The role of neuroimaging in understanding the impact of neuroplasticity after CNS damage

2020 ◽  
pp. 185-198
Author(s):  
Nick S. Ward
Keyword(s):  
Functional Neuroimaging ◽  
Recovery Of Function ◽  
Brain Activity ◽  
Complete Recovery ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Brain Organization ◽  
Brain Reorganization ◽  
Invasive Techniques ◽  
The Impact

After stroke, there is little restitution of neural tissue, but reorganization of surviving neural networks appears to be important for recovery of function. Non-invasive techniques such as functional magnetic resonance imaging and magnetoencephalography allow some aspects of this brain reorganization to be studied in humans. For example, early after stroke there appears to be an upregulation in task-related activity which diminishes with time, but more particularly with recovery. Those with the most complete recovery tend to have the most ‘normal’ activation patter, and those with less complete recovery tend to rely on additional brain regions. Disruption of activity in these additional regions can impair performance in stroke patients suggesting that these new patterns of brain activity can support what recovered function there is. In other words, this reorganization is functionally relevant. Advances in functional neuroimaging now allow the study of alterations in connections between brain regions. Understanding how brain organization is related to anatomical damage, as well as impairment and recovery that can take place over weeks and months following stroke opens the way for functional brain imaging to become a clinically useful tool in rehabilitation, particularly in our ability to predict outcomes and response to novel therapies. Understanding the dynamic process of systems level reorganization will allow greater understanding of the mechanisms of recovery and potentially improve our ability to deliver effective restorative therapy.

The role of neuroimaging in understanding the impact of neuroplasticity after CNS damage

2015 ◽  
pp. 161-173
Author(s):  
Nick Ward
Keyword(s):  
Functional Neuroimaging ◽  
Recovery Of Function ◽  
Complete Recovery ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Brain Organization ◽  
Brain Reorganization ◽  
Invasive Techniques ◽  
The Impact

After stroke, there is little restitution of neural tissue, but reorganization of surviving neural networks appears to be important for recovery of function. Non-invasive techniques such as functional magnetic resonance imaging and magnetoencephalography allow some aspects of this brain reorganization to be studied. For example, early after stroke there appears to be an upregulation in task-related activity, which diminishes with time and recovery. Those with the most complete recovery tend to have the most ‘normal’ activation pattern, and those with less complete recovery tend to rely on additional brain regions. This reorganization is functionally relevant. Advances in functional neuroimaging allow the study of alterations in connections between brain regions. Understanding how brain organization is related to anatomical damage, as well as impairment and recovery that can take place over weeks and months following stroke opens the way for functional brain imaging to become a clinically useful tool in rehabilitation.

scholarly journals Functional neuroimaging of psychiatric disorders: exploring hidden behaviour

2004 ◽  
Vol 34 (4) ◽  
pp. 577-581 ◽  
Author(s):  
P. C. FLETCHER
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Cognitive Strategies ◽  
Healthy Person ◽  
Brain Regions ◽  
Task Demands ◽  
Unrealistic Expectation ◽  
Positron Emission ◽  
The Impact ◽  
Function Mapping

From the outset, people have had high expectations of functional neuroimaging. Many will have been disappointed. After roughly a decade of widespread use, even an enthusiastic advocate must be diffident about the impact of the two most frequently used techniques – positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) – upon clinical psychiatry. Perhaps this disappointment arises from an unrealistic expectation of what these techniques are able to tell us about the workings of the normal and the disordered brain. Anyone who hoped for intricate and unambiguous region-to-function mapping was always going to be disappointed. This expectation presupposes, among other things, a thorough understanding of the cognitive functions that are to be mapped onto the brain regions. This understanding, however, while developing, is still rudimentary. Mapping disorder along comparable lines is even more complex since it demands two levels of understanding. The first is of the healthy region-to-function mapping, the second of the disordered region-to-function mapping, which immediately demands a consideration of the nature of the function in the disordered state. After all, someone with schizophrenia, when confronted with a psychological task, might tackle it in a very different way, in terms of the cognitive strategies used, from a healthy person confronted with the same task. The observation that brain activity differs across the two individuals would only be interpretable insofar as one thoroughly understood the processes that each individual invoked in response to the task demands.

scholarly journals The Impact of Sports-Related Concussions on the Language System

2018 ◽  
Vol 1 (1) ◽  
pp. 36-46
Author(s):  
Patrick S Ledwidge
Keyword(s):  
Brain Activity ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Long Term Effects ◽  
Brain Potentials ◽  
Language System ◽  
Induced Changes ◽  
The Impact ◽  
Language Network

Sports-related Concussions (SRC) and their potential long-term effects are a growing concern among athletes and their families. Research utilizing functional brain imaging/recording techniques (e.g., fMRI, ERP) seeks to explain how neurocognitive brain activity changes in the days and years following SRC. Although language deficits are documented following non-sports related concussion there remains a striking lack of research on how SRCs may influence the language system and their supporting neural mechanisms. Neuroimaging findings, however, demonstrate that SRCs alter structural and functional pathways within the frontotemporal language network. Brain regions included in this network generate language-related event-related brain potentials (ERPs), including the N400 and P600. ERPs have been used to demonstrate long-term neurocognitive alterations associated with concussion and may also provide objective and robust markers of SRC-induced changes to the language system.

scholarly journals Methodological Considerations in Conducting an Olfactory fMRI Study

2013 ◽  
Vol 27 (3) ◽  
pp. 267-276 ◽  
Author(s):  
Faezeh Vedaei ◽  
Mohammad Fakhri ◽  
Mohammad Hossein Harirchian ◽  
Kavous Firouznia ◽  
Yones Lotfi ◽  
...  
Keyword(s):  
Functional Neuroimaging ◽  
Neurological Diseases ◽  
Brain Regions ◽  
Brain Network ◽  
Functional Brain Imaging ◽  
Behavioral Studies ◽  
Fmri Study ◽  
Methodological Considerations ◽  
Technical Principles ◽  
Review Current

The sense of smell is a complex chemosensory processing in human and animals that allows them to connect with the environment as one of their chief sensory systems. In the field of functional brain imaging, many studies have focused on locating brain regions that are involved during olfactory processing. Despite wealth of literature about brain network in different olfactory tasks, there is a paucity of data regarding task design. Moreover, considering importance of olfactory tasks for patients with variety of neurological diseases, special contemplations should be addressed for patients. In this article, we review current olfaction tasks for behavioral studies and functional neuroimaging assessments, as well as technical principles regarding utilization of these tasks in functional magnetic resonance imaging studies.

scholarly journals Reconstructing lost BOLD signal in individual participants using deep machine learning

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuxiang Yan ◽  
Louisa Dahmani ◽  
Jianxun Ren ◽  
Lunhao Shen ◽  
Xiaolong Peng ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Functional Neuroimaging ◽  
Brain Regions ◽  
Specific Information ◽  
Bold Signal ◽  
Signal Loss ◽  
Brain Organization ◽  
Good Correspondence ◽  
Functional Relationships

Abstract Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles governing BOLD activity in one dataset and reconstruct artificially compromised regions in an independent dataset, frame by frame. Intriguingly, BOLD time series extracted from reconstructed frames are correlated with the original time series, even though the frames do not independently carry any temporal information. Moreover, reconstructed functional connectivity maps exhibit good correspondence with the original connectivity maps, indicating that the model recovers functional relationships among brain regions. We replicated this result in two healthy datasets and in patients whose scans suffered signal loss due to intracortical electrodes. Critically, the reconstructions capture individual-specific information. Deep machine learning thus presents a unique opportunity to reconstruct compromised BOLD signal while capturing features of an individual’s own functional brain organization.

scholarly journals Organization of Propagated Intrinsic Brain Activity in Individual Humans

2019 ◽  
Vol 30 (3) ◽  
pp. 1716-1734 ◽  
Author(s):  
Ryan V Raut ◽  
Anish Mitra ◽  
Scott Marek ◽  
Mario Ortega ◽  
Abraham Z Snyder ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Organization ◽  
Individual Level ◽  
Slow Activity ◽  
Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

scholarly journals A neurocognitive investigation of the impact of socializing with a robot on empathy for pain

2019 ◽  
Vol 374 (1771) ◽  
pp. 20180034 ◽  
Author(s):  
Emily S. Cross ◽  
Katie A. Riddoch ◽  
Jaydan Pratts ◽  
Simon Titone ◽  
Bishakha Chaudhury ◽  
...  
Keyword(s):  
Social Relationships ◽  
Functional Neuroimaging ◽  
Region Of Interest ◽  
Brain Regions ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Functional Region ◽  
Repetition Suppression ◽  
Empathy For Pain ◽  
The Impact

To what extent can humans form social relationships with robots? In the present study, we combined functional neuroimaging with a robot socializing intervention to probe the flexibility of empathy, a core component of social relationships, towards robots. Twenty-six individuals underwent identical fMRI sessions before and after being issued a social robot to take home and interact with over the course of a week. While undergoing fMRI, participants observed videos of a human actor or a robot experiencing pain or pleasure in response to electrical stimulation. Repetition suppression of activity in the pain network, a collection of brain regions associated with empathy and emotional responding, was measured to test whether socializing with a social robot leads to greater overlap in neural mechanisms when observing human and robotic agents experiencing pain or pleasure. In contrast to our hypothesis, functional region-of-interest analyses revealed no change in neural overlap for agents after the socializing intervention. Similarly, no increase in activation when observing a robot experiencing pain emerged post-socializing. Whole-brain analysis showed that, before the socializing intervention, superior parietal and early visual regions are sensitive to novel agents, while after socializing, medial temporal regions show agent sensitivity. A region of the inferior parietal lobule was sensitive to novel emotions, but only during the pre-socializing scan session. Together, these findings suggest that a short socialization intervention with a social robot does not lead to discernible differences in empathy towards the robot, as measured by behavioural or brain responses. We discuss the extent to which long-term socialization with robots might shape social cognitive processes and ultimately our relationships with these machines. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

scholarly journals A review of the new minimally invasive brain stimulation techniques in psychiatry

2001 ◽  
Vol 23 (2) ◽  
pp. 100-109 ◽  
Author(s):  
Jeong-Ho Chae ◽  
Xingbao Li ◽  
Ziad Nahas ◽  
F. Andrew Kozel ◽  
Mark S. George
Keyword(s):  
Minimally Invasive ◽  
Brain Stimulation ◽  
Functional Neuroimaging ◽  
Neuropsychiatric Disorders ◽  
Brain Regions ◽  
Therapeutic Tools ◽  
Invasive Techniques ◽  
The Brain ◽  
Neuroimaging Techniques ◽  
Deep Brain

New knowledge about the specific brain regions involved in neuropsychiatric disorders is rapidly evolving due to recent advances in functional neuroimaging techniques. The ability to stimulate the brain in awake alert adults without neurosurgery is a real advance that neuroscientists have long dreamed for. Several novel and minimally invasive techniques to stimulate the brain have recently developed. Among these newer somatic interventions, transcranial magnetic stimulation (TMS), vagus nerve stimulation (VNS) and deep brain stimulation (DBS) show promise as therapeutic tools in the treatment of neuropsychiatric disorders. This article reviews the history, methodology, and the future of these minimally invasive brain stimulation (MIBS) techniques and their emerging research and therapeutic applications in psychiatry

Auditory verbal hallucinations: neuroimaging and treatment

2016 ◽  
Vol 47 (2) ◽  
pp. 199-208 ◽  
Author(s):  
M. M. Bohlken ◽  
K. Hugdahl ◽  
I. E. C. Sommer
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Neural Correlates ◽  
Brain Regions ◽  
Behavioural Therapy ◽  
Special Focus ◽  
Comprehensive Overview ◽  
Auditory Verbal Hallucinations ◽  
Research Areas ◽  
Control Functions

Auditory verbal hallucinations (AVH) are a frequently occurring phenomenon in the general population and are considered a psychotic symptom when presented in the context of a psychiatric disorder. Neuroimaging literature has shown that AVH are subserved by a variety of alterations in brain structure and function, which primarily concentrate around brain regions associated with the processing of auditory verbal stimuli and with executive control functions. However, the direction of association between AVH and brain function remains equivocal in certain research areas and needs to be carefully reviewed and interpreted. When AVH have significant impact on daily functioning, several efficacious treatments can be attempted such as antipsychotic medication, brain stimulation and cognitive–behavioural therapy. Interestingly, the neural correlates of these treatments largely overlap with brain regions involved in AVH. This suggests that the efficacy of treatment corresponds to a normalization of AVH-related brain activity. In this selected review, we give a compact yet comprehensive overview of the structural and functional neuroimaging literature on AVH, with a special focus on the neural correlates of efficacious treatment.

scholarly journals Breathlessness in COPD: linking symptom clusters with brain activity

2021 ◽  
pp. 2004099
Author(s):  
Sarah L. Finnegan ◽  
Olivia K. Harrison ◽  
Catherine J. Harmer ◽  
Mari Herigstad ◽  
Najib M. Rahman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Symptom Burden ◽  
Functional Brain Imaging ◽  
Self Report ◽  
Machine Learning Techniques ◽  
Chronic Obstructive ◽  
Unsupervised Machine Learning ◽  
Learning Techniques

RationaleCurrent models of breathlessness often fail to explain disparities between patients' experiences of breathlessness and objective measures of lung function. While a mechanistic understanding of this discordance has thus far remained elusive, factors such as mood, attention and expectation have all been implicated as important modulators of breathlessness. Therefore, we have developed a model to better understand the relationships between these factors using unsupervised machine learning techniques. Subsequently we examined how expectation-related brain activity differed between these symptom-defined clusters of participants.MethodsA cohort of 91 participants with mild-to-moderate chronic obstructive pulmonary disease (COPD) underwent functional brain imaging, self-report questionnaires and clinical measures of respiratory function. Unsupervised machine learning techniques of exploratory factor analysis and hierarchical cluster modelling were used to model brain-behaviour-breathlessness links.ResultsWe successfully stratified participants across four key factors corresponding to mood, symptom burden and two capability measures. Two key groups resulted from this stratification, corresponding to high and low symptom burden. Compared to the high symptom load group, the low symptom burden group demonstrated significantly greater brain activity within the anterior insula, a key region thought to be involved in monitoring internal bodily sensations (interoception).ConclusionsThis is the largest functional neuroimaging study of COPD to date and is the first to provide a clear model linking brain, behaviour and breathlessness expectation. Furthermore, it was possible to stratify participants into groups, which then revealed differences in brain activity patterns. Together, these findings highlight the value of multi-modal models of breathlessness in identifying behavioural phenotypes, and for advancing understanding of differences in breathlessness burden.

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