Learning a New Selection Rule in Visual and Frontal Cortex

Cerebral Cortex, August 2016;26: 3611–3626 doi:10.1093/cercor/bhw155 Advance Access Publication Date: 6 June 2016 Original Article ORIGINAL ARTICLE Learning a New Selection Rule in Visual and Frontal Cortex Chris van der Togt1, Liviu Stănişor1, Arezoo Pooresmaeili1, Larissa Albantakis2, Gustavo Deco3, and Pieter R. Roelfsema1,4,5 1 Department of Vision and Cognition, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, The Netherlands, 2Madison School of Medicine, Department of Psychiatry, University of Wisconsin, 6001 Research Park Boulevard, Madison, WI 53719, USA, 3 Dept. de Tecnologies de la Informació i les Comunicacions, Universitat Pompeu Fabra, C\ Tanger, 122-140, 08018 Barcelona, Spain, 4Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, The Netherlands and 5Psychiatry Department, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands Address correspondence to email: Chris van der Togt and Liviu Stănişor contributed equally to this work. Abstract How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new iconselection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey’s choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. Key words: frontal eye fields, learning, primary visual cortex, visual attention, visual routines Introduction Imagine that you want to learn a new game. There are multiple ways to learn the rules. For example, you can choose to study the manual. However, in many cases, the best way to learn is to try to optimize your strategy while playing, making many errors at the start. Virtually in all games, you will have to learn to attend features that matter, for example, the shape of the chess pieces or the symbols on cards, and to ignore the rest. However, how do you distribute your attention and make decisions when you do not yet know the rules? In previous work, researchers have gained insight into the neuronal mechanisms underlying sensory decisions. Many studies have focused on the parietal and motor cortex in tasks © The Author 2016. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact 3612 | Cerebral Cortex , 2016, Vol. 26, No. 8 where monkeys choose to move their eyes to one of a number of positions (Schall 1991; Schall et al. 1995; Hanes and Schall 1996; Kim and Shadlen 1999; Gold and Shadlen 2001, 2007; Murthy et al. 2001; Ding and Gold 2012). These studies revealed that eye movement decisions are implemented as a race or a competition between pools of neurons that code for different eye movement decisions. When the sensory evidence in favor of one of the eye movements is strong, neurons that code for this eye movement quickly ramp up their activity, but the buildup of activity is more gradual and reaction times are prolonged if the evidence is weak. In these previous tasks, the monkeys were familiar with the rule so that it was strategic to wait for more evidence and to postpone the response when the stimulus was weak. The optimal strategy may be different when the stimulus is clearly visible, but the rules are unknown. How is a decision made in this situation? Do monkeys also postpone their decision in the absence of evidence for one or the other decision? In the present study, we were interested in the changes in the representations in the visual and frontal cortex when monkeys learn a new rule. The role of the frontal cortex in decision-making has been well established (Schall 1991; Schall et al. 1995; Hanes and Schall 1996; Kim and Shadlen 1999; Murthy et al. 2001; Ding and Gold 2012), but we here also investigated the influence of decision-making on neuronal activity in visual cortex because of the intimate relationship between decision-making and shifts of attention. The decision to make an eye movement is invariably associated with a shift of attention to the location of the eye movement target (Kowler et al. 1995; Deubel and Schneider 1996). Furthermore, learning an unknown rule implies that one learns to attend to the relevant features and to ignore irrelevant ones. Learning, therefore, has a pronounced influence on the distribution of attention. Specifically, visual objects that have been associated with a high reward in previous trials will usually attract attention in later trials (Della Libera and Chelazzi 2009; Raymond and O’Brien 2009; Hickey et al. 2010; Anderson et al. 2011; Chelazzi et al. 2013). Also at a neuronal level, the representations of stimuli that have been associated with high rewards are enhanced in visual, parietal, and frontal cortex. Their representations resemble the representation of attended stimuli (Kim and Shadlen 1999; Maunsell 2004; Serences 2008; Peck et al. 2009; Stănişor et al. 2013). Because the present study does not aim to dissociate the influence of attention from the influence of eye movement selection on neuronal activity, we will use the more neutral term “selection signal” to describe the effects of stimulus selection on activity in visual and frontal cortex. Leveraging on earlier work that examined how monkeys learn arbitrary associations between stimuli and responses (Chen and Wise 1995a, 1995b, 1996; Asaad et al. 1998; Tremblay et al. 1998; Erickson and Desimone 1999; Jagadeesh et al. 2001; Wirth et al. 2003; Brasted and Wise 2004; Pasupathy and Miller 2005), we devised a new icon-selection task that allowed us to investigate selection signals related to motor planning in the frontal cortex and to shifts of attention in the visual cortex. Specifically, we presented a new pair of shapes (icons) to the monkeys in every session that were connected by (...truncated)