Displaying publications 1 - 20 of 27 in total

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  1. Poznanski RR, Cacha LA, Latif AZA, Salleh SH, Ali J, Yupapin P, et al.
    J Integr Neurosci, 2019 03 30;18(1):1-10.
    PMID: 31091842 DOI: 10.31083/j.jin.2019.01.105
    The physicality of subjectivity is explained through a theoretical conceptualization of guidance waves informing meaning in negentropically entangled non-electrolytic brain regions. Subjectivity manifests its influence at the microscopic scale of matter originating from de Broglie 'hidden' thermodynamics as action of guidance waves. The preconscious experienceability of subjectivity is associated with a nested hierarchy of microprocesses, which are actualized as a continuum of patterns of discrete atomic microfeels (or "qualia"). The mechanism is suggested to be through negentropic entanglement of hierarchical thermodynamic transfer of information as thermo-qubits originating from nonpolarized regions of actin-binding proteinaceous structures of nonsynaptic spines. The resultant continuous stream of intrinsic information entails a negentropic action (or experiential flow of thermo-quantum internal energy that results in a negentropic force) which is encoded through the non-zero real component of the mean approximation of the negentropic force as a 'consciousness code'. Consciousness consisting of two major subprocesses: (1) preconscious experienceability and (2) conscious experience. Both are encapsulated by nonreductive physicalism and panexperiential materialism. The subprocess (1) governing "subjectivity" carries many microprocesses leading to the actualization of discrete atomic microfeels by the 'consciousness code'. These atomic microfeels constitute internal energy that results in the transfer intrinsic information in terms of thermo-qubits. These thermo-qubits are realized as thermal entropy and sensed by subprocess (2) governing "self-awareness" in conscious experience.
  2. Goodman G, Poznanski RR, Cacha L, Bercovich D
    J Integr Neurosci, 2015 Sep;14(3):281-93.
    PMID: 26477360 DOI: 10.1142/S0219635215500235
    Great advances have been made in signaling information on brain activity in individuals, or passing between an individual and a computer or robot. These include recording of natural activity using implants under the scalp or by external means or the reverse feeding of such data into the brain. In one recent example, noninvasive transcranial magnetic stimulation (TMS) allowed feeding of digitalized information into the central nervous system (CNS). Thus, noninvasive electroencephalography (EEG) recordings of motor signals at the scalp, representing specific motor intention of hand moving in individual humans, were fed as repetitive transcranial magnetic stimulation (rTMS) at a maximum intensity of 2.0[Formula: see text]T through a circular magnetic coil placed flush on each of the heads of subjects present at a different location. The TMS was said to induce an electric current influencing axons of the motor cortex causing the intended hand movement: the first example of the transfer of motor intention and its expression, between the brains of two remote humans. However, to date the mechanisms involved, not least that relating to the participation of magnetic induction, remain unclear. In general, in animal biology, magnetic fields are usually the poor relation of neuronal current: generally "unseen" and if apparent, disregarded or just given a nod. Niels Bohr searched for a biological parallel to complementary phenomena of physics. Pertinently, the two-brains hypothesis (TBH) proposed recently that advanced animals, especially man, have two brains i.e., the animal CNS evolved as two fundamentally different though interdependent, complementary organs: one electro-ionic (tangible, known and accessible), and the other, electromagnetic (intangible and difficult to access) - a stable, structured and functional 3D compendium of variously induced interacting electro-magnetic (EM) fields. Research on the CNS in health and disease progresses including that on brain-brain, brain-computer and brain-robot engineering. As they grow even closer, these disciplines involve their own unique complexities, including direction by the laws of inductive physics. So the novel TBH hypothesis has wide fundamental implications, including those related to TMS. These require rethinking and renewed research engaging the fully complementary equivalence of mutual magnetic and electric field induction in the CNS and, within this context, a new mathematics of the brain to decipher higher cognitive operations not possible with current brain-brain and brain-machine interfaces. Bohr may now rest.
  3. Cacha LA, Ali J, Rizvi ZH, Yupapin PP, Poznanski RR
    J Integr Neurosci, 2017;16(4):493-509.
    PMID: 28891529 DOI: 10.3233/JIN-170038
    Using steady-state electrical properties of non-ohmic dendrite based on cable theory, we derive electrotonic potentials that do not change over time and are localized in space. We hypothesize that clusters of such stationary, local and permanent pulses are the electrical signatures of enduring memories which are imprinted through nonsynaptic plasticity, encoded through epigenetic mechanisms, and decoded through electrotonic processing. We further hypothesize how retrieval of an engram is made possible by integration of these permanently imprinted standing pulses in a neural circuit through neurotransmission in the extracellular space as part of conscious recall that acts as a guiding template in the reconsolidation of long-term memories through novelty characterized by uncertainty that arises when new fragments of memories reinstate an engram by way of nonsynaptic plasticity that permits its destabilization. Collectively, these findings seem to reinforce this hypothesis that electrotonic processing in non-ohmic dendrites yield insights into permanent electrical signatures that could reflect upon enduring memories as fragments of long-term memory engrams.
  4. Al-Marri F, Reza F, Begum T, Hitam WHW, Jin GK, Xiang J
    J Integr Neurosci, 2018 Aug 15;17(3):257-269.
    PMID: 30338955 DOI: 10.31083/JIN-170058
    Visual cognitive function is important in the construction of executive function in daily life. Perception of visual number form (e.g. Arabic digits) and numerosity (numeric magnitude) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of number representations are complex events when their semantic categories are assimilated together with concepts of shape and color. Color perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green color vision testing. However, there has been little study of visual cognitive function assessment using such pseudoisochromatic plates. 25 healthy normal trichromat volunteers were recruited and studied using a 128-sensor net to record event-related electroencephalogram. Subjects were asked to respond by pressing numbered buttons when they saw the number and non-number plates of the Ishihara color vision test. Amplitudes and latencies of N100 and P300 event related potential components were analyzed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns, and Granger causation (effective connectivity) were analyzed from 128 electrode sites. No significant differences between N100 event related potential components for either stimulus indicates early selective attention processing was similar for number and non-number plate stimuli, but non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 event related potential component with a slower reaction time compared to number plate stimuli imply the allocation of attentional load was more in non-number plate processing. A different pattern of the asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for number plate tasks and higher intensity in the right hemisphere for non-number plate tasks. Asymmetric cortical activation and connectivity patterns revealed that number recognition occurred in the occipital and left frontal areas where as the consequence was limited to the occipital area during the non-number plate processing. Finally, results demonstrated that the visual recognition of numbers dissociates from the recognition of non-numbers at the level of defined neural networks. Number recognition was not only a process of visual perception and attention, but was also related to a higher level of cognitive function, that of language.
  5. Al-Marri F, Reza F, Begum T, Hitam WHW, Jin GK, Xiang J
    J Integr Neurosci, 2017 Oct 25.
    PMID: 29081422 DOI: 10.3233/JIN-170058
    Visual cognitive function is important to build up executive function in daily life. Perception of visual Number form (e.g., Arabic digit) and numerosity (magnitude of the Number) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of Number representations are complex occurrences when their semantic categories are assimilated with other concepts of shape and colour. Colour perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green colour vision testing. However, there is a lack of study of visual cognitive function assessment using these pseudoisochromatic plates. We recruited 25 healthy normal trichromat volunteers and extended these studies using a 128-sensor net to record event-related EEG. Subjects were asked to respond by pressing Numbered buttons when they saw the Number and Non-number plates of the Ishihara colour vision test. Amplitudes and latencies of N100 and P300 event related potential (ERP) components were analysed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns and Granger causation (effective connectivity) were analysed from 128 electrode sites. No major significant differences between N100 ERP components in either stimulus indicate early selective attention processing was similar for Number and Non-number plate stimuli, but Non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 ERP component with a slower reaction time compared to Number plate stimuli imply the allocation of attentional load was more in Non-number plate processing. A different pattern of asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for Number plate tasks and higher intensity in the right hemisphere for Non-number plate tasks. Asymmetric cortical activation and connectivity patterns revealed that Number recognition occurred in the occipital and left frontal areas where as the consequence was limited to the occipital area during the Non-number plate processing. Finally, the results displayed that the visual recognition of Numbers dissociates from the recognition of Non-numbers at the level of defined neural networks. Number recognition was not only a process of visual perception and attention, but it was also related to a higher level of cognitive function, that of language.
  6. Poznanski RR
    J Integr Neurosci, 2009 Sep;8(3):345-69.
    PMID: 19938210
    The continuity of the mind is suggested to mean the continuous spatiotemporal dynamics arising from the electrochemical signature of the neocortex: (i) globally through volume transmission in the gray matter as fields of neural activity, and (ii) locally through extrasynaptic signaling between fine distal dendrites of cortical neurons. If the continuity of dynamical systems across spatiotemporal scales defines a stream of consciousness then intentional metarepresentations as templates of dynamic continuity allow qualia to be semantically mapped during neuroimaging of specific cognitive tasks. When interfaced with a computer, such model-based neuroimaging requiring new mathematics of the brain will begin to decipher higher cognitive operations not possible with existing brain-machine interfaces.
  7. Poznanski RR, Cacha LA
    J Integr Neurosci, 2012 Dec;11(4):417-37.
    PMID: 23351050 DOI: 10.1142/S0219635212500264
    Passive dendrites become active as a result of electrostatic interactions by dielectric polarization in proteins in a segment of a dendrite. The resultant nonlinear cable equation for a cylindrical volume representation of a dendritic segment is derived from Maxwell's equations under assumptions: (i) the electric field is restricted longitudinally along the cable length; (ii) extracellular isopotentiality; (iii) quasi-electrostatic conditions; (iv) isotropic membrane and homogeneous medium with constant conductivity; and (v) protein polarization contributes to intracellular capacitive effects through a well defined nonlinear capacity-voltage characteristic; (vi) intracellular resistance and capacitance in parallel are connected to the membrane in series. Under the above hypotheses, traveling wave solutions of the cable equation are obtained as propagating fronts of electrical excitation associated with capacitive charge-equalization and dispersion of continuous polarization charge densities in an Ohmic cable. The intracellular capacitative effects of polarized proteins in dendrites contribute to the conduction process.
  8. Begum T, Reza F, Ahmed I, Abdullah JM
    J Integr Neurosci, 2014 Mar;13(1):71-88.
    PMID: 24738540 DOI: 10.1142/S0219635214500058
    Simple geometric and organic shapes and their arrangement are being used in different neuropsychology tests for the assessment of cognitive function, special memory and also for the therapy purpose in different patient groups. Until now there is no electrophysiological evidence of cognitive function determination for simple geometric, organic shapes and their arrangement. Then the main objective of this study is to know the cortical processing and amplitude, latency of visual induced N170 and P300 event related potential components on different geometric, organic shapes and their arrangement and different educational influence on it, which is worthwhile to know for the early and better treatment for those patient groups. While education influenced on cognitive function by using auditory oddball task, little is known about the influence of education on cognitive function induced by visual attention task in case of the choice of geometric, organic shapes and their arrangements. Using a 128-electrode sensor net, we studied the responses of the choice of the different geometric and organic shapes randomly in experiment 1 and their arrangements in experiment 2 in the high, medium and low education groups. In both experiments, subjects push the button "1" or "2" if like or dislike, respectively. Total 45 healthy subjects (15 in each group) were recruited. ERPs were measured from 11 electrode sites and analyzed to see the evoked N170/N240 and P300 ERP components. There were no differences between like and dislike in amplitudes even in latencies in every stimulus in both experiments. We fixed geometric shapes and organic shapes stimuli only, not like and dislike. Upon the stimulus types, N170 ERP component was found instead of N240, in occipito-temporal (T5, T6, O1 and O2) locations where the amplitude is the highest at O2 location and P300 was distributed in the central (Cz and Pz) locations in both experiments in all groups. In experiment 1, significant low amplitude and non-significant larger latency of the N170 component are found out at O1 location for both stimuli in low education group comparing medium education groups, but in experiment 2, there is no significant difference between stimuli among groups in amplitude and latency. In both experiments, P300 component was found in Cz and Pz locations though the amplitudes are higher at Cz than Pz areas. In experiment 1, medium education group evoked significantly (geometric shape stimuli, P = 0.05; organic shape stimuli, P = 0.02) higher amplitude of P300 component comparing low education group at Cz location. Whereas, there is no significant difference of amplitudes among groups across stimuli in Cz and Pz locations in experiment 2. Latencies have no significant differences in both experiments among groups also, but longer latency are found in low education group at Cz location comparing medium education group, though not significant. We conclude that simple geometric shapes, organic shapes and their arrangements evoked visual N170 component at temporo-occipital areas with right lateralization and P300 ERP component at centro-parietal areas. Significant low amplitude of N170 and P300 ERP components and longer latencies during different shape stimuli in low education group prove that, low education significantly influence on visual cognitive functions in low education group.
  9. Razali K, Mohamed WMY
    J Integr Neurosci, 2023 Jul 04;22(4):87.
    PMID: 37519176 DOI: 10.31083/j.jin2204087
    BACKGROUND: Parkinson's disease (PD), the most prevalent motoric neurodegenerative disease, has been intensively studied to better comprehend its complicated pathogenesis. Chronic neuroinflammation is a major factor contributing to the development of PD. Reportedly, high-mobility group box 1 (HMGB1) protein is capable of mediating neuroinflammatory response. In this regard, knowledge mapping of the research linking HMGB1 to PD is necessary.

    OBJECTIVE: Herein, we perform a dynamic and longitudinal bibliometric analysis to explore the hotspots and current trends of HMGB1-related PD publications during the past decade.

    METHODS: All PD publications focusing on HMGB1 protein were retrieved from the PubMed database using the search terms "Parkinson's disease" and "hmgb1". Using filters, only English articles published between 2011 and 2022 were selected. The Bibliometrix and Biblioshiny packages from R software were used to conduct the bibliometric analysis.

    RESULTS: The filtered search identified 47 articles (34 original articles and 13 review articles), published between 2011 and 2022. There was an increase trend in the number of articles published, with an annual growth rate of 19.35 percent. In terms of research and scientific collaboration in this field, the United States is in the lead, followed by China, Malaysia, and Australia. Compared to other countries, the United States and China had the highest level of collaboration in this research area. Neuroinflammation, microglia, and receptor for advanced glycation end-products (RAGE) represent the top three frontiers and hotspots for HMGB1-related PD research. According to the thematic evolution analysis, over the last decade, PD, HMGB1 and microglia were addressed individually, however, since 2017, these topics were frequently discussed within the same cluster: neuroinflammation. Furthermore, PD, HMGB1, and neuroinflammation domains co-occurred in majority of the research discussion.

    CONCLUSIONS: The link between HMGB1 and PD was realized a decade ago and becomes increasingly important over time. Our findings can aid scholars in comprehending the global context of HMGB1/PD relationship and provide significant insights for future PD research.

  10. Cacha LA, Poznanski RR
    J Integr Neurosci, 2014 Jun;13(2):253-92.
    PMID: 25012712 DOI: 10.1142/S0219635214400081
    A theoretical framework is developed based on the premise that brains evolved into sufficiently complex adaptive systems capable of instantiating genomic consciousness through self-awareness and complex interactions that recognize qualitatively the controlling factors of biological processes. Furthermore, our hypothesis assumes that the collective interactions in neurons yield macroergic effects, which can produce sufficiently strong electric energy fields for electronic excitations to take place on the surface of endogenous structures via alpha-helical integral proteins as electro-solitons. Specifically the process of radiative relaxation of the electro-solitons allows for the transfer of energy via interactions with deoxyribonucleic acid (DNA) molecules to induce conformational changes in DNA molecules producing an ultra weak non-thermal spontaneous emission of coherent biophotons through a quantum effect. The instantiation of coherent biophotons confined in spaces of DNA molecules guides the biophoton field to be instantaneously conducted along the axonal and neuronal arbors and in-between neurons and throughout the cerebral cortex (cortico-thalamic system) and subcortical areas (e.g., midbrain and hindbrain). Thus providing an informational character of the electric coherence of the brain - referred to as quantum coherence. The biophoton field is realized as a conscious field upon the re-absorption of biophotons by exciplex states of DNA molecules. Such quantum phenomenon brings about self-awareness and enables objectivity to have access to subjectivity in the unconscious. As such, subjective experiences can be recalled to consciousness as subjective conscious experiences or qualia through co-operative interactions between exciplex states of DNA molecules and biophotons leading to metabolic activity and energy transfer across proteins as a result of protein-ligand binding during protein-protein communication. The biophoton field as a conscious field is attributable to the resultant effect of specifying qualia from the metabolic energy field that is transported in macromolecular proteins throughout specific networks of neurons that are constantly transforming into more stable associable representations as molecular solitons. The metastability of subjective experiences based on resonant dynamics occurs when bottom-up patterns of neocortical excitatory activity are matched with top-down expectations as adaptive dynamic pressures. These dynamics of on-going activity patterns influenced by the environment and selected as the preferred subjective experience in terms of a functional field through functional interactions and biological laws are realized as subjectivity and actualized through functional integration as qualia. It is concluded that interactionism and not information processing is the key in understanding how consciousness bridges the explanatory gap between subjective experiences and their neural correlates in the transcendental brain.
  11. Jarrar Q, Ayoub R, Jarrar Y, Aburass H, Goh KW, Ardianto C, et al.
    J Integr Neurosci, 2023 Jul 26;22(4):104.
    PMID: 37519168 DOI: 10.31083/j.jin2204104
    BACKGROUND: Mefenamic acid (MFA), a common analgesic, causes central nervous system (CNS) toxicity at high doses with a proposed activity on the Gamma-aminobutyric acid (GABA) system. However, it remains unknown whether flumazenil (FMZ), a GABA type A receptor (GABAAR) antagonist, can reverse MFA toxicity.

    METHODS: The behavioral and neurophysiological effects of MFA were investigated in mice with and without FMZ pre-treatment. The elevated zero maze (EZM) and marble burying tests were used to assess anxiety-like behaviors and burying activities, respectively. The standard bar test was used to evaluate catalepsy, while the actophotometer test was used to measure locomotor activity. Seizure intensity was scored, and fatalities were counted.

    RESULTS: Without FMZ pre-treatment, MFA induced behavioral and neurophysiological effects in a dose-dependent manner as follows: At a dose of 20 mg/kg, i.p, MFA-treated mice exhibited anxiety-like behaviors, which was determined by a significant increase in the time spent in the closed areas and a significant decrease in the number of entries to the open areas of the EZM apparatus. These mice also showed a significant decrease in the burying activity, manifested as a significant decrease in the number of buried marbles. At 40 mg/kg, i.p., MFA-treated mice showed catalepsy that was associated with a significant decrease in locomotor activity. At a dose of 80 mg/kg, i.p., mice developed fatal tonic-clonic seizures (seizure score = 4). Pre-treatment with FMZ (5 mg/kg, i.p.) significantly reversed the anxiety-like behaviors and restored marble-burying activity. Additionally, FMZ prevented catalepsy, significantly restored locomotor activity, reduced seizure intensity (seizure score = 0.3) and significantly reduced mortalities.

    CONCLUSIONS: The present study's findings indicate that activation of the GABAAR is involved in the CNS toxicity of MFA, and FMZ reverses MFA toxicity by interfering with this receptor.

  12. Sahu R, Dash SR, Cacha LA, Poznanski RR, Parida S
    J Integr Neurosci, 2020 Mar 30;19(1):1-9.
    PMID: 32259881 DOI: 10.31083/j.jin.2020.01.24
    Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accurate diagnosis and appropriate drug therapy to patients. This work aims to categorize electroencephalography signals on different channels' recordings for classifying and predicting epileptic seizures. The collection of the electroencephalography recordings contained in the dataset attributes 179 information and 11,500 instances. Instances are of five categories, where one is the symptoms of epilepsy seizure. We have used traditional, ensemble methods and deep machine learning techniques highlighting their performance for the epilepsy seizure detection task. One dimensional convolutional neural network, ensemble machine learning techniques like bagging, boosting (AdaBoost, gradient boosting, and XG boosting), and stacking is implemented. Traditional machine learning techniques such as decision tree, random forest, extra tree, ridge classifier, logistic regression, K-Nearest Neighbor, Naive Bayes (gaussian), and Kernel Support Vector Machine (polynomial, gaussian) are used for classifying and predicting epilepsy seizure. Before using ensemble and traditional techniques, we have preprocessed the data set using the Karl Pearson coefficient of correlation to eliminate irrelevant attributes. Further accuracy of classification and prediction of the classifiers are manipulated using k-fold cross-validation methods and represent the Receiver Operating Characteristic Area Under the Curve for each classifier. After sorting and comparing algorithms, we have found the convolutional neural network and extra tree bagging classifiers to have better performance than all other ensemble and traditional classifiers.
  13. Yuvaraj R, Murugappan M, Ibrahim NM, Omar MI, Sundaraj K, Mohamad K, et al.
    J Integr Neurosci, 2014 Mar;13(1):89-120.
    PMID: 24738541 DOI: 10.1142/S021963521450006X
    Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders.
  14. Koizumi A, Poznanski RR
    J Integr Neurosci, 2016 Jan 14.
    PMID: 26762484
    The starburst amacrine cell (SAC) plays a fundamental role in retinal motion perception. In the vertebrate retina, SAC dendrites have been shown to be directionally selective in terms of their Ca[Formula: see text] responses for stimuli that move centrifugally from the soma. The mechanism by which SACs show Ca[Formula: see text] bias for centrifugal motion is yet to be determined with precision. Recent morphological studies support a presynaptic delay in glutamate receptor activation induced Ca[Formula: see text] release from bipolar cells preferentially contacting SACs. However, bipolar cells are known to be electrotonically coupled so time delays between the bipolar cells that provide input to SACs seem unlikely. Using fluorescent microscopy and imunnostaining, we found that the endoplasmic reticulum (ER) is omnipresent in the soma extending to the distal processes of SACs. Consequently, a working hypothesis on heterogeneity of intracellular Ca[Formula: see text] dynamics from ER is proposed as a possible explanation for the cause of speed tuning of direction-selective Ca[Formula: see text] responses in dendrites of SACs.
  15. Zafar R, Malik AS, Kamel N, Dass SC, Abdullah JM, Reza F, et al.
    J Integr Neurosci, 2015 Jun;14(2):155-68.
    PMID: 25939499 DOI: 10.1142/S0219635215500089
    Brain is the command center for the body and contains a lot of information which can be extracted by using different non-invasive techniques. Electroencephalography (EEG), Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are the most common neuroimaging techniques to elicit brain behavior. By using these techniques different activity patterns can be measured within the brain to decode the content of mental processes especially the visual and auditory content. This paper discusses the models and imaging techniques used in visual decoding to investigate the different conditions of brain along with recent advancements in brain decoding. This paper concludes that it's not possible to extract all the information from the brain, however careful experimentation, interpretation and powerful statistical tools can be used with the neuroimaging techniques for better results.
  16. Zafar R, Kamel N, Naufal M, Malik AS, Dass SC, Ahmad RF, et al.
    J Integr Neurosci, 2017;16(3):275-289.
    PMID: 28891512 DOI: 10.3233/JIN-170016
    Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).
  17. Izan NF, Salleh SH, Ting CM, Noman F, Sh-Hussain H, Poznanski RR, et al.
    J Integr Neurosci, 2020 Sep 30;19(3):479-487.
    PMID: 33070527 DOI: 10.31083/j.jin.2020.03.222
    The purpose is to estimate the effectiveness of electrocardiograms during resting and active participation by the differentiation between the electrical activity of the heart while standing and sitting in a resting state. The concern is to identify the electrocardiogram parameters that did not show significant changes within these positions. The electrocardiogram parameters can be considered to be a standard marker for medically compromised patients. The electrocardiogram is recorded in the standing and sitting positions focusing on healthy participants using standard electrode placement of lead-I. Combined lead-I patterns (camel-hump or ST-segment prolongation) are usually seen in neurologic injury or hypothermia patients. The pairwise comparisons of a year data are about 454,400 cycles of sitting and 493,470 cycles of standing data. Thus, it is essential to quantify the nature and magnitude of changes seen in the electrocardiogram with a change of posture from sitting to standing in a healthy individual. This makes the findings of electrocardiogram analysis in this paper interesting in which some parameters (i.e., camel-hump patterns in lead-I) are helpful for clinical interpretations and could be suggestive of neurologic injury.
  18. Poznanski RR
    J Integr Neurosci, 2010 Sep;9(3):299-335.
    PMID: 21064220
    Optical imaging of dendritic calcium signals provided evidence of starburst amacrine cells exhibiting calcium bias to somatofugal motion. In contrast, it has been impractical to use a dual-patch clamp technique to record membrane potentials from both proximal dendrites and distal varicosities of starburst amacrine cells in order to unequivocally prove that they are directionally sensitive to voltage, as was first suggested almost two decades ago. This paper aims to extend the passive cable model to an active cable model of a starburst amacrine cell that is intrinsically dependent on the electrical properties of starburst amacrine cells, whose various macroscopic currents are described quantitatively. The coupling between voltage and calcium just below the membrane results in a voltage-calcium system of coupled nonlinear Volterra integral equations whose solutions must be integrated into a prescribed model for example, for a synaptic couplet of starburst amacrine cells. Networks of starburst amacrine cells play a fundamental role in the retinal circuitry underlying directional selectivity. It is suggested that the dendritic plexus of starburst amacrine cells provides the substrate for the property of directional selectivity, while directional selectivity is a property of the exclusive layerings and confinement of their interconnections within the sublaminae of the inner plexiform layer involving cone bipolar cells and directionally selective ganglion cells.
  19. Paudel P, Park SE, Seong SH, Fauzi FM, Jung HA, Choi JS
    J Integr Neurosci, 2023 Jan 05;22(1):10.
    PMID: 36722239 DOI: 10.31083/j.jin2201010
    BACKGROUND: Cholecystokinin (CCK) is one of the most abundant peptides in the central nervous system and is believed to function as a neurotransmitter as well as a gut hormone with an inverse correlation of its level to anxiety and depression. Therefore, CCK receptors (CCKRs) could be a relevant target for novel antidepressant therapy.

    METHODS: In silico target prediction was first employed to predict the probability of the bromophenols interacting with key protein targets based on a model trained on known bioactivity data and chemical similarity considerations. Next, we tested the functional effect of natural bromophenols from Symphyocladia latiuscula on the CCK2 receptor followed by a molecular docking simulation to predict interactions between a compound and the binding site of the target protein.

    RESULTS: Results of cell-based functional G-protein coupled receptor (GPCR) assays demonstrate that bromophenols 2,3,6-tribromo-4,5-dihydroxybenzyl alcohol (1), 2,3,6-tribromo-4,5-dihydroxybenzyl methyl ether (2), and bis-(2,3,6-tribromo-4,5-dihydroxybenzyl) ether (3) are full CCK2 antagonists. Molecular docking simulation of 1‒3 with CCK2 demonstrated strong binding by means of interaction with prime interacting residues: Arg356, Asn353, Val349, His376, Phe227, and Pro210. Simulation results predicted good binding scores and interactions with prime residues, such as the reference antagonist YM022.

    CONCLUSIONS: The results of this study suggest bromophenols 1-3 are CCK2R antagonists that could be novel therapeutic agents for CCK2R-related diseases, especially anxiety and depression.

  20. Usman MB, Ojha S, Jha SK, Chellappan DK, Gupta G, Singh SK, et al.
    J Integr Neurosci, 2022 Jan 28;21(1):41.
    PMID: 35164477 DOI: 10.31083/j.jin2101041
    Computational approach to study of neuronal impairment is rapidly evolving, as experiments and intuition alone could not explain the complexity of brain system. The increase in an overwhelming amount of new data from both theory and computational modeling necessitate the development of databases and tools for analysis, visualization, and interpretation of neuroscience data. To ensure the sustainability of this development, consistent update and training of young professionals are imperative. For this purpose, relevant articles, chapters, and modules are essential to keep abreast of developments. Therefore, this article seeks to outline the biological databases and analytical tools along with their applications. It's envisaged that knowledge along this line would be a "training recipe" for young talents and guide for professionals and researchers in neuroscience.
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