What Is Personality?

2018 ◽  
pp. 7-82
Author(s):  
Dragan M. Svrakic ◽  
Mirjana Divac-Jovanovic
Keyword(s):  
Working Memory ◽  
Mental Life ◽  
Functional Brain ◽  
Self Reflection ◽  
Liquid Modernity ◽  
Mental Experience ◽  
Functional Brain Networks ◽  
The Mind ◽  
Memory Support ◽  
The Impact

This chapter reviews the neuroscience of brain and mind development. Recent advances in cognitive neuroscience, such as the concept of nonconscious working memory, support the psychanalytic concept of early object relations, which are believed to be the “elementary particles of the mind”: each contains a percept, a self-reflection, and the related affect and thus is not divisible to lower order units of mental experience. The functional brain networks giving rise to mental faculties (cognition, motivation, and emotions) are informed by these highly personal units of experience. Such “personalized” mental faculties self-organize into semistable subsystems within the mind, each providing a specific adaptive advantage to the mind as a whole. The impact of sociocultural transitions on human mental life, as well as the concepts of normal, postmodern, and fluid self in the context of conservativism, postmodernism, and liquid modernity, are discussed in detail.

scholarly journals Author Correction: Dynamic reconfiguration of functional brain networks during working memory training

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Karolina Finc ◽  
Kamil Bonna ◽  
Xiaosong He ◽  
David M. Lydon-Staley ◽  
Simone Kühn ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Networks ◽  
Dynamic Reconfiguration ◽  
Working Memory Training ◽  
Memory Training ◽  
Functional Brain ◽  
Functional Brain Networks

The impact of early-onset cannabis use on functional brain correlates of working memory

2010 ◽  
Vol 34 (6) ◽  
pp. 837-845 ◽  
Author(s):  
Benjamin Becker ◽  
Daniel Wagner ◽  
Euphrosyne Gouzoulis-Mayfrank ◽  
Elmar Spuentrup ◽  
Jörg Daumann
Keyword(s):  
Working Memory ◽  
Early Onset ◽  
Cannabis Use ◽  
Functional Brain ◽  
Brain Correlates ◽  
The Impact

Task-merging for finer separation of functional brain networks in working memory

Cortex ◽  
2020 ◽  
Vol 125 ◽  
pp. 246-271 ◽  
Author(s):  
Nicole Sanford ◽  
Jennifer C. Whitman ◽  
Todd S. Woodward
Keyword(s):  
Working Memory ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Sparse Graphical Models for Functional Connectivity Networks: Best Methods and the Autocorrelation Issue

2017 ◽  
Author(s):  
Yunan Zhu ◽  
Ivor Cribben
Keyword(s):  
Graphical Models ◽  
Graphical Model ◽  
Brain Networks ◽  
Information Criterion ◽  
Selection Method ◽  
Absolute Deviation ◽  
Data Set ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
The Impact

AbstractSparse graphical models are frequently used to explore both static and dynamic functional brain networks from neuroimaging data. However, the practical performance of the models has not been studied in detail for brain networks. In this work, we have two objectives. First, we compare several sparse graphical model estimation procedures and several selection criteria under various experimental settings, such as different dimensions, sample sizes, types of data, and sparsity levels of the true model structures. We discuss in detail the superiority and deficiency of each combination. Second, in the same simulation study, we show the impact of autocorrelation and whitening on the estimation of functional brain networks. We apply the methods to a resting-state functional magnetic resonance imaging (fMRI) data set. Our results show that the best sparse graphical model, in terms of detection of true connections and having few false-positive connections, is the smoothly clipped absolute deviation (SCAD) estimating method in combination with the Bayesian information criterion (BIC) and cross-validation (CV) selection method. In addition, the presence of autocorrelation in the data adversely affects the estimation of networks but can be helped by using the CV selection method. These results question the validity of a number of fMRI studies where inferior graphical model techniques have been used to estimate brain networks.

scholarly journals Striatal iron content is linked to reduced fronto-striatal brain function under working memory load

2019 ◽  
Author(s):  
Karen M. Rodrigue ◽  
Ana M. Daugherty ◽  
Chris M. Foster ◽  
Kristen M. Kennedy
Keyword(s):  
Working Memory ◽  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Iron Content ◽  
Brain Function ◽  
Memory Load ◽  
Dependent Manner ◽  
Working Memory Load ◽  
Functional Brain ◽  
The Impact

AbstractNon-heme iron accumulation contributes to age-related decline in brain structure and cognition via a cascade of oxidative stress and inflammation, although its effect on brain function is largely unexplored. Thus, we examine the impact of striatal iron on dynamic range of BOLD modulation to working memory load. N=166 healthy adults (age 20-94) underwent cognitive testing and an imaging session including n-back (0-, 2-, 3-, and 4-back fMRI), R2*-weighted imaging, and pcASL to measure cerebral blood flow. A statistical model was constructed to predict voxelwise BOLD modulation by age, striatal iron content and an age × iron interaction, controlling for cerebral blood flow, sex, and task response time. A significant interaction between age and striatal iron content on BOLD modulation was found selectively in the putamen, caudate, and inferior frontal gyrus. Greater iron was associated with reduced modulation to difficulty, particularly in middle-aged and younger adults with greater iron content. Further, iron-related decreases in modulation were associated with poorer executive function in an age-dependent manner. These results suggest that iron may contribute to differences in functional brain activation prior to older adulthood, highlighting the potential role of iron as an early factor contributing to trajectories of functional brain aging.

scholarly journals Impact of Transcutaneous Auricular Vagus Nerve Stimulation on Large-Scale Functional Brain Networks: From Local to Global

2021 ◽  
Vol 12 ◽  
Author(s):  
Thorsten Rings ◽  
Randi von Wrede ◽  
Timo Bröhl ◽  
Sophia Schach ◽  
Christoph Helmstaedter ◽  
...  
Keyword(s):  
Vagus Nerve ◽  
Nerve Stimulation ◽  
Mode Of Action ◽  
Vagus Nerve Stimulation ◽  
Large Scale ◽  
Brain Networks ◽  
Short Term ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
The Impact

Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel non-invasive brain stimulation technique considered as a potential supplementary treatment option for a wide range of diseases. Although first promising findings were obtained so far, the exact mode of action of taVNS is not fully understood yet. We recently developed an examination schedule to probe for immediate taVNS-induced modifications of large-scale epileptic brain networks. With this schedule, we observed short-term taVNS to have a topology-modifying, robustness- and stability-enhancing immediate effect on large-scale functional brain networks from subjects with focal epilepsies. We here expand on this study and investigate the impact of short-term taVNS on various local and global characteristics of large-scale evolving functional brain networks from a group of 30 subjects with and without central nervous system diseases. Our findings point to differential, at first glance counterintuitive, taVNS-mediated alterations of local and global topological network characteristics that result in a reconfiguration of networks and a modification of their stability and robustness properties. We propose a model of a stimulation-related stretching and compression of evolving functional brain networks that may help to better understand the mode of action of taVNS.

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