Feature-based attention increases the selectivity of population responses in primate visual cortex.

By J. Martinez-Trujillo, Stefan Treue. 2004

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In Cognitive Neuroscience

Citations in the corpus

Theory of Mind: A Neural Prediction Problem (2013, neutral): “…speed and accuracy of performance by increasing overall neural responses to attended stimuli (Feldman and Friston, 2010; Friston, 2010; Herrmann et al., 2010; Hillyard et al., 1998; Kok et al., 2012b; Martinez-Trujillo and Treue, 2004; Reynolds and Heeger, 2009; Treue and Martínez-Trujillo, 1999).”
The Role of Alpha-Band Brain Oscillations as a Sensory Suppression Mechanism during Selective Attention (2011, methodology): “…features, such as color or motion parameters, facilitating the processing of subsequent stimuli incorporating the attended feature, independently of spatial location (e.g., Corbetta et al., 1991; Martinez-Trujillo and Treue, 2004; Wylie et al., 2004, 2006; Most and Astur, 2007; Egner et al., 2008).”
How Do Expectations Shape Perception? (2018, background): “A similar physiological mechanism has also been proposed to underlie adaptation [71,83–85] and attention [86].”
Feature-based attention in visual cortex. (2006, background): “Martinez-Trujillo and Treue [19, 38 ] examined attentional modulation in MT, which is important in the perception of visual motion [39,40].”
Hierarchical Models in the Brain (2008, background): “This selective modulation of afferents mirrors the gain-control mechanisms invoked for attention; e.g., [58,59].”
The Normalization Model of Attention (2009, background): “(B) Feature-based attention caused a sharpening of motion direction tuning (adapted from Martinez-Trujillo and Treue, 2004).”
Free-energy and the brain (2007, background): “This selective modulation of afferents is exactly the same as gain-control mechanisms that have been invoked for attention (e.g., Treue and Maunsell 1996; Martinez-Trujillo and Treue 2004).”
A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure (2016, methodology): “Thus, our model reflects the similarity-gain principle posited by Martinez-Trujillo and Treue.”
Structure and function of visual area MT. (2005, background): “…(Martinez-Trujillo & Treue 2002) and, for feature-based attention, as a function of the similarity between the attended feature and that preferred by the neuron, actually becoming negative as the attended feature approaches the antipreferred feature of the neuron (Martinez-Trujillo & Treue 2004).”
An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed (2006, methodology): “To simulate human like behavior, we assume that the feature responses are modulated in a top-down manner by multiplicative gain modulation [26, 12].”
Distinct Computational Principles Govern Multisensory Integration in Primary Sensory and Association Cortices. (2016, neutral): “auditory) report [34].”
Sensorimotor Integration in Speech Processing: Computational Basis and Neural Organization (2011, positive): “The idea that attention can modulate gain is well established (Boynton, 2005; McAdams and Maunsell, 1999; ) illustrating attentional effects on sensory response functions based on a ''featuresimilarity gain model'' (Martinez-Trujillo and Treue, 2004).”
A free energy principle for the brain. (2006, background): “This selective modulation of afferents is exactly the same as gain control mechanisms that have been invoked for attention (e.g., Treue and Maunsell, 1996; Martinez-Trujillo and Treue, 2004).”
A mechanistic cortical microcircuit of attention for amplification, normalization and suppression. (2015, methodology): “8a), as suggested by single-unit recordings in MT (Martinez-Trujillo & Treue, 2004) and V4 (David et al., 2008).”