'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification
Abstract
Deep networks provide a potentially rich interconnection between neuroscientific and artificial approaches to understanding visual intelligence, but the relationship between artificial and neural representations of complex visual form has not been elucidated at the level of single-unit selectivity. Taking the approach of an electrophysiologist to characterizing single CNN units, we found many units exhibit translation-invariant boundary curvature selectivity approaching that of exemplar neurons in the primate mid-level visual area V4. For some V4-like units, particularly in middle layers, the natural images that drove them best were qualitatively consistent with selectivity for object boundaries. Our results identify a novel image-computable model for V4 boundary curvature selectivity and suggest that such a representation may begin to emerge within an artificial network trained for image categorization, even though boundary information was not provided during training. This raises the possibility that single-unit selectivity in CNNs will become a guide for understanding sensory cortex.
Data availability
No new datasets were generated in the course of this research. The model this research is based on is openly available from the Berkeley Artificial Intelligence Lab.
-
BVLC reference caffenetBAIR BVLC CaffeNet Model.
Article and author information
Author details
Funding
National Science Foundation (Graduate Research Fellowship)
- Dean A Pospisil
National Science Foundation (CRCNS Grant IIS-1309725)
- Anitha Pasupathy
- Wyeth Bair
Google (Google Faculty Research Award)
- Wyeth Bair
National Institutes of Health (Grant R01 EY-018839)
- Anitha Pasupathy
National Institutes of Health Office of Research Infrastructure Programs (Grant RR-00166 to the Washington National Primate Research Center)
- Anitha Pasupathy
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animal procedures for this study, including implants, surgeries and behavioral training, conformed to NIH and USDA guidelines and were performed under an institutionally approved protocol at the Johns Hopkins University (Pasupathy and Connor, 2001) protocol #PR98A63 and the University of Washington (El-Shamayleh and Pasupathy, 2016) UW protocol #4133-01.
Reviewing Editor
- Eilon Vaadia, The Hebrew University of Jerusalem, Israel
Version history
- Received: May 14, 2018
- Accepted: December 17, 2018
- Accepted Manuscript published: December 20, 2018 (version 1)
- Version of Record published: January 16, 2019 (version 2)
- Version of Record updated: February 1, 2021 (version 3)
Copyright
© 2018, Pospisil 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
-
- 2,689
- Page views
-
- 372
- Downloads
-
- 41
- Citations
Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
- Structural Biology and Molecular Biophysics
Acid-sensing ion channels (ASICs) are trimeric proton-gated sodium channels. Recent work has shown that these channels play a role in necroptosis following prolonged acidic exposure like occurs in stroke. The C-terminus of ASIC1a is thought to mediate necroptotic cell death through interaction with receptor interacting serine threonine kinase 1 (RIPK1). This interaction is hypothesized to be inhibited at rest via an interaction between the C- and N-termini which blocks the RIPK1 binding site. Here, we use two transition metal ion FRET methods to investigate the conformational dynamics of the termini at neutral and acidic pH. We do not find evidence that the termini are close enough to be bound while the channel is at rest and find that the termini may modestly move closer together during acidification. At rest, the N-terminus adopts a conformation parallel to the membrane about 10 Å away. The distal end of the C-terminus may also spend time close to the membrane at rest. After acidification, the proximal portion of the N-terminus moves marginally closer to the membrane whereas the distal portion of the C-terminus swings away from the membrane. Together these data suggest that a new hypothesis for RIPK1 binding during stroke is needed.
-
- Neuroscience
Decisions under uncertainty are often biased by the history of preceding sensory input, behavioral choices, or received outcomes. Behavioral studies of perceptual decisions suggest that such history-dependent biases affect the accumulation of evidence and can be adapted to the correlation structure of the sensory environment. Here, we systematically varied this correlation structure while human participants performed a canonical perceptual choice task. We tracked the trial-by-trial variations of history biases via behavioral modeling and of a neural signature of decision formation via magnetoencephalography (MEG). The history bias was flexibly adapted to the environment and exerted a selective effect on the build-up (not baseline level) of action-selective motor cortical activity during decision formation. This effect added to the impact of the current stimulus. We conclude that the build-up of action plans in human motor cortical circuits is shaped by dynamic prior expectations that result from an adaptive interaction with the environment.