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Analysis and modeling of CA1 pyramidal neurons for the article: Deficits in neuronal architecture and their role in reduced neuronal network activity in a mouse model of overexpression of Dyrk1A
No full textContents: Repo Contents. -- System Requirements. -- Installation Guide. -- Demo. -- License. -- Issues. -- CitationPeer reviewe
Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets
No full textDeficits in neuronal architecture but not over-inhibition are main determinants of reduced neuronal network activity in a mouse model of overexpression of Dyrk1A
Full text linkAltres ajuts: CERCA Programme/Generalitat de Catalunya ; The CIBER of Rare Diseases is an initiative of the ISCIIIIn this study, we investigated the impact of Dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) overexpression, a gene associated with Down syndrome, on hippocampal neuronal deficits in mice. Our findings revealed that mice overexpressing Dyrk1A (TgDyrk1A; TG) exhibited impaired hippocampal recognition memory, disrupted excitation-inhibition balance, and deficits in long-term potentiation (LTP). Specifically, we observed layer-specific deficits in dendritic arborization of TG CA1 pyramidal neurons in the stratum radiatum. Through computational modeling, we determined that these alterations resulted in reduced storage capacity and compromised integration of inputs, with decreased high γ oscillations. Contrary to prevailing assumptions, our model suggests that deficits in neuronal architecture, rather than over-inhibition, primarily contribute to the reduced network. We explored the potential of environmental enrichment (EE) as a therapeutic intervention and found that it normalized the excitation-inhibition balance, restored LTP, and improved short-term recognition memory. Interestingly, we observed transient significant dendritic remodeling, leading to recovered high γ. However, these effects were not sustained after EE discontinuation. Based on our findings, we conclude that Dyrk1A overexpression-induced layer-specific neuromorphological disturbances impair the encoding of place and temporal context. These findings contribute to our understanding of the underlying mechanisms of Dyrk1A-related hippocampal deficits and highlight the challenges associated with long-term therapeutic interventions for cognitive impairments
Dynamics and functional connectivity in a network derived from anatomical data of the mouse brain
Full text linkTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2025, Tutors: Linus Manubens Gil, Jordi Soriano FraderaThis project studies the collective dynamics of a neural network constructed from experimental connectivity data of the mouse brain. The Izhikevich model has been used to simulate the dynamics of neurons under different noise and excitatory strength conditions. The analysis has focused on how these parameters affect the global synchronization of the network, as well as on the comparison of three structural configurations: the original one, one with randomly redistributed connections, and another one with an eliminated module of the original network. From the activity data, functional matrices have been generated, and measures such as mean degree, global efficiency, and degree of modularity have been calculated. The results show how the structural properties
influence the functional organization of the network and its synchronization capacit
Computationl and modeling approaches to multi-scale anatomical description of neuronal circuitry
Full text linkDuring the last century the nervous system has been mainly studied from a reductionistic approach, based on the hypothesis that understanding in depth single neurons or limited neuronal populations would lead to general conclusions on brain function. However, to what extent anatomical details of single neurons can affect the wiring of the networks they form is a largely overlooked question. Intellectual disability provides an excellent opportunity to explore the relevance of fine structural details, because many disorders show specific architectural alterations that correlate with cognitive performance.
In this Thesis, I aimed to study how the network topology of neuronal circuits is affected by dendritic architectural features in a mouse model of intellectual disability, namely Down's syndrome, and upon the rewiring effect of pro-cognitive treatment. I did so from three points of view:
1. The exploration of a 2D minimal computational model of cortical layer II/III parameterized by experimental data on dendritic tree architecture of healthy mice and two Down syndrome mouse models
2. The study of within-region morphological variations of hippocampal CA1 pyramidal neurons and their dependency of spatial embedding and cellularity in healthy mice and a Down syndrome mouse model.
3. The development of an experimental and computational framework for whole brain multiscale assessment and reconstruction.
My work revealed that the dendritic tree architecture and the distribution of synaptic contacts have significant implications on how optimal single neurons are for information processing efficiency and storage capacity, and that those single-neuron features permeate to the network level, determining the computational capacities of neural ensembles.
Also, I found position-dependent neuromorphological inhomogeneities in CA1 pyramids along with variations of neuronal cell density, suggesting that intrinsic properties of CA1 can vary across its extension. Those inhomogeneities were different in healthy and TgDyrk1A mice, possibly affecting emergent functional aspects.
In my Thesis I faced challenges to bridge structure and function and to study morphological inhomogeneities at different scale (single cell and cell population). To solve
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those challenges, I developed computational methods for 3D mapping cellular population and dendritic density and assessed their validity. I also developed a computational modeling framework that allows the instantiation of multi-scale biologically realistic networks. Finally, I optimized the CLARITY whole-brain clearing technique and developed a pipeline to apply our population-based analysis and multi-scale modeling methods to the structural interrogation of whole brains, and to study the implications of the neuronal morphospace on the topology of neuronal circuitry.Durant l’últim segle, el sistema nerviós s’ha estudiat des d’un punt de vista reduccionista, basant-se en la hipòtesi que entendre en profunditat neurones individuals o fraccions petites de poblacions neuronals portaria a conclusions generals sobre la funció del cervell. De totes maneres, fins a quin punt detalls anatòmics de neurones individuals poden afectar la connectivitat de les xarxes que formen, és una qüestió que en gran part s’ha passat per alt. Les discapacitats intel·lectuals proporcionen una oportunitat excel·lent per explorar la rellevància de detalls estructurals, perquè molts trastorns cognitius mostren alteracions arquitectòniques específiques que correlacionen amb habilitats cognitives.
En aquesta Tesi, pretenia estudiar com la topologia dels circuits neuronals és afectada per característiques arquitectòniques en un model murí de discapacitat intel·lectual, en concret de síndrome de Down, i per tractaments pro-cognitius amb efectes de remodel·lació de la xarxa. Ho he fet des de tres punts de vista: 1. L’exploració d’un model computacional 2D mínim de la capa cortical II/III parametritzat amb dades experimentals d’arquitectura dendrítica ens els nostres models de síndrome de Down.
2. L’estudi de neurones individuals, la seva diversitat i propietats morfològiques d’escala mesoscòpica en el model murí TgDyrk1A de síndrome de Down.
3. El desenvolupament d’un marc experimental i computacional per a l’estudi del problema des d’una perspectiva multi-escala.
La meva feina ha mostrat que l’arquitectura dendrítica i la distribució de contactes sinàptics tenen implicacions significatives en l’optimalitat de neurones individuals per a l’eficiència en el processat d’informació i per a la capacitat d’emmagatzemar memòries, i que aquestes dues quantitats permeen al nivell de xarxa, determinant les capacitats computacionals de conjunts de neurones.
També, he trobat variacions neuromorfològiques a CA1 dependents de la posició en neurones piramidals, acompanyades per variacions en densitat cel·lular, apuntat que propietats intrínseques de CA1 poden variar al llarg de la seva extensió. Aquestes inhomogeneitats eren diferents en ratolins sans i TgDyrk1A, possiblement tenint efectes en aspectes funcionals emergents concrets.
xiv
En la meva Tesi he afrontat reptes en lligar estructura i funció i en l’estudi de les inhomogeneïtats morfològiques en múltiples escales (de cèl·lula individual i de poblacions). Per a assolir aquests reptes, he desenvolupat mètodes computacionals per al mapejat 3D de poblacions cel·lulars i de densitats dendrítiques i he avaluat la seva validesa. També he desenvolupat un marc de modelització que permet l’instanciació multi-escala de xarxes neuronals biològicament realistes. Finalment, he optimitzat la tècnica de clarejat de cervell sencer CLARITY i he desenvolupat un pipeline per a aplicar les nostres eines d’anàlisi de poblacions i els mètodes multi-escala de model·lizatió per a l’anàlisi estructural de cervells sencers, i per a l’estudi de les implicacions del morfoespai neuronal en la topologia de la circuiteria neuronal.Programa de doctorat en Biomedicin
BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets
No full textComputationl and modeling approaches to multi-scale anatomical description of neuronal circuitry
No full textDuring the last century the nervous system has been mainly studied from a reductionistic approach, based on the hypothesis that understanding in depth single neurons or limited neuronal populations would lead to general conclusions on brain function. However, to what extent anatomical details of single neurons can affect the wiring of the networks they form is a largely overlooked question. Intellectual disability provides an excellent opportunity to explore the relevance of fine structural details, because many disorders show specific architectural alterations that correlate with cognitive performance.
In this Thesis, I aimed to study how the network topology of neuronal circuits is affected by dendritic architectural features in a mouse model of intellectual disability, namely Down's syndrome, and upon the rewiring effect of pro-cognitive treatment. I did so from three points of view:
1. The exploration of a 2D minimal computational model of cortical layer II/III parameterized by experimental data on dendritic tree architecture of healthy mice and two Down syndrome mouse models
2. The study of within-region morphological variations of hippocampal CA1 pyramidal neurons and their dependency of spatial embedding and cellularity in healthy mice and a Down syndrome mouse model.
3. The development of an experimental and computational framework for whole brain multiscale assessment and reconstruction.
My work revealed that the dendritic tree architecture and the distribution of synaptic contacts have significant implications on how optimal single neurons are for information processing efficiency and storage capacity, and that those single-neuron features permeate to the network level, determining the computational capacities of neural ensembles.
Also, I found position-dependent neuromorphological inhomogeneities in CA1 pyramids along with variations of neuronal cell density, suggesting that intrinsic properties of CA1 can vary across its extension. Those inhomogeneities were different in healthy and TgDyrk1A mice, possibly affecting emergent functional aspects.
In my Thesis I faced challenges to bridge structure and function and to study morphological inhomogeneities at different scale (single cell and cell population). To solve
xii
those challenges, I developed computational methods for 3D mapping cellular population and dendritic density and assessed their validity. I also developed a computational modeling framework that allows the instantiation of multi-scale biologically realistic networks. Finally, I optimized the CLARITY whole-brain clearing technique and developed a pipeline to apply our population-based analysis and multi-scale modeling methods to the structural interrogation of whole brains, and to study the implications of the neuronal morphospace on the topology of neuronal circuitry.Durant l’últim segle, el sistema nerviós s’ha estudiat des d’un punt de vista reduccionista, basant-se en la hipòtesi que entendre en profunditat neurones individuals o fraccions petites de poblacions neuronals portaria a conclusions generals sobre la funció del cervell. De totes maneres, fins a quin punt detalls anatòmics de neurones individuals poden afectar la connectivitat de les xarxes que formen, és una qüestió que en gran part s’ha passat per alt. Les discapacitats intel·lectuals proporcionen una oportunitat excel·lent per explorar la rellevància de detalls estructurals, perquè molts trastorns cognitius mostren alteracions arquitectòniques específiques que correlacionen amb habilitats cognitives.
En aquesta Tesi, pretenia estudiar com la topologia dels circuits neuronals és afectada per característiques arquitectòniques en un model murí de discapacitat intel·lectual, en concret de síndrome de Down, i per tractaments pro-cognitius amb efectes de remodel·lació de la xarxa. Ho he fet des de tres punts de vista: 1. L’exploració d’un model computacional 2D mínim de la capa cortical II/III parametritzat amb dades experimentals d’arquitectura dendrítica ens els nostres models de síndrome de Down.
2. L’estudi de neurones individuals, la seva diversitat i propietats morfològiques d’escala mesoscòpica en el model murí TgDyrk1A de síndrome de Down.
3. El desenvolupament d’un marc experimental i computacional per a l’estudi del problema des d’una perspectiva multi-escala.
La meva feina ha mostrat que l’arquitectura dendrítica i la distribució de contactes sinàptics tenen implicacions significatives en l’optimalitat de neurones individuals per a l’eficiència en el processat d’informació i per a la capacitat d’emmagatzemar memòries, i que aquestes dues quantitats permeen al nivell de xarxa, determinant les capacitats computacionals de conjunts de neurones.
També, he trobat variacions neuromorfològiques a CA1 dependents de la posició en neurones piramidals, acompanyades per variacions en densitat cel·lular, apuntat que propietats intrínseques de CA1 poden variar al llarg de la seva extensió. Aquestes inhomogeneitats eren diferents en ratolins sans i TgDyrk1A, possiblement tenint efectes en aspectes funcionals emergents concrets.
xiv
En la meva Tesi he afrontat reptes en lligar estructura i funció i en l’estudi de les inhomogeneïtats morfològiques en múltiples escales (de cèl·lula individual i de poblacions). Per a assolir aquests reptes, he desenvolupat mètodes computacionals per al mapejat 3D de poblacions cel·lulars i de densitats dendrítiques i he avaluat la seva validesa. També he desenvolupat un marc de modelització que permet l’instanciació multi-escala de xarxes neuronals biològicament realistes. Finalment, he optimitzat la tècnica de clarejat de cervell sencer CLARITY i he desenvolupat un pipeline per a aplicar les nostres eines d’anàlisi de poblacions i els mètodes multi-escala de model·lizatió per a l’anàlisi estructural de cervells sencers, i per a l’estudi de les implicacions del morfoespai neuronal en la topologia de la circuiteria neuronal.Programa de doctorat en Biomedicin
Non-homogenous axonal bouton distribution in whole-brain single cell neuronal networks
No full text<p>We examined the distribution of pre-synaptic contacts in axons of mouse neurons and constructed whole-brain single-cell neuronal networks using an extensive dataset of 1891 fully reconstructed neurons. We found that bouton locations were not homogeneous throughout the axon and among brain regions. As our algorithm was able to generate whole-brain single-cell connectivity matrices from full morphology reconstruction datasets, we further found that non-homogeneous bouton locations have a significant impact on network wiring, including degree distribution, triad census and community structure. By perturbing neuronal morphology, we further explored the link between anatomical details and network topology. In our in-silico exploration, we found that dendritic and axonal tree span would have the greatest impact on network wiring, followed by synaptic contact deletion. Our results suggest that neuroanatomical details must be carefully addressed in studies of whole brain networks at the single cell level. </p>
<p>We provide here the tags information, important intermediate variables and related data that were used for the analysis of the paper "Non-homogenous axonal bouton distribution in whole-brain single cell neuronal networks" in submission.</p>
<p>Table S1: Full names of all cell types involved, acronyms, number of neurons, and average bouton density.<br>Table S2: Comparison between the bouton density calculated from our data and other articles.<br>Table S3: Statistical tests in Figure 3, including correlation and independence statistical test of degree distribution and triad census among different networks.<br>Table S4: Network analysis results: average path length,clustering coefficient, hubs and authorities scores and triad census. </p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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