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Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Local Anesthetics: Common Agents and Their Applications01:23

Local Anesthetics: Common Agents and Their Applications

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Local anesthetics (LAs) are commonly used for various applications in medical and dental procedures. Some of the common agents used are cocaine, lidocaine, and bupivacaine.
Cocaine is an ester of benzoic acid and methylecgogine. It is used to anesthetize and vasoconstrict locally. Currently, it is used primarily for topical applications. It is beneficial for surgeries on the upper respiratory tract, providing anesthesia and shrinking the mucosa. Cocaine in the form of cocaine hydrochloride is...
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Local Anesthetics: Clinical Application as Spinal Anesthesia01:11

Local Anesthetics: Clinical Application as Spinal Anesthesia

1.5K
Spinal anesthetics are given during lower abdomen and limb surgeries to block sensory and motor neurons. They are administered in the mid to low lumbar regions, primarily acting on the cauda equina's nerve roots. The blockade level depends on the local anesthetic (LA) concentration. Usually, low LA concentrations are sufficient to block sensory fibers, while only high LA concentrations block motor fibers. Other factors like injection volume and speed, the patient's posture, and the drug...
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Local Anesthetics: Clinical Application as Epidural Anesthesia01:29

Local Anesthetics: Clinical Application as Epidural Anesthesia

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Epidural anesthetics are administered in the fat-filled epidural space, the outermost part of the spinal canal. This technique is commonly employed for pain management and anesthesia during lower abdomen and pelvis surgeries or labor and delivery.
Since epidural anesthetics can be infused through an epidural catheter, all types of drugs, including short-acting ones, can be administered. Chloroprocaine and lidocaine are examples of short and long-duration anesthetics, respectively. Bupivacaine...
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Local Anesthetics: Clinical Application as Intravenous Regional Anesthesia01:16

Local Anesthetics: Clinical Application as Intravenous Regional Anesthesia

1.4K
Intravenous regional anesthesia or the Bier block technique is used to anesthetize a specific limb or extremity. It uses exsanguinated or blood-drained vessels to transport local anesthetics or LAs to the peripheral nerve trunks. Lidocaine without vasoconstrictors like epinephrine is most commonly used for this technique. Other drugs used are prilocaine, ropivacaine, and chloroprocaine. Bupivacaine is not recommended for this technique due to its high cardiac toxicity.
One of the advantages of...
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Local Anesthetics: Clinical Application as Surface, Infiltration, and Conduction Block Anesthesia01:30

Local Anesthetics: Clinical Application as Surface, Infiltration, and Conduction Block Anesthesia

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Depending on the target organ, local anesthetics (LAs) can be administered via various routes. In surface anesthesia, LAs are applied directly to the surface of the skin or mucous membranes. It is widely used for topical skin numbing before venipuncture or minor surgical procedures. Commonly used surface local anesthetics are lidocaine or benzocaine sprays or creams. Surface anesthesia occurs within 5 minutes and lasts for about 60 minutes. One of the main disadvantages of topical anesthesia is...
2.1K

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Related Experiment Video

Updated: Feb 8, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

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Fully Automatic Lesion Localization and Characterization: Application to Brain Tumors Using Multiparametric

Alexis Arnaud, Florence Forbes, Nicolas Coquery

    IEEE Transactions on Medical Imaging
    |July 4, 2018
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    This study introduces an automated method for brain tumor analysis, combining quantitative magnetic resonance (MR) parameters with advanced statistics. The approach accurately localizes and characterizes tumors, improving diagnostic capabilities.

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    Area of Science:

    • Neuroimaging
    • Biostatistics
    • Medical Physics

    Background:

    • Brain tumor analysis requires both spatial localization and physiological characterization.
    • Current automated methods address these tasks separately, often requiring manual intervention.
    • Integrating quantitative magnetic resonance (MR) parameters with advanced statistical tools is needed for a unified approach.

    Purpose of the Study:

    • To develop a fully automated method for joint spatial localization and physiological characterization of brain tumors.
    • To leverage quantitative MR parameters and advanced multivariate statistical tools for improved tumor analysis.
    • To capture complex interactions between physiological parameters using generalized Student distributions.

    Main Methods:

    • Utilized quantitative magnetic resonance (MR) parameters from 53 rats (36 with tumors).
    • Employed generalized Student distributions and probabilistic mixtures to model tissue types and lesion heterogeneity.
    • Developed discriminative multivariate features to create individual lesion signatures and a statistical fingerprint model.

    Main Results:

    • Successfully demonstrated a fully automated method for joint brain tumor localization and characterization.
    • Captured non-trivial interactions between physiological parameters using advanced distributional models.
    • The statistical fingerprint model effectively characterized lesion types while accounting for inter-subject variability.

    Conclusions:

    • The proposed automated method offers a significant advancement in brain tumor analysis by integrating localization and characterization.
    • The use of generalized Student distributions and probabilistic mixtures enhances the modeling of complex biological data.
    • This generic procedure shows promise for improving the accuracy and efficiency of brain tumor diagnosis.