scholarly journals Simultaneous Normalization and Compensatory Changes in Right Hemisphere Connectivity during Aphasia Therapy

2021 ◽  
Vol 11 (10) ◽  
pp. 1330
Author(s):  
Tammar Truzman ◽  
Elizabeth Rochon ◽  
Jed Meltzer ◽  
Carol Leonard ◽  
Tali Bitan
Keyword(s):  
Phonological Processing ◽  
Right Hemisphere ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Language Therapy ◽  
Aphasia Therapy ◽  
Neural Processes ◽  
Treatment Changes ◽  
Components Analysis ◽  
Left Hemisphere Stroke

Changes in brain connectivity during language therapy were examined among participants with aphasia (PWA), aiming to shed light on neural reorganization in the language network. Four PWA with anomia following left hemisphere stroke and eight healthy controls (HC) participated in the study. Two fMRI scans were administered to all participants with a 3.5-month interval. The fMRI scans included phonological and semantic tasks, each consisting of linguistic and perceptual matching conditions. Between the two fMRI scans, PWA underwent Phonological Components Analysis treatment. Changes in effective connectivity during the treatment were examined within right hemisphere (RH) architecture. The results illustrate that following the treatment, the averaged connectivity of PWA across all perceptual and linguistic conditions in both tasks increased resemblance to HC, reflecting the normalization of neural processes associated with silent object name retrieval. In contrast, connections that were specifically enhanced by the phonological condition in PWA decreased in their resemblance to HC, reflecting emerging compensatory reorganization in RH connectivity to support phonological processing. These findings suggest that both normalization and compensation play a role in neural language reorganization at the chronic stage, occurring simultaneously in the same brain.

scholarly journals Acquired dysgraphia in adults following right or left-hemisphere stroke

2014 ◽  
Vol 8 (3) ◽  
pp. 236-242 ◽  
Author(s):  
Jaqueline de Carvalho Rodrigues ◽  
Denise Ren da Fontoura ◽  
Jerusa Fumagalli de Salles
Keyword(s):  
Left Hemisphere ◽  
Phonological Processing ◽  
Word Processing ◽  
Right Hemisphere ◽  
Case Series ◽  
Lexical Route ◽  
Right Hemisphere Damage ◽  
Dual Route Model ◽  
Left Hemisphere Stroke ◽  
Graphemic Buffer

OBJECTIVE: This study aimed to assess the strengths and difficulties in word and pseudoword writing in adults with left- and right-hemisphere strokes, and discuss the profiles of acquired dysgraphia in these individuals.METHODS: The profiles of six adults with acquired dysgraphia in left- or right-hemisphere strokes were investigated by comparing their performance on word and pseudoword writing tasks against that of neurologically healthy adults. A case series analysis was performed on the patients whose impairments on the task were indicative of acquired dysgraphia.RESULTS: Two patients were diagnosed with lexical dysgraphia (one with left hemisphere damage, and the other with right hemisphere damage), one with phonological dysgraphia, another patient with peripheral dysgraphia, one patient with mixed dysgraphia and the last with dysgraphia due to damage to the graphemic buffer. The latter patients all had left-hemisphere damage (LHD). The patterns of impairment observed in each patient were discussed based on the dual-route model of writing.CONCLUSION: The fact that most patients had LHD rather than right-hemisphere damage (RHD) highlights the importance of the former structure for word processing. However, the fact that lexical dysgraphia was also diagnosed in a patient with RHD suggests that these individuals may develop writing impairments due to damage to the lexical route, leading to heavier reliance on phonological processing. Our results are of significant importance to the planning of writing interventions in neuropsychology.

scholarly journals Classification of Schizophrenia by Combination of Brain Effective and Functional Connectivity

2021 ◽  
Vol 15 ◽  
Author(s):  
Zongya Zhao ◽  
Jun Li ◽  
Yanxiang Niu ◽  
Chang Wang ◽  
Junqiang Zhao ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Right Hemisphere ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Event Related Potentials ◽  
Single Type ◽  
Support Vector ◽  
Phase Lag ◽  
Related Potentials

At present, lots of studies have tried to apply machine learning to different electroencephalography (EEG) measures for diagnosing schizophrenia (SZ) patients. However, most EEG measures previously used are either a univariate measure or a single type of brain connectivity, which may not fully capture the abnormal brain changes of SZ patients. In this paper, event-related potentials were collected from 45 SZ patients and 30 healthy controls (HCs) during a learning task, and then a combination of partial directed coherence (PDC) effective and phase lag index (PLI) functional connectivity were used as features to train a support vector machine classifier with leave-one-out cross-validation for classification of SZ from HCs. Our results indicated that an excellent classification performance (accuracy = 95.16%, specificity = 94.44%, and sensitivity = 96.15%) was obtained when the combination of functional and effective connectivity features was used, and the corresponding optimal feature number was 15, which included 12 PDC and three PLI connectivity features. The selected effective connectivity features were mainly located between the frontal/temporal/central and visual/parietal lobes, and the selected functional connectivity features were mainly located between the frontal/temporal and visual cortexes of the right hemisphere. In addition, most of the selected effective connectivity abnormally enhanced in SZ patients compared with HCs, whereas all the selected functional connectivity features decreased in SZ patients. The above results showed that our proposed method has great potential to become a tool for the auxiliary diagnosis of SZ.

Direct Causal Networks for the Study of Transcranial Magnetic Stimulation Effects on Focal Epileptiform Discharges

2015 ◽  
Vol 25 (05) ◽  
pp. 1550006 ◽  
Author(s):  
Dimitris Kugiumtzis ◽  
Vasilios K. Kimiskidis
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Network Structure ◽  
Magnetic Stimulation ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Epileptic Focus ◽  
Sham Stimulation ◽  
Focal Seizures ◽  
Epileptiform Discharges ◽  
The Brain

Background: Transcranial magnetic stimulation (TMS) can have inhibitory effects on epileptiform discharges (EDs) of patients with focal seizures. However, the brain connectivity before, during and after EDs, with or without the administration of TMS, has not been extensively explored. Objective: To investigate the brain network of effective connectivity during ED with and without TMS in patients with focal seizures. Methods: For the effective connectivity a direct causality measure is applied termed partial mutual information from mixed embedding (PMIME). TMS-EEG data from two patients with focal seizures were analyzed. Each EEG record contained a number of EDs in the majority of which TMS was administered over the epileptic focus. As a control condition, sham stimulation over the epileptogenic zone or real TMS at a distance from the epileptic focus was also performed. The change in brain connectivity structure was investigated from the causal networks formed at each sliding window. Conclusion: The PMIME could detect distinct changes in the network structure before, within, and after ED. The administration of real TMS over the epileptic focus, in contrast to sham stimulation, terminated the ED prematurely in a node-specific manner and regained the network structure as if it would have terminated spontaneously.

Applying Basic Neuroscience to Aphasia Therapy

1995 ◽  
Vol 4 (4) ◽  
pp. 88-93 ◽  
Author(s):  
Kristen A. Keefe
Keyword(s):  
Learning And Memory ◽  
Neural Plasticity ◽  
Behavioral Interventions ◽  
Cortical Reorganization ◽  
Mammalian Brain ◽  
Cortical Injury ◽  
Aphasia Therapy ◽  
Neural Processes ◽  
Adult Mammalian Brain ◽  
Environmental Demands

Advances in basic neuroscience have increased our knowledge about the neural processes underlying learning and memory and the cortical reorganization that occurs in response to environmental demands and cortical injury. This article provides a selective review of published studies conducted in animals that examine functional and structural substrates of neural plasticity in the adult mammalian brain, and discusses the implications of this knowledge for aphasia therapy. The processes and constraints identified in the studies reviewed can be used to refine and justify current aphasia therapies, as well as to design additional behavioral interventions.

scholarly journals Salience Network Disruption in US Army Soldiers with PTSD

2018 ◽  
Author(s):  
Chadi Abdallah ◽  
Christopher Averill ◽  
Amy Ramage ◽  
Lynnette Averill ◽  
Selin Goktas ◽  
...  
Keyword(s):  
Resting State ◽  
Right Hemisphere ◽  
Brain Connectivity ◽  
Brain Network ◽  
Data Driven ◽  
Salience Network ◽  
Symptom Provocation ◽  
Us Army ◽  
Data Driven Approach ◽  
Army Soldiers

BACKGROUND: Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph- based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty US Army soldiers with PTSD compared to controls. METHODS: 102 participants with (n=50) or without PTSD (n=52) completed functional magnetic resonance imaging (fMRI) at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. RESULTS: In contrast to during resting-state, where there were no group differences, we found a significantly higher GBCr, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal- ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting-state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. CONCLUSION: In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

scholarly journals Determination of Dynamic Brain Connectivity via Spectral Analysis

2021 ◽  
Vol 15 ◽  
Author(s):  
Peter A. Robinson ◽  
James A. Henderson ◽  
Natasha C. Gabay ◽  
Kevin M. Aquino ◽  
Tara Babaie-Janvier ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Brain Structure ◽  
Brain Connectivity ◽  
Spatial Scales ◽  
Effective Connectivity ◽  
Physical Nature ◽  
Building Blocks ◽  
Brain Dynamics ◽  
Compact Representation ◽  
The Brain

Spectral analysis based on neural field theory is used to analyze dynamic connectivity via methods based on the physical eigenmodes that are the building blocks of brain dynamics. These approaches integrate over space instead of averaging over time and thereby greatly reduce or remove the temporal averaging effects, windowing artifacts, and noise at fine spatial scales that have bedeviled the analysis of dynamical functional connectivity (FC). The dependences of FC on dynamics at various timescales, and on windowing, are clarified and the results are demonstrated on simple test cases, demonstrating how modes provide directly interpretable insights that can be related to brain structure and function. It is shown that FC is dynamic even when the brain structure and effective connectivity are fixed, and that the observed patterns of FC are dominated by relatively few eigenmodes. Common artifacts introduced by statistical analyses that do not incorporate the physical nature of the brain are discussed and it is shown that these are avoided by spectral analysis using eigenmodes. Unlike most published artificially discretized “resting state networks” and other statistically-derived patterns, eigenmodes overlap, with every mode extending across the whole brain and every region participating in every mode—just like the vibrations that give rise to notes of a musical instrument. Despite this, modes are independent and do not interact in the linear limit. It is argued that for many purposes the intrinsic limitations of covariance-based FC instead favor the alternative of tracking eigenmode coefficients vs. time, which provide a compact representation that is directly related to biophysical brain dynamics.

Stroke

2008 ◽  
Author(s):  
Hochang Ben Lee ◽  
John R. Lipsey
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Cognitive Deficits ◽  
Cognitive Rehabilitation ◽  
Right Hemisphere ◽  
Stroke Survivors ◽  
Language Therapy ◽  
Rehabilitation Outcomes ◽  
Psychiatric Complication

With an annual incidence of more than 600,000 cases, thromboembolic stroke is the third leading cause of death in the United States after heart disease and cancer (Kochanek et al., 2004). The number of stroke survivors has increased to 4.5 million adults nationally as the management of acute stroke continues to improve (AHA, 2002). Psychiatric syndromes are common complications of stroke and are associated with psychologic distress, increased impairment, poor rehabilitation outcomes, and excess morbidity. The purpose of this chapter is to describe clinically important poststroke psychiatric disorders and suggest appropriate treatment. Cognitive deficits are the most common psychiatric complication of stroke and affect nearly all stroke survivors. The type of cognitive disturbance depends on the location of the brain injury. Left hemisphere strokes frequently cause aphasia. Right hemisphere strokes cause substantial (but often underrecognized) cognitive impairments such as diminished insight, decreased attention, impaired spatial reasoning, and neglect syndromes. Furthermore, depending on the location of a stroke, other functions such as motivation, memory, judgment, and impulse control may also be affected. A large stroke or a series of small strokes affecting both hemispheres may lead to the global cognitive impairment of dementia. When a series of strokes is involved, the cognitive decline develops in a stepwise manner. This vascular dementia or multi-infarct dementia may be difficult to distinguish from Alzheimer’s disease. Autopsy studies of patients diagnosed with vascular dementia have often demonstrated the presence of Alzheimer’s disease pathology. As many as 25% of all dementia cases are attributable to a combined neuropathology of Alzheimer’s disease and multiple infarcts (Massoud et al., 1999). In addition to strategies such as speech and language therapy, physical and occupational therapy, and cognitive rehabilitation, pharmacologic treatment may improve cognitive deficits in some stroke patients. The parallels between vascular dementia and Alzheimer’s disease, as well as the evidence that reduced cholinergic function may play a role in both (Gottfries et al., 1994) have encouraged the use of acetylcholinesterase inhibitors (eg, donepezil) in vascular dementia. These drugs have shown modest benefits in such patients (Roman et al., 2005), and their use is described in Chapter 20.

Acquired disorders of language and their treatment

2020 ◽  
pp. 279-290
Author(s):  
Alex Leff ◽  
Jenny Crinion
Keyword(s):  
Drug Therapy ◽  
Brain Stimulation ◽  
Main Part ◽  
Evidence Base ◽  
Language Therapy ◽  
Stroke Patients ◽  
Speech And Language Therapy ◽  
Non Invasive ◽  
Aphasia Therapy

This chapter covers the classification of acquired aphasic syndromes. It illustrates some of the speech errors aphasic stroke patients make with videos of a patient describing a picture and attempting to repeat words. The main part of the chapter assesses the evidence base for speech and language therapy (SALT) and answers the following questions: Does SALT work? What is the correct dose and intensity? And is it ever too late for SALT intervention? We then discuss two main adjuvants to SALT: one old—drug therapy; one new—non-invasive brain stimulation. Finally, we examine the role for e-rehabilitation and augmentative aids before asking what the future might hold for aphasia therapy, and wondering if it might already be here.

scholarly journals Asymmetric high-order anatomical brain connectivity sculpts effective connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 871-890
Author(s):  
Arseny A. Sokolov ◽  
Peter Zeidman ◽  
Adeel Razi ◽  
Michael Erb ◽  
Philippe Ryvlin ◽  
...  
Keyword(s):  
White Matter ◽  
Dynamic Range ◽  
Diffusion Processes ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Structural Connectivity ◽  
Laplacian Matrix ◽  
Graph Laplacian ◽  
Brain Regions ◽  
High Order

Bridging the gap between symmetric, direct white matter brain connectivity and neural dynamics that are often asymmetric and polysynaptic may offer insights into brain architecture, but this remains an unresolved challenge in neuroscience. Here, we used the graph Laplacian matrix to simulate symmetric and asymmetric high-order diffusion processes akin to particles spreading through white matter pathways. The simulated indirect structural connectivity outperformed direct as well as absent anatomical information in sculpting effective connectivity, a measure of causal and directed brain dynamics. Crucially, an asymmetric diffusion process determined by the sensitivity of the network nodes to their afferents best predicted effective connectivity. The outcome is consistent with brain regions adapting to maintain their sensitivity to inputs within a dynamic range. Asymmetric network communication models offer a promising perspective for understanding the relationship between structural and functional brain connectomes, both in normalcy and neuropsychiatric conditions.

scholarly journals Dynamics of brain connectivity after stroke

2019 ◽  
Vol 30 (6) ◽  
pp. 605-623 ◽  
Author(s):  
Adela Desowska ◽  
Duncan L. Turner
Keyword(s):  
Brain Connectivity ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Connectivity Pattern ◽  
Compensatory Mechanisms ◽  
Neural Structure ◽  
Motor Network ◽  
The Central Nervous System ◽  
Dynamic Time ◽  
The Impact

Abstract Recovery from a stroke is a dynamic time-dependent process, in which the central nervous system reorganises to accommodate for the impact of the injury. The purpose of this paper is to review recent longitudinal studies of changes in brain connectivity after stroke. A systematic review of research papers reporting functional or effective connectivity at two or more time points in stroke patients was conducted. Stroke leads to an early reduction of connectivity in the motor network. With recovery time, the connectivity increases and can reach the same levels as in healthy participants. The increase in connectivity is correlated with functional motor gains. A new, more randomised pattern of connectivity may then emerge in the longer term. In some instances, a pattern of increased connectivity even higher than in healthy controls can be observed, and is related either to a specific time point or to a specific neural structure. Rehabilitation interventions can help improve connectivity between specific regions. Moreover, motor network connectivity undergoes reorganisation during recovery from a stroke and can be related to behavioural recovery. A detailed analysis of changes in connectivity pattern may enable a better understanding of adaptation to a stroke and how compensatory mechanisms in the brain may be supported by rehabilitation.

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