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      Evidence for Mediodorsal Thalamus and Prefrontal Cortex Interactions during Cognition in Macaques

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          Abstract

          It is proposed that mediodorsal thalamus contributes to cognition via interactions with prefrontal cortex. However, there is relatively little evidence detailing the interactions between mediodorsal thalamus and prefrontal cortex linked to cognition in primates. This study investigated these interactions during learning, memory, and decision-making tasks in rhesus monkeys using a disconnection lesion approach. Preoperatively, monkeys learned object-in-place scene discriminations embedded within colorful visual backgrounds. Unilateral neurotoxic lesions to magnocellular mediodorsal thalamus (MDmc) impaired the ability to learn new object-in-place scene discriminations. In contrast, unilateral ablations to ventrolateral and orbital prefrontal cortex (PFv+o) left learning intact. A second unilateral MDmc or PFv+o lesion in the contralateral hemisphere to the first operation, causing functional MDmc–PFv+o disconnection across hemispheres, further impaired learning object-in-place scene discriminations, although object discrimination learning remained intact. Adaptive decision-making after reward satiety devaluation was also reduced. These data highlight the functional importance of interactions between MDmc and PFv+o during learning object-in-place scene discriminations and adaptive decision-making but not object discrimination learning. Moreover, learning deficits observed after unilateral removal of MDmc but not PFv+o provide direct behavioral evidence of the MDmc role influencing more widespread regions of the frontal lobes in cognition.

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          Most cited references70

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          Limbic connections of the orbital and medial prefrontal cortex in macaque monkeys.

          Previous studies have shown that the orbital and medial prefrontal cortex (OMPFC) is extensively connected with medial temporal and cingulate limbic structures. In this study, the organization of these projections was defined in relation to architectonic areas within the OMPFC. All of the limbic structures were substantially connected with the following posterior and medial orbital areas: the posteromedial, medial, intermediate, and lateral agranular insular areas (Iapm, Iam, Iai, and Ial, respectively) and areas 11m, 13a, 13b, 14c and 14r. In contrast, lateral orbital areas 12o, 12m, and 12l and medial wall areas 24a,b and 32 were primarily connected with the amygdala, the temporal pole, and the cingulate cortex. Data were not obtained on the posteroventral medial wall. Three distinct projections were recognized from the basal amygdaloid nucleus: 1) The dorsal part projected to area 12l; 2) the ventromedial part projected to most areas in the posterior and medial orbital cortex except for area Iai, 12o, 13a, and 14c; and 3) the ventrolateral part projected to orbital areas 12o, Iai, 13a, 14c, and to the medial wall areas. The accessory basal and lateral amygdaloid nuclei projected most strongly to areas in the posterior and medial orbital cortex. The medial, anterior cortical, and central amygdaloid nuclei and the periamygdaloid cortex were connected with the posterior orbital areas. The projection from the hippocampus originated from the rostral subiculum and terminated in the medial orbital areas. The same region was reciprocally connected with the anteromedial nucleus of the thalamus, which received input from the rostral subiculum. The parahippocampal cortical areas (including the temporal polar, entorhinal, perirhinal, and posterior parahippocampal cortices) were primarily connected with posterior and medial orbital areas, with some projections to the dorsal part of the medial wall. The rostral cingulate cortex sent fibers to the medial wall, to the medial orbital areas, and to lateral areas 12o, 12r, and Iai. The posterior cingulate gyrus, including the caudomedial lobule, was especially strongly connected with area 11m.
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            The role of the thalamus in the flow of information to the cortex.

            The lateral geniculate nucleus is the best understood thalamic relay and serves as a model for all thalamic relays. Only 5-10% of the input to geniculate relay cells derives from the retina, which is the driving input. The rest is modulatory and derives from local inhibitory inputs, descending inputs from layer 6 of the visual cortex, and ascending inputs from the brainstem. These modulatory inputs control many features of retinogeniculate transmission. One such feature is the response mode, burst or tonic, of relay cells, which relates to the attentional demands at the moment. This response mode depends on membrane potential, which is controlled effectively by the modulator inputs. The lateral geniculate nucleus is a first-order relay, because it relays subcortical (i.e. retinal) information to the cortex for the first time. By contrast, the other main thalamic relay of visual information, the pulvinar region, is largely a higher-order relay, since much of it relays information from layer 5 of one cortical area to another. All thalamic relays receive a layer-6 modulatory input from cortex, but higher-order relays in addition receive a layer-5 driver input. Corticocortical processing may involve these corticothalamocortical 're-entry' routes to a far greater extent than previously appreciated. If so, the thalamus sits at an indispensable position for the modulation of messages involved in corticocortical processing.
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              Investigation of the single case in neuropsychology: confidence limits on the abnormality of test scores and test score differences.

              Neuropsychologists often need to estimate the abnormality of an individual patient's test score, or test score discrepancies, when the normative or control sample against which the patient is compared is modest in size. Crawford and Howell [The Clinical Neuropsychologist 12 (1998) 482] and Crawford et al. [Journal of Clinical and Experimental Neuropsychology 20 (1998) 898] presented methods for obtaining point estimates of the abnormality of test scores and test score discrepancies in this situation. In the present study, we extend this work by developing methods of setting confidence limits on the estimates of abnormality. Although these limits can be used with data from normative or control samples of any size, they will be most useful when the sample sizes are modest. We also develop a method for obtaining point estimates and confidence limits on the abnormality of a discrepancy between a patient's mean score on k-tests and a test entering into that mean. Computer programs that implement the formulae for the confidence limits (and point estimates) are described and made available.
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                Author and article information

                Journal
                Cereb Cortex
                Cereb. Cortex
                cercor
                cercor
                Cerebral Cortex (New York, NY)
                Oxford University Press
                1047-3211
                1460-2199
                November 2015
                15 May 2015
                15 May 2015
                : 25
                : 11
                : 4519-4534
                Affiliations
                [1 ]Glickenhaus Laboratory of Neuropsychology and Friedman Brain Institute, Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai , New York, NY 10029, USA
                [2 ]Department of Bioengineering, Imperial College London, South Kensington , London SW7 2BP, UK
                [3 ]Department of Experimental Psychology, Oxford University , Oxford OX1 3UD, UK
                Author notes
                Address correspondence to Anna S. Mitchell, Department of Experimental Psychology, Oxford University, South Parks Road, Oxford OX1 3UD, UK. Email: anna.mitchell@ 123456psy.ox.ac.uk
                Article
                bhv093
                10.1093/cercor/bhv093
                4816796
                25979086
                3642ff5e-540b-47eb-85f3-b64ec9f1b19b
                © The Author 2015. Published by Oxford University Press

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Neurology
                amnesia,decision-making,dysfunction,learning,monkey,orbitofrontal cortex,prefrontal cortex
                Neurology
                amnesia, decision-making, dysfunction, learning, monkey, orbitofrontal cortex, prefrontal cortex

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