Neural correlates of the complexity of rhythmic finger tapping

• Published in: NeuroImage (Orlando, Fla.) Vol. 20; no. 2; pp. 918 - 926
• Main Authors: Dhamala, Mukeshwar, Pagnoni, Giuseppe, Wiesenfeld, Kurt, Zink, Caroline F, Martin, Megan, Berns, Gregory S
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.10.2003; Elsevier Limited
• Subjects: Adult; Algorithms; Behavior; Brain; Brain - physiology; Brain Mapping; Female; Fingers - innervation; Fingers - physiology; Humans; Image Processing, Computer-Assisted; Linear Models; Magnetic Resonance Imaging; Male; Movement - physiology; Phase transitions; Ratios; Rhythm; Studies
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/S1053-8119(03)00304-5

Using functional magnetic resonance imaging (fMRI), we studied the neural correlates of the complexity of rhythmic finger tapping. Our experiments measured the brain activity of 13 subjects performing rhythmic tapping on a response box with multistable rhythms of 1 to 5 different interresponse intervals. From the button press response times, we constructed phase portraits where we identified the number of clusters of periodic points in a rhythm that corresponded to the number of different beats of the rhythm performed. We then constructed a statistical model for correlation analysis involving the following behavioral parameters: rate of tapping and number of beats in a rhythm. The tapping rate correlated with the brain activity in the ipsilateral pre/postcentral gyrus, and the number of beats (complexity) was correlated with activations in the primary motor cortex, supplementary motor area, basal ganglia, thalamus, and cerebellum. A region of interest (ROI) average analysis showed that the complexity of a rhythm had a differential correlation with the activity in these regions. The cerebellum and the thalamus showed increasing activity, and the basal ganglia showed decreasing activity with complexity of a rhythm. These results identify the areas involved in a rhythm generation and the modulation of brain activity with the complexity.