Abstract
ABSTRACTThere is now a large literature in neuroscience highlighting how some neurons respond highly selectively to high-level information (e.g. cells that respond to specific faces) and a growing literature in psychology and computer science showing that artificial neural networks often learn highly selective representations. Nevertheless, the vast majority of neuroscientists reject “grandmother cell” theories out of hand, and many psychologists reject localist models based on neuroscience. In this review, I detail some of the conceptual confusions regarding grandmother cells that have contributed to this state of affairs, and review the literature of single-unit recording studies in artificial neural networks that may provide insights into why some neurons respond in a highly selective manner. I then briefly review the contributions from leading theorists in psychology and neuroscience. My hope this special issue contributes to a more productive debate on an important issue that has often been characterised by misunderstandings between disciplines.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.