This study was supported by the LABEX CORTEX (ANR-11-LABX-0042) of Universit&#233; de Lyon, within the program &#8216;&#8216;Investissements d&#8217;Avenir&#8217;&#8217; (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR).

All methods described here have been approved by the Ethics Committee of the Department of Psychology of University Lyon 2 and informed consent was obtained from all participants.
NOTE: Participants were recruited by means of notices posted in the local community and at the University.
1. Participants
<ol>
	<li>Ensure that participants have a driving license and at least two years of driving experience.</li>
	<li>Ensure that participants have normal or corrected to normal vision and audition.</li>
	<li>Ensure that participants do not suffer from a mental illness (e.g., schizophrenia).</li>
	<li>Recruit a similar number of females and males.</li>
	<li>Equip participants with a heart rate belt linked to a watch to monitor heart rate.</li>
	<li>Ask participants to choose freely their own preferred music track (examples of participants choice: Uptown Funk by Mark Ronson featuring Bruno Mars or Cheerleader by OMI). Ask participants to provide that music track on a USB stick. Use this track to create different musical backgrounds for the experiment (see section 3).</li>
</ol>
2. Driving simulation
NOTE: The following steps are described based on a new driving simulator, a BB_Sim developed at the Universit&#233; de Sherbrooke, which includes one computer, three screens, as well as a steering wheel and acceleration and braking pedals for driving controls. The initial study was conducted with a different driving simulator using the open-source OpenSD2S software18.
<ol>
	<li>Set the driving simulation driving noise (i.e., engine of the driven vehicle) at &#177; 25dB.</li>
	<li>Seat the participant in front of the simulator, approximately 60 cm from the screens (three screens located in front of the participant,&#160;48 cm x 30 cm each,&#160;covering a total of&#160;137.52&#176; of the visual angle on the horizontal axis and 28.65&#176; of the visual angle on the vertical axis), in a modified car seat.</li>
	<li>Let the participant adjust the distance between the seat and the pedals with the handle underneath the seat.</li>
	<li>Once the participant is comfortably positioned, provide instructions on using the features of the simulator (i.e., how to interact with the acceleration and braking pedals and the steering wheel).</li>
	<li>Inform the participant about simulation sickness that can sometimes occur, and let the participant know that the simulation will be stopped at any time if necessary.</li>
	<li>Use a rural roadway with one traffic lane per direction with five left bends and five right bends and without any traffic.</li>
</ol>
3. Musical background
<ol>
	<li>Use software to modify the tempo of the music, without any pitch modification.</li>
	<li>Create four auditory backgrounds for each participant: (1) No Music, with no additional music played; (2) Music, each participant preferred music track without modification; (3) Music +10, each participant preferred music track with an increased tempo. The tempo is increased by 10 % of the regular tempo; (4) Music-10, each participant preferred music track with a decreased tempo. The tempo is decreased by 10 % of the regular tempo.</li>
	<li>Control the intensity of the music. Music intensity is known to modify driving performances19. Set the intensity to 75 dB for all auditory backgrounds but the No Music condition.</li>
	<li>Use a software to play one of the four musical backgrounds for the entire duration of each drive. Play the music on two lateral powered monitor speakers located on the right and on the left of the participant.</li>
</ol>
4. Simulated car-following task
<ol>
	<li>Provide instructions concerning the task: &#34;Drive as you would do in a real-life situation. Your goal is to follow the vehicle in front of you at a close but safe constant distance, as if following a friend on an unknown route.&#34;&#160;Inform the participant that there is no traffic or obstacles on the path.</li>
	<li>Start the simulation with a training phase in order to familiarize the participant with the driving simulator, the simulated environment, the vehicle controls, and the car-following task. When the participant feels comfortable, stop the training phase.</li>
	<li>Proceed with the experimental drives. Launch the simulated car-following task and one of the four musical backgrounds.</li>
	<li>Start recording the heart rate data at the beginning of each simulated car-following task and end it at the end of that driving task.</li>
	<li>For the simulated car driving task, have the driver first drive for 50 m before stopping at a &#34;Stop&#34;&#160;sign. Once the participant&#8217;s vehicle has stopped, a leading vehicle appears on the road at the left of the intersection. Instruct the participant to follow the vehicle. After an initial phase in which the speed of the leading vehicle is stationary and set at 20 kph allowing the driven vehicle to catch up, its speed then varies sinusoidally between 45 kph and 70 kph within each period of 60 s for a total of 3 min. Then, ask the participant to stop driving.</li>
	<li>For the car-following task, use a two-lane road with opposite traffic directions. In order to provide a realistic driving environment, use a road section with a balanced number of left (n = 5) and right bends (n = 5) with various radii of curvature from 45 m to 300 m. Additionally, add visual elements on the edges of the road section such as trees, barriers, fields, and landform.</li>
	<li>Repeat the car-following task for each of the four musical backgrounds. The car-following task takes about 4 min (3 min of actual car-following plus the beginning and ending of the driving simulation). 
	NOTE: The duration of the car-following task can be extended if required.</li>
	<li>Take a 5 min break between each car-following task to reduce carryover effects.</li>
	<li>Counterbalance the order of presentation of the four musical backgrounds between participants using a Latin square design.</li>
</ol>
5. Data collection
<ol>
	<li>Collect the participants&#39;&#160;subjective mood after each condition using the Brief Mood Introspection Scale (BMIS)20 validated in French21,22. This questionnaire provides data on participants&#39;&#160;mood on four mood dimensions: pleasant/unpleasant, arousal/calm, positive/tired, and negative/relaxed.</li>
	<li>Collect physiological measures. Compute the mean heart rate and heart rate variability over the entire drive for each experimental condition using the data recorded by the heart rate monitoring watch at a sample per second. In practice, compute mean heart rate by averaging all the data collected during each experimental condition and heart rate variability by calculating the standard deviation on the same data.</li>
	<li>Measure objective driving behaviors through the mean inter-vehicular time and the inter-vehicular time variability. Record both driven and leading vehicle position and speed at each time step at a sample rate of 60 Hz.
	<ol>
		<li>At each time step, compute the inter-vehicular time as the time required for the driven vehicle to reach the position of the lead vehicle if the position of the lead vehicle was frozen and the speed of the driven vehicle was constant.</li>
		<li>Average all the values collected for a drive to obtain the mean inter-vehicular time and compute the standard deviation on those values to obtain the inter-vehicular time variability. 
		NOTE: Several variables can be computed to qualify driving behaviors during a car-following task. The inter-vehicular time is particularly well-suited as it offers an indication of the safety margin between the driven vehicle and the lead vehicle chosen by the driver.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

The proposed method is well suited for cognitive ergonomic investigations as it offers an excellent compromise between experimental control and ecological vailidity16. If a strong experimental control is required to ensure that the collected results are related to the experimental manipulations, no results are of interest if restricted to the experimental conditions. Indeed, scientific results are of interest if transferable to real life situations. These assertions do not mean that only real-life...

Car driving activity has increased quickly over the last decades and is now a daily activity for many individuals in modern societies. In line with this growth, car-driving activity has become a hot topic of investigation for the human factor community1.
There is an extremely limited number of major cultural activities that typically define humankind regardless of the population and the period of history considered2. Music is one of these activities along with tool use and symbolic reasoning underpinning language abilities3. Playing and listening to music is therefore a crucial individual and social activity. Based on an exhaustive literature review, Sch&#228;fer et al.4 found about 130 different non-redundant functions associated to music listening and three music listening meta-functions were then identified: (1) arousal and mood regulation, (2) self-awareness achievement, and (3) social relatedness expression. As a consequence, people are frequently listening to music in a variety of situations and locations5. Among those situations, listening to music while driving is extremely common with drivers reporting listening to music during about three quarters of their driving time6.
Music listening is known to impact the listener&#8217;s emotional state7 and thus to induce mood changes in a variety of situations and research areas8. According to the mood congruency theory, a person&#8217;s behavior is related to his/her mood9 with evidence gained from both neuroimaging10 and behavioral experiments11. Following this rationale, music listening can change drivers&#8217; mood, which in turn can change driving behaviors.
Musically-induced mood changes while driving were found to result in performance improvements under certain conditions or impairments under other conditions. On the one hand, in complex and highly demanding driving environments, calm music was found to mitigate affective states:&#160; it has a softening effect on negative emotions, reduces the level of stress, and improves driver&#8217;s relaxation and calm12. This relaxing effect was reported to be more efficient when using abrupt music changes compared to gradual music changes13. On the other hand, people were slower to detect hazards in driving scenes when anger was previously induced through music and guided imagery compared with neutral mood performances14. Happy music listening while driving was also found to be detrimental to lateral control efficiency, while sad music had no significant effect on lateral control of the vehicle15. In brief, drivers&#8217; mood can impact driving performances in opposite ways depending on the music and associated mood induction and on the driving situation considered.
The purpose of the method reported here is to offer an experimentally well-controlled driving situation to investigate the impact of music listening on driving behaviors. To ensure the reproducibility of the driving situation, a method based on driving simulation has been implemented. At the first glance, a driving simulation might be considered as a degraded version of real driving investigations. However, the reality is more complex, and a given experimental setup cannot be considered as the best experimental solution in absolute terms. Rather the best experimental setup is the one that suits the most accurately the needs of the investigation concerned16. If real car-driving is the experimental setup that best reproduces the everyday life driving situations, it also comes with some drawbacks: driver safety in case of experimental manipulations, potential impairments in terms of driving performances, and difficulties in the control of the driving environment, including traffic, weather conditions, light conditions, level of ambient noise, etc. Conversely, if driving simulators are not as realistic as real vehicles, experimental conditions and manipulations can be strictly controlled and replicated17. As a result, different participants can be exposed to the exact same experimental conditions. In addition, experimental manipulations potentially impairing driving performances are made possible as only virtual safety (and not real safety) is engaged. Altogether, a driving simulation offers an excellent compromise between the need to conserve the driving activity natural (i.e., external validity) and the need for a strong experimental control (i.e., internal validity).

<table border="0" cellpadding="0" cellspacing="0" style="width:1036px;" width="1036">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="33">
			<td height="33" style="height:33px;width:216px;">Audacity software</td>
			<td style="width:271px;">Audacity</td>
			<td style="width:115px;">Open source</td>
			<td style="width:435px;">https://www.audacityteam.org</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Driving simulator</td>
			<td style="width:271px;">Universit&#233; de Sherbrooke</td>
			<td style="width:115px;">BB sim</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Polar watch with heart rate monitor</td>
			<td style="width:271px;">Polar</td>
			<td style="width:115px;">RC3</td>
			<td>https://www.polar.com/fr</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Speakers</td>
			<td style="width:271px;">Yamaha</td>
			<td style="width:115px;">MSP3</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Steering wheel and pedals</td>
			<td style="width:271px;">Logitech</td>
			<td style="width:115px;">G27</td>
			<td></td>
		</tr>
	</tbody>
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driving under the influence: how music listening affects driving behaviors

Car driving is a daily activity for many individuals in modern societies. Drivers often listen to music while driving. The method presented here investigates how listening to music influences driving behaviors. A driving simulation was selected because it offers both a well-controlled environment and a good level of ecological validity. Driving behaviors were assessed through a car-following task. In practice, participants were instructed to follow a lead vehicle as they would do in real life. The lead vehicle speed changed over time requiring constant speed adjustments for the participants. The inter-vehicular time was used to assess driving behaviors. To complement the driving behaviors, the subjective mood and physiological level of arousal were also collected. As such, the results collected using this method offer insights on both the human internal state (i.e., subjective mood and physiological arousal) and driving behaviors in the car following task.

The main comparisons are based on the following experimental conditions. The first experimental condition is No Music versus Music, a comparison between the No Music background and the individual preferred Music background using a pairwise t-test. These analyses were meant to assess the influence of listening to preferred music compared to a control condition without music. The second experimental condition is four different musical backgrounds, a comparison between No Music, Music, Music +10 and Music -10 corre...

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Driving Under the Influence: How Music Listening Affects Driving Behaviors

Here, we present a protocol to assess driving behaviors while following a vehicle in a simulated driving environment. The presented protocol is used to compare the impact of different auditory backgrounds on driving behaviors.

Car driving is a daily activity for many individuals in modern societies. Drivers often listen to music while driving. The method presented here ...

driving-under-influence-how-music-listening-affects-driving

Research

JoVE Journal

Behavior

12.3K Views.  University Lyon 2. Here, we present a protocol to assess driving behaviors while following a vehicle in a simulated driving environment. The presented protocol is used to compare the impact of different auditory backgrounds on driving behaviors.

Video: Driving Under the Influence: How Music Listening Affects Driving Behaviors

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are deliberately planned, while others spontaneously occur below conscious awareness. The deliberate component of this dichotomy has been studied extensively in several contexts, while the spontaneous component remains largely under-explored. Moreover, how perceptual processes modulate these movement classes is still unclear. In particular, a currently debated issue is whether the visuomotor system is governed by the spatial percept produced by a visual illusion or whether it is not affected by the illusion and is governed instead by the veridical percept. Bistable percepts such as 3D depth inversion illusions (DIIs) provide an excellent context to study such interactions and balance, particularly when used in combination with reach-to-grasp movements. In this study, a methodology is developed that uses a DII to clarify the role of top-down processes on motor action, particularly exploring how reaches toward a target on a DII are affected in both deliberate and spontaneous movement domains.

It is unclear how top-down signals from the ventral visual stream affect movement. We developed a paradigm to test motor behavior towards a target on a 3D depth inversion illusion. Significant differences are reported in both deliberate, goal-directed movements and automatic actions under illusory and veridical viewing conditions.

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are ...

Irrelevant Stimuli and Action Control: Analyzing the Influence of Ignored Stimuli via the Distractor-Response Binding Paradigm

Selection tasks in which simple stimuli (e.g. letters) are presented and a target stimulus has to be selected against one or more distractor stimuli are frequently used in the research on human action control. One important question in these settings is how distractor stimuli, competing with the target stimulus for a response, influence actions. The distractor-response binding paradigm can be used to investigate this influence. It is particular useful to separately analyze response retrieval and distractor inhibition effects. Computer-based experiments are used to collect the data (reaction times and error rates). In a number of sequentially presented pairs of stimulus arrays (prime-probe design), participants respond to targets while ignoring distractor stimuli. Importantly, the factors response relation in the arrays of each pair (repetition vs. change) and distractor relation (repetition vs. change) are varied orthogonally. The repetition of the same distractor then has a different effect depending on response relation (repetition vs. change) between arrays. This result pattern can be explained by response retrieval due to distractor repetition. In addition, distractor inhibition effects are indicated by a general advantage due to distractor repetition. The described paradigm has proven useful to determine relevant parameters for response retrieval effects on human action.

The distractor-response binding paradigm is described. It can be used to shed light on the influence irrelevant stimuli, competing with targets for a response, can have on human action. Both response retrieval effects and distractor inhibition effects can be analyzed within the paradigm.

Selection tasks in which simple stimuli (e.g. letters) are presented and a target stimulus has to be selected against one or more distractor stimuli are ...

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson&#8217;s disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Behavioral tasks that allow for the assessment of perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) are presented. Synchronization of finger tapping to the beat of an auditory stimuli and detecting rhythmic irregularities provides a means of uncovering rhythm disorders.

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here ...

Applying Stereotactic Injection Technique to Study Genetic Effects on Animal Behaviors

Stereotactic injection is a useful technique to deliver high titer lentiviruses to targeted brain areas in mice. Lentiviruses can either overexpress or knockdown gene expression in a relatively focused region without significant damage to the brain tissue. After recovery, the injected mouse can be tested on various behavioral tasks such as the Open Field Test (OFT) and the Forced Swim Test (FST). The OFT is designed to assess locomotion and the anxious phenotype in mice by measuring the amount of time that a mouse spends in the center of a novel open field. A more anxious mouse will spend significantly less time in the center of the novel field compared to controls. The FST assesses the anti-depressive phenotype by quantifying the amount of time that mice spend immobile when placed into a bucket of water. A mouse with an anti-depressive phenotype will spend significantly less time immobile compared to control animals. The goal of this protocol is to use the stereotactic injection of a lentivirus in conjunction with behavioral tests to assess how genetic factors modulate animal behaviors.

Stereotactic injection of lentiviruses expressing cDNAs or shRNAs can modulate gene expression in specific brain areas of mice. Here, we present a protocol to combine stereotactic injections with behavioral tasks, such as the Open Field Test (OFT) and the Forced Swim Test (FST).

Stereotactic injection is a useful technique to deliver high titer lentiviruses to targeted brain areas in mice. Lentiviruses can either overexpress or ...

Assessing the Effects of Music Listening on Psychobiological Stress in Daily Life

Music listening is associated with stress-reducing effects. However, most of the results on music listening and stress were gathered in experimental settings. As music listening is a popular activity of daily life, it is of utmost importance to study the effects of music listening on psychobiological stress in an everyday, daily-life setting. Here, a study protocol is presented that allows the assessment of associations between music listening and psychobiological stress in daily life by noninvasively measuring salivary cortisol (as a marker of the Hypothalamic-Pituitary-Adrenal (HPA) axis) and salivary alpha-amylase (as a marker of the Autonomic Nervous System (ANS)). The protocol includes advice on the study design (e.g., sampling protocol), the materials and methods (e.g., the assessment of psychobiological stress in daily life, the assessment of music listening, and the manual), the selection of participants (e.g., the approval of the institutional review board and inclusion criteria), and the statistical analyses (e.g., the multilevel approach). The representative results provide evidence for a stress-reducing effect of music listening in daily life. Particularly, specific reasons for listening to music (especially relaxation), as well as the presence of others while doing so, increase this stress-reducing effect. At the same time, music listening in daily life differentially affects the HPA axis and ANS functioning, thus emphasizing the need for a multi-dimensional assessment of stress in daily life.

A study protocol is presented on how to assess associations between music listening and psychobiological stress (as measured by subjective stress levels, salivary cortisol, and salivary alpha-amylase) in daily life. Advice on study design, materials, methods, selection of participants, and statistical handling is provided. Representative results are presented and discussed.

Music listening is associated with stress-reducing effects. However, most of the results on music listening and stress were gathered in experimental ...

How to Use the H1 Deep Transcranial Magnetic Stimulation Coil for Conditions Other than Depression

Deep transcranial magnetic stimulation (dTMS) is a relatively new technique that uses different coils for the treatment of different neuropathologies. The coils are made of soft copper windings in multiple planes that lie adjacent to the skull. They are located within a special helmet so that their magnetic fields combine and improve depth penetration. The H1 dTMS coil is designed to stimulate bilateral prefrontal cortices with greater effective stimulation over the left than the right. By positioning the left side of the coil close to the left dorsolateral prefrontal cortex (DLPFC), the H1 coil was used in a multisite study, leading to FDA approval for treatment-resistant depression. In this same position, the H1 coil was also explored as a possible treatment for negative symptoms of schizophrenia, bipolar depression, and migraine. When moved to different positions over the subject's skull, the H1 coil was also explored as a possible treatment for other conditions. Such manipulation of the H1 coil was demonstrated for PTSD and alcohol dependence by positioning it over the medial prefrontal cortex (mPFC), for anxiety by positioning it over the right prefrontal cortex (rPFC), for auditory hallucinations and tinnitus by positioning it over the temporoparietal junction (TPJ), and for Parkinson's and fatigue from multiple sclerosis (MS) by positioning it over the motor cortex (MC) and PFC. Corresponding electrical field diagrams measured with an oscilloscope through a saline-filled head are included.

The H1 deep transcranial magnetic stimulation coil is FDA-cleared for the treatment of depression. We demonstrate how to utilize the H1 for other conditions, such as auditory hallucinations and PTSD, by moving the helmet to different locations over the subject's skull.

Deep transcranial magnetic stimulation (dTMS) is a relatively new technique that uses different coils for the treatment of different neuropathologies. The ...

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities.

This manuscript describes how to use the wavelet entropy index to analyze high-density electroencephalography (EEG) and electrocardiography (ECG) data. We show that the irregularity of cerebral and cardiac activities became more coordinated during mindfulness-based stress reduction practice.

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One ...

Assessment of Social Transmission of Food Preferences Behaviors

Olfactory recognition deficits are suggested to be able to serve as clinical marker to differentiate Alzheimer&#39;s disease (AD) subjects from healthy aging groups. For example, olfactory dysfunction in AD can present as impairment in olfactory recognition, emerging during early stages of the disease and worsening while the disease progresses. The social transmission of food preferences (STFP) task is based on a rudimentary form of communication between rodents concerning distant foods dependent on the transmission of olfactory cues. Healthy wild-type mice would prefer to eat a novel, flavored food that was previously cued by a conspecific, and this food preference would be hampered in transgenic AD mice, such as the APP/PS1 model. Indeed, a strong preference for the cued food in C57Bl6/J mice of 3 months of age was found, and this was reduced in 3 months old transgenic APP/PS1 mice. In summary, STFP task could be a powerful measure to be integrated in present subclinical detection assays of AD.

This paper presents a protocol for the investigation of social transmission of food preference in mice. The advantages and possible applications for this procedure, for instance, in detecting early changes in AD mouse models, are highlighted. To conclude, interpretation of the results in light of critical details are discussed.

Olfactory recognition deficits are suggested to be able to serve as clinical marker to differentiate Alzheimer&#39;s disease (AD) subjects from healthy ...

Assessing the Influence of Personality on Sensitivity to Magnetic Fields in Zebrafish

To orient themselves in their environment, animals integrate a wide array of external cues, which interact with several internal factors, such as personality. Here, we describe a behavioral protocol designed for the study of the influence of zebrafish personality on their orientation response to multiple external environmental cues, specifically water currents and magnetic fields. This protocol aims to understand whether proactive or reactive zebrafish display different rheotactic thresholds (i.e., the flow speed at which the fish start swimming upstream) when the surrounding magnetic field changes its direction. To identify zebrafish with the same personality, fish are introduced in the dark half of a tank connected with a narrow opening to a bright half. Only proactive fish explore the novel, bright environment. Reactive fish do not exit the dark half of the tank. A swimming tunnel with low flow rates is used to determine the rheotactic threshold. We describe two setups to control the magnetic field in the tunnel, in the range of the earth&#8217;s magnetic field intensity: one that controls the magnetic field along the flow direction (one dimension) and one that allows a three-axial control of the magnetic field. Fish are filmed while experiencing a stepwise increase of the flow speed in the tunnel under different magnetic fields. Data on the orientation behavior are collected through a video-tracking procedure and applied to a logistic model to allow the determination of the rheotactic threshold. We report representative results collected from shoaling zebrafish. Specifically, these demonstrate that only reactive, prudent fish show variations of the rheotactic threshold when the magnetic field varies in its direction, while proactive fish do not respond to magnetic field changes. This methodology can be applied to the study of magnetic sensitivity and rheotactic behavior of many aquatic species, both displaying solitary or shoaling swimming strategies.

We describe a behavioral protocol designed to assess how zebrafish&#8217;s personalities influence their response to water currents and weak magnetic fields. Fishes with the same personalities are separated based on their explorative behavior. Then, their rheotactic orientation behavior in a swimming tunnel with a low flow rate and under different magnetic conditions is observed.

To orient themselves in their environment, animals integrate a wide array of external cues, which interact with several internal factors, such as ...

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Collision warning system plays a key role in the prevention of driving distractions and drowsy driving. Previous studies have proven the advantages of tactile warnings in reducing driver&#8217;s brake response time. At the same time, tactile warnings have been proved effective in take-over request (TOR) for partially autonomous vehicles.
How the performance of tactile warnings can be optimized is an ongoing hot research topic in this field. Thus, the presented low-cost driving simulation software and methods are introduced to attract more researchers to take part in the investigation. The presented protocol has been divided into five sections: 1) participants, 2) driving simulation software configuration, 3) driving simulator preparation, 4) vibrating toolkit configuration and preparation, and 5) conducting the experiment.
In the exemplar study, participants wore the tactile vibrating toolkit and performed an established car-following task using the customized driving simulation software. The front vehicle braked intermittently, and vibrating warnings were delivered whenever the front vehicle was braking. Participants were instructed to respond as quickly as possible to the sudden brakes of the front vehicle. Driving dynamics, such as the brake response time and brake response rate, were recorded by the simulation software for data analysis.
The presented protocol offers insight into the exploration of the effectiveness of tactile warnings on different body locations. In addition to the car-following task that is demonstrated in the exemplar experiment, this protocol also provides options&#160;to apply other paradigms to the driving simulation studies by making simple software configuration without any code development. However, it is important to note that due to its affordable price, the driving simulation software and hardware introduced here may not be able to fully compete with other high-fidelity commercial driving simulators. Nevertheless, this protocol can act as an affordable and user-friendly alternative to the general high-fidelity commercial driving simulators.

This protocol describes a driving simulation platform and a tactile vibrating toolkit for the investigation of driving-related research. An exemplar experiment exploring the effectiveness of tactile warnings is also presented.&#160;

Collision warning system plays a key role in the prevention of driving distractions and drowsy driving. Previous studies have proven the advantages of ...