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translationalneuromodeling / tapas

TAPAS - Translational Algorithms for Psychiatry-Advancing Science
https://translationalneuromodeling.github.io/tapas/
GNU General Public License v3.0
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Interpretation of HGF output #33

Closed cmill22 closed 3 years ago

cmill22 commented 5 years ago

Dear Dr Mathys,

I am a complete novice in computational modelling and the HGF and have been struggling to understand what some of the Greek symbols represent in the model output when fitting the HGF to some practice, continuous data. For example, in the 'p_prc' output file (mu_0, sigma_0, rho, om, pi_u etc) and in the 'traj' output file (e.g. muhat, sigma hat etc). Would you be able to explain what these symbols, or some of the key symbols, represent in the model?

Thank you so much for your kind help,

Chantal

chmathys commented 5 years ago

Dear Chantal,

These are explained in the model-specific documentation in the initial comment section of tapas_hgf_config.m You will find more on these quantities in the following papers:

Mathys, C., Daunizeau, J., Friston, K.J., Stephan, K.E., 2011. A Bayesian foundation for individual learning under uncertainty. Front. Hum. Neurosci. 5, 39. https://doi.org/10.3389/fnhum.2011.00039

Mathys, C., Lomakina, E.I., Daunizeau, J., Iglesias, S., Brodersen, K.H., Friston, K.J., Stephan, K.E., 2014. Uncertainty in perception and the Hierarchical Gaussian Filter. Front. Hum. Neurosci 8, 825. https://doi.org/10.3389/fnhum.2014.00825

Best wishes, Christoph

On 16 November 2018 at 5:44:49 pm, cmill22 (notifications@github.com) wrote:

Dear Dr Mathys,

I am a complete novice in computational modelling and the HGF and have been struggling to understand what some of the Greek symbols represent in the model output when fitting the HGF to some practice, continuous data. For example, in the 'p_prc' output file (mu_0, sigma_0, rho, om, pi_u etc) and in the 'traj' output file (e.g. muhat, sigma hat etc). Would you be able to explain what these symbols, or some of the key symbols, represent in the model?

Thank you so much for your kind help,

Chantal

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