Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.
نویسندگان
چکیده
Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.
منابع مشابه
Reward Hierarchical Temporal Memory Model for Memorizing and Computing Reward Prediction Error by Neocortex
In humans and animals, reward prediction error encoded by dopamine systems is thought to be important in the temporal difference learning class of reinforcement learning (RL). With RL algorithms, many brain models have described the function of dopamine and related areas, including the basal ganglia and frontal cortex. In spite of this importance, how the reward prediction error itself is compu...
متن کاملSurprised at All the Entropy: Hippocampal, Caudate and Midbrain Contributions to Learning from Prediction Errors
Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used...
متن کاملCognitive Science Honors Thesis A Computational Account of Sensory Prediction Error Gating in Reinforcement Learning Models
A successful return in tennis requires a tennis player first to determine where best to place her return and then to correctly execute her swing. If she makes an errant return, she now faces a credit assignment problem: Should this negative outcome be attributed to poor shot selection or to an error in motor execution? McDougle et al. propose a solution to this problem when the source of the er...
متن کاملHierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning
In Bayesian brain theories, hierarchically related prediction errors (PEs) play a central role for predicting sensory inputs and inferring their underlying causes, e.g., the probabilistic structure of the environment and its volatility. Notably, PEs at different hierarchical levels may be encoded by different neuromodulatory transmitters. Here, we tested this possibility in computational fMRI s...
متن کاملMFM: Multiple Forward Model Architecture for Sequence Processing
A multiple forward model (MFM) architecture is proposed for sequence identi cation, learning and production. MFM is inspired by Wolpert and Kawato's [ 1998 ] multiple paired forward and inverse models architecture for motor control. In particular, learning of sequencespeci c modules and switching among multiple sequences are demonstrated. Appropriate sequence modules are chosen and maintained o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- The Journal of neuroscience : the official journal of the Society for Neuroscience
دوره 33 13 شماره
صفحات -
تاریخ انتشار 2013