Dimensionality of object representations in monkey inferotemporal cortex
By Sidney R. Lehky, Roozbeh Kiani, Hossein Esteky, Keiji Tanaka. 2014
51 citations recorded by the source corpus.
We have calculated the intrinsic dimensionality of visual object representations in anterior inferotemporal (AIT) cortex, based on responses of a large sample of cells stimulated with photographs of diverse objects. Because dimensionality was dependent on data set size, we determined asymptotic dimensionality as both the number of neurons and number of stimulus image approached infinity. Our final dimensionality estimate was 93 (SD: 11), indicating that there is basis set of approximately 100 independent features that characterize the dimensions of neural object space. We believe this is the first estimate of the dimensionality of neural visual representations based on single-cell neurophysiological data. The dimensionality of AIT object representations was much lower than the dimensionality of the stimuli. We suggest that there may be a gradual reduction in the dimensionality of object representations in neural populations going from retina to inferotemporal cortex as receptive fields become increasingly complex.
Subfields: Cognitive Neuroscience, Molecular Biology
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In Cognitive Neuroscience
- Stefano Fusi
- Mattia Rigotti
- Earl K. Miller
- Xiao-Jing Wang
- Christopher Summerfield
- Marcus K. Benna
- Michael J Frank
- J. Cohen
In Molecular Biology
Citations in the corpus
- Why neurons mix: high dimensionality for higher cognition. (2016, background): “Indeed, it is known from fMRI and electrophysiological studies that the dissimilarity matrix, which essentially contains the distances between the points in the firing rate space and hence determines the dimensionality is often invariant across subjects (hyperalignment) [53], and across species [54]”