ABSTRACT—Contemporary theories of learning typically assume that learning is driven by prediction errors—in other words, that we learnmorewhen our predictions turn out to be incorrect than we do when our predictions are correct. Results from the recording of electrical brain ac-tivity suggest one mechanism by which this might happen; we seem to direct visual attention toward the likely causes of previous prediction errors. This can happen very rap-idly—within less than 200milliseconds of the error-causing object being presented. It is tempting to infer that if learning is driven by prediction errors, then little can be learned in the absence of feedback. Such a conclusion is unwarranted. In fact, the substantial learning that is sometimes t...
Learning from past mistakes is of prominent importance for successful future behavior. In the presen...
Abstract. Infrequent events, such as unexpected absence of outcomes (prediction errors), have a detr...
Predictive coding models of perception suggest that predicted sensory signals are attenuated (silenc...
Prediction error (‘‘surprise’’) affects the rate of learning: We learn more rapidly about cues for w...
Prediction error ("surprise") affects the rate of learning: We learn more rapidly about cues for whi...
Prediction error ("surprise") affects the rate of learning: We learn more rapidly about cues for whi...
The encoding of sensory information in the human brain is thought to be optimised by two principal p...
The encoding of sensory information in the human brain is thought to be optimised by two principal p...
Item does not contain fulltextReinforcement learning (RL) theory states that learning is driven by p...
Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demons...
Prediction errors (PE) are a central notion in theoretical models of reinforcement learning, percept...
Confronted with a rich sensory environment, the brain must learn statistical regularities across sen...
Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demons...
Item does not contain fulltextLearning from past mistakes is of prominent importance for successful ...
Confronted with a rich sensory environment, the brain must learn statistical regularities across sen...
Learning from past mistakes is of prominent importance for successful future behavior. In the presen...
Abstract. Infrequent events, such as unexpected absence of outcomes (prediction errors), have a detr...
Predictive coding models of perception suggest that predicted sensory signals are attenuated (silenc...
Prediction error (‘‘surprise’’) affects the rate of learning: We learn more rapidly about cues for w...
Prediction error ("surprise") affects the rate of learning: We learn more rapidly about cues for whi...
Prediction error ("surprise") affects the rate of learning: We learn more rapidly about cues for whi...
The encoding of sensory information in the human brain is thought to be optimised by two principal p...
The encoding of sensory information in the human brain is thought to be optimised by two principal p...
Item does not contain fulltextReinforcement learning (RL) theory states that learning is driven by p...
Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demons...
Prediction errors (PE) are a central notion in theoretical models of reinforcement learning, percept...
Confronted with a rich sensory environment, the brain must learn statistical regularities across sen...
Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demons...
Item does not contain fulltextLearning from past mistakes is of prominent importance for successful ...
Confronted with a rich sensory environment, the brain must learn statistical regularities across sen...
Learning from past mistakes is of prominent importance for successful future behavior. In the presen...
Abstract. Infrequent events, such as unexpected absence of outcomes (prediction errors), have a detr...
Predictive coding models of perception suggest that predicted sensory signals are attenuated (silenc...