This protocol details basic tasks that can be used to detect different profiles of timing disorders, and also to uncover cases of beat deafness or poor sensory motor synchronization in the general population. First, ask the participants to carry out synchronization tasks using finger tapping to the beat of a simple and complex auditory stimuli. Then analyze the synchronization data using circular statistics and identify the cases of poor synchronization relative to a normative group or to a control group.
Next, submit the participant to rhythm perception tasks in which she or he is asked to detect deviations from the beat in sequences of synchronous tones or in musical excerpts, analyze the data from the rhythm perception tasks to assess whether the participant detected deviations from the beat and compare the performance to that of a normative group or of a control group to uncover cases of poor rhythm perception. Ultimately, results can identify and characterize individuals with timing disorders in the general population using synchronization and rhythm perception tasks. This method can help answer key questions in the field of cognitive neurosciences or rhythm, such as which mechanisms are responsible for perceiving the beat or moving to the beat, like in dance.
Demonstrating this procedure will be my PhD student Valenti. Connect the standard MIDI percussion instrument to the computer via a conventional MIDI interface from the software interface. Select the pacing stimulus for the synchronization task and choose the appropriate tempo that is 400 5600 or 750 milliseconds between the tones or between the beats of the complex stimulus.
Then ensure that the stimuli are delivered at a comfortable volume level over the headphones. Ask a participant to tap on the MIDI percussion instrument using the index finger of her or his dominant hand, and in synchrony with the tones of the asynchronous sequence or with the musical beats for more complex stimuli. Also instruct the participant to tap as regularly as possible without changing the tapping rate while synchronizing with the pacing stimulus.
Now start the stimulus presentation and the recording of taps after presenting the last tone or musical beat. End the recording of taps for each tapping trial. Represent the taps as angles in the unitary circle relative to the time of the tones or of the beats.
The angles are used to compute the mean resultant vector. Run the ccue function to compute the synchronization accuracy. Namely the angle of the vector are which measures on average, how far from the pacing stimulus the participant taps as the argument for the function.
Provide the angles of vector R in radiance. Then use the circ R test function to test whether the distribution of the dots around the circle is random. Enter the angles in radiance as the argument for the function.
Next, run the Cirque R function to compute the synchronization consistency, namely the length of the vector R as the variability in the discrepancy between the time of the taps and the pacing stimuli. Again, provide the angles in radiance as the argument for the function to uncover cases of poor synchronization accuracy, or poor consistency. Run a corrected T-test implemented in the Inglis computer program using individual data.
Enter the mean and standard deviation of the synchronization accuracy and the sample size of the normative or control group. Provide the synchronization accuracy for the participant to be compared to the normative or control group. Click on the compute button to obtain the results of the corrected T-test.
Note whether the participant performed significantly poorer than the normative or control group. Enter the mean and standard deviation of the synchronization consistency and the sample size of the normative or control group. Also provide the synchronization consistency for the participant who is to be compared to the normative or control group.
First, select the stimulus and choose the appropriate tempo. Then ensure that the stimuli are delivered over the headphones at a comfortable volume level. Instruct the participant to listen to the stimulus and then judge after its presentation whether a change in the interval between the stimuli or beats is present.
Encourage the participant to pay attention to the entire sequence. Now, start the stimulus presentation. Ask the participant to respond by pressing one of two keys on the computer keyboard.
After the presentation of the stimulus, count the of responses when the change present in the stimulus has been correctly detected. Compute the hit rates. Count the number of responses when the participant reported to change in the interval between stimuli or beats when there was no change.
Compute the false alarm rate. Calculate the Z-score for the hits rate and the FA rate, and then calculate the difference DPR to evaluate individual results. Compare the performance of a participant to a normative or control group and identify cases of poor rhythm perception.
Enter the mean and standard deviation of D Prime and the sample size of the normative or control group. Also provide the DPR value for the participant who is to be compared to the normative or control group. In a recent representative study on beat deafness, a group of 10 non-musicians defined poor synchronizers showed particularly poor synchronization with the beat of music or of a metronome.
These data showed that poor synchronizers did not differ from a group of 23 control participants. In terms of accuracy, all participants anticipated the pacing stimuli when tapping along with an asynchronous sequence, a phenomenon which is referred to as mean negative asynchrony. In contrast, poor synchronizers were significantly less consistent than controls across all stimuli and ioi.
Ibis synchronization consistency is very sensitive to synchronization deficits and thereby represents an ideal measure for uncovering and characterizing individual differences is interestingly in the rhythm perception tasks. Both poor synchronizers and controls were similarly affected by the amount of change in the auditory sequence in both I synchronous stimuli and music. Poor synchronizers did not perform worse than controls.
The analysis of individual differences in beat deafness or poor synchronization reveals various profiles as can be seen. Poor synchronization may or may not be accompanied by poor rhythm perception. After watching this video, you should have a good understanding of how to measure sensor motor synchronization via tapping tasks and rhythm perception via anine detection tasks as a way to uncover rhythm perception and synchronization disorders, and to identify individual differences in a given population.
