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  1. Mohd Nawi, N. S. A., Rahmad, A. A., Abdul Hamid, K., Rahman, S., Osman, S. S., Surat, S., et al.
    MyJurnal
    The connectivity patterns among the DMN nodes when the brain is resting are still in great debate. Among the unknowns is whether a dominant node exists in the network and if any, how does it influences the other nodes. Resting state functional magnetic resonance imaging (rsfMRI) was utilized in data acquisition on 25 healthy male and female participants. The DMN nodes selected were posterior cingulate cortex (PCC), bilateral inferior parietal cortex (IPL) and medial prefrontal cortex (mPFC). Fully connected causal models were constructed comprising four DMN nodes. The time invariant covariance of the random fluctuations between nodes was then estimated to obtain the effective connectivity (EC) between the DMN nodes. The EC values among the DMN nodes were averaged over the participants using Bayesian Parameter Averaging (BPA). All the DMN nodes have self-inhibitory dynamics. All connections between nodes were significant (P > 0.9) with a condition for any of the two nodes, one node inhibited the others. The PCC which exhibited the highest signal intensity was in fact inhibited by others. Inter-hemispheric RIPC to LIPC connections acted the same way, with excitatory LIPC to RIPC and inhibitory RIPC to LIPC connections. The results also showed a stronger mPFC to RIPC connection in the right hemisphere (as compared to mPFC to LIPC connection in the left hemisphere) and a weaker PCC to RIPC connection in the right hemisphere (as compared to PCC to LIPC connection in the left hemisphere). PCC can be regarded as a dominant node among the four nodes, being connected to all other nodes in different ways. All the four nodes were significantly activated and connected to each other even though the brain was in a state of resting.
    Matched MeSH terms: Parietal Lobe
  2. Saeed N, Khoo CS, Remli R, Law ZK, Periyasamy P, Osman SS, et al.
    Front Neurol, 2018;9:966.
    PMID: 30564184 DOI: 10.3389/fneur.2018.00966
    Leptospirosis is a spirochetal zoonotic disease with a wide clinical spectrum, often underdiagnosed especially when presented as an acute neurological manifestation. We report a case of a 24-year-old man with serologically positive leptospirosis, who presented with altered sensorium, seizures and subsequently developed cortical blindness. His brain MRI revealed bilateral occipital and later parietal lobe cerebritis.
    Matched MeSH terms: Parietal Lobe
  3. Mohamad, M., Yusoff, A.N., Mukari, S.Z.M., Abdullah, A., Abd Hamid, A.I.
    MyJurnal
    This study was carried out to investigate the effects of noisy background on brain activation during a working memory task. Fourteen healthy male subjects underwent silent functional Magnetic Resonance Imaging (fMRI) scans while listening to words presented verbally against quiet (WIS) and noisy (WIN) backgrounds. The stimuli were binaurally presented to the subjects at 70 dB sound pressure level (SPL) in both conditions. Group results indicated significant (p < 0.001) bilateral widespread of brain activations in the primary auditory cortex, superior temporal gyrus, inferior frontal gyrus, supramarginal gyrus and inferior parietal lobes during WIS. Additional significant activation was observed in the middle cingulate cortex and anterior cingulate cortex during WIN, suggesting the involvement of cingulate cortex in working memory processing against a noisy background. The mean percentage of signal change in all regions was higher during WIN as compared to WIS. Right hemispheric predominance was observed for both conditions in primary auditory cortex and middle frontal gyrus and this could be attributed to the increased difficulty of the tasks. The results obtained from this study demonstrated that background noise increased task demand and difficulty. Task demand was found to play an important role in determining the activation magnitude in the brain areas during working memory task.
    Matched MeSH terms: Parietal Lobe
  4. Jawed S, Amin HU, Malik AS, Faye I
    PMID: 31133829 DOI: 10.3389/fnbeh.2019.00086
    This study analyzes the learning styles of subjects based on their electroencephalo-graphy (EEG) signals. The goal is to identify how the EEG features of a visual learner differ from those of a non-visual learner. The idea is to measure the students' EEGs during the resting states (eyes open and eyes closed conditions) and when performing learning tasks. For this purpose, 34 healthy subjects are recruited. The subjects have no background knowledge of the animated learning content. The subjects are shown the animated learning content in a video format. The experiment consists of two sessions and each session comprises two parts: (1) Learning task: the subjects are shown the animated learning content for an 8-10 min duration. (2) Memory retrieval task The EEG signals are measured during the leaning task and memory retrieval task in two sessions. The retention time for the first session was 30 min, and 2 months for the second session. The analysis is performed for the EEG measured during the memory retrieval tasks. The study characterizes and differentiates the visual learners from the non-visual learners considering the extracted EEG features, such as the power spectral density (PSD), power spectral entropy (PSE), and discrete wavelet transform (DWT). The PSD and DWT features are analyzed. The EEG PSD and DWT features are computed for the recorded EEG in the alpha and gamma frequency bands over 128 scalp sites. The alpha and gamma frequency band for frontal, occipital, and parietal regions are analyzed as these regions are activated during learning. The extracted PSD and DWT features are then reduced to 8 and 15 optimum features using principal component analysis (PCA). The optimum features are then used as an input to the k-nearest neighbor (k-NN) classifier using the Mahalanobis distance metric, with 10-fold cross validation and support vector machine (SVM) classifier using linear kernel, with 10-fold cross validation. The classification results showed 97% and 94% accuracies rate for the first session and 96% and 93% accuracies for the second session in the alpha and gamma bands for the visual learners and non-visual learners, respectively, for k-NN classifier for PSD features and 68% and 100% accuracies rate for first session and 100% accuracies rate for second session for DWT features using k-NN classifier for the second session in the alpha and gamma band. For PSD features 97% and 96% accuracies rate for the first session, 100% and 95% accuracies rate for second session using SVM classifier and 79% and 82% accuracy for first session and 56% and 74% accuracy for second session for DWT features using SVM classifier. The results showed that the PSDs in the alpha and gamma bands represent distinct and stable EEG signatures for visual learners and non-visual learners during the retrieval of the learned contents.
    Matched MeSH terms: Parietal Lobe
  5. Chee Pin Chee
    Med J Malaysia, 1987 Dec;42(4):309-13.
    PMID: 3331410
    An unusual case of proximal migration of a Hakim's valve intracranially into a porencephalic cyst two years after insertion of the ventriculo-peritoneal shunt in a neonate is reported. The underlying cause is discussed. It is recommended that all shunt should be anchored with nonabsorbable suture material properly on to the pericranium.
    Matched MeSH terms: Parietal Lobe/radiography*
  6. Nasser NS, Sharifat H, Rashid AA, Hamid SA, Rahim EA, Loh JL, et al.
    Front Psychol, 2020;11:556060.
    PMID: 33224051 DOI: 10.3389/fpsyg.2020.556060
    Background: Problematic Instagram use (PIGU), a specific type of internet addiction, is prevalent among adolescents and young adults. In certain instances, Instagram acts as a platform for exhibiting photos of risk-taking behavior that the subjects with PIGU upload to gain likes as a surrogate for gaining peer acceptance and popularity.

    Aims: The primary objective was to evaluate whether addiction-specific cues compared with neutral cues, i.e., negative emotional valence cues vs. positive emotional valence cues, would elicit activation of the dopaminergic reward network (i.e., precuneus, nucleus accumbens, and amygdala) and consecutive deactivation of the executive control network [i.e., medial prefrontal cortex (mPFC) and dorsolateral prefrontal cortex (dlPFC)], in the PIGU subjects.

    Method: An fMRI cue-induced reactivity study was performed using negative emotional valence, positive emotional valence, and truly neutral cues, using Instagram themes. Thirty subjects were divided into PIGU and healthy control (HC) groups, based on a set of diagnostic criteria using behavioral tests, including the Modified Instagram Addiction Test (IGAT), to assess the severity of PIGU. In-scanner recordings of the subjects' responses to the images and regional activity of the neural addiction pathways were recorded.

    Results: Negative emotional valence > positive emotional valence cues elicited increased activations in the precuneus in the PIGU group. A negative and moderate correlation was observed between PSC at the right mPFC with the IGAT scores of the PIGU subjects when corrected for multiple comparisons [r = -0.777, (p < 0.004, two-tailed)].

    Conclusion: Addiction-specific Instagram-themed cues identify the neurobiological underpinnings of Instagram addiction. Activations of the dopaminergic reward system and deactivation of the executive control network indicate converging neuropathological pathways between Instagram addiction and other types of addictions.

    Matched MeSH terms: Parietal Lobe
  7. Nurul Azreen Hashim, Norley Shuib, Salina Mohamed, Ling SL, Khariah Mat Nor
    Delayed neuropsychiatric sequelae is an important condition which commonly occur during recovery from acute carbon monoxide poisoning. Typical presentation would be apathy, disorientation, amnesia, hypokinesia, bizarre behavior, insomnia and neurological manifestations such as gait disturbance, hypertonia and tremor. We report here a case of a man presented with delayed neuropsychiatric sequelae one month after the carbon monoxide poisoning in his suicidal attempt. He presented with the typical presentation and diagnosis confirmed with the MRI findings. His MRI showed abnormal signal in subcortical hemisphere white matter of both temporo-fronto-parietal-occipital regions along the insula and both globus pallidus. He was treated with Olanzapine, Fluvoxamine, Chlorpromazine and Levodopa and his condition slowly improved. It is important for clinicians to recognize the symptoms and risk factors to develop delayed neuropsychiatric sequelae in patients who previously had carbon monoxide poisoning.
    Matched MeSH terms: Parietal Lobe
  8. Tai MS, Sia SF, Kadir KAA, Idris MI, Tan KS
    Case Rep Neurol, 2020 12 14;12(Suppl 1):149-155.
    PMID: 33505287 DOI: 10.1159/000501069
    Background: Coughing due to respiratory tract infections may lead to internal carotid artery (ICA) dissection.

    Aim: We are presenting a patient with an unusual cough-induced ICA dissection.

    Case Report: A 42-year-old health care worker presented with bilateral hand numbness which resolved spontaneously. This initial episode was followed 9 days later with intermittent episodes of right hand and leg weakness with speech difficulty. Two days later, he had another episode of speech difficulty. One week prior to the first presentation, he had upper respiratory tract infection with ongoing strong bouts of coughing. Magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) of the brain showed early ischaemic changes at the left frontal and left parietal regions. MR angiography (MRA) showed high signal intensity at the left proximal ICA and poor flow beyond the left carotid bulb. Cerebral angiography revealed left ICA dissection.

    Conclusion: Proper identification of cough-induced extracranial ICA dissection is important because this is treatable.

    Matched MeSH terms: Parietal Lobe
  9. Chai WJ, Abd Hamid AI, Abdullah JM
    Front Psychol, 2018;9:401.
    PMID: 29636715 DOI: 10.3389/fpsyg.2018.00401
    Since the concept of working memory was introduced over 50 years ago, different schools of thought have offered different definitions for working memory based on the various cognitive domains that it encompasses. The general consensus regarding working memory supports the idea that working memory is extensively involved in goal-directed behaviors in which information must be retained and manipulated to ensure successful task execution. Before the emergence of other competing models, the concept of working memory was described by the multicomponent working memory model proposed by Baddeley and Hitch. In the present article, the authors provide an overview of several working memory-relevant studies in order to harmonize the findings of working memory from the neurosciences and psychological standpoints, especially after citing evidence from past studies of healthy, aging, diseased, and/or lesioned brains. In particular, the theoretical framework behind working memory, in which the related domains that are considered to play a part in different frameworks (such as memory's capacity limit and temporary storage) are presented and discussed. From the neuroscience perspective, it has been established that working memory activates the fronto-parietal brain regions, including the prefrontal, cingulate, and parietal cortices. Recent studies have subsequently implicated the roles of subcortical regions (such as the midbrain and cerebellum) in working memory. Aging also appears to have modulatory effects on working memory; age interactions with emotion, caffeine and hormones appear to affect working memory performances at the neurobiological level. Moreover, working memory deficits are apparent in older individuals, who are susceptible to cognitive deterioration. Another younger population with working memory impairment consists of those with mental, developmental, and/or neurological disorders such as major depressive disorder and others. A less coherent and organized neural pattern has been consistently reported in these disadvantaged groups. Working memory of patients with traumatic brain injury was similarly affected and shown to have unusual neural activity (hyper- or hypoactivation) as a general observation. Decoding the underlying neural mechanisms of working memory helps support the current theoretical understandings concerning working memory, and at the same time provides insights into rehabilitation programs that target working memory impairments from neurophysiological or psychological aspects.
    Matched MeSH terms: Parietal Lobe
  10. Mohd Nor NS, Fong CY, Rahmat K, Vanessa Lee WM, Zaini AA, Jalaludin MY
    Eur Endocrinol, 2018 Apr;14(1):59-61.
    PMID: 29922355 DOI: 10.17925/EE.2018.14.1.59
    Cerebral oedema is the most common neurological complication of diabetic ketoacidosis (DKA). However, ischaemic and haemorrhagic brain injury has been reported infrequently. A 10-year old girl who was previously well presented with severe DKA. She was tachycardic with poor peripheral perfusion but normotensive. However, two fast boluses totalling 40 ml/kg normal saline were given. She was transferred to another hospital where she was intubated due to drowsiness. Rehydration fluid (maintenance and 48-hour correction for 7.5% dehydration) was started followed by insulin infusion. She was extubated within 24 hours of admission. Her ketosis resolved soon after and subcutaneous insulin was started. However, about 48 hours after admission, her Glasgow Coma Scale score dropped to 11/15 (E4M5V2) with expressive aphasia and upper motor neuron signs. One dose of mannitol was given. Her symptoms improved gradually and at 26-month follow-up she had a near-complete recovery with only minimal left lower limb weakness. Serial magnetic resonance imaging brain scans showed vascular ischaemic injury at the frontal-parietal watershed regions with haemorrhagic transformation. This case reiterates the importance of monitoring the neurological status of patient's with DKA closely for possible neurological complications including an ischaemic and haemorrhagic stroke.
    Matched MeSH terms: Parietal Lobe
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