scholarly journals Multistability and metastability: understanding dynamic coordination in the brain

2012 ◽  
Vol 367 (1591) ◽  
pp. 906-918 ◽  
Author(s):  
J. A. Scott Kelso
Keyword(s):  
Large Scale ◽  
Neural Circuits ◽  
Neural Circuitry ◽  
Skill Learning ◽  
Coordination Dynamics ◽  
Dynamic Coordination ◽  
Action And Perception ◽  
Intentional Change ◽  
Complex Goal ◽  
The Brain

Multistable coordination dynamics exists at many levels, from multifunctional neural circuits in vertebrates and invertebrates to large-scale neural circuitry in humans. Moreover, multistability spans (at least) the domains of action and perception, and has been found to place constraints upon, even dictating the nature of, intentional change and the skill-learning process. This paper reviews some of the key evidence for multistability in the aforementioned areas, and illustrates how it has been measured, modelled and theoretically understood. It then suggests how multistability—when combined with essential aspects of coordination dynamics such as instability, transitions and (especially) metastability—provides a platform for understanding coupling and the creative dynamics of complex goal-directed systems, including the brain and the brain–behaviour relation.

scholarly journals Genetic transformation of structural and functional circuitry rewires the Drosophila brain

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Sonia Sen ◽  
Deshou Cao ◽  
Ramveer Choudhary ◽  
Silvia Biagini ◽  
Jing W Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Neural Circuits ◽  
Projection Neuron ◽  
Central Complex ◽  
Neuronal Progenitor ◽  
Drosophila Brain ◽  
Circuit Formation ◽  
Functional Circuitry ◽  
The Brain

Acquisition of distinct neuronal identities during development is critical for the assembly of diverse functional neural circuits in the brain. In both vertebrates and invertebrates, intrinsic determinants are thought to act in neural progenitors to specify their identity and the identity of their neuronal progeny. However, the extent to which individual factors can contribute to this is poorly understood. We investigate the role of orthodenticle in the specification of an identified neuroblast (neuronal progenitor) lineage in the Drosophila brain. Loss of orthodenticle from this neuroblast affects molecular properties, neuroanatomical features, and functional inputs of progeny neurons, such that an entire central complex lineage transforms into a functional olfactory projection neuron lineage. This ability to change functional macrocircuitry of the brain through changes in gene expression in a single neuroblast reveals a surprising capacity for novel circuit formation in the brain and provides a paradigm for large-scale evolutionary modification of circuitry.

scholarly journals The neural correlates of consciousness: an analysis of cognitive skill learning

1998 ◽  
Vol 353 (1377) ◽  
pp. 1889-1901 ◽  
Author(s):  
◽  
M. E. Raichle
Keyword(s):  
Neural Correlates ◽  
Neural Circuitry ◽  
Cognitive Skill ◽  
Functional Brain Imaging ◽  
Skill Learning ◽  
Neural Correlates Of Consciousness ◽  
Baseline Activity ◽  
Before And After ◽  
Imaging Strategy ◽  
The Brain

This paper presents a functional brain–imaging strategy designed to isolate neural correlates of consciousness in humans. This strategy is based on skill learning. In the example presented (rapidly generating verbs for visually presented nouns), a cognitive skill is examined before and after practice. As shown, there are marked qualitative differences in the neural circuitry supporting performance of this task in the naive and practised state that include, importantly, both increases and decreases from the baseline activity of the brain.

Surgical Performance From a Psychological Perspective

2018 ◽  
Author(s):  
Aidan Moran ◽  
Nick Sevdalis ◽  
Lauren Wallace
Keyword(s):  
Cognitive Training ◽  
Motor Imagery ◽  
Neural Circuits ◽  
Skill Learning ◽  
Fine Motor ◽  
Surgical Performance ◽  
Training Techniques ◽  
Skilled Performance ◽  
And Performance ◽  
The Brain

At first glance, there are certain similarities between performance in surgery and that in competitive sports. Clearly, both require exceptional gross and fine motor ability and effective concentration skills, and both are routinely performed in dynamic environments, often under time constraints. On closer inspection, however, crucial differences emerge between these skilled domains. For example, surgery does not involve directly antagonistic opponents competing for victory. Nevertheless, analogies between surgery and sport have contributed to an upsurge of research interest in the psychological processes that underlie expertise in surgical performance. Of these processes, perhaps the most frequently investigated in recent years is that of motor imagery (MI) or the cognitive simulation skill that enables us to rehearse actions in our imagination without engaging in the physical movements involved. Research on motor imagery training (MIT; also called motor imagery practice, MIP) has important theoretical and practical implications. Specifically, at a theoretical level, hundreds of experimental studies in psychology have demonstrated the efficacy of MIT/MIP in improving skill learning and skilled performance in a variety of fields such as sport and music. The most widely accepted explanation of these effects comes from “simulation theory,” which postulates that executed and imagined actions share some common neural circuits and cognitive mechanisms. Put simply, imagining a skill activates some of the brain areas and neural circuits that are involved in its actual execution. Accordingly, systematic engagement in MI appears to “prime” the brain for optimal skilled performance. At the practical level, as surgical instruction has moved largely from an apprenticeship model (the so-called see one, do one, teach one approach) to one based on simulation technology and practice (e.g., the use of virtual reality equipment), there has been a corresponding growth of interest in the potential of cognitive training techniques (e.g., MIT/MIP) to improve and augment surgical skills and performance. Although these cognitive training techniques suffer both from certain conceptual confusion (e.g., with regard to the clarity of key terms) and inadequate empirical validation, they offer considerable promise in the quest for a cost-effective supplementary training tool in surgical education. Against this background, it is important for researchers and practitioners alike to explore the cognitive psychological factors (such as motor imagery) that underlie surgical skill learning and performance.

scholarly journals Cortical Column and Whole Brain Imaging of Neural Circuits with Molecular Contrast and Nanoscale Resolution

2018 ◽  
Author(s):  
Ruixuan Gao ◽  
Shoh M. Asano ◽  
Srigokul Upadhyayula ◽  
Pisarev Igor ◽  
Daniel E. Milkie ◽  
...  
Keyword(s):  
Neural Development ◽  
High Speed ◽  
Large Scale ◽  
Neural Circuits ◽  
Light Sheet ◽  
Synaptic Proteins ◽  
Light Sheet Microscopy ◽  
Mouse Cortex ◽  
Molecular Contrast ◽  
The Brain

AbstractOptical and electron microscopy have made tremendous inroads in understanding the complexity of the brain, but the former offers insufficient resolution to reveal subcellular details and the latter lacks the throughput and molecular contrast to visualize specific molecular constituents over mm-scale or larger dimensions. We combined expansion microscopy and lattice light sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entire Drosophila brain, including synaptic proteins at dendritic spines, myelination along axons, and presynaptic densities at dopaminergic neurons in every fly neuropil domain. The technology should enable statistically rich, large scale studies of neural development, sexual dimorphism, degree of stereotypy, and structural correlations to behavior or neural activity, all with molecular contrast.One Sentence SummaryCombined expansion and lattice light sheet microscopy enables high speed, nanoscale molecular imaging of neural circuits over large volumes.

scholarly journals Genetic dissection of neural circuits underlying sexually dimorphic social behaviours

2016 ◽  
Vol 371 (1688) ◽  
pp. 20150109 ◽  
Author(s):  
Daniel W. Bayless ◽  
Nirao M. Shah
Keyword(s):  
Neural Circuits ◽  
Laboratory Mouse ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Sexually Dimorphic ◽  
Genetic Dissection ◽  
Technical Innovations ◽  
Males And Females ◽  
The Brain ◽  
Social Behaviours

The unique hormonal, genetic and epigenetic environments of males and females during development and adulthood shape the neural circuitry of the brain. These differences in neural circuitry result in sex-typical displays of social behaviours such as mating and aggression. Like other neural circuits, those underlying sex-typical social behaviours weave through complex brain regions that control a variety of diverse behaviours. For this reason, the functional dissection of neural circuits underlying sex-typical social behaviours has proved to be difficult. However, molecularly discrete neuronal subpopulations can be identified in the heterogeneous brain regions that control sex-typical social behaviours. In addition, the actions of oestrogens and androgens produce sex differences in gene expression within these brain regions, thereby highlighting the neuronal subpopulations most likely to control sexually dimorphic social behaviours. These conditions permit the implementation of innovative genetic approaches that, in mammals, are most highly advanced in the laboratory mouse. Such approaches have greatly advanced our understanding of the functional significance of sexually dimorphic neural circuits in the brain. In this review, we discuss the neural circuitry of sex-typical social behaviours in mice while highlighting the genetic technical innovations that have advanced the field.

scholarly journals Grand Unified Theories of the brain need better understanding of behavior: the two-tiered emergence of function.

2018 ◽  
Author(s):  
VIktor Jirsa ◽  
Anthony Randal McIntosh ◽  
Raoul Huys
Keyword(s):  
Brain Function ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Epileptic Seizures ◽  
Theoretical Work ◽  
Coordination Dynamics ◽  
Brain Functioning ◽  
Brain And Behavior ◽  
And Behavior ◽  
The Brain

Over the last few decades, neuroscience, and various associated disciples, has expanded enormously in terms of output, tools, methods, concepts and large-scale projects. In spite of these developments, the principles underlying brain function and behavior are of yet only partially understood. We claim that brain functioning requires the elucidation of the rules associated with all possible task realizations, rather than targeting the activity underlying a specific realization. A first step into that direction was taken by approaches focusing on dynamical structures underlying task performances, as exemplified by Coordination Dynamics. Theoretically, this approach is founded on Haken’s Synergetics, which provides a mechanism through which the degrees of freedom associated with high-dimensional systems may be effectively reduced to one or a few functional ones. This dimensionality reduction, however, is only valid in the vicinity of phase transitions, which severely limits the framework’s domain of explanation. This limitation does not hold for the recently advanced framework of Structured Flows on Manifolds (SFM), which is similar in spirit yet complementary to Synergetics. Following novel theoretical work on the onset, propagation, and offset of epileptic seizures, we expand the SFM framework, and propose that the resulting two-tiered fast-slow dynamics may be a generic mathematical organization underlying and linking brain and behavior.

Implantable neural interfaces

2018 ◽  
Author(s):  
Stefano Vassanelli
Keyword(s):  
Brain Function ◽  
Large Scale ◽  
Ionic Channels ◽  
Patch Clamp Technique ◽  
Advantages And Disadvantages ◽  
Optogenetic Stimulation ◽  
Physical Interfaces ◽  
The Brain

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.

What Has Direct Cortical and Subcortical Electrostimulation Taught Us about Neurolinguistics?

2019 ◽  
pp. 185-211
Author(s):  
Hugues Duffau
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Great Accuracy ◽  
Subcortical White Matter ◽  
Cerebral Lesions ◽  
Physiological Basis ◽  
Postoperative Mri ◽  
The Brain

Investigating the neural and physiological basis of language is one of the most important challenges in neurosciences. Direct electrical stimulation (DES), usually performed in awake patients during surgery for cerebral lesions, is a reliable tool for detecting both cortical and subcortical (white matter and deep grey nuclei) regions crucial for cognitive functions, especially language. DES transiently interacts locally with a small cortical or axonal site, but also nonlocally, as the focal perturbation will disrupt the entire subnetwork sustaining a given function. Thus, in contrast to functional neuroimaging, DES represents a unique opportunity to identify with great accuracy and reproducibility, in vivo in humans, the structures that are actually indispensable to the function, by inducing a transient virtual lesion based on the inhibition of a subcircuit lasting a few seconds. Currently, this is the sole technique that is able to directly investigate the functional role of white matter tracts in humans. Thus, combining transient disturbances elicited by DES with the anatomical data provided by pre- and postoperative MRI enables to achieve reliable anatomo-functional correlations, supporting a network organization of the brain, and leading to the reappraisal of models of language representation. Finally, combining serial peri-operative functional neuroimaging and online intraoperative DES allows the study of mechanisms underlying neuroplasticity. This chapter critically reviews the basic principles of DES, its advantages and limitations, and what DES can reveal about the neural foundations of language, that is, the large-scale distribution of language areas in the brain, their connectivity, and their ability to reorganize.

scholarly journals Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

2021 ◽  
Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Mri ◽  
Similarity Measures ◽  
Principal Component ◽  
Brain Anatomy ◽  
Morphological Operations ◽  
Mr Images ◽  
Tilt Correction ◽  
Brain Mr Images ◽  
The Brain

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

A new method to predict anomaly in brain network based on graph deep learning

2020 ◽  
Vol 31 (6) ◽  
pp. 681-689
Author(s):  
Jalal Mirakhorli ◽  
Hamidreza Amindavar ◽  
Mojgan Mirakhorli
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Network ◽  
High Order ◽  
Brain Diseases ◽  
Simultaneous Occurrence ◽  
Generative Adversarial Network ◽  
The Brain ◽  
Brain Connections

AbstractFunctional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent years by mapping the topology of the brain connections, named connectopic mapping. Based on the fact that healthy and unhealthy brain regions and functions differ slightly, studying the complex topology of the functional and structural networks in the human brain is too complicated considering the growth of evaluation measures. One of the applications of irregular graph deep learning is to analyze the human cognitive functions related to the gene expression and related distributed spatial patterns. Since a variety of brain solutions can be dynamically held in the neuronal networks of the brain with different activity patterns and functional connectivity, both node-centric and graph-centric tasks are involved in this application. In this study, we used an individual generative model and high order graph analysis for the region of interest recognition areas of the brain with abnormal connection during performing certain tasks and resting-state or decompose irregular observations. Accordingly, a high order framework of Variational Graph Autoencoder with a Gaussian distributer was proposed in the paper to analyze the functional data in brain imaging studies in which Generative Adversarial Network is employed for optimizing the latent space in the process of learning strong non-rigid graphs among large scale data. Furthermore, the possible modes of correlations were distinguished in abnormal brain connections. Our goal was to find the degree of correlation between the affected regions and their simultaneous occurrence over time. We can take advantage of this to diagnose brain diseases or show the ability of the nervous system to modify brain topology at all angles and brain plasticity according to input stimuli. In this study, we particularly focused on Alzheimer’s disease.

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