Evidence map›Paper›PMID 24920021›Full record

ArticleJournal of neurophysiology2014

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings.

Monty A Escabí, Heather L Read, Jonathan Viventi, Dae-Hyeong Kim, Nathan C Higgins, Douglas A Storace, Andrew S K Liu, Adam M Gifford, John F Burke, Matthew Campisi and 9 more

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
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

42 citing papers in PubMed.

  1. Review
  2. Review
  3. Distinct Cortical Populations Drive Multisensory Modulation of Segregated Auditory Sources.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. A Soft, High-Density Neuroelectronic Array.Npj flexible electronics · 2023
    Article
  12. Ultra-Thin Flexible Encapsulating Materials for Soft Bio-Integrated Electronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
  13. Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface.IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference · 2022
    Article
  14. Article
  15. Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  16. Article
  17. Article
  18. Review
  19. MRI-Compatible and Conformal Electrocorticography Grids for Translational Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    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

19 authors.

Monty A EscabíDepartment of Psychology, University of Connecticut, Storrs, Connecticut; Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut; Department of Electrical Engineering, University of Connecticut, Storrs, Connecticut;
Heather L ReadDepartment of Psychology, University of Connecticut, Storrs, Connecticut; Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut;
Jonathan ViventiCenter for Neural Science, New York University, New York, New York; Department of Electrical and Computer Engineering, Polytechnic Institute of New York University, Brooklyn, New York;
Dae-Hyeong KimCenter for Nanoparticle Research of Institute for Basic Science, School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea;
Nathan C HigginsDepartment of Psychology, University of Connecticut, Storrs, Connecticut;
Douglas A StoraceDepartment of Psychology, University of Connecticut, Storrs, Connecticut;
Andrew S K LiuBioengineering Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania;
Adam M GiffordNeuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania;
John F BurkeNeuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania;
Matthew CampisiDepartment of Electrical and Computer Engineering, Polytechnic Institute of New York University, Brooklyn, New York;
Yun-Soung KimDepartment of Materials Science and Engineering, Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois;
Andrew E AvrinDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania;
Van der Spiegel JanDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania;
Yonggang HuangDepartments of Mechanical Engineering and Civil and Environmental Engineering, Northwestern University, Evanston, Illinois;
Ming LiState Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China;
Jian WuDepartment of Engineering Mechanics, Tsinghua University, Beijing, China;
John A RogersDepartment of Materials Science and Engineering, Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois;
Brian LittDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania;
Yale E CohenDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Otorhinolaryngology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania ycohen@mail.med.upenn.edu.

Funding

An Implantable Device to predict and Prevent SeizuresR01NS041811 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DICHTER, MARC A · 2001 to 2011
$13.0M
Evolution of seizure precursors in refactory epilepsyR01NS048598 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI LITT, BRIAN · 2005 to 2008
$2.2M
Neuralynx for Translational ResearchS10RR031724 · NCRR · UNIVERSITY OF PENNSYLVANIA · PI LITT, BRIAN · 2011 to 2011
$225k
Optical imaging of the input and output of the olfactory bulbF32DC012981 · NIDCD · YALE UNIVERSITY · PI STORACE, DOUGLAS ANTHONY · 2013 to 2015
$165k
NCRR NIH HHS S10 RR031724NIDCD NIH HHS F32 DC012981NINDS NIH HHS R01-NS-041811NINDS NIH HHS R01-NS-48598
6 · The paper itself

Abstract

Our understanding of the large-scale population dynamics of neural activity is limited, in part, by our inability to record simultaneously from large regions of the cortex. Here, we validated the use of a large-scale active microelectrode array that simultaneously records 196 multiplexed micro-electrocortigraphical (μECoG) signals from the cortical surface at a very high density (1,600 electrodes/cm(2)). We compared μECoG measurements in auditory cortex using a custom "active" electrode array to those recorded using a conventional "passive" μECoG array. Both of these array responses were also compared with data recorded via intrinsic optical imaging, which is a standard methodology for recording sound-evoked cortical activity. Custom active μECoG arrays generated more veridical representations of the tonotopic organization of the auditory cortex than current commercially available passive μECoG arrays. Furthermore, the cortical representation could be measured efficiently with the active arrays, requiring as little as 13.5 s of neural data acquisition. Next, we generated spectrotemporal receptive fields from the recorded neural activity on the active μECoG array and identified functional organizational principles comparable to those observed using intrinsic metabolic imaging and single-neuron recordings. This new electrode array technology has the potential for large-scale, temporally precise monitoring and mapping of the cortex, without the use of invasive penetrating electrodes.

Indexed as

AnimalsAuditory CortexBrain MappingElectroencephalographyEvoked Potentials, AuditoryMaleMicroelectrodesOptical ImagingRatsauditory cortexelectrocorticographytonotopytopographyμECoG

Identifiers

PMID24920021
PMCPMC4137255

What OpenQuestion holds

Textmetadata
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.