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      Increase in short-term memory capacity induced by down-regulating individual theta frequency via transcranial alternating current stimulation

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          Abstract

          Working memory (WM) and short-term memory (STM) supposedly rely on the phase-amplitude coupling (PAC) of neural oscillations in the theta and gamma frequency ranges. The ratio between the individually dominant gamma and theta frequencies is believed to determine an individual’s memory capacity. The aim of this study was to establish a causal relationship between the gamma/theta ratio and WM/STM capacity by means of transcranial alternating current stimulation (tACS). To achieve this, tACS was delivered at a frequency below the individual theta frequency. Thereby the individual ratio of gamma to theta frequencies was changed, resulting in an increase of STM capacity. Healthy human participants ( N = 33) were allocated to two groups, one receiving verum tACS, the other underwent a sham control protocol. The electroencephalogram (EEG) was measured before stimulation and analyzed with regard to the properties of PAC between theta and gamma frequencies to determine individual stimulation frequencies. After stimulation, EEG was recorded again in order to find after-effects of tACS in the oscillatory features of the EEG. Measures of STM and WM were obtained before, during and after stimulation. Frequency spectra and behavioral data were compared between groups and different measurement phases. The tACS- but not the sham stimulated group showed an increase in STM capacity during stimulation. WM was not affected in either groups. An increase in task-related theta amplitude after stimulation was observed only for the tACS group. These augmented theta amplitudes indicated that the manipulation of individual theta frequencies was successful and caused the increase in STM capacity.

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          Most cited references45

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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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            Removing electroencephalographic artifacts by blind source separation.

            Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.
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              Working memory, short-term memory, and general fluid intelligence: a latent-variable approach.

              A study was conducted in which 133 participants performed 11 memory tasks (some thought to reflect working memory and some thought to reflect short-term memory), 2 tests of general fluid intelligence, and the Verbal and Quantitative Scholastic Aptitude Tests. Structural equation modeling suggested that short-term and working memories reflect separate but highly related constructs and that many of the tasks used in the literature as working memory tasks reflect a common construct. Working memory shows a strong connection to fluid intelligence, but short-term memory does not. A theory of working memory capacity and general fluid intelligence is proposed: The authors argue that working memory capacity and fluid intelligence reflect the ability to keep a representation active, particularly in the face of interference and distraction. The authors also discuss the relationship of this capability to controlled attention, and the functions of the prefrontal cortex.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                08 May 2015
                2015
                : 9
                : 257
                Affiliations
                [1] 1Experimental Psychology Lab, Department of Psychology, Cluster for Excellence “Hearing4all”, European Medical School, Faculty for Medicine and Health Sciences, University of Oldenburg Oldenburg, Germany
                [2] 2Research Center Neurosensory Science, University of Oldenburg Oldenburg, Germany
                [3] 3Department of Psychology, University of Oslo Oslo, Norway
                [4] 4The Mind Research Network Albuquerque, NM, USA
                Author notes

                Edited by: Klaus Gramann, Berlin Institute of Technology, Germany

                Reviewed by: Vincenzo Romei, University of Essex, UK; Paul Sauseng, University of Surrey, UK

                *Correspondence: Christoph S. Herrmann, Experimental Psychology Lab, Department of Psychology, Cluster for Excellence “Hearing4all”, European Medical School, Faculty for Medicine and Health Sciences, University of Oldenburg, Ammerländer Heerstraße 116-118, Oldenburg 26129, Germany christoph.herrmann@ 123456uni-oldenburg.de

                Indicates shared last-authorship.

                Article
                10.3389/fnhum.2015.00257
                4424841
                26005411
                851dfee2-8c42-4dad-8401-38ddda678b79
                Copyright © 2015 Vosskuhl, Huster and Herrmann.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 February 2015
                : 21 April 2015
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 68, Pages: 10, Words: 8243
                Categories
                Neuroscience
                Original Research

                Neurosciences
                short-term memory,working memory,theta-gamma coupling,tacs,phase-amplitude coupling
                Neurosciences
                short-term memory, working memory, theta-gamma coupling, tacs, phase-amplitude coupling

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