Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex
By James V. Haxby, Maria Ida Gobbini, Maura L. Furey, Alumit Ishai, J. L. Schouten, P. Pietrini. Science, 2001
4,071 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/7549e383e527ebcebb131edd57fcb08874d5d77a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Nikolaus Kriegeskorte
- John-Dylan Haynes
- James V. Haxby
- Gaël Varoquaux
- Russell A. Poldrack
- Rebecca Saxe
- Jörn Diedrichsen
- Stanislas Dehaene
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Dacheng Tao
- Trevor Darrell
- Andrea Vedaldi
- Xiaogang Wang
- Ming-Hsuan Yang
- Andrew Zisserman
- Li Fei-Fei
Citations in the corpus
- The fusiform face area: a cortical region specialized for the perception of faces (2006, background): “In an important challenge to a more modular view of face and object processing, Haxby et al. (2001) argued that objects and faces are coded via the distributed profile of response across much of the ventral visual pathway.”
- Cross‐validation failure: Small sample sizes lead to large error bars (2017, background): “I explored vibration effects in decoding using the face versus place opposition in the Haxby et al. (2001) which fMRI should not predict the experimental condition.”
- The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data (2015, methodology): “To validate the toolbox on real imaging data, we used data from a study by Haxby et al. (2001) which is publicly available (http:// data . pymvpa . org/datasets/haxby2001/).”
- The logic of syntactic priming and acceptability judgments (2016, positive): “For example, multi-voxel pattern analysis, a class of machine learning algorithms that examine patterns of neural activity (Haxby et al., 2001), has revealed regions of the left temporal cortex that appear to bind arguments to something roughly like thematic roles (Frankland & Greene, 2015).”
- A Reduced-Dimension fMRI Shared Response Model (2015, background): “Dataset Subjs TRs (s/TR) Region of interest (ROI) Voxels sherlock (audio-visual movie) [21] 16 1976 (2) posterior medial cortex (PMC) [22] 813 raider (audio-visual movie) [10] 10 2203 (3) ventral temporal cortex (VT) [23] 500/H forrest (audio movie) [24] 18 3599 (2) planum temporale (PT) [25] 1300/H”
- Connectionist models of development (2003, background): “As we shall see, connectionist models can also inform neuroscience, for example, by providing computational insights into why different brain regions are specialized for different functions.”
- Searchlight analysis: Promise, pitfalls, and potential (2013, positive): “(Carlson et al., 2003; Haxby et al., 2001; Haynes and Rees, 2005; Kamitani and Tong, 2006; Kay et al., 2008; Mitchell et al., 2008).”
- Support vector machines for temporal classification of block design fMRI data (2005, positive): “The work in predictive modeling has primarily been developed by Strother and Hansen (Hansen et al., 1999; Kjems et al., 2002; Kustra and Strother, 2001; LaConte et al., 2003a; Lautrup et al., 1994; Morch et al., 1997; Shaw et al., 2003; Strother et al., 2002) with recent explicit testing of distribu”
- Distinct representations for facial identity and changeable aspects of faces in the human temporal lobe (2004, background): “Indeed, a recent study has shown that our perception of faces could be based on a distributed pattern of response across the whole temporal lobe rather than on the activity of a few specialised modules (Haxby et al., 2001).”
- Extracting information from neuronal populations: information theory and decoding approaches (2009, background): “Interestingly, a few studies have already shown the value of decoding for extracting information from populations of voxels”