About

Takaki Komiyama is a researcher focused on understanding how animals modify their behavior through experience, emphasizing the activity of neuronal ensembles in behaving animals and how this activity changes with learning. His laboratory studies the plasticity of neuronal microcircuits during learning processes, utilizing advanced techniques such as in vivo two-photon calcium imaging, optogenetics, electrophysiology, genetics, and behavioral analysis. His work has revealed that neurons with diverse task-related response types are spatially intermingled in the motor cortex, and that activity coupling among neurons with similar response types increases during learning, suggesting the formation of intermingled subnetworks of functionally-related neurons in a learning-related manner. His research extends to exploring the cellular and molecular mechanisms underlying microcircuit plasticity, the extent of neuronal activity changes over days to weeks, and the necessity of observed activity and plasticity for learning. Through his contributions, he advances the understanding of neural circuit dynamics and plasticity in the context of learning and memory formation.

Research topics

• Neuroscience
• Computer Science
• Psychology
• Biology
• Artificial Intelligence
• Materials science
• Paleontology
• Chemistry
• Optoelectronics
• Physics
• Cell biology
• Nanotechnology
• Data science
• Telecommunications

Selected publications

• Complementary cortical and thalamic contributions to cell type–specific striatal activity dynamics during movement

  Science Advances · 2026-01-28

  articleOpen accessSenior authorCorresponding

  Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs drive cell type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) with distinct roles in movement control. In mice performing skilled locomotion, we recorded from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing. A recurrent neural network (RNN) classifier and clustering analysis revealed functionally heterogeneous subpopulations in each population, with dMSNs preferentially activated at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially activated during onset/offset and execution, respectively, though dMSN- and iMSN-projecting neurons in each region showed similar patterns. Locomotion phase-specific rhythmic activity was found in a subset of thalamic dMSN-projecting neurons and dMSNs. Cortex or thalamus inactivation reduced MSN activity. These findings suggest that corticostriatal and thalamostriatal inputs convey complementary motor signals via shared and cell type-specific pathways.

  PublisherDOI

• Adaptive reorganization of history encoding in the retrosplenial cortex supports flexible decision-making strategies

  Neuron · 2026-05-01

  articleSenior author
  PublisherDOI

• Complementary cortical and thalamic contributions to cell-type-specific striatal activity dynamics during movement

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-17

  preprintSenior author

  Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs drive cell-type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) with distinct roles in movement control. In mice performing skilled locomotion, we recorded from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing. An RNN classifier and clustering analysis revealed functionally heterogeneous subpopulations in each population, with dMSNs preferentially activated at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially activated during onset/offset and execution, respectively, though dMSN- and iMSN-projecting neurons in each region showed similar patterns. Locomotion phase-specific rhythmic activity was found in a subset of thalamic dMSN-projecting neurons and dMSNs. Cortex or thalamus inactivation reduced MSN activity. These findings suggest that corticostriatal and thalamostriatal inputs convey complementary motor signals via shared and cell-type-specific pathways.

  PublisherDOI

• Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning

  Science · 2025-04-17 · 51 citations

  articleOpen accessSenior authorCorresponding

  Synaptic plasticity underlies learning by modifying specific synaptic inputs to reshape neural activity and behavior. However, the rules governing which synapses will undergo different forms of plasticity in vivo during learning and whether these rules are uniform within individual neurons remain unclear. Using in vivo longitudinal imaging with single-synapse resolution in the mouse motor cortex during motor learning, we found that apical and basal dendrites of layer 2/3 (L2/3) pyramidal neurons showed distinct activity-dependent synaptic plasticity rules. The strengthening of apical and of basal synapses is predicted by local coactivity with nearby synapses and activity coincident with postsynaptic action potentials, respectively. Blocking postsynaptic spiking diminished basal synaptic potentiation without affecting apical plasticity. Thus, individual neurons use multiple activity-dependent plasticity rules in a compartment-specific manner in vivo during learning.

  PublisherOA PDFDOI

• Como seu cérebro cria novas memórias? Neurocientistas descobrem “regras” de como os neurônios codificam novas informações

  2025-04-25

  preprintOpen accessSenior author
  PublisherDOI

• Targeted stimulation of motor cortex neural ensembles drives learned movements

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-06 · 1 citations

  preprintOpen accessSenior authorCorresponding

  Abstract During the execution of learned motor skills, the neural population in the layer 2/3 (L2/3) of the primary motor cortex (M1) expresses a reproducible spatiotemporal activity pattern. It is debated whether M1 actively participates in generating the activity pattern or it only passively reflects patterned inputs. Furthermore, it is unclear whether this learned activity pattern causally drives the learned movement. We addressed these issues using in vivo two-photon calcium imaging combined with holographic optogenetic stimulation of specific ensembles of M1 L2/3 neurons in mice engaged in a skilled lever-press task. We briefly and synchronously stimulated ∼20 neurons whose activity onset in voluntary trials precedes movement onsets. This stimulation, despite lacking temporal patterns, induced movements that resembled the learned movement, while producing spatiotemporal activity patterns in other M1 neurons not directly stimulated that resembled the activity during the voluntary learned movement. Trial-by-trial variability of optogenetically triggered population activity in the non-target neurons correlated with the variability in the induced movements. These trial-by-trial variabilities were predicted by the initial state of M1 population activity immediately preceding the optogenetic stimulation. Stimulation of the neurons whose activity followed voluntary movement onsets failed to induce the learned movement. Thus, the learned activity pattern in M1 L2/3 can be generated when the M1 network is prepared at the optimal initial state and receives precise triggering inputs, supporting the active role of M1 in learned activity generation. The resulting activity pattern then causally drives the learned movement.

  PublisherOA PDFDOI

• Complementary cortical and thalamic contributions to cell-type-specific striatal activity dynamics during movement

  Zenodo (CERN European Organization for Nuclear Research) · 2025-12-22

  otherOpen accessSenior author

  Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs influence cell-type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) that exhibit distinct roles in movement control, and receives converging cortical and thalamic inputs. We performed 2-photon imaging from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing, as mice executed a skilled locomotion task. We used recurrent neural network (RNN) classifiers and hierarchical clustering analyses to reveal functionally heterogeneous subpopulations in each population. We found that dMSNs were preferentially active at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially active during onset/offset and execution, respectively. dMSN- and iMSN-projecting neurons in each region showed similar trial-averaged activity patterns, although single-trial features might contribute to cell-type-specific differences. Furthermore, a subset of thalamic neurons projecting to dMSNs encoded rhythmic limb movements in a locomotion phase-specific manner, a pattern also found in a small subset of dMSNs. Inactivation of either cortex or thalamus substantially reduced MSN activity. These results suggest that corticostriatal and thalamostriatal inputs contribute complementary motor-related information via shared and cell-type-specific pathways.

  PublisherDOI

• Complementary cortical and thalamic contributions to cell-type-specific striatal activity dynamics during movement

  DRYAD · 2025-12-18

  datasetOpen accessSenior author

  Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs influence cell-type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) that exhibit distinct roles in movement control, and receives converging cortical and thalamic inputs. We performed 2-photon imaging from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing, as mice executed a skilled locomotion task. We used recurrent neural network (RNN) classifiers and hierarchical clustering analyses to reveal functionally heterogeneous subpopulations in each population. We found that dMSNs were preferentially active at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially active during onset/offset and execution, respectively. dMSN- and iMSN-projecting neurons in each region showed similar trial-averaged activity patterns, although single-trial features might contribute to cell-type-specific differences. Furthermore, a subset of thalamic neurons projecting to dMSNs encoded rhythmic limb movements in a locomotion phase-specific manner, a pattern also found in a small subset of dMSNs. Inactivation of either cortex or thalamus substantially reduced MSN activity. These results suggest that corticostriatal and thalamostriatal inputs contribute complementary motor-related information via shared and cell-type-specific pathways.

  PublisherDOI

• Cholinergic feedback for modality- and context-specific modulation of sensory representations

  Science · 2025-06-19 · 3 citations

  articleSenior authorCorresponding

  The brain's ability to prioritize sensory information is crucial for adaptive behavior, yet its mechanisms remain unclear. We investigated basal forebrain cholinergic neurons modulating olfactory bulb (OB) circuits in mice. The activity of cholinergic feedback axons in OB correlated with orofacial movements, with little responses to passively experienced odors. When mice engaged in an olfactory task, OB cholinergic axons rapidly shifted their response patterns from movement correlated to odor aligned. This response shift was absent in cholinergic axons projecting to the dorsal cortex during olfactory task engagement, and in OB, during an auditory task. Inactivation of OB-projecting cholinergic neurons impaired olfactory task performance and reduced odor responses in OB granule cells. Thus, the cholinergic system dynamically modulates sensory processing in a modality-specific and context-dependent manner.

  PublisherDOI

• How does your brain create new memories? Neuroscientists discover ‘rules’ for how neurons encode new information

  2025-04-17

  articleOpen accessSenior author
  PublisherDOI

Recent grants

• Collaborative Research: MEMONET: Understanding memory in neuronal networks through a brain-inspired spin-based artificial intelligence

  NSF · $435k · 2019–2022

• Cortical Control of Motor Learning

  NIH · $3.7M · 2015–2025

• NIH Grant U01NS094342

  NIH · $3.0M · 2018

• Inter-area communications in a decision-making circuit

  NIH · $158k · 2020–2022

• Collaborative Research: Autonomous Computing Materials

  NSF · $346k · 2019–2022

Frequent coauthors

• Liqun Luo

  Howard Hughes Medical Institute

  24 shared

• Chi Ren

  University of California, San Diego

  20 shared

• Eun Jung Hwang

  17 shared

• Ryoma Hattori

  University of California, San Diego

  15 shared

• Duygu Kuzum

  University of California, San Diego

  14 shared

• Xin Liu

  University of California, San Diego

  14 shared

• Nathan G. Hedrick

  University of California, San Diego

  10 shared

• Lora B. Sweeney

  Institute of Science and Technology Austria

  9 shared

Education

• PhD, Neurosciences

  Stanford University

  2006

• BS, Biochemistry

  University of Tokyo

  2001