Network model of top-down influences on local gain and contextual interactions in visual cortex

By V. Piëch, Wu Li, George N. Reeke Jr., C. Gilbert. 2013

84 citations recorded by the source corpus.

Subfields: Biophysics, Cognitive Neuroscience, Neuroscience

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biophysics

1. Abhinav Kumar Gupta
2. Jitendra Malik
3. Heiko Neumann
4. Rahul Sukthankar
5. Tobias Brosch
6. Kristen Grauman
7. Dinesh Jayaraman
8. Andrea Vedaldi

In Cognitive Neuroscience

1. Jitendra Malik
2. Tobias Brosch
3. Heiko Neumann
4. Rahul Sukthankar
5. Abhinav Kumar Gupta
6. Abhinav Shrivastava
7. Alexei A. Efros
8. Andrew Zisserman

In Neuroscience

1. Jitendra Malik
2. Heiko Neumann
3. Abhinav Kumar Gupta
4. Abhinav Shrivastava
5. Tobias Brosch

Citations in the corpus

• Beyond Skip Connections: Top-Down Modulation for Object Detection (2016, background): “There is strong evidence of such top-down context, feedback and lateral processing in the human visual pathway [7, 13, 15, 25, 28, 30, 31, 37, 53, 54]; wherein, the topdown signals are responsible for modulating low-level features [13, 15, 37, 53, 54] as well as act as attentional mechanism for sele”
• Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback (2014, methodology): “Recently a model of cortical FB was proposed to investigate the influences context have on local feature representations in V1 (Piëch et al., 2013; Gilbert & Li, 2013).”