Neurons in LIP contribute to two distinct stages of processing during a search task. The working memory for the sought-after feature and then the focusing of attention on target location.
Levichkina, E., Saalmann, Y. B., & Vidyasagar, T. R. (2017). Coding of spatial attention priorities and object features in the macaque lateral intraparietal cortex. Physiological Reports, 5(5), e13136.
An excellent and comprehensive review of the brain basis of visual attention. Worthy of yours.
Moore, T., & Zirnsak, M. (2017). Neural Mechanisms of Selective Visual Attention. Annual Review of Psychology, 68, 47-72.
New Miller Lab paper:
Jia, N., Brincat, S.L., Salazar-Gomez, A., Panko, M., Guenther, F. and Miller, E.K. (2017) Decoding of intended saccade direction in an oculomotor brain-computer interface. Journal of Neural Engineering, 2017. https://doi.org/10.1088/1741-2552/aa5a3e
Abstract
Objective. To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from of hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. Approach. We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. Main results. Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Significance. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for point and click computer operation as used in most current AAC systems.
The title says it all. A comprehensive review on how salience is determined and used by the brain.
Veale, R., Hafed, Z. M., & Yoshida, M. (2017). How is visual salience computed in the brain? Insights from behaviour, neurobiology and modelling. Phil. Trans. R. Soc. B, 372(1714), 20160113.
Ester et al addressed the dichotomy of source vs site in visual attention. The frontoparietal cortex has long been thought to be the “source” of top-down attention signals that enhance activity at “sites” in posterior (sensory) cortex that represent visual stimuli. They used fMRI, a roving searchlight analysis, and an inverted encoding model to show that stimulus representations are all over the cortex and enhanced by attention. This calls the dichotomy between source and site into question.
Ibos and Freedman show that spatial and feature-based attention independently modulate activity in area LIP and that they added together. This suggests a common function of gating task-relevant features, whether they are spatial or non-spatial.
Michael Halassa, Guoping Feng, and colleagues show that a genetic deficit found in patients with ADHD produces (in mice) deficit in the thalamic reticular nucleus. This adds to Halassa’s recent work (also in Nature) suggesting that attention is focused when the prefrontal cortex acts on sensory cortex via the thalamus. It adds a link to potential path to treatment. Cool.
Thalamic reticular impairment underlies attention deficit in Ptchd1Y/− mice
Michael F. Wells, Ralf D. Wimmer, L. Ian Schmitt, Guoping Feng & Michael M. Halassa
Increases in beta power associated with top-down attention. Beta seemed unite visual cortex. There was a more homogeneous pattern of beta correlation across the cortex during top-down vs bottom-up attention.
Bekisz, M., Bogdan, W., Ghazaryan, A., Waleszczyk, W. J., Kublik, E., & Wróbel, A. (2016). The Primary Visual Cortex Is Differentially Modulated by Stimulus-Driven and Top-Down Attention. PloS one, 11(1), e0145379.
Oscillatory synchrony of prefrontal parvalbumin plays a role in top-down control of attention.
Kim, H., Ährlund-Richter, S., Wang, X., Deisseroth, K., & Carlén, M. (2016). Prefrontal Parvalbumin Neurons in Control of Attention. Cell, 164(1), 208-218.
Bichot et al find that a particular part of the prefrontal cortex is the source of information about an object when we search for it. In other words, when you look for your missing keys, this is the part of the brain that reminds you what they look like.