Iowa-Gambling Task use-case

docs/source/learn.md

@@ -186,32 +186,40 @@ Examples of possible applications and extensions of the standards Hierarchical G
 ::::{grid} 1 1 2 3
 :gutter: 1
 
-:::{grid-item-card}  Inferring cardiac beliefs using Bayesian filtering
+:::{grid-item-card} Inferring cardiac beliefs using Bayesian filtering
 :link: example_1
 :link-type: ref
 
 Application of continuous Bayesian filtering to cardiac physiological recordings to infer interoceptive beliefs and their volatility.
 
 :::
 
-:::{grid-item-card}  Value and volatility coupling with an input node
+:::{grid-item-card} Value and volatility coupling with an input node
 :link: example_2
 :link-type: ref
 :img-top: ./images/input_mean_precision.png
 
 Dynamic inference over both the mean and variance of a normal distribution.
 :::
 
-:::{grid-item-card}  Multi-armed bandit task with independent reward and punishments
+:::{grid-item-card} Multi-armed bandit task with independent reward and punishments
 :link: example_3
 :link-type: ref
 :img-top: ./images/multiarmedbandittask.png
 
 A generalisation of the binary Hierarchical Gaussian Filter to multiarmed bandit where the probabilities of the outcomes are evolving independently.
 :::
 
+### Non-parametric predictive coding
+
+::::{grid} 1 1 2 3
+
+:::{grid-item-card} Self-organizing neural network using Dirichlet Process nodes
+:link: example_3
+=======
 :::{grid-item-card}  Causal discovery for predictive coding
 :link: example_4
+
 :link-type: ref
 :img-top: ./images/causal_discovery.png