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      The Contribution of AMPA and NMDA Receptors to Persistent Firing in the Dorsolateral Prefrontal Cortex in Working Memory

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          Abstract

          Many tasks demand that information is kept online for a few seconds before it is used to guide behavior. The information is kept in working memory as the persistent firing of neurons encoding the memorized information. The neural mechanisms responsible for persistent activity are not yet well understood. Theories attribute an important role to ionotropic glutamate receptors, and it has been suggested that NMDARs are particularly important for persistent firing because they exhibit long time constants. Ionotropic AMPARs have shorter time constants and have been suggested to play a smaller role in working memory. Here we compared the contribution of AMPARs and NMDARs to persistent firing in the dlPFC of male macaque monkeys performing a delayed saccade to a memorized spatial location. We used iontophoresis to eject small amounts of glutamate receptor antagonists, aiming to perturb, but not abolish, neuronal activity. We found that both AMPARs and NMDARs contributed to persistent activity. Blockers of the NMDARs decreased persistent firing associated with the memory of the neuron's preferred spatial location but had comparatively little effect on the representation of the antipreferred location. They therefore decreased the information conveyed by persistent firing about the memorized location. In contrast, AMPAR blockers decreased activity elicited by the memory of both the preferred and antipreferred location, with a smaller effect on the information conveyed by persistent activity. Our results provide new insights into the contribution of AMPARs and NMDARs to persistent activity during working memory tasks.

          SIGNIFICANCE STATEMENT Working memory enables us to hold on to information that is no longer available to the senses. It relies on the persistent activity of neurons that code for the memorized information, but the detailed mechanisms are not yet well understood. Here we investigated the role of NMDARs and AMPARs in working memory using iontophoresis of antagonists in the PFC of monkeys remembering the location of a visual stimulus for an eye movement response. AMPARs and NMDARs both contributed to persistent activity. NMDAR blockers mostly decreased persistent firing associated with the memory of the neuron's preferred spatial location, whereas AMPAR blockers caused a more general suppression. These results provide new insight into the contribution of AMPARs and NMDARs to working memory.

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          Most cited references67

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          Working Memory: Theories, Models, and Controversies

          I present an account of the origins and development of the multicomponent approach to working memory, making a distinction between the overall theoretical framework, which has remained relatively stable, and the attempts to build more specific models within this framework. I follow this with a brief discussion of alternative models and their relationship to the framework. I conclude with speculations on further developments and a comment on the value of attempting to apply models and theories beyond the laboratory studies on which they are typically based.
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            Cellular basis of working memory

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              Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

              This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.
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                Author and article information

                Journal
                J Neurosci
                J. Neurosci
                jneuro
                jneurosci
                J. Neurosci
                The Journal of Neuroscience
                Society for Neuroscience
                0270-6474
                1529-2401
                18 March 2020
                18 March 2020
                : 40
                : 12
                : 2458-2470
                Affiliations
                [1] 1Department of Vision & Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands,
                [2] 2Cognitive Neuroimaging Unit, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction des Sciences du Vivant/Institut d'Imagerie Biomédicale, Institut National de la Santé et de la Recherche Médicale, NeuroSpin Center, Université Paris-Sud, Université Paris-Saclay, 91191 Gif-sur-Yvette, France,
                [3] 3Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands, and
                [4] 4Psychiatry Department, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
                Author notes
                Correspondence should be addressed to Pieter R. Roelfsema at p.roelfsema@ 123456nin.knaw.nl

                Author contributions: B.v.V., T.v.K., and P.R.R. designed research; B.v.V., T.v.K., D.V., and P.R.R. performed research; B.v.V., T.v.K., D.V., and P.R.R. analyzed data; B.v.V., T.v.K., D.V., and P.R.R. edited the paper; B.v.V., T.v.K., and P.R.R. wrote the paper; T.v.K. wrote the first draft of the paper.

                *B.v.V., T.v.K., and d.V. contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1625-0034
                Article
                2121-19
                10.1523/JNEUROSCI.2121-19.2020
                7083532
                32051326
                62c878b0-e7a1-40d9-83fc-6bc61b076cda
                Copyright © 2020 van Vugt et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 9 August 2019
                : 24 December 2019
                : 2 February 2020
                Categories
                Research Articles
                Systems/Circuits

                ampar,macaque monkey,nmdar,pfc,working memory
                ampar, macaque monkey, nmdar, pfc, working memory

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