Inherent in visual scene analysis is a bottleneck associated with the need to sequentially sample locations with foveating eye movements. The concept of a ‘saliency map’ topographically encoding stimulus conspicuity over the visual scene has proven to be an efficient predictor of eye movements. Our work reviews insights into the neurobiological implementation of visual salience computation. We start by summarizing the role that different visual brain areas play in salience computation, whether at the level of feature analysis for bottom-up salience or at the level of goal-directed priority maps for output behaviour. We then delve into how a subcortical structure, the superior colliculus (SC), participates in salience computation. The SC represents a visual saliency map via a centre-surround inhibition mechanism in the superficial layers, which feeds into priority selection mechanisms in the deeper layers, thereby affecting saccadic and microsaccadic eye movements. Lateral interactions in the local SC circuit are particularly important for controlling active populations of neurons. This, in turn, might help explain long-range effects, such as those of peripheral cues on tiny microsaccades. Finally, we show how a combination of in vitro neurophysiology and large-scale computational modelling is able to clarify how salience computation is implemented in the local circuit of the SC.This article is part of the themed issue ‘Auditory and visual scene analysis’.

We directly compared the results of a video free-viewing task and visually guided saccade tasks (step and gap) among three different species: marmoset, macaque, and human. We found that all species exhibit qualitatively similar saccadic kinematics and saliency-driven saccadic behavior albeit with different parameters. Our results suggest that the marmoset possesses similar neural mechanisms to macaque and human for saccadic control, and it is an appropriate model to study neural mechanisms for active vision and attention.

Table of contentsA1 Functional advantages of cell-type heterogeneity in neural circuitsTatyana O. SharpeeA2 Mesoscopic modeling of propagating waves in visual cortexAlain DestexheA3 Dynamics and biomarkers of mental disordersMitsuo KawatoF1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneuronsVladislav Sekulić, Frances K. SkinnerF2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brainsDaniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán SomogyváriF3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir JosićO1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generatorsIrene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo VaronaO2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrainEunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun ChoiO3 Modeling auditory stream segregation, build-up and bistabilityJames Rankin, Pamela Osborn Popp, John RinzelO4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fieldsAlejandro Tabas, André Rupp, Emili Balaguer-BallesterO5 A simple model of retinal response to multi-electrode stimulationMatias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish MeffinO6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination taskVeronika Koren, Timm Lochmann, Valentin Dragoi, Klaus ObermayerO7 Input-location dependent gain modulation in cerebellar nucleus neuronsMaria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker SteuberO8 Analytic solution of cable energy function for cortical axons and dendritesHuiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo YuO9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal networkJimin Kim, Will Leahy, Eli ShlizermanO10 Is the model any good? Objective criteria for computational neuroscience model selectionJustas Birgiolas, Richard C. Gerkin, Sharon M. CrookO11 Cooperation and competition of gamma oscillation mechanismsAtthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan GielenO12 A discrete structure of the brain wavesYuri Dabaghian, Justin DeVito, Luca PerottiO13 Direction-specific silencing of the Drosophila gaze stabilization systemAnmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby MaimonO14 What does the fruit fly think about values? A model of olfactory associative learningChang Zhao, Yves Widmer, Simon Sprecher,Walter SennO15 Effects of ionic diffusion on power spectra of local field potentials (LFP)Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen...

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63The saccade is a stereotypic behavior whose investigation improves our understanding 64 of how primate brains implement precise motor control. Furthermore, saccades offer 65 an important window into the cognitive and attentional state of the brain. Historically, 66saccade studies have largely relied on macaque. However, the cortical network giving 67 rise to the saccadic command is difficult to study in macaque because relevant cortical 68 areas lie in sulci and are difficult to access. Recently, a New World monkey -the 69 marmoset -has garnered attention as an attractive alternative to macaque because 70 of its smooth cortical surface, its smaller body, and its amenability to transgenic 71technology. However, adoption of marmoset for oculomotor research has been limited 72due to a lack of in-depth descriptions of marmoset saccade kinematics and their ability 73to perform psychophysical and cognitive tasks. Here, we directly compare free-viewing 74and visually-guided behavior of marmoset, macaque, and human engaged in identical 75 tasks under similar conditions. In video free-viewing task, all species exhibited 76 qualitatively similar saccade kinematics including saccade main sequence up to 25º in 77amplitude. Furthermore, the conventional bottom-up saliency model predicted gaze 78 targets at similar rates for all species. We further verified their visually-guided behavior 79by training them with step and gap saccade tasks. All species showed similar gap 80 effect and express saccades in the gap paradigm. Our results suggest that the three 81 species have similar natural and task-guided visuomotor behavior. The marmoset can 82 be trained on saccadic tasks and thus can serve as a model for oculomotor, attention, 83and cognitive research. 84 85 86Humans, like other primates, rely heavily on vision for daily life. Only the center of our 89 retina has high visual resolution, so we must constantly move our eyes to collect 90 information about the world in an effective manner. Three to four times per second our 91 brain sends a signal to point our eyes to a new location using a fast, ballistic rotation 92 of the eyeballs known as a saccade (Yarbus 1967). 93 94Our understanding of the neural mechanisms underlying the human visual and 95 oculomotor systems and the interaction between them are based largely on research 96 in macaque (e.g., Felleman and Van Essen 1991;Fuchs 1967; Knöll et al. 2018; 97 Markov et al. 2014;Mustari 2017). Indeed, macaque has a visual brain remarkably 98 similar to human and has been the major source of our understanding on how the 99 visual cortex functions (Hubel and Wiesel 1969; Vanni et al. 2020), as well as how eye 100

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