Lasting deficit in inhibitory control with mild traumatic brain injury

Xu, Benjamin; Sandrini, Marco; Levy, Sarah; Volochayev, Rita; Awosika, Oluwole O.; Butman, John A.; Pham, Dzung L.; Cohen, Leonardo G.

doi:10.1038/s41598-017-14867-y

Cited by 21 publications

(9 citation statements)

References 58 publications

(66 reference statements)

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“…These results suggest the presence of a response inhibition deficit following mTBI. Fischer et al (2013) confirmed the reverse brain activation pattern observed by Xu et al (2017) when studying chronic, mild-to-moderate TBI; these authors identified bilateral BOLD signal increases in the caudate nuclei and in the left superior temporal, inferior temporal and cerebellar cortices, especially in relation to failures to inhibit a response.…”

Section: Executive Functionsupporting

confidence: 59%

“…Impairment of response inhibition has been noted acutely, up to ∼2.3 years after mTBI and up to ∼5.7 years after TBIs of mixed severity ( Dimoska-Di Marco et al, 2011 ; Xu et al, 2017 ), no distinction being drawn between complicated and uncomplicated mTBI. Nevertheless, a large meta-analysis of 41 studies found no relationship between inhibition performance and TBI severity ( Dimoska-Di Marco et al, 2011 ).…”

Section: Executive Functionmentioning

confidence: 99%

“…In an acute mTBI sample, Dall’acqua et al (2016) used MRI to identify a positive correlation between bilateral frontal volume reductions and performance on a response inhibition task. By studying BOLD signals recorded during a choice reaction task, Xu et al (2017) found that chronic mTBI participants exhibited a brain activation pattern in the cerebello-thalamo-cortical network which was reversed compared to that of HCs. Specifically, whereas the task’s Go condition was associated with significantly weaker activation of this network in the mTBI group, its Switch condition was linked to significantly stronger activation in mTBI patients.…”

Section: Executive Functionmentioning

confidence: 99%

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Neuroimaging and Psychometric Assessment of Mild Cognitive Impairment After Traumatic Brain Injury

Calvillo

Irimia

2020

Front. Psychol.

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Traumatic brain injury (TBI) can be serious partly due to the challenges of assessing and treating its neurocognitive and affective sequelae. The effects of a single TBI may persist for years and can limit patients’ activities due to somatic complaints (headaches, vertigo, sleep disturbances, nausea, light or sound sensitivity), affective sequelae (post-traumatic depressive symptoms, anxiety, irritability, emotional instability) and mild cognitive impairment (MCI, including social cognition disturbances, attention deficits, information processing speed decreases, memory degradation and executive dysfunction). Despite a growing amount of research, study comparison and knowledge synthesis in this field are problematic due to TBI heterogeneity and factors like injury mechanism, age at or time since injury. The relative lack of standardization in neuropsychological assessment strategies for quantifying sequelae adds to these challenges, and the proper administration of neuropsychological testing relative to the relationship between TBI, MCI and neuroimaging has not been reviewed satisfactorily. Social cognition impairments after TBI (e.g., disturbed emotion recognition, theory of mind impairment, altered self-awareness) and their neuroimaging correlates have not been explored thoroughly. This review consolidates recent findings on the cognitive and affective consequences of TBI in relation to neuropsychological testing strategies, to neurobiological and neuroimaging correlates, and to patient age at and assessment time after injury. All cognitive domains recognized by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) are reviewed, including social cognition, complex attention, learning and memory, executive function, language and perceptual-motor function. Affect and effort are additionally discussed owing to their relationships to cognition and to their potentially confounding effects. Our findings highlight non-negligible cognitive and affective impairments following TBI, their gravity often increasing with injury severity. Future research should study (A) language, executive and perceptual-motor function (whose evolution post-TBI remains under-explored), (B) the effects of age at and time since injury, and (C) cognitive impairment severity as a function of injury severity. Such efforts should aim to develop and standardize batteries for cognitive subdomains—rather than only domains—with high ecological validity. Additionally, they should utilize multivariate techniques like factor analysis and related methods to clarify which cognitive subdomains or components are indeed measured by standardized tests.

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Section: Executive Functionsupporting

confidence: 59%

Section: Executive Functionmentioning

confidence: 99%

Section: Executive Functionmentioning

confidence: 99%

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Neuroimaging and Psychometric Assessment of Mild Cognitive Impairment After Traumatic Brain Injury

Calvillo

Irimia

2020

Front. Psychol.

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“…It has been shown frequently that dual-task performance is more sensitive to change than single task in patients with previous concussion. 26,27 This long term, specifically dual-task deficit may suggest that impaired inhibitory control and/or attentional resources last longer than changes in simple sensory processing, which may explain our acutely concussed sample's differences in both simple visual and dual-task visual reaction time.…”

Section: Concussed Vs Non-concussed Performancementioning

confidence: 91%

Visuo-oculomotor Function and Reaction Times in Athletes with and without Concussion

Cochrane¹,

Christy

Almutairi

et al. 2019

Optom Vis Sci

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Significance.-Oculomotor tests in concussion commonly show impairment in smooth pursuit and saccadic function. Honing in on the systems likely to be affected by concussion will streamline use of oculomotor function as a supplemental diagnostic and prognostic tool, as well as improve our understanding of the pathophysiology of concussion. Purpose.-This study investigates oculomotor function between concussed and healthy collegiate athletes, as well as determines measurement test-retest reliability of those tools. Methods.-Eighty-seven healthy athletes were recruited from a US Division 1 sports university and completed a 30-minute vestibular ocular testing battery in an enclosed rotary chair system equipped with 100Hz eye-tracking goggles. Forty-three individuals completed the battery twice. Twenty-eight individuals with a current diagnosis of concussion also completed the battery. All participants were ages 18-24. Bivariate statistical tests examined differences in scores across groups, and intraclass coefficients were computed to test reliability. Results.-Concussed individuals had significantly longer saccadic, visual, and dual-task reaction times and reduced saccadic accuracy. There was no difference in optokinetic reflex gain, but few

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“…Reaction time (RT) was used. This test was chosen because it is less affected by mild traumatic brain injury [28].…”

Section: Methodsmentioning

confidence: 99%

Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure

Augsburger

Galatzer‐Levy

2020

BMC Psychiatry

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Background: Though lifetime exposure to traumatic events is significant, only a minority of individuals develops symptoms of posttraumatic stress disorder (PTSD). Post-trauma alterations in neurocognitive and affective functioning are likely to reflect changes in underlying brain networks that are predictive of PTSD. These constructs are assumed to interact in a highly complex way. The aim of this exploratory study was to apply machine learning models to investigate the contribution of these interactions on PTSD symptom development and identify measures indicative of circuit related dysfunction. Methods: N = 94 participants admitted to the emergency room of an inner-city hospital after trauma exposure completed a battery of neurocognitive and emotional tests 1 month after the incident. Different machine learning algorithms were applied to predict PTSD symptom severity and clusters after 3 months based. Results: Overall, model accuracy did not differ between PTSD clusters, though the importance of cognitive and emotional domains demonstrated both key differences and overlap. Alterations in higher-order executive functioning, speed of information processing, and processing of emotionally incongruent cues were the most important predictors. Conclusions: Data-driven approaches are a powerful tool to investigate complex interactions and can enhance the mechanistic understanding of PTSD. The study identifies important relationships between cognitive processing and emotion recognition that may be valuable to predict and understand mechanisms of risk and resilience responses to trauma prospectively.

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Lasting deficit in inhibitory control with mild traumatic brain injury

Cited by 21 publications

References 58 publications

Neuroimaging and Psychometric Assessment of Mild Cognitive Impairment After Traumatic Brain Injury

Neuroimaging and Psychometric Assessment of Mild Cognitive Impairment After Traumatic Brain Injury

Visuo-oculomotor Function and Reaction Times in Athletes with and without Concussion

Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure

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