Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. How these hexagonal patterns arise has excited intense interest. It has previously been shown how a selforganizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? A neural model is proposed that converts path integration signals into hexagonal grid cell patterns of multiple scales. This GRID model creates only grid cell patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support a unified computational framework for explaining how entorhinal-hippocampal interactions support spatial navigation.
In natural behavior, animals have access to multiple sources of information, but only a few of these sources are relevant for learning and actions. Beyond choosing an appropriate action, making good decisions entails the ability to choose the relevant information, but fundamental questions remain about the brain's information sampling policies. Recent studies described the neural correlates of seeking information about a reward, but it remains unknown whether, and how, neurons encode choices of instrumental information, in contexts in which the information guides subsequent actions. Here we show that parietal cortical neurons involved in oculomotor decisions encode, before an information sampling saccade, the reduction in uncertainty that the saccade is expected to bring for a subsequent action. These responses were distinct from the neurons' visual and saccadic modulations and from signals of expected reward or reward prediction errors. Therefore, even in an instrumental context when information and reward gains are closely correlated, individual cells encode decision variables that are based on informational factors and can guide the active sampling of action-relevant cues.information sampling | saccades | attention | decisions | reward I n natural behavior, animals have access to multiple sources of information, but few of these sources are relevant for learning or action. Making good decisions therefore entails not only the selection of the ultimate action but, more primarily, the decision of which source of information to sample. Decisions about information sampling are central for tasks as diverse as making a medical diagnosis (which is the best test to prescribe?), making categorization decisions (which is the most informative feature?) (1, 2), and guiding skilled actions (what should I keep my eyes on while driving?). Despite the ubiquity and significance of active sampling mechanisms, few studies have been devoted to understanding these mechanisms and their importance for decision theories. Evidence accumulation has been extensively examined in decision research (3) but has been portrayed as a passive process, in the sense that decision makers rely on predetermined (experimenter selected) sources of information but cannot themselves determine which source to consult to guide a future action.Recent studies begin to shed light on this question by showing that animals (including pigeons, monkeys, and humans) prefer to observe cues that are predictive rather than nonpredictive about a future reward, and that the value of informative cues is encoded in the orbital frontal cortex and midbrain dopamine (DA) cells (4, 5). These investigations, however, have been limited to noninstrumental contexts in which animals seek to obtain information about a reward merely in order to know, but cannot act based on the information. Very little is known about the much more common scenario in which animals sample instrumental information to make decisions and guide future actions (6).Understanding instrumental sampling poses...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.