The Caltech component of the proposed Center, """"""""The Role of Attention in Detecting and Recognizing Objects,"""""""" is organized around the central theme of attentional aspects of object recognition, using techniques that the Koch lab has employed successfully in the past: human psychophysics, computational (abstract) and neuronally-plausible (biophysical) modelling. The research is organized in 3 aims, each of them with obvious relevance to different groups in the center:
AIM 1 : Human psychophysics of attention and recognition in natural scenes will parallel electrophysiological work in monkeys (DiCarlo) and determine the effects of """"""""physical"""""""" distance between stimuli (i.e. clutter) and """"""""similarity"""""""" distance between targets and distractors (i.e. task complexity) on a task's attentional requirements. This will help determine the limits of the current HMAX feed-forward recognition system (Riesenhuber and Poggio).
AIM 2 : In light of these constraints, the computational model of saliency previously developed in Koch's group will be integrated with the HMAX feed-forward recognition system (Riesenhuber and Poggio) to implement attentional modulation of object recognition.
AIM 3 : Finally, the Koch group will make use of its experience in the field of biophysical modelling to study detailed, biologically plausible models of the MAX operation at the level of simple neuronal feedback circuits or individual cortical neurons which will aim to account for electrophysiological results obtained in the Ferster group.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory Grants (P20)
Project #
1P20MH066239-01A1
Application #
6824632
Study Section
Special Emphasis Panel (ZMH1)
Project Start
2003-09-30
Project End
2007-07-31
Budget Start
Budget End
Support Year
1
Fiscal Year
2003
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Baldassi, Carlo; Alemi-Neissi, Alireza; Pagan, Marino et al. (2013) Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons. PLoS Comput Biol 9:e1003167
Glezer, Laurie S; Jiang, Xiong; Riesenhuber, Maximilian (2009) Evidence for highly selective neuronal tuning to whole words in the ""visual word form area"". Neuron 62:199-204
Riesenhuber, Maximilian; Wolff, Brian S (2009) Task effects, performance levels, features, configurations, and holistic face processing: a reply to Rossion. Acta Psychol (Amst) 132:286-92
Kouh, Minjoon; Poggio, Tomaso (2008) A canonical neural circuit for cortical nonlinear operations. Neural Comput 20:1427-51
Einhauser, Wolfgang; Koch, Christof; Makeig, Scott (2007) The duration of the attentional blink in natural scenes depends on stimulus category. Vision Res 47:597-607
Jiang, Xiong; Bradley, Evan; Rini, Regina A et al. (2007) Categorization training results in shape- and category-selective human neural plasticity. Neuron 53:891-903
Finn, Ian M; Priebe, Nicholas J; Ferster, David (2007) The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex. Neuron 54:137-52
Finn, Ian M; Ferster, David (2007) Computational diversity in complex cells of cat primary visual cortex. J Neurosci 27:9638-48
Serre, Thomas; Oliva, Aude; Poggio, Tomaso (2007) A feedforward architecture accounts for rapid categorization. Proc Natl Acad Sci U S A 104:6424-9
Cadieu, Charles; Kouh, Minjoon; Pasupathy, Anitha et al. (2007) A model of V4 shape selectivity and invariance. J Neurophysiol 98:1733-50

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