Neural mechanisms of proactive and reactive inhibitory control : Studies in healthy volunteers and schizophrenia patients

The neural underpinnings of our ability to restrain actions in advance (i.e. proactive inhibition) and stop actions in reaction to some event (i.e. reactive inhibition) remain largely unknown. In this thesis we used neuroimaging (functional magnetic resonance imaging, fMRI) and brain stimulation (transcranial magnetic stimulation, TMS) to explore the mechanisms underlying proactive and reactive inhibition in the healthy brain and the brain affected by schizophrenia. In particular, we focused on how three brain regions – the right inferior frontal cortex (rIFC), the supplementary motor complex (SMC), and the striatum – interact to exert proactive and reactive inhibition over the primary motor cortex (M1). There are three main findings. First, the SMC and the striatum appear to play a role in both proactive and reactive inhibition, whereas the rIFC seems to be involved in reactive inhibition only. Second, during reactive inhibition, the rIFC appears to exert control over M1 via the SMC and the striatum. Third, patients with schizophrenia (as well as their unaffected siblings) are impaired in proactive inhibition, whereas reactive inhibition seems to be spared. Impaired proactive inhibition in schizophrenia is associated with reduced frontostriatal activation and poor working memory. Together, these findings provide insight into the mechanisms at play in behavioral control, highlighting the importance of frontostriatal pathways in restraining and stopping actions

La différenciation pédagogique en badminton

Pédagogie différenciée : illustration lors d'un cycle badminton. Inventaire des pistes possibles : formes de groupement des élèves, aménagement matériel, modification ou adaptation du règlement, proposition de situations d'apprentissage adaptées, évaluation différenciée ..

Comparison of upper body strength and power between professional and college aged rugby league players

The subjective belief of what will happen plays an important role across many cognitive domains, including response inhibition. However, tasks that study inhibition do not distinguish between the processing of objective contextual cues indicating stop-signal probability and the subjective expectation that a stop-signal will or will not occur. Here we investigated the effects of stop-signal probability and the expectation of a stop-signal on proactive inhibition. Twenty participants performed a modified stop-signal anticipation task while being scanned with functional magnetic resonance imaging. At the beginning of each trial, the stop-signal probability was indicated by a cue (0% or > 0%), and participants had to indicate whether they expected a stop-signal to occur (yes/no/don't know). Participants slowed down responding on trials with a > 0% stop-signal probability, but this proactive response slowing was even greater when they expected a stop-signal to occur. Analyses were performed in brain regions previously associated with proactive inhibition. Activation in the striatum, supplementary motor area and left dorsal premotor cortex during the cue period was increased when participants expected a stop-signal to occur. In contrast, activation in the right inferior frontal gyrus and right inferior parietal cortex activity during the stimulus-response period was related to the processing of contextual cues signalling objective stop-signal probability, regardless of expectation. These data show that proactive inhibition depends on both the processing of objective contextual task information and the subjective expectation of stop-signals

Test-retest reliability of fMRI activation during prosaccades and antisaccades

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Contrasting neural effects of aging on proactive and reactive response inhibition

Two distinct forms of response inhibition may underlie observed deficits in response inhibition in aging. We assessed whether age-related neurocognitive impairments in response inhibition reflect deficient reactive inhibition (outright stopping) or also deficient proactive inhibition (anticipatory response slowing), which might be particularly evident with high information load. We used functional magnetic resonance imaging in young (n = 25, age range 18-32) and older adults (n = 23, 61-74) with a stop-signal task. Relative to young adults, older adults exhibited impaired reactive inhibition (i.e., longer stop-signal reaction time) and increased blood oxygen level-dependent (BOLD) signal for successful versus unsuccessful inhibition in the left frontal cortex and cerebellum. Furthermore, older adults also exhibited impaired proactive slowing, but only as a function of information load. This load-dependent behavioral deficit was accompanied by a failure to increase blood oxygen level-dependent (BOLD) signal under high information load in lateral frontal cortex, presupplementary motor area and striatum. Our findings suggest that inhibitory deficits in older adults are caused both by reduced stopping abilities and by diminished preparation capacity during information overload

Children with ADHD symptoms show deficits in reactive but not proactive inhibition, irrespective of their formal diagnosis

Contains fulltext : 197245.pdf (publisher's version ) (Open Access

Putaminal Volume in Frontotemporal Lobar Degeneration and Alzheimer Disease: Differential Volumes in Dementia Subtypes and Controls

BACKGROUND AND PURPOSE: Frontostriatal (including the putamen) circuit-mediated cognitive dysfunction has been implicated in frontotemporal lobar degeneration (FTLD), but not in Alzheimer disease (AD) or healthy aging. We sought to assess putaminal volume as a measure of the structural basis of relative frontostriatal dysfunction in these groups. MATERIALS AND METHODS: We measured putaminal volume in FTLD subtypes: frontotemporal dementia (FTD, n = 12), semantic dementia (SD, n = 13), and progressive nonfluent aphasia (PNFA, n = 9) in comparison with healthy controls (n = 25) and patients with AD (n = 18). Diagnoses were based on accepted clinical criteria. We conducted manual volume measurement of the putamen blinded to the diagnosis on T1 brain MR imaging by using a standardized protocol. RESULTS: Paired t tests (P < .05) showed that the left putaminal volume was significantly larger than the right in all groups combined. Multivariate analysis of covariance with a Bonferroni correction was used to assess statistical significance among the subject groups (AD, FTD, SD, PNFA, and controls) as independent variables and right/left putaminal volumes as dependent variables (covariates, age and intracranial volume; P < .05). The right putamen in FTD was significantly smaller than in AD and controls; whereas in SD, it was smaller compared with controls with a trend toward being smaller than in AD. There was also a trend toward the putamen in the PNFA being smaller than that in controls and in patients with AD. Across the groups, there was a positive partial correlation between putaminal volume and Mini-Mental State Examination (MMSE). CONCLUSIONS: Right putaminal volume was significantly smaller in FTD, the FTLD subtype with the greatest expected frontostriatal dysfunction; whereas in SD and PNFA, it showed a trend towards being smaller, consistent with expectation, compared to controls and AD; and in SD, compared with AD and controls. Putaminal volume weakly correlated with MMSE

Within-subject variation in BOLD-fMRI signal changes across repeated measurements: Quantification and implications for sample size

Item does not contain fulltextFunctional magnetic resonance imaging (fMRI) can be used to detect experimental effects on brain activity across measurements. The success of such studies depends on the size of the experimental effect, the reliability of the measurements, and the number of subjects. Here, we report on the stability of fMRI measurements and provide sample size estimations needed for repeated measurement studies. Stability was quantified in terms of the within-subject standard deviation (σw) of BOLD signal changes across measurements. In contrast to correlation measures of stability, this statistic does not depend on the between-subjects variance in the sampled group. Sample sizes required for repeated measurements of the same subjects were calculated using this σw. Ten healthy subjects performed a motor task on three occasions, separated by one week, while being scanned. In order to exclude training effects on fMRI stability, all subjects were trained extensively on the task. Task performance, spatial activation pattern, and group-wise BOLD signal changes were highly stable over sessions. In contrast, we found substantial fluctuations (up to half the size of the group mean activation level) in individual activation levels, both in ROIs and in voxels. Given this large degree of instability over sessions, and the fact that the amount of within-subject variation plays a crucial role in determining the success of an fMRI study with repeated measurements, improving stability is essential. In order to guide future studies, sample sizes are provided for a range of experimental effects and levels of stability. Obtaining estimates of these latter two variables is essential for selecting an appropriate number of subjects.11 p