Validation and Refinement of a Laminar Neural Mass Model Using in vivo Mice Data

Treballs Finals de Màster en Física dels Sistemes Complexos i Biofísica, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Tutors: Pau Clusella Cober1ó Roser Sánchez-Todo, Jordi Soriano FraderaGamma oscillations (30-80 Hz) play a crucial role in cognitive functions and are associated with neurological disorders, including Alzheimer’s disease. Non-invasive brain stimulation techniques, such as 40 Hz transcranial alternating current stimulation (tACS), offer potential in modulating these oscillations and impact cognitive functions. The complexity of the brain, however, necessitates the use of advanced models for effective understanding and the development of therapies. This study aims to validate a framework combining Neural Mass Models (NMMs) with volume conduction physics that takes into account the brain’s physical properties and the distribution of synapses across cortical layers. The validation involves predicting a synaptic distribution across various neuronal groups and employing a Genetic Algorithm (GA) to iteratively refine the model to match experimental data. Key findings include the ability of the NMM to achieve greater similarity with experimental results by varying stochastic noise and the dominance of gamma and alpha oscillations in experimental data aligning well with model predictions. The GA also shows robustness in fitting the model to experimental data, and the predicted synaptic distribution is evaluated against existing literature for physiological accuracy. Despite limitations, our enhanced NMM provides valuable insights into cortical layer interactions, contributing to the understanding of human brain function and the development of treatments for neurological disorders

Long-term calcium imaging reveals functional development in hiPSC derived cultures comparable to human but not rat primary cultures

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutor: Jordi Soriano FraderaHuman brains are often modelled based on primary cultures from rodents, mostly rats, which do not replicate well its complexity. Here, the advantages of neuronal cultures derived from human induced pluripotent stem cells (hiPSCs) are studied and compared with rat and human primary cultures. Data is obtained from spontaneous activity recordings using calcium fluorescence imaging, and analysed in the context of complex networks to obtain the functional connectivity traits of the different conditions. hiPSCs cultures showed rich activity patterns and functional features. Ratcultures, by contrast, had a very rigid activity and poor functional traits. Human primary cultures had a similar behaviour as hiPSCs. Our study shows that hiPSC technology is an excellent tool to model human–like networks in vitro, which may help to better model alterations caused by damage or neurodegeneratio

Long-term calcium imaging reveals functional development in hiPSC-derived cultures comparable to human but not rat primary cultures

Models for human brain-oriented research are often established on primary cultures from rodents, which fails to recapitulate cellular specificity and molecular cues of the human brain. Here we investigated whether neuronal cultures derived from human induced pluripotent stem cells (hiPSCs) feature key advantages compared with rodent primary cultures. Using calcium fluorescence imaging, we tracked spontaneous neuronal activity in hiPSC-derived, human, and rat primary cultures and compared their dynamic and functional behavior as they matured.We observed that hiPSC-derived cultures progressively changed upon development, exhibiting gradually richer activity patterns and functional traits. By contrast, rat primary cultures were locked in the same dynamic state since activity onset. Human primary cultures exhibited features in between hiPSC-derived and rat primary cultures, although traits from the former predominated. Our study demonstrates that hiPSC-derived cultures are excellent models to investigate development in neuronal assemblies, a hallmark for applications that monitor alterations caused by damage or neurodegeneration