1. Neuroscience
Download icon

Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortex

  1. Xiaoxuan Jia  Is a corresponding author
  2. Ha Hong
  3. Jim DiCarlo
  1. Massachusetts Institute of Technology, United States
Research Article
  • Cited 0
  • Views 125
  • Annotations
Cite this article as: eLife 2021;10:e60830 doi: 10.7554/eLife.60830

Abstract

Temporal continuity of object identity is a feature of natural visual input, and is potentially exploited -- in an unsupervised manner -- by the ventral visual stream to build the neural representation in inferior temporal (IT) cortex. Here we investigated whether plasticity of individual IT neurons underlies human core-object-recognition behavioral changes induced with unsupervised visual experience. We built a single-neuron plasticity model combined with a previously established IT population-to-recognition-behavior linking model to predict human learning effects. We found that our model, after constrained by neurophysiological data, largely predicted the mean direction, magnitude and time course of human performance changes. We also found a previously unreported dependency of the observed human performance change on the initial task difficulty. This result adds support to the hypothesis that tolerant core object recognition in human and non-human primates is instructed -- at least in part -- by naturally occurring unsupervised temporal contiguity experience.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files, in the most useful format (https://github.com/jiaxx/temporal_learning_paper). Datasets from previous studies (IT population dataset (Majaj et al., 2015) and IT plasticity data (Li & DiCarlo, 2010)) are also compiled in the most useful format and saved in the same github location. Original datasets for previous studies can be obtained by directly contacting the corresponding authors of those studies ((Majaj et al., 2015) and (Li & DiCarlo, 2010)). Source data files for figure 2,4,5 and 6 are provided in the github repo as well.

Article and author information

Author details

  1. Xiaoxuan Jia

    Dept. of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    jxiaoxuan@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5484-9331
  2. Ha Hong

    Dept. of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jim DiCarlo

    McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (2-RO1-EY014970-06)

  • Jim DiCarlo

Simons Foundation (SCGB [325500])

  • Jim DiCarlo

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: All human experiments were done in accordance with the MIT Committee on the Use of Humans as Experimental Subjects (COUHES; the protocol number is 0812003043). We used Amazon Mechanical Turk (MTurk), an online platform where subjects can participate in non-profit psychophysical experiments for payment based on the duration of the task. In the description of each task, it is clearly stated that participation is voluntary and subjects may quit at any time. Subjects can preview each task before agreeing to participate. Subjects will also be informed that anonymity is assured and the researchers will not receive any personal information. MTurk requires subjects to read task descriptions before agreeing to participate. If subjects successfully complete the task, they anonymously receive payment through the MTurk interface.

Reviewing Editor

  1. Thomas Serre, Brown University, United States

Publication history

  1. Received: July 8, 2020
  2. Accepted: June 10, 2021
  3. Accepted Manuscript published: June 11, 2021 (version 1)

Copyright

© 2021, Jia et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 125
    Page views
  • 16
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Neuroscience
    Mikkel Malling Beck et al.
    Research Article

    Human dexterous motor control improves from childhood to adulthood, but little is known about the changes in cortico-cortical communication that support such ontogenetic refinement of motor skills. To investigate age-related differences in connectivity between cortical regions involved in dexterous control we analyzed electroencephalographic data from 88 individuals (range 8-30y) performing a visually-guided precision grip task using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB). Our results demonstrate that bidirectional coupling in a canonical 'grasping network' is associated with precision grip performance across age groups. We further demonstrate greater backward coupling from higher-order to lower-order sensorimotor regions from late adolescence in addition to differential associations between connectivity strength in a premotor-prefrontal network and motor performance for different age groups. We interpret these findings as reflecting greater use of top-down and executive control processes with development. These results expand our understanding of the cortical mechanisms that support dexterous abilities through development.

    1. Neuroscience
    Tom P Franken et al.
    Research Article

    Locomotion generates adventitious sounds which enable detection and localization of predators and prey. Such sounds contain brisk changes or transients in amplitude. We investigated the hypothesis that ill-understood temporal specializations in binaural circuits subserve lateralization of such sound transients, based on different time of arrival at the ears (interaural time differences, ITDs). We find that Lateral Superior Olive (LSO) neurons show exquisite ITD-sensitivity, reflecting extreme precision and reliability of excitatory and inhibitory postsynaptic potentials, in contrast to Medial Superior Olive neurons, traditionally viewed as the ultimate ITD-detectors. In vivo, inhibition blocks LSO excitation over an extremely short window, which, in vitro, required synaptically-evoked inhibition. Light and electron microscopy revealed inhibitory synapses on the axon initial segment as the structural basis of this observation. These results reveal a neural vetoing mechanism with extreme temporal and spatial precision and establish the LSO as the primary nucleus for binaural processing of sound transients.