The influence of feature salience over microsaccades in normal and blindsight humans and monkeys: an experimental and theoretical investigation
Final Report Abstract
In this project, we sought to understand the properties of microsaccades, or tiny eye movements, under a variety of visual conditions, and with both normal subjects and subjects having a lesion in their primary visual cortex (V1). These latter subjects lose conscious perception in a portion of the visual field, but they exhibit residual performance capabilities (called “blindsight”) suggestive of compensation by other brain pathways for vision. Thus, understanding properties of microsaccades in these subjects can help clarify the mechanisms of not just microsaccade generation and/or blindsight, but also of motor control on the one hand and visual perception and cognition on the other. The project was part of a collaboration with Prof. Masatoshi Yoshida (National Institute for Physiological Sciences, Japan), who is a world renowned expert on blindsight, and who has successfully established a viable animal model for this phenomenon. In our project, we studied how microsaccade frequency and direction can be modulated by visual stimuli, and by the “visual salience” of various scene regions. Salience refers to the conspicuity of a certain region in an image, irrespective of visual features. For example, a luminous white dot over a black background can be salient, but also a moving colored dot over a different colored background of identical luminance can still be salient. In our project, we have carefully characterized robust modulations of microsaccades after peripheral visual stimulus onsets, and we have also compared these modulations in normal subjects and subjects with V1 lesions. We have additionally simulated these modulations in computational models, and started relating them to modulations with natural scenes (as opposed to simplified, constrained laboratory stimuli). Our primary findings are that V1 lesions are associated with lateralized biases in microsaccade directions, but that visual stimulus onsets still modulated microsaccades in a predictable manner. This manner can be simulated very effectively in computational models as a “balanced system” that “oscillates” in space and time, with an important property of these oscillations being that the spatial and temporal phases of the oscillations dictate whether and how a given microsaccade can be influenced by a given stimulus. We have also identified that the superior colliculus (SC), a brainstem structure involved in vision and action, is critical for the balance, oscillations, and influence of salience representations. We are currently developing a biophysically accurate spiking neuron SC model, which integrates salience representations and microsaccades, and this model can potentially be used in future human-factors computer interfaces that model scene salience, in order to either predict or manipulate an operator’s attentional state. This could be useful, for example, in flight control or any other scenario in which human operators face a large visual field of both computer parameters/switches and natural scene input into their visual system. Among the most significant academic surprises associated with our project was our discovery that microsaccade-related balance and oscillations reveal a most unexpected new way to think about the brain mechanisms for “attention”, which is a hugely popular topic in systems neuroscience since more than 30-40 years ago. Our work so far in this project has garnered media mention, exemplified by the following samples: http://www.cin.uni-tuebingen.de/news-events/news-press/detail/view/151/page/1/press-releasewhat-is-attention.html http://pooneil.sakura.ne.jp/archives/permalink/001601.php http://neurosciencenews.com/eye-movement-attention-neuroscience-4070/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed:+neuroscience-rssfeeds-neuroscience-news+(Neuroscience+News+Updates) http://www.psypost.org/2016/04/tiny-eye-movements-filter-important-stimuli-relay-brain-42343 https://idw-online.de/de/news649447
Publications
- (2017) Alteration of the microsaccadic velocity-amplitude main sequence relationship after visual transients: implications for models of saccade control. Journal of neurophysiology 117 (5) 1894–1910
Buonocore, Antimo; Chen, Chih-Yang; Tian, Xiaoguang; Idrees, Saad; Münch, Thomas A.; Hafed, Ziad M.
(See online at https://doi.org/10.1152/jn.00811.2016) - (2017) Informative Cues Facilitate Saccadic Localization in Blindsight Monkeys. Frontiers in systems neuroscience 11 5
Yoshida, Masatoshi; Hafed, Ziad M.; Isa, Tadashi
(See online at https://doi.org/10.3389/fnsys.2017.00005) - (2015). A model of repetitive microsaccades, coupled with pre-microsaccadic changes in vision, is sufficient to account for both attentional capture and inhibition of return in Posner cueing. Proceedings of MODVIS 2015
Hafed, Z. M. & Tian, X.
- (2015). Neuronal response gain enhancement prior to microsaccades. Current Biology, Vol. 25, pp. 2065-2074
Chen, C. -Y., Ignashchenkova, A., Thier, P., & Hafed, Z. M.
(See online at https://doi.org/10.1016/j.cub.2015.06.022) - (2015). Probing perceptual performance after microsaccades. Journal of Neuroscience, Vol. 35, No. 7, pp. 2842-2844
Tian, X. & Chen, C. -Y.
(See online at https://doi.org/10.1523/JNEUROSCI.4983-14.2015) - (2015). Vision, perception, and attention through the lens of microsaccades: mechanisms and implications. Frontiers in Systems Neuroscience (Special Research Topic on Perisaccadic Vision), 9:167
Hafed, Z. M., Chen, C. -Y., & Tian, X.
(See online at https://dx.doi.org/10.3389/fnsys.2015.00167) - (2016). A causal role for the cortical frontal eye fields in microsaccade deployment. PLOS Biology, Vol. 14, No. 8: e1002531
Peel, T. R., Hafed, Z. M., Dash, S., Lomber, S. G., & Corneil, B. D.
(See online at https://doi.org/10.1371/journal.pbio.1002531) - (2016). A microsaccadic account of attentional capture and inhibition of return in Posner cueing. Frontiers in Systems Neuroscience (Special Research Topic on Perisaccadic Vision), 10:23
Tian, X., Yoshida, M., & Hafed, Z. M.
(See online at https://doi.org/10.3389/fnsys.2016.00023) - (2017). How is visual salience computed in the brain? Insights from behaviour, neurobiology, and modelling. Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 372, No. 1714
Veale, R., Hafed, Z. M., & Yoshida, M.
(See online at https://doi.org/10.1098/rstb.2016.0113)
