Attention Extracts Signal in External Noise: A BOLD fMRI Study

Lü, Zhong-Lin; Li, Xiangrui; Tjan, Bosco S.; Dosher, Barbara Anne; Chu, Wilson

doi:10.1162/jocn.2010.21511

Cited by 27 publications

(27 citation statements)

References 54 publications

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“…However, within this orchestra the interaction of “gains” and “losses” of processing power contributes equally to promote salience of currently important concepts and reduce distraction (Lu et al, 2011). “Loss” may not necessarily imply a cost but may, instead, signify a reduction of distraction leading to an enhanced focus of processing power.…”

Section: Does Enhancement Come With a Cost?mentioning

confidence: 99%

Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition?

et al. 2014

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In the past several years, the number of studies investigating enhancement of cognitive functions through non-invasive brain stimulation (NBS) has increased considerably. NBS techniques, such as transcranial magnetic stimulation and transcranial current stimulation, seem capable of enhancing cognitive functions in patients and in healthy humans, particularly when combined with other interventions, including pharmacologic, behavioral and cognitive therapies. The “net zero-sum model”, based on the assumption that brain resources are subjected to the physical principle of conservation of energy, is one of the theoretical frameworks proposed to account for such enhancement of function and its potential cost. We argue that to guide future neuroenhancement studies, the net-zero sum concept is helpful, but only if its limits are tightly defined.

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Section: Does Enhancement Come With a Cost?mentioning

confidence: 99%

Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition?

et al. 2014

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“…Spatial attention has been shown to robustly modulate responses to stimulus contrast in behavioral (Carrasco, Penpeci-Talgar, & Eckstein, 2000; Herrmann et al, 2010; Ling & Carrasco, 2006; Lu & Dosher, 1998; Morrone, Denti, & Spinelli, 2002, 2004; Pestilli & Carrasco, 2005; Pestilli, Ling, & Carrasco, 2009; Pestilli, Viera, & Carrasco, 2007; Yigit-Elliott, Palmer, & Moore, 2011), single unit (Buracas & Boynton, 2007; Li, Lu, Tjan, Dosher, & Chu, 2008; Martinez-Trujillo & Treue, 2002; McAdams & Reid, 2005; Reynolds & Chelazzi, 2004; Reynolds et al, 2000; Williford & Maunsell, 2006) and neuroimaging studies (Buracas & Boynton, 2007; Liu, 2005; Lu, Li, Tjan, Dosher, & Chu, 2011; Murray & He, 2006; Pestilli, 2011). Yet, neither behavioral nor neurophysiology studies have systematically characterized the contrast dependence of FBA.…”

Section: Introductionmentioning

confidence: 99%

Feature-based attention enhances performance by increasing response gain

2012

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Covert spatial attention can increase contrast sensitivity either by changes in contrast gain or by changes in response gain, depending on the size of the attention field and the size of the stimulus (Herrmann, Montaser-Kouhsari, Carrasco, & Heeger, 2010), as predicted by the normalization model of attention (Reynolds & Heeger, 2009). For feature-based attention, unlike spatial attention, the model predicts only changes in response gain, regardless of whether the featural extent of the attention field is small or large. To test this prediction, we measured the contrast dependence of feature-based attention. Observers performed an orientation-discrimination task on a spatial array of grating patches. The spatial locations of the gratings were varied randomly so that observers could not attend to specific locations. Feature-based attention was manipulated with a 75% valid and 25% invalid pre-cue, and the featural extent of the attention field was manipulated by introducing uncertainty about the upcoming grating orientation. Performance accuracy was better for valid than for invalid pre-cues, consistent with a change in response gain, when the featural extent of the attention field was small (low uncertainty) or when it was large (high uncertainty) relative to the featural extent of the stimulus. These results for feature-based attention clearly differ from results of analogous experiments with spatial attention, yet both support key predictions of the normalization model of attention.

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“…If the mean BOLD signal in a region reflects the total activity of cells responding to both signal and noise, then attention should reduce mean BOLD responses for low-contrast signals presented in noise. Lu, Li, Tjan, Dosher, and Chu (2011) found support for this prediction, showing that attending to low-contrast gratings in high levels of external noise led to reduced mean BOLD responses in V1, whereas attention increased responses to the low-contrast grating when it was presented alone.…”

Section: Attention: the Perceptual Template Modelmentioning

confidence: 84%

Integrating theoretical models with functional neuroimaging

Pratte

Tong

2017

Journal of Mathematical Psychology

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The development of mathematical models to characterize perceptual and cognitive processes dates back almost to the inception of the field of psychology. Since the 1990s, human functional neuroimaging has provided for rapid empirical and theoretical advances across a variety of domains in cognitive neuroscience. In more recent work, formal modeling and neuroimaging approaches are being successfully combined, often producing models with a level of specificity and rigor that would not have been possible by studying behavior alone. In this review, we highlight examples of recent studies that utilize this combined approach to provide novel insights into the mechanisms underlying human cognition. The studies described here span domains of perception, attention, memory, categorization, and cognitive control, employing a variety of analytic and model-inspired approaches. Across these diverse studies, a common theme is that individually tailored, creative solutions are often needed to establish compelling links between multi-parameter models and complex sets of neural data. We conclude that future developments in model-based cognitive neuroscience will have great potential to advance our theoretical understanding and ability to model both low-level and high-level cognitive processes.

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Attention Extracts Signal in External Noise: A BOLD fMRI Study

Cited by 27 publications

References 54 publications

Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition?

Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition?

Feature-based attention enhances performance by increasing response gain

Integrating theoretical models with functional neuroimaging

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