Knowledge about the hemodynamic model that mediates synaptic activity and measured magnetic resonance signal is essential in understanding brain activation. Neural effi cacy is a hemodynamic parameter that would change the evoked hemodynamic responses. In this work, brain activation and neural effi cacy of the activated brain areas during simple addition task in two different backgrounds were studied using fMRI. The objectives were to determine the activated areas during the performance of arithmetic addition in quiet (AIQ) and noisy (AIN) background and to investigate the relationship between neural effi cacy and height extent of activation for the respective areas. Eighteen healthy male participants performed simple arithmetic addition in quiet and in noise. Bilateral cerebellum, superior temporal gyrus (STG), temporal pole (TP) and supplementary motor area (SMA) were signifi cantly (p < 0.05) activated during AIQ and AIN. Left middle frontal gyrus (L-MFG), right superior frontal gyrus (R-SFG), right superior orbital gyrus (R-SOG) and bilateral insula were more active in quiet as compared to in noise while the left middle cingulate cortex (L-MCC), left amygdala (L-AMG), right temporal pole (R-TP) and left cerebellum (L-CER) were more active in noise as compared to in quiet. The t value for most of the activated regions was found to be inversely proportional to the neural effi cacy. Signifi cant (p < 0.05) negative relationship between t value and neural effi cacy were found for R-STG and bilateral cerebellum during AIQ, while for AIN, similar relationships were found in R-CER, R-STG and R-TP. This study suggests that while being signifi cantly activated, the hemodynamic responses of these brain regions could have been suppressed by the stimulus resulting in an intensity decrease with increasing neural efficacy

Despite a vast number of studies that were focused on the roles of superior temporal gyrus (STG) and cerebellum as sensory area, little is known about their involvement in cognitive function such as attention and perception. The present fMRI study aimed to identify this cognitive role from brain activation profile of STG and cerebellum obtained from an arithmetic addition task. Eighteen healthy right hand dominance male adults participated in this study. They were instructed to solve single-digit addition tasks in quiet and noisy background during the fMRI scan. Both the in-quiet and in-noise addition tasks activated the bilateral STG and cerebellum (lobule VI and lobule VII) significantly but differentially. In both quiet and noisy conditions, STG activation is dominant in the left hemisphere while cerebellum showed a right hemisphere dominance. Bilateral STG and cerebellum (lobule VI) activation decreasedin noise, conversely cerebellum (lobule VII) activation increased in noise. These asymmetrical activation indicated hemispheric lateralization and differential behaviors of both brain areas in different environment while performing simple arithmetic addition task.
Cerebellum

Background: In spite of extensive research conducted to study how human brain works, little is known about a special function of the brain that stores and manipulates information—the working memory—and how noise influences this special ability. In this study, Functional magnetic resonance imaging (fMRI) was used to investigate brain responses to arithmetic problems solved in noisy and quiet backgrounds. Methods: Eighteen healthy young males performed simple arithmetic operations of addition and subtraction with in-quiet and in-noise backgrounds. The MATLAB-based Statistical Parametric Mapping (SPM8) was implemented on the fMRI datasets to generate and analyse the activated brain regions. Results: Group results showed that addition and subtraction operations evoked extended activation in the left inferior parietal lobe, left precentral gyrus, left superior parietal lobe, left supramarginal gyrus, and left middle temporal gyrus. This supported the hypothesis that the human brain relatively activates its left hemisphere more compared with the right hemisphere when solving arithmetic problems. The insula, middle cingulate cortex, and middle frontal gyrus, however, showed more extended right hemispheric activation, potentially due to the involvement of attention, executive processes, and working memory. For addition operations, there was extensive left hemispheric activation in the superior temporal gyrus, inferior frontal gyrus, and thalamus. In contrast, subtraction tasks evoked a greater activation of similar brain structures in the right hemisphere. For both addition and subtraction operations, the total number of activated voxels was higher for in-noise than in-quiet conditions. Conclusion: These findings suggest that when arithmetic operations were delivered auditorily, the auditory, attention, and working memory functions were required to accomplish the executive processing of the mathematical calculation. The respective brain activation patterns appear to be modulated by the noisy background condition.

This study investigated the functional specialisation characteristics of brain in multiple right-hand dominant subjects pertaining to the activation of the cerebral motor cortices evoked by unilateral finger tapping, especially in primary motor (M1) and supplementary motor (SMA) areas. This multiple-subject study used unilateral (UNIright and UNIleft) selfpaced tapping of hand fingers to activate the M1 and SMA. Brain activation characteristics were analysed using statistical parametric mapping (SPM). Activation for UNIright and UNIleft showed the involvement of contralateral and ipsilateral M1 and SMA. A larger activation area but with a lower percentage of signal change (PSC) were observed in the left M1 due to the control on UNIright (4164 voxels at α = 0.001, PSC = 1.650) as compared to the right M1 due to the control on UNIleft (2012 voxels at α = 0.001, PSC = 2.377). This is due to the influence of the tapping rate effects which is greater than what could be produced by the average effects of the dominant and sub-dominant hands. The significantly higher PSC value observed in the right M1 (p < 0.05) is due to a higher control demand used by the brain in coordinating the tapping of the sub-dominant fingers. The findings obtained from this study showed strong evidence of the existence of brain functional specialisation and could be used as baseline references in determining the most probable motor pathways in a sample of subjects.

Introduction: This multiple-subject fMRI study continue to further investigate brain activation within and effective connectivity between the significantly (p<0.001) activated primary motor area (M1), supplementary motor area (SMA) with the inclusion of BA44 during unimanual (UNIright and UNIleft) and bimanual (BIM) self-paced tapping of hand fingers. Methods: The activation extent (spatial and height) and effective connectivity were analysed using statistical parametric mapping (SPM), dynamic causal modeling (DCM) and the novel method of Bayesian model selection (BMS) for group studies. Results: Group results for UNIright and UNIleft showed contra-lateral and ipsi-lateral involvement of M1 and SMA. The results for BIM showed bilateral activation in M1, SMA and BA44. A larger activation area but with lower percentage of signal change (PSC) are observed in the left M1 due to the control on UNIright as compared to the right M1 due to the control on UNIleft. This is discussed as due to the influence of the tapping rate effects that is greater than what would be produced by the average effects of the dominant and sub-dominant hand. However, the higher PSC observed in the right M1 is due to a higher control demand used by the brain in coordinating the tapping of the sub-dominant hand fingers. Connectivity analysis indicated M1 as the intrinsic input for UNIright and UNIleft while for BIM, the inputs were both M1s. During unilateral finger tapping, the contra-lateral M1 acts as the input center which in turn triggers the propagation of signal unidirectionally to other regions of interest. The results obtained for BIM (BIMleft and BIMright) however yield a model with less number of significant connection. M1-M1 connection is unidirectional for UNIleft and UNIright originating from contra-lateral M1, and is inhibited during BIM. Conclusion: By taking into consideration the presence of outliers that could have arisen in any subject under study, BMS for group study has successfully chosen a model that has the best balance between accuracy (fit) and complexity.

Objective: This study investigates functional specialisation in, and effective connectivity between the precentral gyrus (PCG) and supplementary motor area (SMA) in seven right handed female subjects. Methods: Unimanual (UNIright and UNIleft) and bimanual (BIM) self-paced tapping of hand fingers were performed by the subjects to activate PCG and SMA. Brain activations and effective connectivity were analysed using statistical parametric mapping (SPM), dynamic causal modeling (DCM) and Bayesian model selection (BMS) and were reported based on group fixed (FFX) and random (RFX) effects analyses. Results: Group results showed that the observed brain activation for UNIright and UNIleft fulfill contralateral behavior of motor coordination with a larger activation area for UNIright. The activation for BIM occurs in both hemispheres with BIMright showing higher extent of activation as compared to BIMleft. Region of interest (ROI) analyses reveal that the number of activated voxel (NOV) and percentage of signal change (PSC) on average is higher in PCG than SMA for all tapping conditions. However, comparing between hemispheres for both UNI and BIM, higher PSC is observed in the right PCG and the left SMA. DCM and BMS results indicate that most subjects prefer PCG as the intrinsic input for UNIright and UNIleft. The input was later found to be bi-directionally connected to SMA for UNIright.The bi-directional model was then used for BIM in the left and right hemispheres. The model was in favour of six out of seven subjects. DCM results for BIM indicate the existance of interhemispheric connectivity between the right and left hemisphere PCG. Conclusion: The findings strongly support the existence of functional specialisation and integration i.e. effective connectivity in human brain during finger tapping and can be used as baselines in determining the probable motor coordination pathways and their connection strength in a population of subjects

Introduction: Binaural beats (BB) provisions alpha and gamma have been suggested to modulate working memory (WM), while white noise (WN) acted as a control condition. Methods: The current study overlays WN on alpha and gamma tones to study its modulating role on WM performance. A block-design n-back task paradigm used to determine the effect of load on embedded BB on WM performance using functional magnetic resonance imaging. Results: Six young adults (3 males and 3 females) with mean age of 23.5 ± 0.84 within the Kota Bharu vicinity participated in the study. A repeated-measures ANOVA (p<0.05) on response accuracy indicate medium effect size on condition (η2 =0.420), and large effect sizes on groups (η2 = 0.388) and load (η2 = 0.487). The potential practical difference is more evident on low- (0-back) and high-load (3-back). GWN provision marginally excels, implying its entrainment may benefit WM processing. A repeated-measures ANOVA (p<0.05) on reaction time (RT) implied a large effect size on all variables (condition: η2 =0.065, groups: η2 =0.227 and load: η2 =0.169). It was observed that BB exposure elicits a slow processing speed which worsens RT. The neural correlates suggest activated regions in GWN and AWN are associated with attentional mechanisms and WM processes. Conclusion: Preliminary findings indicate both embedded BB has a potential to improve WM performance with the cost of slower processing speed. GWN provision modulates attentional mechanisms benefiting WM performance and AWN may enhance performance in extreme ends of WM load.