Evidence map›Paper›PMID 26944858›Full record

ArticleNeuroImage2016

ICA-derived cortical responses indexing rapid multi-feature auditory processing in six-month-old infants.

Caterina Piazza, Chiara Cantiani, Zeynep Akalin-Acar, Makoto Miyakoshi, April A Benasich, Gianluigi Reni, Anna Maria Bianchi, Scott Makeig

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

21 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

8 authors at 4 institutions in 2 countries.

Caterina PiazzaDepartment of Electronics Information and Bioengineering, Politecnico di Milano, Milano, Italy; Bioengineering Lab, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy. Electronic address: caterina.piazza@polimi.it.
Chiara CantianiDepartment of Developmental Neuropsychology, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy.
Zeynep Akalin-AcarSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
Makoto MiyakoshiSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
April A BenasichCenter for Molecular & Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.
Gianluigi ReniBioengineering Lab, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy.
Anna Maria BianchiDepartment of Electronics Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Scott MakeigSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
IRCCS Eugenio Medea · ITUniversity of California, San Diego · USPolitecnico di Milano · ITRutgers, The State University of New Jersey · US

Funding

EEGLAB: Software for Analysis of Human Brain DynamicsR01NS047293 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Arnaud Delorme, Scott Makeig · 2004 to 2026
$10.2M
NINDS NIH HHS R01 NS047293
6 · The paper itself

Abstract

The abilities of infants to perceive basic acoustic differences, essential for language development, can be studied using auditory event-related potentials (ERPs). However, scalp-channel averaged ERPs sum volume-conducted contributions from many cortical areas, reducing the functional specificity and interpretability of channel-based ERP measures. This study represents the first attempt to investigate rapid auditory processing in infancy using independent component analysis (ICA), allowing exploration of source-resolved ERP dynamics and identification of ERP cortical generators. Here, we recorded 60-channel EEG data in 34 typically developing 6-month-old infants during a passive acoustic oddball paradigm presenting 'standard' tones interspersed with frequency- or duration-deviant tones. ICA decomposition was applied to single-subject EEG data. The best-fitting equivalent dipole or bilaterally symmetric dipole pair was then estimated for each resulting independent component (IC) process using a four-layer infant head model. Similar brain-source ICs were clustered across subjects. Results showed ERP contributions from auditory cortex and multiple extra-auditory cortical areas (often, bilaterally paired). Different cortical source combinations contributed to the frequency- and duration-deviant ERP peak sequences. For ICs in an ERP-dominant source cluster located in or near the mid-cingulate cortex, source-resolved frequency-deviant response N2 latency and P3 amplitude at 6 months-of-age predicted vocabulary size at 20 months-of-age. The same measures for scalp channel F6 (though not for other frontal channels) showed similar but weaker correlations. These results demonstrate the significant potential of ICA analyses to facilitate a deeper understanding of the neural substrates of infant sensory processing.

Indexed as

Data Interpretation, StatisticalPrincipal Component AnalysisAuditory CortexBrain MappingElectroencephalographyFemaleHumansInfantMaleNerve NetPitch PerceptionReproducibility of ResultsSensitivity and SpecificityEEGEvent-related potentialIndependent component analysisInfantsRapid auditory discriminationSource localization

Identifiers

PMID26944858
PMCPMC5978406
OpenAlexW2290314769

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.