BCI Toolbox is a Python implementation of the hierarchical Bayesian Causal Inference (BCI) model for multisensory research. BCI model is a statistical framework for understanding the causal relationships between sensory inputs and prior expectations of a common cause, which can account for human perception in a number of tasks, including temporal numerosity judgment (Shams et al., 2005; Wozny et al., 2008), spatial localization judgment (Körding et al., 2007; Wozny & Shams, 2011), size-weight illusion paradigm (Peters et al., 2016), rubber-hand illusion paradigm (Chancel et al., 2022; Chancel & Ehrsson, 2023).
Release files for bcitoolbox 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bcitoolbox-0.3.0.tar.gz | 500.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bcitoolbox-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.0 MB
Release files / bcitoolbox-0.3.0.tar.gz
| Download URL | bcitoolbox-0.3.0.tar.gz |
|---|---|
| Size | 500.9 kB |
| Tags | Source |
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twine/4.0.2 CPython/3.9.13
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Release files / bcitoolbox-0.3.0-py3-none-any.whl
| Download URL | bcitoolbox-0.3.0-py3-none-any.whl |
|---|---|
| Size | 519.9 kB |
| Tags | Python 3 |
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twine/4.0.2 CPython/3.9.13
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