Quiz 5

Module 5 focused on cutting-edge advancements in neuroimaging, including 7T MRI for ultra-high-resolution imaging, AI and machine learning for automated analysis, portable neuroimaging devices for point-of-care diagnostics, and future trends like quantum sensors and biophotonics.

Instructions:

  1. Read each question carefully before answering.
  2. For Multiple Choice Questions, select the best answer by choosing A, B, C, or D.
  3. For True/False Questions, indicate whether the statement is True or False.
  4. For Fill-in-the-Blank Questions, write the most accurate word or phrase to complete the sentence.
  5. Take your time to reflect on the concepts and review your answers if needed.

Innovations in Ultra-High-Resolution Imaging

A __________ MRI scanner uses a stronger magnetic field than traditional MRI, enabling clearer and more detailed images. *

A MRI scanner uses a stronger magnetic field than traditional MRI, enabling clearer and more detailed images.

Ultra-high-field MRIs can achieve __________ resolution, allowing the visualization of microstructures like individual cortical layers. *

Ultra-high-field MRIs can achieve resolution, allowing the visualization of microstructures like individual cortical layers.

What advantage does a 7T MRI provide over standard 1.5T or 3T MRIs? *
In what way does 7T MRI improve functional imaging (fMRI)? *
A 7T MRI can visualize subtle microstructural abnormalities in diseases like multiple sclerosis. *
Ultra-high-resolution imaging cannot identify early-stage changes in neurodegenerative diseases. *

Machine Learning and AI in Neuroimaging Analysis

What is a key application of AI in neuroimaging? *
What does automated image analysis in neuroimaging involve? *
AI models can analyze MRI scans to predict the onset of __________ years before clinical symptoms appear. *

AI models can analyze MRI scans to predict the onset of years before clinical symptoms appear.

Machine learning techniques can identify __________ in neuroimaging data, which are associated with specific conditions like schizophrenia. *

Machine learning techniques can identify in neuroimaging data, which are associated with specific conditions like schizophrenia.

AI can personalize rehabilitation plans for stroke patients by analyzing post-stroke brain scans. *
Predictive analytics in neuroimaging cannot determine treatment outcomes for neurological disorders. *

Portable Neuroimaging Devices

Portable MRI devices are designed to be used in __________ settings, such as outpatient clinics, ambulances, or at home. *

Portable MRI devices are designed to be used in settings, such as outpatient clinics, ambulances, or at home.

Near-Infrared Spectroscopy (NIRS) measures brain __________ and hemodynamics in real time. *

Near-Infrared Spectroscopy (NIRS) measures brain and hemodynamics in real time.

Which of the following techniques is commonly used in portable devices to monitor brain electrical activity? *
How are portable neuroimaging devices beneficial in pre-hospital care? *
Portable neuroimaging devices are not suitable for remote or underserved areas. *
Portable EEG devices can monitor brain activity and detect seizures in non-clinical settings. *

Future Trends in Neuroimaging: Quantum Sensors and Biophotonics

Quantum sensors measure weak __________ fields generated by neuronal activity with unprecedented precision. *

Quantum sensors measure weak fields generated by neuronal activity with unprecedented precision.

Biophotonics involves the use of __________ to study biological systems and brain activity. *

Biophotonics involves the use of to study biological systems and brain activity.

What is a potential application of biophotonics in Alzheimer’s research? *
Quantum sensors are expected to: *
Quantum sensors are already widely available in clinical neuroimaging settings. *
Biophotonics allows for non-invasive brain mapping without the need for dyes or electrodes. *