ArticleFrontiers in neural circuits2013
A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.
Article in Frontiers in neural circuits, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed.
- Antifragile control systems in neuronal processing: a sensorimotor perspective.Biological cybernetics · 2025Review
- Goal-directed vocal planning in a songbird.eLife · 2024Article
- Article
- How the conception of control influences our understanding of actions.Nature reviews. Neuroscience · 2023Review
- Resonance as a Design Strategy for AI and Social Robots.Frontiers in neurorobotics · 2022Article
- Learning to Expect: Predicting Sounds During Movement Is Related to Sensorimotor Association During Listening.Frontiers in human neuroscience · 2019Article
- The Craving and Excitement of Social Networking Sites Addicts: Based on Cue-Reactivity.Frontiers in psychology · 2019Article
- Building a state space for song learning.Current opinion in neurobiology · 2018Review
- Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.eLife · 2017Article
- A Neural Code That Is Isometric to Vocal Output and Correlates with Its Sensory Consequences.PLoS biology · 2016Article
- Toward an Integration of Deep Learning and Neuroscience.Frontiers in computational neuroscience · 2016Article
- A Comprehensive Account of Sound Sequence Imitation in the Songbird.Frontiers in computational neuroscience · 2016Article
- A Duet for one.Consciousness and cognition · 2015Review
- Naturalistic stimulation drives opposing heterosynaptic plasticity at two inputs to songbird cortex.Nature neuroscience · 2015Article
- Vocal motor changes beyond the sensitive period for song plasticity.Journal of neurophysiology · 2014Article
- Thinking in circuits: toward neurobiological explanation in cognitive neuroscience.Biological cybernetics · 2014Review
- Evidence for a causal inverse model in an avian cortico-basal ganglia circuit.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- Auditory synapses to song premotor neurons are gated off during vocalization in zebra finches.eLife · 2014Article
- An automated procedure for evaluating song imitation.PloS one · 2014Article
- Closed-loop neuroscience and neuroengineering.Frontiers in neural circuits · 2014Article
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3 authors.
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Abstract
Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.
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