Induced sensorimotor cortex plasticity remediates chronic treatment-resistant visual neglect

O’Shea, Jacinta; Revol, Patrice; Cousijn, Helena; Near, Jamie; Petitet, Pierre; Jacquin-Courtois, Sophie; Johansen‐Berg, Heidi; Rode, Gilles; Rossetti, Yves

doi:10.7554/elife.26602

Cited by 55 publications

(102 citation statements)

References 74 publications

(81 reference statements)

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“…In healthy individuals, rightward PA increased BOLD response in the left inferior parietal cortex 30 . Our cortical thickness and diffusion results suggest an implication of left prefrontal cortex in prism-induced neglect compensation, consistent with the observation that effective PA in neglect is facilitated by TMS-based disinhibition of the left motor cortex 31 . Altogether, these findings fit well with the fronto-parietal organization of attention networks in the primate brain 32 .…”

Section: Discussionsupporting

confidence: 90%

Anatomical predictors of successful prism adaptation in chronic visual neglect

Lunven

Rode

Bourlon

et al. 2017

Preprint

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Visual neglect is a frequent and disabling consequence of right hemisphere damage. Previous evidence demonstrated a probable role of posterior callosal dysfunction in the chronic persistence of neglect signs. Prism adaptation is a non-invasive and convenient technique to rehabilitate chronic visual neglect, but it is not effective in all patients. Here we hypothesized that prism adaptation improves left neglect by facilitating compensation through the contribution of the left, undamaged hemisphere. To test this hypothesis, we assessed the relationship between prism adaptation effects, cortical thickness and white matter integrity in a group of 14 patients with unilateral right-hemisphere strokes and chronic visual neglect. Consistent with our hypothesis, patients who benefitted from prism adaptation had a thicker cortex in temporo-parietal, prefrontal and cingulate areas of the left, undamaged hemisphere.Additionally, these patients had higher microstructural integrity of the body and genu of the corpus callosum. These callosal regions connect temporo-parietal, sensorimotor and prefrontal areas. Thus, prism adaptation may ameliorate signs of left visual neglect by promoting the contribution of the left hemisphere to neglect compensation. These results support current hypotheses on the role of the healthy hemisphere in the compensation for stroke-induced, chronic neuropsychological deficits, and suggest that prism adaptation can foster this role by exploiting sensorimotor/prefrontal circuits for neglect compensation. Highlights:• Visual neglect is a disabling condition resulting from right hemisphere damage • Prism adaptation is a promising therapy, but not all patients respond • We assessed the anatomical predictors of patients' response to prism adaptation • Study of cortical thickness and white matter integrity • Importance of fronto-parietal networks in the left, healthy hemisphere for recovery • Importance of callosal connections in the genu and body for recovery

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Section: Discussionsupporting

confidence: 90%

Anatomical predictors of successful prism adaptation in chronic visual neglect

Lunven

Rode

Bourlon

et al. 2017

Preprint

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“…Here we exploit this variation to test a causal mechanistic hypothesis about how sensorimotor memories in human brain are formed, retained and enhanced. Primary motor cortex (M1) has been identified as a critical region for the maintenance of newly acquired visuomotor maps following sensorimotor adaptation in both primates (Wise et al 1998;Li et al 2001;Paz et al 2003;Paz et al 2005;Inoue et al 2016) and humans (Hadipour-Niktarash et al 2007;Hunter et al 2009;Galea et al 2010;Landi et al 2011;Leow et al 2016;O'Shea et al 2017). We previously demonstrated that left M1 anodal transcranial direct current stimulation (a-tDCS) applied during adaptation to a 10-degree rightward displacement of the visual field (prism adaptation, PA) enhances consolidation of the prism after-effect (AE) in the healthy brain .…”

Section: Introductionmentioning

confidence: 99%

“…Due to the size of the voxel, adjacent regions of sensory cortex (S1) were also included in the measure of M1 metabolites. This is a common methodological limitation of MRS studies (Stagg et al 2009;Lunghi et al 2015;Antonenko et al 2017;Ip et al 2017;Kolasinski et al 2017;O'Shea et al 2017). Although we cannot rule out the contribution of S1 to our results, M1 is likely to play a predominant role because of a convergence of studies implicating it in the consolidation of adaptation memory (Wise et al 1998;Li et al 2001;Paz et al 2003;Paz et al 2005;Hadipour-Niktarash et al 2007;Landi et al 2011;Leow et al 2016).…”

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confidence: 99%

“…Within any CLP block, targets appeared either 12 cm to the left or 12 cm to the right of the centre of the screen (50% on each side), following a pseudorandom sequence in which target location transitions were generated if the same location appeared twice in a row. Visual feedback was limited to the last two thirds of the reaching movement in order to limit strategic adjustment(Redding and Wallace 1996;O'Shea et al 2014;Inoue et al 2015;O'Shea et al 2017) and lasted until 500 ms after participants touched the screen to allow for them to perceive their terminal reach endpoint error. After this time, the LC shutter turned opaque and participants had to return to the starting position (i.e.…”

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confidence: 99%

“…The differences in movement speed and target location between prism exposure (CLP trials) and AE probes (OLP) enabled us to assay generalised AE that were not contaminated by extensive training of a specific movement dynamic and local learning at a certain target location(Kitazawa et al 1997). This type of AE is thought to be relevant for neglect rehabilitation(Serino et al 2006;O'Shea et al 2017).In all four PA sessions, the tDCS electrodes were positioned and the stimulation switched on at the end of the baseline phase (20 CLPs, 30 OLPs). In the online condition, the PA phase (E1-7: 10 CLPs per block during the first 2 blocks, 20 CLPs per block in the remaining ones; AE1-7: 15 OLPs per block) started as soon as the stimulation reached its constant level.…”

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Causal explanation of individual differences in human sensorimotor memory formation

Petitet

O’Reilly

Gonçalves

et al. 2018

Preprint

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Sensorimotor cortex mediates the formation of adaptation memory. Individuals differ in the rate at which they acquire, retain, and generalize adaptation. We present a mechanistic explanation of the neurochemical and computational causes of this variation in humans. Neuroimaging identified structural, functional and neurochemical covariates of a computational parameter that determines memory persistence. To establish causality, we increased sensorimotor cortex excitability during adaptation, using transcranial direct current stimulation. As predicted, this increased retention. Inter-individual variance in the stimulation-induced E:I increase predicted the computational change, which predicted the memory gain. These relations 1 All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/255091 doi: bioRxiv preprint first posted online Jan. 29, 2018; did not hold, and memory was unchanged, with stimulation applied before adaptation. This cognitive state dependent effect was modulated by the BDNF val66met genetic polymorphism. Memory was enhanced by stimulation in Val/Val carriers only, implicating a mechanistic role for activity-dependent BDNF secretion. Sensorimotor cortex E:I causally determines the time constant of memory persistence, explaining phenotypic variation in adaptation decay.

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Methodology for tDCS integration with fMRI

Esmaeilpour

Shereen

Ghobadi‐Azbari

et al. 2019

Human Brain Mapping

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Understanding and reducing variability of response to transcranial direct current stimulation (tDCS) requires measuring what factors predetermine sensitivity to tDCS and tracking individual response to tDCS. Human trials, animal models, and computational models suggest structural traits and functional states of neural systems are the major sources of this variance. There are 118 published tDCS studies (up to October 1, 2018) that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS. FMRI can potentially contribute as: a measure of cognitive state‐level variance in baseline brain activation before tDCS; inform the design of stimulation montages that aim to target functional networks during specific tasks; and act as an outcome measure of functional response to tDCS. In this systematic review, we explore methodological parameter space of tDCS integration with fMRI spanning: (a) fMRI timing relative to tDCS (pre, post, concurrent); (b) study design (parallel, crossover); (c) control condition (sham, active control); (d) number of tDCS sessions; (e) number of follow up scans; (f) stimulation dose and combination with task; (g) functional imaging sequence (BOLD, ASL, resting); and (h) additional behavioral (cognitive, clinical) or quantitative (neurophysiological, biomarker) measurements. Existing tDCS‐fMRI literature shows little replication across these permutations; few studies used comparable study designs. Here, we use a representative sample study with both task and resting state fMRI before and after tDCS in a crossover design to discuss methodological confounds. We further outline how computational models of current flow should be combined with imaging data to understand sources of variability. Through the representative sample study, we demonstrate how modeling and imaging methodology can be integrated for individualized analysis. Finally, we discuss the importance of conducting tDCS‐fMRI with stimulation equipment certified as safe to use inside the MR scanner, and of correcting for image artifacts caused by tDCS. tDCS‐fMRI can address important questions on the functional mechanisms of tDCS action (e.g., target engagement) and has the potential to support enhancement of behavioral interventions, provided studies are designed rationally.

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Induced sensorimotor cortex plasticity remediates chronic treatment-resistant visual neglect

Cited by 55 publications

References 74 publications

Anatomical predictors of successful prism adaptation in chronic visual neglect

Anatomical predictors of successful prism adaptation in chronic visual neglect

Causal explanation of individual differences in human sensorimotor memory formation

Methodology for tDCS integration with fMRI

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