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Arousal

Arousal is a physiological and psychological state of being awake and reactive to stimuli.
It involves the activation of the reticular formation in the brainstem, the autonomic nervous system, and the limbic system, which regulates emotions and motivations.
Arousal can be influenced by various factors, such as sleep, stress, and attention, and is essential for cognitive function, mood, and overall well-being.
Disruptions in arousal can lead to conditions like insomnia, narcolepsy, and attention deficit hyperactivity disorder (ADHD).
Understanding and optimizing arousal is crucial for enhancing research accuracy, reproducibility, and scientific discovery.
PubCompare.ai's AI-driven Arousal Optimization tools can help locate the best protocols and products from literature, pre-prints, and patents, making manual protocol searches a thing of the past.

Most cited protocols related to «Arousal»

Validation of NimStim Facial Expressions

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Publication 2009

Adult Anger Arousal Asian Americans Europeans Face Fear Females Hair Latinos Males Muscle Tonus Negroid Races Oral Cavity

Affective Ratings of Visual Stimuli

Before the experimental session, the participants were given details about the contents of the images and familiarized themselves with the dimensions through the use of example stimuli. In addition, participants were informed that if they felt any discomfort during the session, they should report it immediately in order to stop the experiment.
Each participant was presented with 362 images chosen pseudorandomly from all of the categories, with the constraint that no more than three stimuli of one category were presented in succession. In all, 12 different sets of stimuli were prepared on the basis of this rule. On average, 55 ratings were collected for each picture. The sessions started with an instructional screen and 12 practice trials, with a longer time limit for the first seven of these trials. In the main experiment, each picture was presented in full-screen view for 3 s. After the first presentation of each stimulus, rating scales were displayed on a new screen to the right, and a smaller version of the image was presented on the left side of the screen. The small picture and rating scales remained available to the participant until she or he had completed all three ratings. The participants had 3 s to complete ratings on each dimension, amounting to 9 s in total. After the participant had completed all ratings, the offset picture and scale disappeared and were immediately replaced by the next picture in the series.
Three continuous bipolar semantic sliding scales were shown, each ranging from 1 to 9. Participants indicated their ratings by moving a bar over a horizontal scale using a standard computer mouse. On the valence scale, participants were asked to complete the sentence, “You are judging this image as . . .” (from 1 = very negative to 9 = very positive, with 5 = neutral). Next, participants judged motivational direction by completing the sentence, “My reaction to this image is . . .” (from 1 = to avoid to 9 = to approach, with 5 = neutral). Finally, participants judged the degree of arousal elicited by pictures with the introductory sentence, “Confronted with this image, you are feeling: …” (from 1 = relaxed to 9 = aroused, with 5 = neutral/ambivalent).
We decided to use semantic bipolar scales in the present study because it has been show that the SAM arousal scale may lead to misinterpretations (Riberio, Pompéia, & Bueno, 2005 (link)). In the original technical manual of IAPS and SAM (Lang et al., 1999 ), the description of one of the extremes of the arousal scale uses the terms relaxed, calm, sluggish, and unaroused. However, the affective space obtained from stimuli in American (Lang et al., 1999 ) and Spanish (Moltó at el., 1999 ; Vila et al., 2001 ) populations showed that the standardized rating is “boomerang-shaped,” with one extreme of the arousal scale being referred to as no reaction. As a result, this extreme anchor of the scale was used only for neutral photographs, whereas the opposite extreme was used to describe both pleasant and unpleasant pictures (arousing, value = 9). On the other hand, Brazilians (Ribeiro et al., 2005 (link)) and Germans (Grühn & Scheibe, 2008 (link)) interpreted the SAM arousal scale differently, and attributed less arousal to pleasant photographs and more arousal to neutral and negative ones. Pleasant images of landscapes, flowers, and babies were rated as being relaxing and calming. This led to a more linear distribution of scores in the affective space.
The present experiment lasted approximately 1 h. An obligatory 10-min break was taken after half of the stimuli had been presented, during which participants were asked to leave the experimental room. The study was conducted on standard PC computers using 24-in. LCD monitors. The core software for stimulus presentation and data acquisition was created using Presentation software (Version 14.6, www.neurobs.com). All responses were analyzed further using the statistical package SPSS (2009 ).

Marchewka A., Żurawski Ł., Jednoróg K, & Grabowska A. (2013). The Nencki Affective Picture System (NAPS): Introduction to a novel, standardized, wide-range, high-quality, realistic picture database. Behavior Research Methods, 46(2), 596-610.

Publication 2013

Arousal Flowers Hispanic or Latino Infant Intracisternal A-Particle Elements Motivation Mus Population Group Teaching

PROMIS Negative Affect Item Banks: Development and Validation

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Publication 2016

Anger Anxiety Arousal Cardiovascular System Cognition Discrimination, Psychology Fatigue Fear Feelings Felis catus Malignant Neoplasms Medically Unexplained Symptoms Nervousness Neurobehavioral Manifestations Reading Frames Sleep

Delineation of Arousal-Related Fiber Tracts

ARAS fiber tracts were identified using regions of interest (ROIs) that were manually traced on the diffusion images using TrackVis (version 5.1), an interactive image analysis software program that is available to the scientific community without charge (34 ). For Case 1, each diffusion image was compared to its corresponding histological section to ensure that radiologic ROIs shared the same borders, size, and contours as the histological ROIs. Histological ROIs were delineated by visual inspection with a light microscope and were confirmed by standard atlases of human neuroanatomy (35 –37 (link)). ROIs were identified for all of the key ARAS source nuclei implicated in arousal: cuneiform/subcuneiform nucleus, pontis oralis, median and dorsal raphe, locus coeruleus, pedunculopontine nucleus, parabrachial complex (combined medial and lateral parabrachial nuclei), and ventral tegmental area (Fig. 1A, B; Figure, Supplemental Digital Content 2, http://links.lww.com/NEN/A336 and Figure, Supplement Digital Content 3, http://links.lww.com/NEN/A337). ROIs were also traced using histological guidance for the thalamic nuclei implicated in the modulation, or gating, of arousal: the reticular nucleus, the central lateral nucleus, and the centromedian/parafascicular nuclear complex (Figure, Supplemental Digital Content 2, http://links.lww.com/NEN/A336). Each brainstem and thalamic ROI served as a seed point from which fiber tracts were generated. Because the brainstem ROIs are known to change in shape, size and contour along the rostro-caudal axis, histological guidance of ROI tracing was performed for every axial diffusion image using its corresponding histological section. Similarly, each thalamic nucleus was traced on the coronal diffusion images with direct guidance by the location of the stained nuclei on corresponding coronal tissue sections. For the intrathalamic connectivity analyses, a 2-ROI-tractography technique was utilized, based on methods developed by Catani et al (38 (link)). Specifically, fiber tracts passing between the reticular nucleus and central lateral nucleus were “virtually dissected” from fiber tracts passing between the reticular nucleus and the centromedian/parafascicular nuclear complex. For Cases 2 and 3, brainstem and thalamic nuclei were traced in accordance with the aforementioned neuroanatomic atlases. We also compared the neuroanatomic localization, contours, and boundaries of these ROIs in Cases 1, 2, and 3 to ensure consistency in the tractography analyses.
There are variations in nomenclature pertaining to the source nuclei of the ARAS in standard neuroanatomic atlases of the human brainstem. In this study, the neuroanatomic localization of the pedunculopontine nucleus was traced according to the brainstem atlas of Paxinos and Huang (35 ), extending from the caudal midbrain to the caudal border of the red nuclei. The neuroanatomic localization of the parabrachial complex was traced according to the brainstem atlas of Olszewski and Baxter (36 ), extending from the mid-pons to the rostral pons.

Edlow B.L., Takahashi E., Wu O., Benner T., Dai G., Bu L., Grant P.E., Greer D.M., Greenberg S.M., Kinney H.C, & Folkerth R.D. (2012). Neuroanatomic Connectivity of the Human Ascending Arousal System Critical to Consciousness and Its Disorders. Journal of Neuropathology and Experimental Neurology, 71(6), 531-546.

Publication 2012

Arousal Brain Stem Cell Nucleus Central Lateral Nucleus Diffusion Epistropheus Homo sapiens Lateral Parabrachial Nucleus Light Microscopy Locus Coeruleus Mesencephalon Nucleus, Cuneiform Pedunculopontine Tegmental Nucleus Pons Raphe, Dorsal Nucleus Red Nucleus Thalamic Nuclei Thalamus Tissues Ventral Tegmental Area

Translated Italian Version of IES-R18

The IES-R18 is a self-report measure of current subjective distress in response to a specific traumatic event. It comprises three subscales representative of the major symptom clusters of post-traumatic stress: intrusion, avoidance, and hyper-arousal.
The English version of the IES-R was translated independently into Italian by a bilingual Italian English teacher. The two translations were then compared, and no differences were found between them. The first final version was given to several bilingual individuals who also completed the English version and provided feedback on differences found in certain items between the English version and the translated version. Based on their comments, a final translation was created. This version was back translated into English by two bilingual psychologists with doctoral degrees who were familiar with psychology. After comparing the back translation with the original inventory, we made several minor revisions. The back-translation procedures were similar to those used in previous studies.31 ,32 (link)

Craparo G., Faraci P., Rotondo G, & Gori A. (2013). The Impact of Event Scale – Revised: psychometric properties of the Italian version in a sample of flood victims. Neuropsychiatric Disease and Treatment, 9, 1427-1432.

Publication 2013

Arousal Physicians

Most recents protocols related to «Arousal»

Detection of Respiratory Effort and Cerebral Activation from Mandibular Movements

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Example 15

In a 15^thexample, reference is made to FIGS. 12 and 13. FIG. 12 shows an example of the first measurement signal stream F1 and of the second measurement signal stream F2 in the situation where the subject suffers a temporary disappearance of all control of cerebral origin, which is characteristic of central hypopnoea. This disappearance is characterized by the mouth opening passively because it is no longer held up by the muscles. It is therefore seen in the streams F1 and F2 that between the peaks the signal does not indicate any activity. On the other hand at the moment of the peak there is observed a high amplitude of the movement of the mandible. Toward the end of the peaks there is seen a movement that corresponds to a non-respiratory frequency, which is the consequence of cerebral activation that will then result in a micro-arousal. The digit 1 indicates the period of hypopnoea where a reduction of the flow is clearly visible on the stream F5th from the thermistor. The digits 2 and 3 indicate the disappearance of mandibular movement in the streams F1 and F2 during the period of central hypopnoea. FIG. 13 shows an example of the first measurement signal stream F1 and of the second measurement signal stream F2 in the situation where the subject experiences a prolonged respiratory effort that will terminate in cerebral activation. It is seen that the signal from the accelerometer F1 indicates at the location indicated by H a large movement of the head and of the mandible. Thereafter the stream F2 remains virtually constant whereas in that F1 from the accelerometer the level drops, which shows that there is in any event a movement of the mandible, which is slowly lowered. There then follows a high peak I that is a consequence of a change in the position of the head during the activation that terminates the period of effort. The digit 1 indicates this long period of effort marked by snoring. It is seen, as indicated by the digit 2, that the effort is increasing with time. This effort terminates, as indicated by the digit 3, in cerebral activation that results in movements of the head and the mandible, indicated by the letter I.

The analysis unit holds in its memory models of these various signals that are the result of processing employing artificial intelligence as described hereinbefore. The analysis unit will process these streams using those results to produce a report on the analysis of those results.

It was found that the accelerometer is particularly suitable for measuring movements of the head whereas the gyroscope, which measures rotation movements, was found to be particularly suitable for measuring rotation movements of the mandible. Thus cerebral activation that leads to rotation of the mandible without the head changing position can be detected by the gyroscope. On the other hand, an IMM type movement will be detected by the accelerometer, in particular if the head moves on this occasion. An RMM type movement will be detected by the gyroscope, which is highly sensitive thereto.

US11864910B2. System comprising a sensing unit and a device for processing data relating to disturbances that may occur during the sleep of a subject (2024-01-09). Sunrise SA [BE]. Inventors: Pierre Martinot [BE].

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Patent 2024

ARID1A protein, human Arousal Exhaling Fingers Gene Expression Regulation Head Head Movements Mandible Medical Devices Memory Movement Muscle Tissue Oral Cavity Respiratory Rate Sleep Thumb Vision

Cerebral Control for Respiratory Event Detection

Not available on PMC !

Example 9

In a ninth example, reference is made to table 3. Table 3 illustrates a typical behaviour of cerebral control for the detection of respiratory events and non-respiratory motor events. It can be seen that to detect an obstructive apnoea-hypopnea, the analysis unit will for example use a median and/or a mean value on the first and second flow of measurement signals. An observation time of at least two breathing cycles or 10 seconds will be preferred to make the analysis more reliable. Obstructive apnoea-hypopnea is characterized by large cerebral control amplitude at the respiratory rate that can be repeated cyclically or non-cyclically. It will end with a large mandibular movement during cerebral activation. In particular, the distribution of the amplitude values of the mandibular movement in the stream under consideration will be analyzed.

To detect breathing effort linked to arousal (RERA), the unit of analysis will proceed in the same way as described in the previous paragraph. To detect a central apnoea-hypopnea the duration of observation will also be at least two breathing cycles or 10 seconds.

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Patent 2024

Arousal Behavior Control Mandible Medical Devices Movement Neoplasm Metastasis Respiratory Rate Sleep Sleep Apnea, Central Sleep Apnea, Obstructive Vision Volition

Measuring Emotional States Through Self-Assessment Manikin

To gain further understanding of whether arousal and mood constitute the underlying mechanism of the relationship between musical tempo and processing speed, a follow-up questionnaire was provided after the participants had completed the tasks. The Self-Assessment Manikin (SAM), a popular picture-oriented questionnaire designed to measure three psychological features of emotion, namely valence, arousal, and dominance (Bradley and Lang, 1994 (link)), was employed. This cross-cultural pictorial style of self-report assessment was selected because it is reliable and has been widely used to measure emotional states (Smith and Morris, 1977 (link)). Use of questionnaire eliminated most of the potential risks of false translation and misunderstanding. Figure 4 presents the SAM version used in the present study. The three affective dimensions were measured using seven-point scales: valence (1 = “unpleasant” to 7 = “pleasant”), arousal (1 = “calm” to 7 = “aroused”), and dominance (1 = “controlled” to 7 = “in control”).

Lin H.M., Kuo S.H, & Mai T.P. (2023). Slower tempo makes worse performance? The effect of musical tempo on cognitive processing speed. Frontiers in Psychology, 14, 998460.

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Publication 2023

Arousal Emotions Mood Self-Assessment

Evaluating Mood and Arousal with UMACL

The Japanese version of the UMACL was used to evaluate the mood of comfort [23 ]. The original checklist, developed by Matthews et al., was created based on dimension theory, making it possible to assess arousal levels [24 (link)]. The scale has two subscales that can be used to evaluate energetic arousal (10 items; vigorous vs. tired: coefficient α = 0.79) and tense arousal (10 items; nervous vs. relaxed: coefficient α = 0.76) [25 ]. High energetic arousal represents active and happy, whereas low tense arousal represents calm and quiet. Participants were asked to respond on a 4-point Likert scale. In a previous study, the mean energetic arousal was 24.4 (standard deviation [SD]: 0.5) for males and 24.4 (SD: 0.4) for females, and the mean tense arousal was 18.5 (SD: 0.4) for males and 17.56 (SD: 0.3) for females [25 ].

Hasuo H., Kusaka N., Sano M., Kanbara K., Kitawaki T., Sakuma H., Sakazaki T., Yoshida K., Shizuma H., Araki H., Suzuki M., Nishiguchi S., Shuzo M., Masuda G., Shimonishi K., Kondo K., Ueda H, & Nakamura Y. (2023). Effects of eating together online on autonomic nervous system functions: a randomized, open-label, controlled preliminary study among healthy volunteers. BioPsychoSocial Medicine, 17, 10.

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Publication 2023

Arousal Females Japanese Males Mood Nervousness

An event-related fMRI paradigm was employed. Participants read the task instructions before entering the scanner. Once inside, a two-button response pad was fixed under their right hand. They were asked to keep their gaze fixed on the center of the screen throughout the experiment. Each trial started with a white fixation cross on a black background followed by a stimulus (face or word). Each stimulus was presented within a thin white frame whose left or right side was of a darker (gray) shade and remained on the screen for 2 s (see Figure 1). Participants had to push the left button with their index finger or the right button with their middle finger if the gray sidebar appeared to the left or to the right of the stimulus, respectively. The inter-stimulus interval ranged pseudo-randomly between 2 and 18.8 s. Each participant performed four functional imaging runs; each run consisted of 72 trials, of which 36 faces (12 happy, 12 angry, 12 neutral) and 36 words (12 positive, 12 negative, 12 neutral). The AFNI (Cox, 1996 (link); Cox and Hyde, 1997 (link)) make_random_timing.py function¹ was used to simulate a series of randomized timing sequences for the trials of each stimulus category, from which the sequence with the best statistical power for the effects of interest was then identified with the 3dDeconvolve program.² Within each category, stimuli were presented in a pseudo-random order, with the constraint that no more than three consecutive stimuli belonging to the same class could occur. Two passive rest blocks were included at the beginning and at the end of each session (range 22.1–24.3 s). Each functional run lasted 8 min and the MRI session included 4 of them.
Participants performed a few practice trials inside the scanner before the experiment started. E-Prime 3.0 software (Psychology Software Tools, Pittsburgh, PA) was used to present the stimuli via the ESys functional MRI System³ remote display, and to collect behavioral responses.
At the end of the experiment, and outside the scanner, participants were asked to rate all the experimental stimuli for their valence and arousal on the Self-Assessment Manikin scale (SAM) (Bradley and Lang, 1994 (link)). The two rating questionnaires were delivered and completed on an Excel spreadsheet displayed on a tablet.

Ballotta D., Maramotti R., Borelli E., Lui F, & Pagnoni G. (2023). Neural correlates of emotional valence for faces and words. Frontiers in Psychology, 14, 1055054.

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Publication 2023

Anger Arousal Darkness Face Fingers fMRI Reading Frames Self-Assessment Tablet

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What are the different types or variations of arousal?

Arousal can manifest in different ways, including physiological arousal (e.g., increased heart rate, blood pressure, and respiration), psychological arousal (e.g., heightened attention, alertness, and emotional responses), and neurobiological arousal (e.g., activation of the reticular formation, autonomic nervous system, and limbic system). Understanding these various forms of arousal is crucial for optimizing research protocols and ensuring accurate, reproducible results.

How can disruptions in arousal lead to health conditions?

Imbalances or disturbances in arousal can contribute to a range of health issues, such as insomnia, narcolepsy, and attention deficit hyperactivity disorder (ADHD). For example, chronic underarousal may result in difficulty staying awake and focused, while overarousal can lead to anxiety, restlessness, and impaired cognitive function. Recognizing and addressing these arousal-related conditions is important for maintaining overall well-being and enhancing research quality.

What are some practical applications of understanding arousal?

Optimizing arousal is essential for a variety of research applications, including cognitive performance, emotional regulation, and task engagement. By understanding the factors that influence arousal, such as sleep, stress, and attention, researchers can design more effective protocols and interventions to support optimal functioning. This knowledge can lead to breakthroughs in fields like neuroscience, psychology, and human physiology.

How can PubCompare.ai help researchers optimize their use of arousal-related protocols?

PubCopmare.ai's AI-driven Arousal Optimization tools can assist researchers in several ways: 1) Efficiently screening protocol literature to identify the most effective arousal-related methods; 2) Leveraging AI to pinpoint critical insights that may be overlooked, such as key differences in protocol effectiveness; and 3) Helping researchers choose the best protocols to ensure reproducibility and accuracy in their arousal-related studies. By streamlining the protocol selection process and highlighting relevant insights, PubCompare.ai can save researchers time and effort, allowing them to focus on their core research goals.

What are some common challenges researchers face when working with arousal-related protocols?

One of the key challenges in working with arousal-related protocols is the inherent variability and complexity of the arousal system. Factors like individual differences, environmental influences, and measurement techniques can all impact the reliability and validity of arousal-related data. Additionally, manually searching through the vast literature to identify the most appropriate protocols can be time-consuming and frustrating. This is where tools like PubCompare.ai can be invaluable, helping researchers navigate the landscape more effeciently and make informed decisions about the best protocols to use.

More about "Arousal"

Arousal is a fundamental physiological and psychological state of being alert, responsive, and reactive to stimuli.
This process involves the activation of various neural systems, including the reticular formation in the brainstem, the autonomic nervous system, and the limbic system, which regulates emotions and motivations.
Arousal can be influenced by a variety of factors, such as sleep, stress, attention, and cognitive function.
Disruptions in arousal can lead to a range of conditions, including insomnia, narcolepsy, and attention deficit hyperactivity disorder (ADHD).
Understanding and optimizing arousal is crucial for enhancing research accuracy, reproducibility, and scientific discovery.
Researchers can utilize tools like MATLAB, Alice 5, MP150 system, Presentation software, Alice 6, Alice 4, SPSS version 25, Alice 4 or 5, and E-Series to measure, analyze, and optimize arousal levels in their studies.
PubCompare.ai's AI-driven Arousal Optimization tools can help locate the best protocols and products from literature, pre-prints, and patents, making manual protocol searches a thing of the past.
By leveraging the latest advancements in artificial intelligence and machine learning, these tools can help researchers uncover the most effective strategies for enhancing arousal and improving research outcomes.
Experience the future of scientific discovery today with PubCompare.ai's cutting-edge technology and say goodbye to tedious manual protocol searches forever.