Data from: Psilocin fosters neuroplasticity in iPSC-derived human cortical neurons

This dataset comprises a collection of structured Excel files containing
quantitative measurements used to generate the graphs of the associated
study on psilocin-induced neuronal plasticity. The data originate from
experiments performed on human cortical neurons differentiated from
induced pluripotent stem cells (iPSCs) derived from independent donors
(cell lines). Each dataset is organized in tabular format and includes
standardized variables describing experimental conditions and outcomes.
Core variables include State (health status), State_Nr (cell line
identifier), State_State_Nr_combined (combined identifier), Batch
(independent differentiation rounds), Treatment (encoded experimental
conditions), and one or more dependent variables representing measured
outcomes. These outcomes include morphological and functional readouts
such as BDNF particle density per neurite length, protein levels (e.g.,
Akt, pAkt), neurite complexity metrics, synaptic protein distribution, and
electrophysiological properties (e.g., action potentials, synaptic
currents). Treatment conditions are numerically encoded and correspond to
defined experimental paradigms, including psilocin exposure,
pharmacological co-treatments (e.g., ketanserin, dynasore and
chelerythrine), and control conditions, as described in accompanying
README file. The dataset captures measurements across multiple time points
and experimental replicates, including biological replicates (distinct
donors) and technical replicates.  The data enable
reproducibility of published figures and support statistical
re-evaluation. Due to the use of human-derived cell lines, the dataset is
de-identified, does not contain personal or sensitive information, and
does not allow any conclusions to be drawn about individual donors.