scholarly journals Network Neuroscience and Personality

2018 ◽  
Vol 1 ◽  
Author(s):  
Sebastian Markett ◽  
Christian Montag ◽  
Martin Reuter
Keyword(s):  
Nervous System ◽  
Individual Differences ◽  
Personality Traits ◽  
Brain Connectivity ◽  
Gray Matter Volume ◽  
Actual Behavior ◽  
Present Contribution ◽  
Nervous Systems ◽  
The Brain ◽  
Network Neuroscience

AbstractPersonality and individual differences originate from the brain. Despite major advances in the affective and cognitive neurosciences, however, it is still not well understood how personality and single personality traits are represented within the brain. Most research on brain-personality correlates has focused either on morphological aspects of the brain such as increases or decreases in local gray matter volume, or has investigated how personality traits can account for individual differences in activation differences in various tasks. Here, we propose that personality neuroscience can be advanced by adding a network perspective on brain structure and function, an endeavor that we label personality network neuroscience.With the rise of resting-state functional magnetic resonance imaging (MRI), the establishment of connectomics as a theoretical framework for structural and functional connectivity modeling, and recent advancements in the application of mathematical graph theory to brain connectivity data, several new tools and techniques are readily available to be applied in personality neuroscience. The present contribution introduces these concepts, reviews recent progress in their application to the study of individual differences, and explores their potential to advance our understanding of the neural implementation of personality.Trait theorists have long argued that personality traits are biophysical entities that are not mere abstractions of and metaphors for human behavior. Traits are thought to actually exist in the brain, presumably in the form of conceptual nervous systems. A conceptual nervous system refers to the attempt to describe parts of the central nervous system in functional terms with relevance to psychology and behavior. We contend that personality network neuroscience can characterize these conceptual nervous systems on a functional and anatomical level and has the potential do link dispositional neural correlates to actual behavior.

scholarly journals From static to temporal network theory: Applications to functional brain connectivity

2017 ◽  
Vol 1 (2) ◽  
pp. 69-99 ◽  
Author(s):  
William Hedley Thompson ◽  
Per Brantefors ◽  
Peter Fransson
Keyword(s):  
Network Theory ◽  
Temporal Dynamics ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Network Activity ◽  
Temporal Network ◽  
Functional Brain ◽  
Brain Connectome ◽  
The Brain ◽  
Network Neuroscience

Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain’s network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i) to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii) to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto.

scholarly journals Do you see the “face”? Individual differences in face pareidolia

2020 ◽  
Vol 14 ◽  
Author(s):  
Liu-Fang Zhou ◽  
Ming Meng
Keyword(s):  
Sex Differences ◽  
Individual Differences ◽  
Personality Traits ◽  
Face Perception ◽  
Clinical Applications ◽  
Neural Mechanisms ◽  
Developmental Factors ◽  
The Face ◽  
The Individual ◽  
The Brain

Abstract People tend to see faces from non-face objects or meaningless patterns. Such illusory face perception is called face pareidolia. Previous studies have revealed an interesting fact that there are huge individual differences in face pareidolia experience among the population. Here, we review previous findings on individual differences in face pareidolia experience from four categories: sex differences, developmental factors, personality traits and neurodevelopmental factors. We further discuss underlying cognitive or neural mechanisms to explain why some perceive the objects as faces while others do not. The individual differences in face pareidolia could not only offer scientific insights on how the brain works to process face information, but also suggest potential clinical applications.

The connectome

2020 ◽  
pp. 113-121
Author(s):  
Olaf Sporns
Keyword(s):  
Nervous System ◽  
Individual Differences ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Areas ◽  
Systematic Account ◽  
Functional Brain ◽  
Connectivity Structure ◽  
Complete Set ◽  
Selection Of

The connectome refers to a comprehensive network map of the connectivity of the nervous system. Such network maps are composed of sets of neural elements, which may correspond to individual neurons or brain areas, and their interconnections, which may correspond to synaptic links or inter-areal pathways. Connectome maps, at a given level of scale, provide a complete and systematic account of brain connectivity that portrays a complete set of anatomical or physiological relationships. This chapter provides an overview of the origins and definitions of the concept and its application to structural and functional brain connectivity, brief surveys of the major findings on the topology of the human connectome and how its connectivity structure shapes dynamic brain activity, and a selection of current themes in the study of individual differences in development and clinical populations.

Putting the Question in Perspective

2019 ◽  
pp. 3-12
Author(s):  
Dale Purves
Keyword(s):  
Nervous System ◽  
Scientific Progress ◽  
Operating Principle ◽  
Neural Function ◽  
Nervous Systems ◽  
The Brain ◽  
Human Nervous System

Basic to the question of whether or not the brain and the rest of the human nervous system have a simple operating principle are some central facts about biology and its relation to neuroscience. What nervous systems do is best appreciated in the context of what all organisms must accomplish in order to survive and prosper, with or without neural assistance. Although the author’s understanding of these issues is no more than that of any other student who pays a modicum of attention to the broader sweep of scientific progress, this chapter considers some points of consensus. The aim is to situate the quest for a principle of neural function in the context of biology writ large.

Personality dynamics in the brain: Individual differences in updating of representations and their phylogenetic roots

2018 ◽  
Author(s):  
Mattie Tops ◽  
Hans IJzerman ◽  
Markus Quirin
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Environmental Conditions ◽  
Political Thought ◽  
Large Scale ◽  
Animal Personality ◽  
Internal Models ◽  
Personality Dimensions ◽  
The Brain ◽  
The Continuum

To cope with changing and unfamiliar situations, individuals process novel information and integrate this information into internal models that were formed through previous experiences. We propose that the continuum of the degree to which people update these internal models when encountering novel information is central to personality dynamics. Personality traits therefore arise at both ends of this continuum. Personality dimensions and behavioral manifestations (such as those reflected in liberal and conservative political thought) are classified at different points along this continuum, as well as according to the availability and flexible situational accessibility of internal models. Our model is rooted in neurobiological evidence (interactions of large-scale brain networks in particular) and shows strong parallels with models of basic animal personality traits. The model thus permits to explain both personality traits and personality dynamics, including phasic and stable adaptations to environmental conditions. Moreover, the model sheds light on the development of personality and its origins through phylogenetic and ontogenetic time.

scholarly journals Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad-Hassan Tayarani-Najaran ◽  
Michael Schmuker
Keyword(s):  
Signal Processing ◽  
Nervous System ◽  
Information Processing ◽  
Traditional Approach ◽  
Comprehensive Overview ◽  
Nervous Systems ◽  
Future Challenges ◽  
Event Based ◽  
The Brain ◽  
Physical Quantities

The nervous systems converts the physical quantities sensed by its primary receptors into trains of events that are then processed in the brain. The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches to sensing and signal processing. The key principle pursued in neuromorphic sensing is to shed the traditional approach of periodic sampling in favor of an event-driven scheme that mimicks sampling as it occurs in the nervous system, where events are preferably emitted upon the change of the sensed stimulus. In this paper we highlight the advantages and challenges of event-based sensing and signal processing in the visual, auditory and olfactory domains. We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities. Our aim is to facilitate research in event-based sensing and signal processing by providing a comprehensive overview of the research performed previously as well as highlighting conceptual advantages, current progress and future challenges in the field.

Individual Differences in Personality Traits

2015 ◽  
Vol 29 (3) ◽  
pp. 107-111
Author(s):  
A. Karimizadeh ◽  
Amin Mahnam ◽  
M. R. Yazdchi ◽  
M. A. Besharat
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Posterior Parietal Cortex ◽  
Gray Matter Volume ◽  
Brain Mri ◽  
Brain Structures ◽  
Brain Regions ◽  
Standard Scale ◽  
Posterior Parietal ◽  
Magnetic Resonance Imaging Mri

Abstract. During the last decade, an increasing number of studies have used neuroscientific methods to examine the relationships between different personality traits and brain structures. This includes the Magnetic Resonance Imaging (MRI)-based analysis of correlations between individual differences in personality traits and the structural variance of specific brain regions. Perfectionism is a personality trait that remains relatively stable over time, and it is influenced by heredity. In this study, the possible brain regions that structurally correlated with both positive and negative perfectionism were investigated. Voxel-based morphometry was used to analyze the whole brain MRI images of 49 participants, and their levels of perfectionism were also evaluated using a standard scale. The statistical analysis revealed significant correlations between negative perfectionism and the gray matter volume of the thalamus and left posterior parietal cortex (precuneus) structures. This finding suggests that differences in perfectionism between individuals may reflect structural variances in these regions of the brain.

Apollos Gift and Curse: Making Music as a model for Adaptive and Maladaptive Plasticity

e-Neuroforum ◽  
2017 ◽  
Vol 23 (2) ◽  
Author(s):  
Eckart Altenmüller ◽  
Shinichi Furuya
Keyword(s):  
Nervous System ◽  
Visual Analysis ◽  
Brain Plasticity ◽  
Brain Connectivity ◽  
Musical Training ◽  
Music Performance ◽  
Fine Motor ◽  
Sensory Motor ◽  
Maladaptive Plasticity ◽  
The Brain

AbstractMusicians with extensive training and playing experience provide an excellent model for studying plasticity of the human brain. The demands placed on the nervous system by music performance are very high and provide a uniquely rich multisensory and motor experience to the player. As confirmed by neuroimaging studies, playing music depends on a strong coupling of perception and action mediated by sensory, motor, and multimodal integration regions distributed throughout the brain. A pianist, for example, must draw on a whole set of complex skills, including translating visual analysis of musical notation into motor movements, coordinating multisensory information with bimanual motor activity, developing fine motor skills in both hands coupled with metric precision, and monitoring auditory feedback to fine-tune a performance as it progresses. This article summarizes research on the effects of musical training on brain function, brain connectivity and brain structure. First we address factors inducing and continuously driving brain plasticity in dedicated musicians, arguing that prolonged goal-directed practice, multi-sensory-motor integration, high arousal, and emotional and social rewards contribute to these plasticity-induced brain adaptations. Subsequently, we briefly review the neuroanatomy and neurophysiology underpinning musical activities. Here we focus on the perception of sound, integration of sound and movement, and the physiology of motor planning and motor control. We then review the literature on functional changes in brain activation and brain connectivity along with the acquisition of musical skills, be they auditory or sensory-motor. In the following section we focus on structural adaptions in the gray matter of the brain and in fiber-tract density associated with music learning. Here we critically discuss the findings that structural changes are mostly seen when starting musical training after age seven, whereas functional optimization is more effective before this age. We then address the phenomenon of de-expertise, reviewing studies which provide evidence that intensive music-making can induce dysfunctional changes which are accompanied by a degradation of skilled motor behavior, also termed “musician’s dystonia”. This condition, which is frequently highly disabling, mainly affects male classical musicians with a history of compulsive working behavior, anxiety disorder or chronic pain. Functional and structural brain changes in these musicians are suggestive of deficient inhibition and excess excitation in the central nervous system, which leads to co-activation of antagonistic pairs of muscles during performance, reducing movement speed and quality. We conclude with a concise summary of the role of brain plasticity, metaplasticity and maladaptive plasticity in the acquisition and loss of musicians’ expertise.

Glucuronyl 3-sulfate occurs exclusively on distal unmyelinated terminals of selected sensory neurons in the peripheral nervous system

1995 ◽  
Vol 53 ◽  
pp. 958-959
Author(s):  
S.S. Spicer ◽  
B.A. Schulte
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Cerebral Cortex ◽  
Peripheral Nervous System ◽  
Sensory Neurons ◽  
Sensory Nerves ◽  
Tissue Antigens ◽  
The Central Nervous System ◽  
The Brain ◽  
Leu 7

Generation of monoclonal antibodies (MAbs) against tissue antigens has yielded several (VC1.1, HNK- 1, L2, 4F4 and anti-leu 7) which recognize the unique sugar epitope, glucuronyl 3-sulfate (Glc A3- SO4). In the central nervous system, these MAbs have demonstrated Glc A3-SO4 at the surface of neurons in the cerebral cortex, the cerebellum, the retina and other widespread regions of the brain.Here we describe the distribution of Glc A3-SO4 in the peripheral nervous system as determined by immunostaining with a MAb (VC 1.1) developed against antigen in the cat visual cortex. Outside the central nervous system, immunoreactivity was observed only in peripheral terminals of selected sensory nerves conducting transduction signals for touch, hearing, balance and taste. On the glassy membrane of the sinus hair in murine nasal skin, just deep to the ringwurt, VC 1.1 delineated an intensely stained, plaque-like area (Fig. 1). This previously unrecognized structure of the nasal vibrissae presumably serves as a tactile end organ and to our knowledge is not demonstrable by means other than its selective immunopositivity with VC1.1 and its appearance as a densely fibrillar area in H&E stained sections.

Ultrastructural morphology of neurosecretory neurons in the barnacle Balanus amphitrite

1990 ◽  
Vol 48 (3) ◽  
pp. 434-435
Author(s):  
Grazia Tagliafierro ◽  
Cristiana Crosa ◽  
Marco Canepa ◽  
Tiziano Zanin
Keyword(s):  
Nervous System ◽  
Ultrastructural Level ◽  
Uranyl Acetate ◽  
Balanus Amphitrite ◽  
Neurosecretory Neurons ◽  
The Central Nervous System ◽  
Ultrathin Sections ◽  
Dense Core Granules ◽  
The Brain ◽  
Ocellar Nerve

Barnacles are very specialized Crustacea, with strongly reduced head and abdomen. Their nervous system is rather simple: the brain or supra-oesophageal ganglion (SG) is a small bilobed structure and the toracic ganglia are fused into a single ventral mass, the suboesophageal ganglion (VG). Neurosecretion was shown in barnacle nervous system by histochemical methods and numerous putative hormonal substances were extracted and tested. Recently six different types of dense-core granules were visualized in the median ocellar nerve of Balanus hameri and serotonin and FMRF-amide like substances were immunocytochemically detected in the nervous system of Balanus amphitrite. The aim of the present work is to localize and characterize at ultrastructural level, neurosecretory neuron cell bodies in the VG of Balanus amphitrite.Specimens of Balanus amphitrite were collected in the port of Genova. The central nervous system were Karnovsky fixed, osmium postfixed, ethanol dehydrated and Durcupan ACM embedded. Ultrathin sections were stained with uranyl acetate and lead citrate. Ultrastructural observations were made on a Philips M 202 and Zeiss 109 T electron microscopy.

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