Evidence map›Paper›PMID 29268193›Full record

ReviewCurrent opinion in neurobiology2018

Building a state space for song learning.

Emily Lambert Mackevicius, Michale Sean Fee

Open access · greenAbstract readReview
In one paragraph

Review in Current opinion in neurobiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Note similarities affect syntactic stability in zebra finches.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Point process models for sequence detection in high-dimensional neural spike trains.Advances in neural information processing systems · 2020
    Article
  10. Actor-critic reinforcement learning in the songbird.Current opinion in neurobiology · 2020
    Review
  11. Article
  12. Flexible Multielectrode Arrays With 2-D and 3-D Contacts forIEEE transactions on components, packaging, and manufacturing technology · 2020
    Article
  13. Memory circuits for vocal imitation.Current opinion in neurobiology · 2020
    Review
  14. Article
  15. Article
  16. Article
  17. Fabrication and Characterization of 3D Multi-Electrode Array on Flexible Substrate forTechnical digest. International Electron Devices Meeting · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Emily Lambert MackeviciusDepartment of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, 46-5133 Cambridge, MA, USA.
Michale Sean FeeDepartment of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, 46-5133 Cambridge, MA, USA. Electronic address: fee@mit.edu.
Massachusetts Institute of Technology · USMcGovern Institute for Brain Research · US

Funding

Neuronal Mechanisms of Motor Exploration in the SongbirdR01DC009183 · NIDCD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI FEE, MICHALE S · 2008 to 2017
$3.1M
NIDCD NIH HHS R01 DC009183
6 · The paper itself

Abstract

The songbird system has shed light on how the brain produces precisely timed behavioral sequences, and how the brain implements reinforcement learning (RL). RL is a powerful strategy for learning what action to produce in each state, but requires a unique representation of the states involved in the task. Songbird RL circuitry is thought to operate using a representation of each moment within song syllables, consistent with the sparse sequential bursting of neurons in premotor cortical nucleus HVC. However, such sparse sequences are not present in very young birds, which sing highly variable syllables of random lengths. Here, we review and expand upon a model for how the songbird brain could construct latent sequences to support RL, in light of new data elucidating connections between HVC and auditory cortical areas. We hypothesize that learning occurs via four distinct plasticity processes: 1) formation of 'tutor memory' sequences in auditory areas; 2) formation of appropriately-timed latent HVC sequences, seeded by inputs from auditory areas spontaneously replaying the tutor song; 3) strengthening, during spontaneous replay, of connections from HVC to auditory neurons of corresponding timing in the 'tutor memory' sequence, aligning auditory and motor representations for subsequent song evaluation; and 4) strengthening of connections from premotor neurons to motor output neurons that produce the desired sounds, via well-described song RL circuitry.

Indexed as

AnimalsBrainLearningModels, NeurologicalNeural PathwaysNeuronsReinforcement, PsychologySongbirdsTime FactorsVocalization, Animal

Identifiers

PMID29268193
PMCPMC12216439
OpenAlexW2777933989

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.