Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India. Electronic address: https://twitter.com/@SuryaAbbur.
Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: https://twitter.com/@mayo_lab.
Curr Opin Neurobiol. 2022 Oct;76:102589. doi: 10.1016/j.conb.2022.102589. Epub 2022 Jun 22.
We review recent efforts to decode visual spatial attention from different types of brain signals, such as spikes and local field potentials (LFPs). Combining signals from more electrodes improves decoding, but the pattern of improvement varies considerably depending on the signal as well as the task (for example, decoding of sensory stimulus/motor intention versus location of attention). We argue that this pattern of results conveys important information not only about the usefulness of a particular brain signal for decoding attention, but also about the spatial scale over which attention operates in the brain. The spatial scale, in turn, likely depends on the extent of underlying mechanisms such as normalization, gain control via excitation-inhibition interactions, and neuromodulatory regulation of attention.
我们回顾了最近从不同类型的脑信号（如尖峰和局部场电位（LFPs））解码视觉空间注意的努力。结合来自更多电极的信号可以提高解码效果，但改进的模式因信号和任务而异（例如，解码感觉刺激/运动意图与注意位置）。我们认为，这种结果模式不仅传达了特定脑信号用于解码注意力的有用性的重要信息，还传达了注意力在大脑中运作的空间尺度的重要信息。反过来，空间尺度可能取决于归一化、通过兴奋-抑制相互作用进行增益控制以及注意力的神经调制调节等基础机制的程度。
