Neurobiological Data
neurobiological data
Antonio C. Roque
The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), hosted by the University of São Paulo (USP), Brazil, and funded by the São Paulo Research Foundation (FAPESP), is offering two post-doctoral fellowships for recent PhDs with outstanding research potential. The fellowship will involve collaborations with research teams and laboratories associated with NeuroMat, strictly related to ongoing research lines developed by NeuroMat. The project may be developed at the laboratories of USP, campuses of São Paulo or Ribeirão Preto, or at UNICAMP, Campinas, in person. We seek candidates capable of developing independent research in one of the research lines below. 1. Stochastic modeling of neurobiological data. Candidates must have a strong background in probability theory with emphasis on stochastic processes. 2. Development of new statistical methods for neurobiological data. Candidates must have a strong background in statistics and data analysis and knowledge of computer programming. 3. Acquisition, processing, and quantitative analysis of neurobiological data. Candidates must have a strong background in neuroscience with previous experience in neurophysiological data acquisition, processing and analysis, and knowledge of computer programming. 4. Instrumentation development associated with brain stimuli. Candidates must have a strong background in electronic instrumentation, robotics, programing, and safety in medical equipment. The fellowship is competitive at an international level, and fellows benefit from extra funds for travel and research expenses plus limited support for relocation expenses.
Through the bottleneck: my adventures with the 'Tishby program'
One of Tali's cherished goals was to transform biology into physics. In his view, biologists were far too enamored by the details of the specific models they studied, losing sight of the big principles that may govern the behavior of these models. One such big principle that he suggested was the 'information bottleneck (IB) principle'. The iIB principle is an information-theoretical approach for extracting the relevant information that one random variable carries about another. Tali applied the IB principle to numerous problems in biology, gaining important insights in the process. Here I will describe two applications of the IB principle to neurobiological data. The first is the formalization of the notion of surprise that allowed us to rigorously estimate the memory duration and content of neuronal responses in auditory cortex, and the second is an application to behavior, allowing us to estimate 'optimal policies under information constraints' that shed interesting light on rat behavior.
The Impact of Racism-related Stress on Neurobiological Systems in Black Americans”
Black Americans experience diverse racism-related stressors throughout the lifespan. Disproportionately high trauma exposure, economic disadvantage, explicit racism and inequitable treatment are stressors faced by many Black Americans. These experiences have a cumulative negative impact on psychological and physical health. However, little is understood about how experiences of racism, such as discrimination, can mediate health outcomes via their effects on neurobiology. I will present clinical, behavioral, physiological and neurobiological data from Black American participants in the Grady Trauma Project, a longstanding study of trauma conducted in inner-city Atlanta. These data will be discussed in the context of both risk and resilience/adaptation perspectives. Finally, recommendations for future clinical neuroscience research and targets for intervention in marginalized populations will be discussed.
Accurate detection of spiking motifs in neurobiological data by learning heterogeneous delays of a spiking neural network
FENS Forum 2024
Self-supervised learning of spiking motifs in neurobiological data
FENS Forum 2024