View in EDS HTML Full Text PDF Full Text

Unconscious Biases in Neural Populations Coding Multiple Stimuli.

Saved in:
Bibliographic Details
Title: Unconscious Biases in Neural Populations Coding Multiple Stimuli.
Authors: Keemink, Sander W., Tailor, Dharmesh V., van Rossum, Mark C. W.
Source: Neural Computation. Dec2018, Vol. 30 Issue 12, p3168-3188. 21p. 5 Graphs.
Subjects: Prejudices, Neurons, Subconsciousness, Maximum likelihood decoding, Gaussian processes
Abstract: Throughout the nervous system, information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However, in many situations, multiple stimuli are simultaneously present; for example, multiple motion patterns might overlap. Here we find that when multiple stimuli that overlap in their neural representation are simultaneously encoded in the population, biases in the read-out emerge. Although the bias disappears in the absence of noise, the bias is remarkably persistent at low noise levels. The bias can be reduced by competitive encoding schemes or by employing complex decoders. To study the origin of the bias, we develop a novel general framework based on gaussian processes that allows an accurate calculation of the estimate distributions of maximum likelihood decoders, and reveals that the distribution of estimates is bimodal for overlapping stimuli. The results have implications for neural coding and behavioral experiments on, for instance, overlapping motion patterns. [ABSTRACT FROM AUTHOR]
Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 133132046
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Unconscious Biases in Neural Populations Coding Multiple Stimuli.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Keemink%2C+Sander+W%2E%22">Keemink, Sander W.</searchLink><br /><searchLink fieldCode="AR" term="%22Tailor%2C+Dharmesh+V%2E%22">Tailor, Dharmesh V.</searchLink><br /><searchLink fieldCode="AR" term="%22van+Rossum%2C+Mark+C%2E+W%2E%22">van Rossum, Mark C. W.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Neural+Computation%22">Neural Computation</searchLink>. Dec2018, Vol. 30 Issue 12, p3168-3188. 21p. 5 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Prejudices%22">Prejudices</searchLink><br /><searchLink fieldCode="DE" term="%22Neurons%22">Neurons</searchLink><br /><searchLink fieldCode="DE" term="%22Subconsciousness%22">Subconsciousness</searchLink><br /><searchLink fieldCode="DE" term="%22Maximum+likelihood+decoding%22">Maximum likelihood decoding</searchLink><br /><searchLink fieldCode="DE" term="%22Gaussian+processes%22">Gaussian processes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Throughout the nervous system, information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However, in many situations, multiple stimuli are simultaneously present; for example, multiple motion patterns might overlap. Here we find that when multiple stimuli that overlap in their neural representation are simultaneously encoded in the population, biases in the read-out emerge. Although the bias disappears in the absence of noise, the bias is remarkably persistent at low noise levels. The bias can be reduced by competitive encoding schemes or by employing complex decoders. To study the origin of the bias, we develop a novel general framework based on gaussian processes that allows an accurate calculation of the estimate distributions of maximum likelihood decoders, and reveals that the distribution of estimates is bimodal for overlapping stimuli. The results have implications for neural coding and behavioral experiments on, for instance, overlapping motion patterns. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=133132046
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1162/neco_a_01130
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 3168
    Subjects:
      – SubjectFull: Prejudices
        Type: general
      – SubjectFull: Neurons
        Type: general
      – SubjectFull: Subconsciousness
        Type: general
      – SubjectFull: Maximum likelihood decoding
        Type: general
      – SubjectFull: Gaussian processes
        Type: general
    Titles:
      – TitleFull: Unconscious Biases in Neural Populations Coding Multiple Stimuli.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Keemink, Sander W.
      – PersonEntity:
          Name:
            NameFull: Tailor, Dharmesh V.
      – PersonEntity:
          Name:
            NameFull: van Rossum, Mark C. W.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 08997667
          Numbering:
            – Type: volume
              Value: 30
            – Type: issue
              Value: 12
          Titles:
            – TitleFull: Neural Computation
              Type: main
ResultId 1