Event Abstract Back to Event Neuroimaging evidence of demand—reservation balance change in the aging brain — An analysis of hemodynamic response function during motor execution Toshiharu Nakai1*, Epifanio Bagarinao1, Makoto Miyakoshi1, SH A. Chen2, Wen-Yih I. Tseng3 and Kayako Matsuo4 1 University of California, San Diego, Center for Research in Biological Systems, United States 2 Nangyang Technorogical University, School of Humanities and Social Sciences, Singapore 3 National Taiwan University College of Medicine, Center for Optoelectronic Biomedicine, Taiwan 4 National Taiwan University, Department of Psychology, Taiwan Purpose It was pointed out that the additional recruitment of brain areas in the elderly was consistent with the compensation hypothesis and characterized neuroplasticity at the systems level [1]. The difference in age-related changes of the BOLD signal (hemodynamic response function: HRF) among the visual areas suggested its physiological background of neuronal network adaptation in the elderly [2]. In this study, we investigated whether such age-related HRF change can be observed in the motor regulation network in order to further confirm the neuroimaging evidence of demand-reservation balance change. The sequential finger tapping task was employed, since it strongly demands activities of both primary and higher motor areas organizing the motor execution network. Method Twenty-two healthy normal young subjects ( < 50 years old, 11 males) and 22 healthy normal elderly subjects (60 - 75, 11 males) gave written informed consent to participate in this study. Two fMRI sessions were performed: 1) TAP: Sequential finger tapping task (2-3-4-5) at 1.5Hz paced by a prompting visual cue, 3 task blocks for each of the right and left sides interleaved with rest blocks, each 18 sec, 2) GRIP: gripping-opening movement of bilateral hands paced by visual presentation of the hand posture for each condition, 3 sec for each movement, 5 task and 6 rest blocks, each 18 sec. Functional data were obtained using a GRE-EPI sequence (TR = 2000 ms, TE = 24 ms, 39 axial slices, 3 mm thick, FOV = 19.2 cm) on a 3T MRI scanner. Functional images were processed using SPM5, and the center coordinates of the ROI (3x3x3 pixels) were determined (2nd level analysis, p<0.001). The BOLD signal was extracted using a Matlab module (BAX [3]). Results The total cluster size of the elderly subjects was significantly larger than that of the younger (GRIP-R, GRIP-L and TAP-L; p < 0.003, TAP-R; p < 0.015). Activation in the following areas was augmented in elderly subjects (p < 0.01). 1) TAP-R: right d/vPMA, SMA, BA3, SPL; 2) TAP-L: left anterior operticulum, SPL, BA4, right SMA, vPMA, BA46/10, CG/ACG, para-hippocampal gyrus; 3) GRIP: bilateral IFG, SMA, SPL (BA7), SOG (BA19), IOG/LOG (BA37). In both experiments, the disappearance of mid-dip (transient HRF amplitude decrease between initial and post-stimulus peaks) was observed at differential peaks in the elderly subjects. In M1, differential activation was not significant between the two age groups (p<0.01) and mid-dip was not observed on the contralateral M1, although the averaged % HRF change was reduced on the contralateral side and augmented on the ipsilateral side in the elderly subjects. These results were compatible with the previous observations in visual areas [2]. Conclusions The results suggested that brain activation was augmented to support the demand for cognitive processing of motor regulation rather than for motor execution itself. Age-related augmentation of brain activation in the higher motor areas, including the associated cortex, depended on the disappearance of mid-dip rather than the increase of % HRF. Mid-dip may represent the stand-by status of the higher motor areas during task performance, even if the demand was low in young subjects. Based on these observations, we hypothesize that the primary and higher motor areas always control a neuronal network unit with different degrees of activation, although the t-statistics for some may be under the threshold of detection using a standard HRF reference. It should also be noted that different HRF shapes between age groups or across brain areas might cause biases in statistical evaluation; for example, differential activation in ACG/CG may be underestimated because of the constant level of the initial-peak.