(A) Top: Schematic of reversal learning task. In the first phase, CS1 but not CS2 is paired with US, while during reversal the contingencies are reversed. Preference between CS1 and CS2 is compared in the test phase. Bottom: Example MBON and DAN activity during reversal learning. (B) The average difference in reported valence for CS2 vs. CS1. Positive or negative values for positive or negative-valence US, respectively, indicate successful reversal learning. Bars indicate standard deviation across model networks. (EPS)</p
The ability to change an established stimulus-behavior association based on feedback is critical for...
<p>(A) Schematic representation of the behavioral training and testing protocol. The rewarded and un...
<p>Boxplots showing the characteristics of the dense collar (<i>blue</i>) and lip (<i>orange</i>) of...
(A) Behavior of output neurons (MBONs) during first-order conditioning. During training, a CS+ (blue...
<p><b>A.</b> The schematic diagram of the model. The network is composed of three parts: input layer...
This repository contains re-test data for a reversal learning task completed by 150 participants, an...
(a)–(c) show the performance of an agent with a value of model decay determined by state-action pred...
<p>(A) When each trial begins, one of the two stimuli, or , is presented in random on a screen. The...
<p>(A) Schematic representation of the behavioural training and testing protocol. The rewarded and u...
<p>(<b>A</b>) Probabilistic Reversal Learning task, showing types of feedback events. (<b>B</b>) RL ...
■ The ability to change an established stimulus–behavior association based on feedback is critical f...
<p><b>(a)</b> Each trial is composed of a cue stimulus presentation, during which the behavioural re...
(A) Behavior during first-order conditioning, similar to Fig 3A, but for a non-plastic network. Beca...
from simple to complex • Reversal learning illustrates a very simple yet computationally challenging...
Humans are capable of correcting their actions based on actions performed in the past, and this abil...
The ability to change an established stimulus-behavior association based on feedback is critical for...
<p>(A) Schematic representation of the behavioral training and testing protocol. The rewarded and un...
<p>Boxplots showing the characteristics of the dense collar (<i>blue</i>) and lip (<i>orange</i>) of...
(A) Behavior of output neurons (MBONs) during first-order conditioning. During training, a CS+ (blue...
<p><b>A.</b> The schematic diagram of the model. The network is composed of three parts: input layer...
This repository contains re-test data for a reversal learning task completed by 150 participants, an...
(a)–(c) show the performance of an agent with a value of model decay determined by state-action pred...
<p>(A) When each trial begins, one of the two stimuli, or , is presented in random on a screen. The...
<p>(A) Schematic representation of the behavioural training and testing protocol. The rewarded and u...
<p>(<b>A</b>) Probabilistic Reversal Learning task, showing types of feedback events. (<b>B</b>) RL ...
■ The ability to change an established stimulus–behavior association based on feedback is critical f...
<p><b>(a)</b> Each trial is composed of a cue stimulus presentation, during which the behavioural re...
(A) Behavior during first-order conditioning, similar to Fig 3A, but for a non-plastic network. Beca...
from simple to complex • Reversal learning illustrates a very simple yet computationally challenging...
Humans are capable of correcting their actions based on actions performed in the past, and this abil...
The ability to change an established stimulus-behavior association based on feedback is critical for...
<p>(A) Schematic representation of the behavioral training and testing protocol. The rewarded and un...
<p>Boxplots showing the characteristics of the dense collar (<i>blue</i>) and lip (<i>orange</i>) of...