6 results match your criteria: "Amiens-Picardy University Medical Center[Affiliation]"

Article Synopsis
  • This study aimed to improve the accuracy of eye-tracking data in conjunction with fMRI by developing a new post-processing platform, allowing better insights into visual attention during cognitive tasks.
  • Sixteen participants engaged in visual tasks while their eye movements were recorded, showing that post-processing significantly enhanced data reliability and participants generally focused well on the screen.
  • The methodology effectively detected visual artifacts, revealing that longer tasks can diminish attention and offering a useful framework for future research in cognitive neuroscience integrating eye-tracking and fMRI.
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Background: Understanding of the cerebrospinal fluid (CSF) circulation is essential for physiological studies and clinical diagnosis. Real-time phase contrast sequences (RT-PC) can quantify beat-to-beat CSF flow signals. However, the detailed effects of free-breathing on CSF parameters are not fully understood.

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Article Synopsis
  • The study investigates how free breathing impacts cerebral venous flow, which is important for understanding brain circulation and clinical practices.
  • Using two MRI techniques, CINE-PC and RT-PC, researchers measured blood flow in various brain veins of 28 healthy individuals to compare their effectiveness and assess breathing's effect on blood flow.
  • Results indicate that RT-PC is accurate in measuring cerebral venous flow and that breathing significantly alters flow rates, particularly in the jugular veins, providing new insights into cerebral circulation mechanisms.
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Background: Since arterial flow is the leading actor in neuro-fluids flow dynamics, it might be interesting to assess whether it is meaningful to study the arterial flow waveform in more detail and whether this provides new important information. Few studies have focused on determining the influence of heart rate variation over time on the arterial flow curve. Therefore, this study aimed to evaluate cerebral arterial flow waveforms at extracranial and intracranial compartments in young and elderly healthy adults, also considering systole and diastole phases.

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In the field of emergency medicine (EM), the use of decision support tools based on artificial intelligence has increased markedly in recent years. In some cases, data are omitted deliberately and thus constitute "data not purposely collected" (DNPC). This accepted information bias can be managed in various ways: dropping patients with missing data, imputing with the mean, or using automatic techniques (e.

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