Informatics ePosters

Neural simulations using NEST are typically executed by a Python script that configures the simulator kernel, builds the network, and runs the simulation. The result is a series of files containing the simulated network activity, which can then be analyzed to provide insights into the neural activity. Despite the…

Scientific progress increasingly relies on interdisciplinary collaborations as experimental and simulation datasets grow in complexity. However, these datasets are often underutilized due to inadequate solutions for data management, sharing, and analysis. Existing solutions address different aspects of the data…

Even with complete knowledge of the underlying wiring diagram using electron microscopy and the neuronal activity through $in~vivo$ recordings, we can only ever correlate neuron function with participation in the various non-random motifs that have been characterized [1, 2]. Causation, however, can only be proven by…

A growing number of neuroimaging tools are being developed to enable data analysis in a more tool-independent manner when analyzing three- and four-dimensional brain imaging data in various statistical settings. Ideally, such tools still offer user interfaces that are accessible to those with a basic understanding of…

Joint exploration of behavior, genes and brain structure holds the promise to provide a better understanding of neural circuits than unimodal data analyses. Several consortia provide extensive data resources of different modalities. However, analyses of heteromodal data require the expertise of computer scientists for…

Quantitative microscopy workflows have evolved dramatically over the last years, progressively becoming more complex with the emergence of deep learning. Long-standing challenges like 3D segmentation of dense microscopy data can finally be addressed, and new imaging modalities are breaking records in both resolution…

Closed-loop neuroscience experimentation, where recorded neural activity is used to modify the experiment on-the-fly, is critical for deducing causal connections and optimizing experimental time. A critical step in creating a closed-loop experiment is real-time inference of neural activity from streaming recordings.…

Advances in computer vision and deep learning have made it possible to gather markerless pose estimation data from consumer-grade cameras. Accessible software tools, such as DeepLabCut, have made it possible to include behavioral pose as one data modality in larger neuroscience projects. Staying at the leading edge of…

The INCF TrainingSuite is a collection of three open access platforms that aims to facilitate self-guided study in different sub-specialisms of neuroscience, data science, and open science. These platforms, presented below, form a framework for integrating training materials and making them FAIR: Findable, Accessible,…