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The ability to symbolise numbers using numerals is unique to humans and the acquisition of this ability needs to be done via learning [1]. Repeated exposure to sensory input can result in learning-induced alterations to the brain, forming memory engrams that are crucial for memory storage and retrieval [2]. Familiarity is an important factor that affects memory performance because familiar stimuli tend to have stronger memory strength with pre-existing knowledge representation stored in long-term memory, while unfamiliar or novel stimuli do not [1,3]. Past studies have suggested a few putative Number Form Area (NFA), located in the ventral occipitotemporal gyrus, are involved in processing visual number symbols [4 – 6]. It has been put forward that the acquisition of the semantic information of the numerical symbols might be a prerequisite for the activation of the NFA. However, much of its semantic information remains unknown. Figure 1 presented the conceptual framework of the present study. The present study aims to explore the brain activation associated with familiar and unfamiliar numerals of single-digit and double-digit. The targeted population of the present study will be Malaysian young adults between the age ranges of 18 to 30 years old. The present study will employ a quantitative cross-sectional observational research design. In particular, a within-subjects experimental study design with two factors: type of familiarity (familiar vs. unfamiliar) and the number of digits (single-digit vs. double-digit), will be used to measure the dependent variables including reaction time, accuracy, and brain activations of each participant in all experimental conditions: (1) familiar single-digit, (2) familiar double-digit, (3) unfamiliar single-digit, and (4) unfamiliar double-digit. An fMRI block design paradigm will be utilised, where the participants will be presented with single-digit and double-digit familiar (Chinese) numerals and unfamiliar (Arabic) numerals during the learning (encoding) phase and will be asked to complete the forced-choice memory task during the memory (retrieval) phase. In the experiment, participants’ structural and functional brain images will be collected using 3-Tesla Achieva MRI Scanner (Achieva, Philips, the Netherlands). Behavioural measurements such as reaction time and accuracy of the answer will be recorded based on the responses given by the participants during the fMRI task. Two-way repeated-measures ANOVA tests will be performed to compare the mean difference in reaction time, accuracy, and brain activation between the conditions. The brain activation will undergo pre- and post-processing using Matlab MATLAB software, Statistical Parametric Mapping 12, CONN toolbox and MarsBar toolbox. A significantly shorter reaction time and higher accuracy are expected to be observed in familiar as compared to unfamiliar conditions because familiar stimuli are being encountered relatively often in different contexts, which are likely to have broader retrieval contexts and stable mental representation stored in the long-term memory. Besides, it is predicted that brain areas such as the thalamus and the NFA will be highly engaged during the familiar conditions because thalamic nuclei have been reported to underpin familiarity memory [3] and the NFA has been put forward to hold a role in processing meaningful visual numerical symbols [4]. As for unfamiliar condition, the hippocampus and prefrontal cortex (PFC) is predicted to be highly engaged because unfamiliar numerals do not have pre-existing representation stored in the memory, thus it may trigger an active memory encoding process during the learning phase. The retrieval of memory of unfamiliar stimuli at a more recent time point after learning is thought to heavily rely on the hippocampus subregions and the PFC that are highly engaged during the memory encoding process. In conclusion, significantly better memory performances will be observed with familiar numerals as compared to unfamiliar numeral conditions. Differential neuronal activations will be observed between familiar and unfamiliar numeral conditions.

Background: Gaming can be very entertaining and through it, gamers are able to develop skills. However, it also may result in one’s getting too obsessed with video games regardless of any circumstances. Unnoticed, it may develop an Internet gaming disorder (IGD). This study aimed to investigate the neural activation involved in cognitive flexibility using fMRI that being triggered by the Stroop color task among Malaysian youngsters and its correlation with designated psychological disorders. Methods: A total of 37 participants (IGD = 19, Control = 18) were recruited to partake in this study. The division of participants according to the cut-off point of IAT and IGDS9-SF. Data were analyzed using MATLAB 8.5 (R2015a) and Statistical Parametric Mapping 12 (SPM 12) to evaluate brain activation. Results: This study found that IGD groups experience hyperactivation in the occipital and parietal lobes especially in the inferior occipital gyrus IOG and inferior parietal gyrus (IPG) but a hypoactivation on the frontal lobe. There a significant mean difference for the right IOG and left supplementary motor area (SMA) between the IGD and control groups at p

Learning and memory are closely related in a way that the ability to learn new information is done through working memory and the retrieval of the learned information is done through long-term memory [1]. Over the years, a keen interest in investigating the functional network and interaction in the brain regions during processing number magnitudes has increased among cognitive neuroscientists [2]. The majority of studies related to brain connectivity, especially on numeral cognition focus on children as these investigations could provide insight into neurodevelopmental performance [3]. In the current study, we aim to explore brain connectivity associated with familiar and unfamiliar numerals of single-digit and double-digit among young adults. Figure 1 demonstrates the conceptual framework of the current study. This is a quantitative experimental design study that uses a combination of cognitive performance assessment and task-based fMRI block design to measure brain connectivity during learning and retrieval of the acquired information. Fifteen healthy young Malaysian adults in the age range of 18-30 years old who meet the inclusion criteria will be recruited via convenience sampling. Participants will be in one group performing two categories of tasks namely familiar (Chinese) and unfamiliar (Arabic) with two conditions each (single-digit and double-digit). A 3-Tesla MRI Philips Achieva (Philips Medical Systems, Best, Netherlands) scanner with a 32-channel SENSE head coil will be used for data acquisition. Descriptive statistics will be used to summarise the socio-demographic characteristics of subjects. The mean difference in reaction time and accuracy of answers for single and double-digit in familiar and unfamiliar numerals will be analysed using two-way repeated-measures ANOVA and reported. The pre-processing of the fMRI images will be carried out using MATLAB software, Statistical Parametric Mapping 12, and CONN toolbox. The identification and comparison of the brain's functional connectivity will be done using the GIFT toolbox and Statistical Parametric Mapping 12. Results will be reported in the form of figures and tables. Both familiar and unfamiliar numerals are expected to activate the fronto-parietal-occipital networks by extracting the network from the cognitive-control domain, sub-cortical domain, and visual domain but with different connectivity values. Unfamiliar numerals are anticipated to have higher connectivity values than familiar numerals. Similar findings are expected to double and single digits, whereby higher connectivity values in double digits than in the single digits. The limited studies on functional connectivity show the main regions involved in mathematic processing are the inferior frontal gyrus (IPG), intraparietal sulcus (IPS), and inferior temporal gyrus (ITG) [4]. The outcome of this study would be beneficial as it could provide baseline data to investigate abnormalities of brain connectivity in learning and memory-related to numerical cognition among the young adult population.

This systematic review examines the empirical evidence from previous fMRI studies on brain activation areas for learning and memory patterns for numerals to understand the question of the brain activation areas found from previous fMRI studies on learning and memory patterns for numerals. Relevant articles in the fields of psychology, neuroscience, paediatrics, and education were extracted from the PubMed database. Keyword searches included "learning", "memory", "brain", "digits", "numerals", and "fMRI". The database search was conducted from July 2022 to August 2022. The data collected was limited to English texts, and studies involving animal experiments were excluded. The remaining articles were screened based on the inclusion and exclusion criteria. Articles included in this review were selected from the database search between 1999 to 2022. Ten full-text articles were identified and evaluated. Examination of brain activation regions in learning and memory patterns for numerals revealed that 30% of studies (n=3) found activation in the hippocampus, inferior parietal lobe and parietal lobe. Subsequently, 20% of the studies (n=2) found activation in the anterior cingulate, caudate nucleus, cerebellum, frontal lobe, inferior frontal gyrus, inferior temporal gyrus, medial temporal lobe, occipital lobe, prefrontal cortex, striatum, and thalamus. The frontoparietal network is considered important for working memory, while the limbic areas are essential for learning and memory. Therefore, future studies should look more closely at the brain's functional and structural regions involved in learning and a more specific memory system.

INTRODUCTION: Temporal lobe epilepsy (TLE) is a chronic disorder of the nervous system with focal seizures that may spread to other brain regions. Present knowledge regarding the spread of seizure is scarce. This study investigated activity in brain regions outside temporal lobe of TLE patient (TLEP) that may be affected by the spread. The findings were compared with healthy subject (HS). MATERIALS AND METHODS: Resting-state functional MRI (rsfMRI) were performed on 14 TLEPs and 14 HSs. Spatial activation, laterality index (LI) and functional connectivity (FC) involving several brain regions were analysed. RESULT: Bilateral precuneus (PRE) and supramarginal gyrus (SMG) which were activated (puncorr.0.001). SMG was found to be moderately right-lateralised in both TLEP and HS with LI = -0.309 and -0.125, respectively. For PRE, HS showed moderate left lateralisation (LI = 0.121), while TLEP showed weak right lateralisation (LI= -0.002). FC results revealed that the activity in PRE and SMG changed over time for HS and TLEP but only in the left hemisphere. CONCLUSION: Although resting-state activations in the two selected brain areas outside the temporal lobe in both hemispheres were incomparable between TLEP and HS, evidences from LI and FC analyses suggested anomalies especially in the left hemisphere that could be due to the spread of seizure.

Working memory (WM) encompasses crucial cognitive processes or abilities to retain and manipulate temporary information for immediate execution of complex cognitive tasks in daily functioning such as reasoning and decision-making. The WM of individuals sustaining traumatic brain injury (TBI) was commonly compromised, especially in the domain of WM. The current study investigated the brain responses of WM in a group of participants with mild-moderate TBI compared to their healthy counterparts employing functional magnetic resonance imaging. All consented participants (healthy: n = 26 and TBI: n = 15) performed two variations of the n-back WM task with four load conditions (0-, 1-, 2-, and 3-back). The respective within-group effects showed a right hemisphere-dominance activation and slower reaction in performance for the TBI group. Random-effects analysis revealed activation difference between the two groups in the right occipital lobe in the guided n-back with cues, and in the bilateral occipital lobe, superior parietal region, and cingulate cortices in the n-back without cues. The left middle frontal gyrus was implicated in the load-dependent processing of WM in both groups. Further group analysis identified that the notable activation changes in the frontal gyri and anterior cingulate cortex are according to low and high loads. Though relatively smaller in scale, this study was eminent as it clarified the neural alterations in WM in the mild-moderate TBI group compared to healthy controls. It confirmed the robustness of the phenomenon in TBI with the reproducibility of the results in a heterogeneous non-Western sample.

Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use fundus photography to monitor the progression of certain eye conditions or diseases. Segmentation of the vessel tree is an essential process of retinal analysis. In this paper, an interactive blood vessel segmentation from retinal fundus image based on Canny edge detection is proposed. Semi-automated segmentation of specific vessels can be done by simply moving the cursor across a particular vessel. The pre-processing stage includes the green color channel extraction, applying Contrast Limited Adaptive Histogram Equalization (CLAHE), and retinal outline removal. After that, the edge detection techniques, which are based on the Canny algorithm, will be applied. The vessels will be selected interactively on the developed graphical user interface (GUI). The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. This proposed approach is useful because different edge detection parameter settings can be applied to the same image to highlight particular vessels for analysis or presentation.

BACKGROUND The auditory and prefrontal cortex supports auditory working memory processing. Many neuroimaging studies have shown hemispheric lateralization of auditory working memory brain regions in the presence of background noise, but few studies have focused on the lateralization of these regions during stochastic resonance. PURPOSE To investigate the effects of stochastic resonance on lateralization of auditory working memory regions, and also to examine the brain-behavior relationship during stochastic resonance. STUDY TYPE Cross-sectional. POPULATION/SUBJECTS Forty healthy young adults (18-24 years old). FIELD STRENGTH/SEQUENCE 3.0T, T1 , and T2 *-weighted imaging. ASSESSMENT The auditory working memory performance was assessed using a backward recall task. Functional magnetic resonance imaging (fMRI) was used to measure brain activity during task performance. Functional MRI data were analyzed using SPM12 and WFU PickAtlas. STATISTICAL TESTS One-way independent analyses of variance (ANOVA) were conducted on the behavioral and functional data to examine the main effect of noise level on performance (P

The present study examined the impact of white noise on word recall performance and brain activity in 40 healthy adolescents, split in two groups (normal and low) depending on their auditory working memory capacity (AWMC). Using functional magnetic resonance imaging, participants performed a backward recall task under four different signal-to-noise ratio (SNR) conditions: 15, 10, 5, and 0-dB SNR. Behaviorally, normal AWMC individuals scored significantly higher than low AWMC individuals across noise levels. Whole-brain analyses showed brain activation not to be statistically different between groups across noise levels. In the normal group, a significant positive relationship was found between performance and number of activated voxels in the right superior frontal gyrus. In the low group, significant positive correlations were found between performance and number of activated voxels in left superior frontal gyrus, left inferior frontal gyrus, and left anterior cingulate cortex. These findings suggest that the strategic structure involved in the enhancement of AWM performance may differ in normal and low AWMC individuals.

Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical attention has been delayed. Commonly, analysis of computed tomography (CT) or magnetic resonance imaging (MRI) is required to determine the severity of a moderate TBI patient. However, due to the rising number of TBI patients these days, employing the CT scan or MRI scan to every potential patient is not only expensive, but also time consuming. Therefore, in this paper, we investigate the possibility of using electroencephalography (EEG) with computational intelligence as an alternative approach to detect the severity of moderate TBI patients. EEG procedure is much cheaper than CT or MRI. Although EEG does not have high spatial resolutions as compared with CT and MRI, it has high temporal resolutions. The analysis and prediction of moderate TBI from EEG using conventional computational intelligence approaches are tedious as they normally involve complex preprocessing, feature extraction, or feature selection of the signal. Thus, we propose an approach that uses convolutional neural network (CNN) to automatically classify healthy subjects and moderate TBI patients. The input to this computational intelligence system is the resting-state eye-closed EEG, without undergoing preprocessing and feature selection. The EEG dataset used includes 15 healthy volunteers and 15 moderate TBI patients, which is acquired at the Hospital Universiti Sains Malaysia, Kelantan, Malaysia. The performance of the proposed method has been compared with four other existing methods. With the average classification accuracy of 72.46%, the proposed method outperforms the other four methods. This result indicates that the proposed method has the potential to be used as a preliminary screening for moderate TBI, for selection of the patients for further diagnosis and treatment planning.

This study investigates (a) whether there is a functional neural activation at the frontal and temporal brain regions during the comprehension of Malay relative clause (RC), and (b) the differences in the activated areas among native (L1) and non-native (L2) Malay language speakers. The subject relative clause (SRC), object relative clause (ORC), and subject-verb-object (SVO) were used as the study stimuli. Participants were asked to do a sentence-picture matching task during an fMRI measurement. The random-effect analysis (RFX) using two-way ANOVA was conducted for the fMRI data. The main effect of the group at the puncorrected < 0.001, cluster size > 20 voxels found that the comprehension of Malay relative clauses had activated frontal and temporal brain regions in L1 and L2. The multiple comparisons of L1>L2 showed a significant difference left-lateralised in the temporo-parietal region. While for L2>L1, the significant activations were indicated as distributed to the frontal, temporal, parietal, and occipital regions that lateralised to the right hemisphere. Conclusions: The findings suggested that the comprehension of Malay relative clauses had caused the activation at different brain regions amongst L1 and L2 groups. It was also found that both L1 and L2 groups showed their preference in SRC, the mean reaction time showed that they had a faster reaction time to comprehend SRC than ORC. The findings from this study can also be applied in clinical language intervention, and it is expected to benefit children and adults with speech and language disorders.

Traumatic brain injury (TBI) is one of the traumas that requires immediate identification and treatment. Delayed in receiving medical attention can bring severe consequences. Conventional way of identifying TBI are from the computed tomography (CT) or magnetic resonance imaging (MRI). However, CT scan or MRI is hard to be performed to all patients as there were limited resources in the hospitals. As an early screening for TBI, EEG is a suitable substitution. Yet, it is time consuming for doctors or expert to perform EEG analysis manually for each patient. Therefore, this study suggests a machine learning method to identify moderate TBI patients. In this study, two type of features were analyzed. First is the raw EEG signal of alpha, beta, theta and gamma frequency bands. The second type of features are the power spectral density (PSD) of the respective frequency bands. The extracted features were used to train a support vector machine (SVM) separately to investigate the most informative frequency band features for identification of moderate TBI. From the result, it is found that alpha band features give the best identification accuracy which is at 87.5% for the raw features and 83.33 % for the PSD.

The effective connectivity can reveal the causal relationships between nodes of the Default Mode Network (DMN), which may reveal any impairment to the network following moderate traumatic brain injury (MTBI). Eight sub-acute MTBI patients and eight controls were recruited for this study. The results indicated that effective connectivity (EC) within MTBI group was higher in number and strength compared to the controls. Moreover, the network hubs within DMN are associated with increased connection strength in MTBI group. The ECs in MTBI are also largely influenced by top-down backward connections. In conclusion, the network reorganization within the DMN reflects the effect of MTBI and may subsequently impair other brain functions. This knowledge can be used to correctly identify the patient for appropriate trauma management.

The rapid development of Internet gaming technology in Malaysia has come with a cost of greater vulnerability in becoming addicted to video games especially for an adolescent whose mental abilities were not matured yet. This study aimed to investigate the differences in human neural activation using fMRI that being triggered by gaming video among Malaysian young adult. The 16 participants with Internet addiction were recruited. They undergo approximate 10 minutes of task-based fMRI scanning that will be presenting an ordered games-related and control short video simultaneously. Data were analyzed using MATLAB 9.3 (R2017b) and Statistical Parametric Mapping 12 (SPM 12) to evaluate brain activation. Based on the result, these the regions activated are known to be linked in visuospatial, somatosensory, semantic memory processing, emotional response, reward, integrating information process, memory retrieval, spatial navigation, and orientation. These findings may yield more in-depth in this study and provide a deeper understanding in developing appropriate guidelines and interventions to treat Internet gaming addicts community, especially in the Malaysian population.

This fMRI study investigated the effects of vibratory stimulation on somatosensory areas during high-frequencies stimulation using a piezoelectric finger stimulation system during an fMRI scan. Twelve healthy right-handed subjects were stimulated at 270 Hz-480 Hz and the fMRI dataset was analysed to generate the activated regions due to the high-frequencies stimulation. The activated regions were identified and thresholded at Puncorrected

Background Modifying brain activity using non-invasive, low intensity transcranial electrical brain stimulation (TES) has rapidly increased during the past 20 years. Alternating current stimulation (ACS), for example, has been shown to alter brain rhythm activities and modify neuronal functioning in the visual system. Daily application of transorbital ACS to patients with optic nerve damage induces functional connectivity reorganization, and partially restores vision. While ACS is thought to mainly modify neuronal mechanisms, e.g. changes in brain oscillations that can be detected by EEG, it is still an open question, whether and how it may alter BOLD activity. Objective We evaluated whether transorbital ACS modulates BOLD activity in early visual cortex using high-resolution 7 Tesla functional magnetic resonance imaging (fMRI). Methods In this feasibility study transorbital ACS in the alpha range and sham ACS was applied in a random block design in five healthy subjects for 20 min at 1 mA. Brain activation in the visual areas V1, V2 and V3 were measured using 7 Tesla fMRI-based retinotopic mapping at the time points before (baseline) and after stimulation. In addition, we collected data from one hemianopic stroke patient with visual cortex damage after ten daily sessions with 25–50 min stimulation duration. Results In healthy subjects transorbital ACS increased the activated cortical surface area, decreased the fMRI response amplitude and increased coherence in the visual cortex, which was most prominent in the full field task. In the patient, stimulation improved contrast sensitivity in the central visual field. BOLD amplitudes and coherence values were increased in most early visual areas in both hemispheres, with the most pronounced activation detected during eccentricity testing in retinotopic mapping. Conclusions This feasibility study showed that transorbital ACS modifies BOLD activity to visual stimulation, which outlasts the duration of the AC stimulation. This is in line with earlier neurophysiological findings of increased power in EEG recordings and functional connectivity reorganization in patients with impaired vision. Accordingly, the larger BOLD response area after stimulation can be explained by more coherent activation and lower variability in the activation. Alternatively, increased neuronal activity can also be taken into account. Controlled trials are needed to systematically evaluate the potential of repetitive transorbital ACS to improve visual function after visual pathway stroke and to determine the cause-effect relationship between neural and BOLD activity changes.

Vibratory (e.g., piezoelectric) devices can stimulate cortical responses from the somatosensory area during functional magnetic resonance imaging. Twelve healthy, right-handed subjects (7 males and 5 females) were scanned with a 3.0 T magnetic resonance imaging scanner and stimulated at 30-240 Hz using a piezoelectric vibrator attached to the subjects’ index fingers. The functional images were analysed to determine the brain activation region by performing random effects analyses at the group level. One-way analysis of variance was used to measure changes in frequency on brain activity. The activated regions were identified with WFU PickAtlas software, and the images were thresholded at Puncorrected < 0.001 for multiple comparisons. The average effect of frequency revealed significant activations in the right insula and right middle frontal gyrus; the corresponding region in the somatosensory area may act as a top-down control signal to improve sensory targets. Results revealed significant differences between frequencies; 90 Hz > 120 Hz activated right inferior parietal gyrus, 120 Hz > 150 Hz activated right cerebellum, and 60 Hz > 90 Hz activated right supramarginal gyrus and bilateral inferior frontal gyrus pars triangularis. Findings indicated the role of secondary somatosensory areas and the cerebellum in performing higher-order functions and discriminating various frequencies during vibratory stimulation. Increasing the patient sample size and testing higher frequencies in future experiments will contribute to furthering brain mapping of somatosensory areas.

The relationship between resting effective connectivity (EC) among default mode network (DMN) regions and auditory working memory (AWM) performance is still poorly understood. In this work, resting-state functional magnetic resonance imaging (rsfMRI) was used to determine the optimum connectivity model between posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC) in 40 healthy male volunteers. in low and normal working memory groups of subjects. Correlation between EC with AWM performance and AWM-capacity was also studied. The participants were divided into two groups which are normal and low AWM-capacity groups based on Malay Version Auditory Verbal Learning Test. The AWM performance was assessed using a word-based backward recall task. Both assessments were conducted outside the MRI scanner. The participants were scanned using a 3-T MRI system and the data were analyzed using statistical parametric mapping (SPM12) and spectral Dynamic Causal Modelling (spDCM). Results revealed that PCC and mPFC were significantly interconnected in both groups. Group analyses showed that the connection between PCC and mPFC exhibits an anti-correlated network. The results also indicated that the AWM performance and AWM-capacity were not associated with EC. These findings suggest that EC at rest between the two regions may not significantly influence cognitive abilities important for this AWM task.

Knowledge about the hemodynamic model that mediates synaptic activity and measured magnetic resonance signal is essential in understanding brain activation. Neural efficacy is a hemodynamic parameter that would change the evoked hemodynamic responses. In this work, brain activation and neural efficacy 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 efficacy 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 significantly (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 efficacy. Signifi cant (p < 0.05) negative relationship between t value and neural efficacy 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 significantly activated, the hemodynamic responses of these brain regions could have been suppressed by the stimulus resulting in an intensity decrease with increasing neural efficacy. DOI : http://dx.doi.org/10.17576/jskm-1201-2014-04

This study aimed to model the psychophysiological interaction (PPI) between the bilateral STG and cerebellum (lobule VI and lobule VII) during an arithmetic addition task. Eighteen young adults participated in this study. They were instructed to solve single-digit addition tasks in quiet and noisy backgrounds during an fMRI scan. Results showed that in both hemispheres, the response in the cerebellum was found to be linearly influenced by the activity in STG (vice-versa) for both in-quiet and in-noise conditions. However, the influence of the cerebellum on STG seemed to be modulated by noise. A two-way PPI model between STG and cerebellum is suggested. The connectivity between the two regions during a simple addition task in a noisy condition is modulated by the participants' higher attention to perceive.

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.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.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.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 fMRI study is about modeling the intrinsic connectivity between Heschl’ gyrus (HG) and superior temporal gyrus (STG) in human primary auditory cortices. Ten healthy male subjects participated and required to listen to white noise stimulus during the fMRI scans. Two intrinsic connectivity models comprising bilateral HG and STG were constructed using statistical parametric mapping (SPM) and dynamic causal modeling (DCM). Group Bayes factor (GBF), positive evidence ratio (PER) and Bayesian model selection (BMS) for group studies were used in model comparison. Group results indicated significant bilateral asymmetrical activation (puncorr

Functional magnetic resonance imaging (fMRI) was used to investigate brain responses due to arithmetic working memory. Nine healthy young male subjects were given simple addition and subtraction instructions in noise and in quiet. The general linear model (GLM) and random field theory (RFT) were implemented in modelling the activation. The results showed that addition and subtraction evoked bilateral activation in Heschl’s gyrus (HG), superior temporal gyrus (STG), inferior frontal gyrus (IFG), supramarginal gyrus (SG) and precentral gyrus (PCG). The HG, STG, SG and PCG activate higher number of voxels in noise as compared to in quiet for addition and subtraction except for IFG that showed otherwise. The percentage of signal change (PSC) in all areas is higher in quiet as compared to in noise. Surprisingly addition (not subtraction) exhibits stronger activation.

A supplementary food mix was prepared from roasted peanut, chickpea and sugar. The effect of this food mix on birth weight was tested on a group of rural women of low socioeconomic group in few villages in Peshawar District of NWFP. A 100 g supplementary food mix providing 16.7 g protein and 520 K. Cal of energy was given daily to a group of mothers in their third trimester, until the time of delivery. Another group of pregnant women acted as control. The results indicated a high maternal weight gain in the supplemented group. Moreover the birth weight, length, head and chest circumference of the new born in the supplemented group was also significantly higher as compared to control group.