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      Mismatch Negativity (MMN) in Freely-Moving Rats with Several Experimental Controls

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          Abstract

          Mismatch negativity (MMN) is a scalp-recorded electrical potential that occurs in humans in response to an auditory stimulus that defies previously established patterns of regularity. MMN amplitude is reduced in people with schizophrenia. In this study, we aimed to develop a robust and replicable rat model of MMN, as a platform for a more thorough understanding of the neurobiology underlying MMN. One of the major concerns for animal models of MMN is whether the rodent brain is capable of producing a human-like MMN, which is not a consequence of neural adaptation to repetitive stimuli. We therefore tested several methods that have been used to control for adaptation and differential exogenous responses to stimuli within the oddball paradigm. Epidural electroencephalographic electrodes were surgically implanted over different cortical locations in adult rats. Encephalographic data were recorded using wireless telemetry while the freely-moving rats were presented with auditory oddball stimuli to assess mismatch responses. Three control sequences were utilized: the flip-flop control was used to control for differential responses to the physical characteristics of standards and deviants; the many standards control was used to control for differential adaptation, as was the cascade control. Both adaptation and adaptation-independent deviance detection were observed for high frequency (pitch), but not low frequency deviants. In addition, the many standards control method was found to be the optimal method for observing both adaptation effects and adaptation-independent mismatch responses in rats. Inconclusive results arose from the cascade control design as it is not yet clear whether rats can encode the complex pattern present in the control sequence. These data contribute to a growing body of evidence supporting the hypothesis that rat brain is indeed capable of exhibiting human-like MMN, and that the rat model is a viable platform for the further investigation of the MMN and its associated neurobiology.

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          Most cited references44

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          Ethotransmission: communication of emotional states through ultrasonic vocalization in rats.

          Adult rats emit two categories of ultrasonic vocalizations, 22 kHz calls and 50 kHz calls. These vocalizations communicate animal's emotional state to other members of the social group. Production of social vocalizations is an evolutionary old activity in vertebrates, and is regulated by well-preserved brain circuitries. The 22 kHz calls express negative, aversive state and are initiated by activity of the mesolimbic cholinergic system originating from laterodorsal tegmental nucleus. The 50 kHz calls express positive, appetitive state and are initiated by activity of the mesolimbic dopaminergic system originating from the ventral tegmental area. The 22 kHz calls serve as warning and alarm calls, while the 50 kHz calls serve as affiliative and social-cooperating calls. These specie-specific vocalizations play role of ethological transmitters, termed ethotransmitters, that is, they are species-specific signals that are selectively recognized by receivers and have capability of changing emotional state of the receivers. Copyright © 2013 Elsevier Ltd. All rights reserved.
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            Cerebral generators of mismatch negativity (MMN) and its magnetic counterpart (MMNm) elicited by sound changes.

            K Alho (1995)
            Infrequent ("deviant") sounds occurring in a sequence of repetitive ("standard") sounds elicit an event-related brain potential (ERP) response called the mismatch negativity (MMN) even in the absence of attention to these sounds. MMN appears to be caused by a neuronal mismatch between the deviant auditory input and a sensory-memory trace representing the standard stimuli. This automatic mismatch process has presumably a central role in discrimination of changes in the acoustic environment outside the focus of attention. Thus, localizing cerebral generators of MMN might help identify brain mechanisms of auditory sensory memory and involuntary attention. This review summarizes results from studies aimed at localizing MMN generators on the basis of (1) scalp-distribution, (2) magnetoencephalographic (MEG), (3) intracranial, and (4) brain-lesion data. These studies indicate that a major MMN source is located in the auditory cortex. However, the exact location of this MMN generator appears to depend on which feature of a sound is changed (e.g., frequency, intensity, or duration), as well as on the complexity of the sound (e.g., a simple tone versus complex sound). Consequently, memory traces for different acoustic features, as well as for sounds of different complexity, might be located in different regions of auditory cortex. However, MMN appears to have generators in other brain structures, too. There is some evidence for contribution of frontal-lobe activity to the MMN, which might be related to the involuntary switching of attention to a stimulus change occurring outside the focus of attention. In addition, intracranial MMN recordings in animals suggest that at least in some species, MMN subcomponents also may be generated in the thalamus and hippocampus.
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              The neural circuitry of pre-attentive auditory change-detection: an fMRI study of pitch and duration mismatch negativity generators.

              Electrophysiological studies have revealed a pre-attentive change-detection system in the auditory modality. This system emits a signal termed the mismatch negativity (MMN) when any detectable change in a regular pattern of auditory stimulation occurs. The precise intracranial sources underlying MMN generation, and in particular whether these vary as a function of the acoustic feature that changes, is a matter of some debate. Using functional magnetic resonance imaging, we show that anatomically distinct networks of auditory cortices are activated as a function of the deviating acoustic feature--in this case, tone frequency and tone duration--strongly supporting the hypothesis that MMN generators in auditory cortex are feature dependent. We also detail regions of the frontal and parietal cortices activated by change-detection processes. These regions also show feature dependence and we hypothesize that they reflect recruitment of attention-switching mechanisms.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                21 October 2014
                : 9
                : 10
                : e110892
                Affiliations
                [1 ]School of Psychology, University of Newcastle, Callaghan, NSW, Australia
                [2 ]Priority Centre for Translational Neuroscience and Mental Health Research, University of Newcastle, Newcastle, NSW, Australia
                [3 ]Schizophrenia Research Institute, Darlinghurst, NSW, Australia
                [4 ]Hunter Medical Research Institute, Newcastle, NSW, Australia
                [5 ]School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
                [6 ]Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland
                [7 ]School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
                [8 ]Neuroscience Research Australia, Randwick, NSW, Australia
                University of Salamanca- Institute for Neuroscience of Castille and Leon and Medical School, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PTM DMH LH WRF JT TWB MH MP US KZ. Performed the experiments: LH CM. Analyzed the data: LH WRF PTM. Contributed reagents/materials/analysis tools: WRF MP DMH PTM. Wrote the paper: LH WRF TWB MH CM MP US KZ DMH PTM.

                Article
                PONE-D-14-26003
                10.1371/journal.pone.0110892
                4205004
                25333698
                2f499d57-1b0a-49c5-9a03-d17edfca58eb
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 June 2014
                : 23 September 2014
                Page count
                Pages: 16
                Funding
                This project was funded by a National Health and Medical Research Council of Australia Project Grant, ID 1026070. The contents of this article are solely the responsibility of the authors and do not reflect the views of the NHMRC ( http://nhmrc.gov.au). Support was received from the University of Newcastle Near Miss grant, CAPEX funding and travel fellowship schemes ( http://www.newcastle.edu.au). Further support was provided by the Hunter Medical Research Institute ( http://www.hmri.com.au) and the Schizophrenia Research Institute ( http://www.schizophreniaresearch.org.au), which are supported by infrastructure funding from NSW Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Electroencephalography
                Neurophysiology
                Brain Electrophysiology
                Sensory Systems
                Auditory System
                Research and Analysis Methods
                Model Organisms
                Animal Models
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All mean amplitude data used for statistical analyses and graphs of mean amplitudes are within the paper and its Supporting Information files.

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