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Orienting attention in time: behavioural and neuroanatomical distinction between exogenous and endogenous shifts

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TLDR
The findings suggest that distinct brain areas are involved in redirecting attention based upon sensory events (bottom-up, exogenous shifts) and based upon cognitive expectations (top-down, endogenous shifts).
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This article is published in Neuropsychologia.The article was published on 2000-06-01. It has received 449 citations till now. The article focuses on the topics: Premotor cortex & Orbitofrontal cortex.

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The attention system of the human brain: 20 years after.

TL;DR: The framework presented in the original article has helped to integrate behavioral, systems, cellular, and molecular approaches to common problems in attention research and has led to increased understanding of aspects of pathology and to some new interventions.
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What makes us tick? Functional and neural mechanisms of interval timing

TL;DR: It is proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.
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Visual attention: The past 25 years

TL;DR: The emphasis of this review is on psychophysical studies, but relevant electrophysiological and neuroimaging studies and models regarding how and where neuronal responses are modulated are also discussed.
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The activation of attentional networks.

TL;DR: The fMRI results suggest that the functional contrasts within this single task differentially activate three separable anatomical networks related to the components of attention.
References
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Statistical parametric maps in functional imaging: A general linear approach

TL;DR: In this paper, the authors present a general approach that accommodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors).
Journal ArticleDOI

Spatial registration and normalization of images

TL;DR: A general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment is presented that minimizes the sum of squares between two images following non linear spatial deformations and transformations of the voxel (intensity) values.
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