ◽  
Course Of Disease

scholarly journals A transient postnatal quiescent period precedes emergence of mature cortical dynamics

2021 ◽  
Author(s):  
Soledad Domínguez ◽  
Liang Ma ◽  
Han Yu ◽  
Gabrielle Pouchelon ◽  
Christian Mayer ◽  
...  
Keyword(s):  
Neural Networks ◽  
Large Scale ◽  
Time Course ◽  
Transition Period ◽  
Activity Patterns ◽  
Developmental Trajectory ◽  
Spatiotemporal Resolution ◽  
Quiescent Period ◽  
Network Operation

AbstractMature neural networks synchronize and integrate spatiotemporal activity patterns to support cognition. Emergence of these activity patterns and functions is believed to be developmentally regulated, but the postnatal time course for neural networks to perform complex computations remains unknown. We investigate the progression of large-scale synaptic and cellular activity patterns across development using high spatiotemporal resolution in vivo electrophysiology in immature mice. We reveal that mature cortical processes emerge rapidly and simultaneously after a discrete but volatile transition period at the beginning of the second postnatal week of rodent development. The transition is characterized by relative neural quiescence, after which spatially distributed, temporally precise, and internally organized activity occurs. We demonstrate a similar developmental trajectory in humans, suggesting an evolutionarily conserved mechanism to transition network operation. We hypothesize that this transient quiescent period is a requisite for the subsequent emergence of coordinated cortical networks.

scholarly journals Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids

2021 ◽  
Vol 22 (5) ◽  
pp. 2659
Author(s):  
Gianluca Costamagna ◽  
Giacomo Pietro Comi ◽  
Stefania Corti
Keyword(s):  
Drug Discovery ◽  
Drug Screening ◽  
Neural Development ◽  
Neurological Disorders ◽  
Large Scale ◽  
Three Dimensional ◽  
Induced Pluripotent Stem Cell ◽  
Cellular Level ◽  
Complex Data ◽  
Complex Data Sets

In the last decade, different research groups in the academic setting have developed induced pluripotent stem cell-based protocols to generate three-dimensional, multicellular, neural organoids. Their use to model brain biology, early neural development, and human diseases has provided new insights into the pathophysiology of neuropsychiatric and neurological disorders, including microcephaly, autism, Parkinson’s disease, and Alzheimer’s disease. However, the adoption of organoid technology for large-scale drug screening in the industry has been hampered by challenges with reproducibility, scalability, and translatability to human disease. Potential technical solutions to expand their use in drug discovery pipelines include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to create isogenic models, single-cell RNA sequencing to characterize the model at a cellular level, and machine learning to analyze complex data sets. In addition, high-content imaging, automated liquid handling, and standardized assays represent other valuable tools toward this goal. Though several open issues still hamper the full implementation of the organoid technology outside academia, rapid progress in this field will help to prompt its translation toward large-scale drug screening for neurological disorders.

scholarly journals THU0070 DEFINING SYNOVIAL SIGNATURES IN THE RAT CIA MODEL: WHAT CAN WE LEARN ABOUT RA PROGRESSION?

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 247.2-248
Author(s):  
D. Ruelas ◽  
R. LI ◽  
C. Franci ◽  
V. Lira ◽  
D. Lopez ◽  
...  
Keyword(s):  
Disease Progression ◽  
Synovial Tissue ◽  
Current Knowledge ◽  
Severe Disease ◽  
Unmet Need ◽  
Poor Response ◽  
Multiple Time ◽  
Combination Therapies ◽  
Course Of Disease ◽  
Time Point

Background:Patients showing inadequate or no response to current therapies represent a key unmet need in rheumatoid arthritis (RA). To address this, novel or combination therapies are of high clinical interest. Identification of novel therapeutic targets requires a greater understanding of the pathogenic molecular drivers in the RA synovium. However, our current knowledge of human molecular patterns that emerge as a result of disease progression is complicated by patient-to-patient heterogeneity and access to synovial tissue.Objectives:Here we use the current knowledge of human synovial heterogeneity to conduct a longitudinal study of global molecular responses in the rat collagen-induced arthritis (CIA) model to better understand synovial biology, improve the preclinical modeling of human disease, and discover novel targets for RA.Methods:A rat CIA model was performed as previously described.1RNA-Seq was performed on 56 knee synovial tissues collected at multiple time points throughout the course of disease. Differential gene expression was determined at each individual time point and longitudinally with disease progression. Published human synovial datasets were used to categorize these genes into myeloid, lymphoid, fibroid, and low inflammatory signatures.2Differentially expressed genes (DEGs) at each time point were compared to human synovial datasets of RA patients before and after treatment. In addition, we compared disease-driven genes in CIA to genes in RA patients that are unchanged following therapy to identify possible combination therapies.Results:Disease pathology in the rat CIA natural history study progressed as expected: significant decreases were seen in body weight, as well as increases in ankle diameter, paw weight, and histopathology scores of joints in collagen-injected vs noninjected rats. There were 1900 DEGs identified between diseased and naïve rats over the course of disease, representing disease-induced gene signatures (Fig. 1). Comparing these DEGs to reported human RA synovial signatures, both the lymphoid and myeloid signatures were found to be highly upregulated. Interestingly, there were no significant DEGs representing the human fibroid and low inflammatory synovial signatures identified in the CIA rat model. This suggests that the rat CIA model most closely models RA patients with an immune synovial phenotype. In addition, we examined the overlap between disease-driven genes in CIA and genes in RA patients that are unchanged following therapy to identify signaling pathways that may be of utility in combination therapy. Of genes that were upregulated in CIA, 94% of genes that mapped to extracellular matrix-receptor pathways remained unchanged in the synovial tissue of RA patients following tocilizumab treatment.Conclusion:Previous studies have shown that nearly 30% of treatment-naïve early RA patients exhibit a strong fibroid phenotype that correlates with less severe disease and a relatively poor response to disease-modifying anti-rheumatic drugs.3These data indicate that the synovial biology associated with such patients (fibroid or pauci-immune) is not well captured in CIA, the most common preclinical RA model. To assess potential new therapies targeting these patients, it will be necessary to develop alternative animal models with more intact fibroid signatures. In addition to these findings, we also characterized the global molecular changes that occur with disease progression in the CIA rat and made a comparison to RA patients on treatment, providing an overall understanding of disease-relevant pathways in the synovium that may point to possible combination therapies.References:[1]Trentham DE, et al.J Exp Med. 1977;146(3):857-868.[2]Dennis G Jr, et al.Arthritis Res Ther. 2014;16(2):R90.[3]Humby F, et al.Ann Rheum Dis. 2019;78(6):761-772.Disclosure of Interests:Debbie Ruelas Employee of: Gilead, Ruidong Li Employee of: Gilead, Christian Franci Employee of: Gilead, Victor Lira Employee of: Gilead, David Lopez Employee of: Gilead, Li Li Employee of: Gilead, Gundula Min-Oo Employee of: Gilead, Julie A. Di Paolo Employee of: Gilead

scholarly journals Monitoring Exotic Beetles with Inexpensive Attractants: A Case Study

Insects ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 462
Author(s):  
Enrico Ruzzier ◽  
Andrea Galli ◽  
Luciano Bani
Keyword(s):  
Native Species ◽  
Large Scale ◽  
Red Wine ◽  
Forest Type ◽  
Popillia Japonica ◽  
Complex Activity ◽  
Local Fauna ◽  
Apple Cider ◽  
Trap Placement

Detecting and monitoring exotic and invasive Coleoptera is a complex activity to implement, and citizen science projects can provide significant contributions to such plans. Bottle traps are successfully used in wildlife surveys and can also be adapted for monitoring alien species; however, a sustainable, large scale trapping plan must take into account the collateral catches of native species and thus minimize its impact on local fauna. In the present paper, we tested the use of bottles baited with standard food products that can be purchased in every supermarket and immediately used (apple cider vinegar, red wine, and 80% ethyl alcohol) in capturing exotic and invasive beetles in the area surrounding Malpensa Airport (Italy). In particular, we reduced the exposition type of the traps in each sampling round to three days in order to minimize native species collecting. We found a significant effect of the environmental covariates (trap placement, temperature, humidity, and forest type) in affecting the efficiency in catching target beetles. Nearly all invasive Nitidulidae and Scarabaeidae known to be present in the area were captured in the traps, with apple cider vinegar usually being the most effective attractant, especially for the invasive Popillia japonica.

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