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Giray, I.

Publications and source records attributed to Giray, I..

2 recordsLinked to original sources

Overarching Programs that Frame Episodes of Focused Cognition

Our goals are achieved through extended task episodes. While its well recognized that such episodes are controlled and executed as a single unit, how this is achieved remains unclear. Key observations during the execution of extended episodes - increased reaction time at episode beginnings and widespread neural activation at episode completions - have suggested that some additional, episode-related goings-on may occur at the beginning and the end. We found that when participants executed episodes of different durations, but involving trials identical in every aspect, distinct episodes elicited distinct activity patterns across the entire cortex at their beginnings as well as at their completions, showing that information related to the overarching episode floods the cortex at these junctures and evidencing a program related to the entire episode that got instated and dismantled when episodes begin and complete. This episode-related program was distinct from rules, contexts, working memory contents, and representations of identity and position of steps - issues well recognized to have a role in task execution and known to elicit distinct activity patterns in frontoparietal regions that typically activate during task execution. Unlike these issues, this program was discernible not only in frontoparietal regions but across the entire cortex, regardless of the level of univariate activation exhibited by that region, indicating that the dynamics of this program involved a massive resetting of neural activity across the entire cortex.

neuroscience↗

InSituPy -- A framework for histology-guided, multi-sample analysis of single-cell spatial transcriptomics data

Single-cell spatial transcriptomics (scST) methodologies allow, in combination with histological stainings, an unprecedented view on disease progression. To comprehensively analyze scST data, bioinformatic analysis frameworks need to integrate the diverse set of data modalities and, just as importantly, enable the joint analysis of multiple datasets from clinical or experimental cohorts together with its corresponding metadata. Here, we present the InSituPy framework to comprehensively analyze single-cell spatial transcriptomic data from a multi-sample level down to the cellular and subcellular level. The framework contains analysis workflows for the integration of image data as well as pathological and biological expert knowledge. Increasing the accessibility of the data for non-bioinformaticians, the framework opens new ways of generating hypotheses, especially in the context of translational research.

bioinformatics↗