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Journal articles on the topic 'Whole brain model'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Delawati, Denna. "KETERAMPILAN BERPIKIR KRITIS: MODEL BRAIN-BASED LEARNING DAN DAN MODEL WHOLE BRAIN TEACHING." Jurnal Bidang Pendidikan Dasar 3, no. 2 (July 5, 2019): 9–14. http://dx.doi.org/10.21067/jbpd.v3i2.3356.

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Penelitian ini bertujuan untuk mengetahui perbedaan keterampilan berpikir krtitis siswa dengan menggunakan model pembelajaran Brain-Based Learning dan model Whole Brain Teaching pada muatan IPA kelas V SDN 3 Senggreng Kecamatan Sumberpucung. Jenis penelitian ini adalah Pra-Eksperimental Design dengan rancangan The Static Group Pretest-Posttest Design. Sampel yang digunakan adalah seluruh kelas 5A sebagai eksperimen 1 dan kelas 5B sebagai eksperimen 2. Instrumen penelitian yang digunakan berupa tes untuk menguji berpikir kritis siswa. Hasil analisis data menunjukkan bahwa keterampilan berpikir kritis dengan menggunakan model Whole Brain Teaching lebih tinggi dibandingkan menggunakan model Brain-Based Learning. Data yang diperoleh menggunakan analisis Uji-t. Dari hasil Uji-t diketahui bahwa sebesar 2,127 dan 2,122, lebih besar ttabel (> 2,020) dan nilai signifikasi 5% menunjukkan bahwa nilai 0,039 dan 0,040 (< 0,05), oleh karena itu hipotesis alternatif diterima. Dengan demikian terdapat perbedaan model Brain-Based Learning dan model Whole Brain Teaching pada keterampilan berpikir kritis IPA kelas V SDN 3 Senggreng Kecamatan Sumberpucung. Diharapan dengan menggunakan model berbasis otak ini, siswa akan lebih mudah memahami materi dan dapat menyelesaikan permasalahan dalam kehidupan sehari-hari.

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2

Handayani, Baiq Sri, and A. D. Corebima. "Model brain based learning (BBL) and whole brain teaching (WBT) in learning." International Journal of Science and Applied Science: Conference Series 1, no. 2 (August 14, 2017): 153. http://dx.doi.org/10.20961/ijsascs.v1i2.5142.

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<p class="Abstract">The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL) and the model of Whole Brain Teaching (WBT). The purposes of this article are to obtain information related to (1) the brain’s natural learning system, (2) analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3) explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1) the brain’s natural learning system are: (a) the nerves in each hemisphere do not work independently, (b) doing more activities can connect more brain nerves, (c) the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2) the characteristics of BBL and WBT are: (a) BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b) the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c) the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3) the typical attribute of them compared to other models are that in BBL there are classical music and gestures in the form of easy exercises, while on the WBT model there are fast instructions and movements as instructions or code of every spoken word.</p>

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Frässle, Stefan, Ekaterina I. Lomakina, Lars Kasper, Zina M. Manjaly, Alex Leff, Klaas P. Pruessmann, Joachim M. Buhmann, and Klaas E. Stephan. "A generative model of whole-brain effective connectivity." NeuroImage 179 (October 2018): 505–29. http://dx.doi.org/10.1016/j.neuroimage.2018.05.058.

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4

Maniglia, Marcello, and Aaron R. Seitz. "Towards a whole brain model of Perceptual Learning." Current Opinion in Behavioral Sciences 20 (April 2018): 47–55. http://dx.doi.org/10.1016/j.cobeha.2017.10.004.

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5

Eagleton, Saramarie, and Anton Muller. "Development of a model for whole brain learning of physiology." Advances in Physiology Education 35, no. 4 (December 2011): 421–26. http://dx.doi.org/10.1152/advan.00007.2011.

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In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed elaborates on these layers by relating the personality traits central to learning to the different quadrants of brain preference, as described by Neethling's brain profile, as the inner layer of the onion. This layer is encircled by the learning styles that describe different information-processing preferences for each brain quadrant. For the middle layer, the different stages of Kolb's learning cycle are classified into the four brain quadrants associated with the different brain processing strategies within the information processing circle. Each of the stages of Kolb's learning cycle is also associated with a specific cognitive learning strategy. These two inner circles are enclosed by the circle representing the role of the environment and instruction on learning. It relates environmental factors that affect learning and distinguishes between face-to-face and technology-assisted learning. This model informs on the design of instructional interventions for physiology to encourage whole brain learning.

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Deshpande, Prasad, and Suhas Baxi. "ST‐IM model: a whole brain approach to implementation." Industrial and Commercial Training 43, no. 4 (June 14, 2011): 228–38. http://dx.doi.org/10.1108/00197851111137843.

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7

Røge, Rasmus E., Kristoffer H. Madsen, Mikkel N. Schmidt, and Morten Mørup. "Infinite von Mises–Fisher Mixture Modeling of Whole Brain fMRI Data." Neural Computation 29, no. 10 (October 2017): 2712–41. http://dx.doi.org/10.1162/neco_a_01000.

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Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises–Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians subsequently normalized. Thus, when performing model selection, the two models are not in agreement. Analyzing multisubject whole brain resting-state fMRI data from healthy adult subjects, we find that the vMF mixture model is considerably more reliable than the gaussian mixture model when comparing solutions across models trained on different groups of subjects, and again we find that the two models disagree on the optimal number of components. The analysis indicates that the fMRI data support more than a thousand clusters, and we confirm this is not a result of overfitting by demonstrating better prediction on data from held-out subjects. Our results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of fMRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.

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TEZCAN, GAMZE. "4MAT Öğretim Modeli, Bütünsel Beyin Modeli’nin Fen Dersi Öz Yeterlik Algısına Etkisi." KIRŞEHİR EĞİTİM FAKÜLTESİ DERGİSİ 18, no. 3 (December 30, 2017): 193–214. http://dx.doi.org/10.29299/kefad.2017.18.3.011.

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Coronel-Oliveros, Carlos, Rodrigo Cofré, and Patricio Orio. "Cholinergic neuromodulation of inhibitory interneurons facilitates functional integration in whole-brain models." PLOS Computational Biology 17, no. 2 (February 18, 2021): e1008737. http://dx.doi.org/10.1371/journal.pcbi.1008737.

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Segregation and integration are two fundamental principles of brain structural and functional organization. Neuroimaging studies have shown that the brain transits between different functionally segregated and integrated states, and neuromodulatory systems have been proposed as key to facilitate these transitions. Although whole-brain computational models have reproduced this neuromodulatory effect, the role of local inhibitory circuits and their cholinergic modulation has not been studied. In this article, we consider a Jansen & Rit whole-brain model in a network interconnected using a human connectome, and study the influence of the cholinergic and noradrenergic neuromodulatory systems on the segregation/integration balance. In our model, we introduce a local inhibitory feedback as a plausible biophysical mechanism that enables the integration of whole-brain activity, and that interacts with the other neuromodulatory influences to facilitate the transition between different functional segregation/integration regimes in the brain.

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Wood, Tobias C., Camilla Simmons, Samuel A. Hurley, Anthony C. Vernon, Joel Torres, Flavio Dell’Acqua, Steve C. R. Williams, and Diana Cash. "Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model." PeerJ 4 (November 1, 2016): e2632. http://dx.doi.org/10.7717/peerj.2632.

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Myelin is a critical component of the nervous system and a major contributor to contrast in Magnetic Resonance (MR) images. However, the precise contribution of myelination to multiple MR modalities is still under debate. The cuprizone mouse is a well-established model of demyelination that has been used in several MR studies, but these have often imaged only a single slice and analysed a small region of interest in the corpus callosum. We imaged and analyzed the whole brain of the cuprizone mouse ex-vivo using high-resolution quantitative MR methods (multi-component relaxometry, Diffusion Tensor Imaging (DTI) and morphometry) and found changes in multiple regions, including the corpus callosum, cerebellum, thalamus and hippocampus. The presence of inflammation, confirmed with histology, presents difficulties in isolating the sensitivity and specificity of these MR methods to demyelination using this model.

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Sarikaya, Bünyamin, and Yusuf Söylemez. "Evaluation of Acquisition of Comprehension Skills According to Whole Brain Model." Universal Journal of Educational Research 6, no. 11 (November 2018): 2444–52. http://dx.doi.org/10.13189/ujer.2018.061107.

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Niu, Atsushi, Kuniko Shimazaki, Yasushi Sugawara, Toshiyuki Mizui, and Nobufumi Kawai. "Heterotopic graft of infant rat brain as an ischemic model for prolonged whole-brain ischemia." Neuroscience Letters 325, no. 1 (May 2002): 37–41. http://dx.doi.org/10.1016/s0304-3940(02)00213-6.

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Brown, R. J., B. J. Jun, A. Beighley, J. Blanchard, K. Iwamoto, N. Harris, S. Bluml, and W. H. McBride. "PL-01 * A PRECLINICAL JUVENILE RAT MODEL OF BRAIN INJURY AFTER FRACTIONATED WHOLE BRAIN IRRADIATION." Neuro-Oncology 16, suppl 5 (November 1, 2014): v168. http://dx.doi.org/10.1093/neuonc/nou267.1.

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14

Gilson, Matthieu, Gorka Zamora-López, Vicente Pallarés, Mohit H. Adhikari, Mario Senden, Adrià Tauste Campo, Dante Mantini, Maurizio Corbetta, Gustavo Deco, and Andrea Insabato. "Model-based whole-brain effective connectivity to study distributed cognition in health and disease." Network Neuroscience 4, no. 2 (January 2020): 338–73. http://dx.doi.org/10.1162/netn_a_00117.

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Neuroimaging techniques are now widely used to study human cognition. The functional associations between brain areas have become a standard proxy to describe how cognitive processes are distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been developed to overcome the limitations of original connectivity measures such as functional connectivity. This goes in line with the many efforts devoted to the assessment of directional interactions between brain areas from the observed neuroimaging activity. This opinion article provides an overview of our model-based whole-brain effective connectivity to analyze fMRI data, while discussing the pros and cons of our approach with respect to other established approaches. Our framework relies on the multivariate Ornstein-Uhlenbeck (MOU) process and is thus referred to as MOU-EC. Once tuned, the model provides a directed connectivity estimate that reflects the dynamical state of BOLD activity, which can be used to explore cognition. We illustrate this approach using two applications on task-evoked fMRI data. First, as a connectivity measure, MOU-EC can be used to extract biomarkers for task-specific brain coordination, understood as the patterns of areas exchanging information. The multivariate nature of connectivity measures raises several challenges for whole-brain analysis, for which machine-learning tools present some advantages over statistical testing. Second, we show how to interpret changes in MOU-EC connections in a collective and model-based manner, bridging with network analysis. Our framework provides a comprehensive set of tools that open exciting perspectives to study distributed cognition, as well as neuropathologies.

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Mancini, Matteo, Qiyuan Tian, Qiuyun Fan, Mara Cercignani, and Susie Y. Huang. "Dissecting whole-brain conduction delays through MRI microstructural measures." Brain Structure and Function 226, no. 8 (August 14, 2021): 2651–63. http://dx.doi.org/10.1007/s00429-021-02358-w.

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AbstractNetwork models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences.

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Cicciarello, Rocco, Domenico d'Avella, Maria Ester Gagliardi, Francesca Albiero, José Vega, Filippo F. Angileri, Antonio D'Aquino, and Francesco Tomasello. "Time-related Ultrastructural Changes in an Experimental Model of Whole Brain Irradiation." Neurosurgery 38, no. 4 (April 1, 1996): 772–80. http://dx.doi.org/10.1227/00006123-199604000-00028.

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17

Martínez-Murillo, R., J. Serrano, A. P. Fernández, and A. Martínez. "Whole-body periodic acceleration reduces brain damage in a focal ischemia model." Neuroscience 158, no. 4 (February 2009): 1390–96. http://dx.doi.org/10.1016/j.neuroscience.2008.12.005.

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18

Jobst, Beatrice M., Selen Atasoy, Adrián Ponce-Alvarez, Ana Sanjuán, Leor Roseman, Mendel Kaelen, Robin Carhart-Harris, Morten L. Kringelbach, and Gustavo Deco. "Increased sensitivity to strong perturbations in a whole-brain model of LSD." NeuroImage 230 (April 2021): 117809. http://dx.doi.org/10.1016/j.neuroimage.2021.117809.

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Klose, Uwe, Marion Batra, and Thomas Nägele. "Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram." BioMed Research International 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/373716.

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Purpose. The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered.Methods. Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line.Results. A consistent fitting of the histograms of all age groups was possible with the proposed model.Conclusions. This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

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Padilla, Nelly, Victor M. Saenger, Tim J. van Hartevelt, Henrique M. Fernandes, Finn Lennartsson, Jesper L. R. Andersson, Morten Kringelbach, Gustavo Deco, and Ulrika Åden. "Breakdown of Whole-brain Dynamics in Preterm-born Children." Cerebral Cortex 30, no. 3 (August 23, 2019): 1159–70. http://dx.doi.org/10.1093/cercor/bhz156.

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Abstract The brain operates at a critical point that is balanced between order and disorder. Even during rest, unstable periods of random behavior are interspersed with stable periods of balanced activity patterns that support optimal information processing. Being born preterm may cause deviations from this normal pattern of development. We compared 33 extremely preterm (EPT) children born at < 27 weeks of gestation and 28 full-term controls. Two approaches were adopted in both groups, when they were 10 years of age, using structural and functional brain magnetic resonance imaging data. The first was using a novel intrinsic ignition analysis to study the ability of the areas of the brain to propagate neural activity. The second was a whole-brain Hopf model, to define the level of stability, desynchronization, or criticality of the brain. EPT-born children exhibited fewer intrinsic ignition events than controls; nodes were related to less sophisticated aspects of cognitive control, and there was a different hierarchy pattern in the propagation of information and suboptimal synchronicity and criticality. The largest differences were found in brain nodes belonging to the rich-club architecture. These results provide important insights into the neural substrates underlying brain reorganization and neurodevelopmental impairments related to prematurity.

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Hughes, Mathew, Paul Hughes, and Ian R. Hodgkinson. "In pursuit of a ‘whole-brain’ approach to undergraduate teaching: implications of the Herrmann brain dominance model." Studies in Higher Education 42, no. 12 (February 24, 2016): 2389–405. http://dx.doi.org/10.1080/03075079.2016.1152463.

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Hashemi, Meysam, Anirudh N. Vattikonda, Viktor Sip, Sandra Diaz-Pier, Alexander Peyser, Huifang Wang, Maxime Guye, Fabrice Bartolomei, Marmaduke M. Woodman, and Viktor K. Jirsa. "On the influence of prior information evaluated by fully Bayesian criteria in a personalized whole-brain model of epilepsy spread." PLOS Computational Biology 17, no. 7 (July 14, 2021): e1009129. http://dx.doi.org/10.1371/journal.pcbi.1009129.

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Individualized anatomical information has been used as prior knowledge in Bayesian inference paradigms of whole-brain network models. However, the actual sensitivity to such personalized information in priors is still unknown. In this study, we introduce the use of fully Bayesian information criteria and leave-one-out cross-validation technique on the subject-specific information to assess different epileptogenicity hypotheses regarding the location of pathological brain areas based on a priori knowledge from dynamical system properties. The Bayesian Virtual Epileptic Patient (BVEP) model, which relies on the fusion of structural data of individuals, a generative model of epileptiform discharges, and a self-tuning Monte Carlo sampling algorithm, is used to infer the spatial map of epileptogenicity across different brain areas. Our results indicate that measuring the out-of-sample prediction accuracy of the BVEP model with informative priors enables reliable and efficient evaluation of potential hypotheses regarding the degree of epileptogenicity across different brain regions. In contrast, while using uninformative priors, the information criteria are unable to provide strong evidence about the epileptogenicity of brain areas. We also show that the fully Bayesian criteria correctly assess different hypotheses about both structural and functional components of whole-brain models that differ across individuals. The fully Bayesian information-theory based approach used in this study suggests a patient-specific strategy for epileptogenicity hypothesis testing in generative brain network models of epilepsy to improve surgical outcomes.

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Crowe, William, Dawen Zhao, Zhongwei Zhang, Lulu Wang, and John Bourland. "NIMG-04. MRI EVALUATION OF THE EFFECT OF WHOLE BRAIN RADIOTHERAPY ON BRAIN METASTASIS." Neuro-Oncology 22, Supplement_2 (November 2020): ii147. http://dx.doi.org/10.1093/neuonc/noaa215.617.

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Abstract Poor prognosis of breast cancer brain metastasis partially results from the inability of therapeutics to penetrate the Blood-Brain-Barrier (BBB). Whole Brain Radiotherapy (WBRT) is standard-of-care for brain metastasis, however the early effects of fractionated WBRT on brain metastases have not been evaluated. Here, we applied longitudinal MRI to study WBRT’s effect on tumor volume, BBB permeability, and tumor-cell killing using anatomic, Dynamic Contrast Enhanced (DCE), and Diffusion-weighted (DW) MRI, evaluating tumor volume, permeability, and cytotoxic effect, respectively. The BCBM mouse model was established with left ventricle MDA-MB231-Br cell injection. MRI occurred before and 24h after 3 daily fractionated 4Gy WBRT (2.4Gy/min) or sham irradiation. In addition to anatomic MRI, DW MRI measured tissue ADC to study cytotoxic effect, and DCE MRI measured BBB permeability, quantified as the permeability variable Ktrans. Before treatment, T2-weighted images revealed hyperintense multifocal lesions in brains, and many had intact BBB indicated by no T1-w contrast-enhancement. WBRT tumors were smaller than sham irradiated tumors after 3 days (p< 0.05), while no difference in the number of new lesions was observed. DW MRI demonstrated increased ADC in WBRT tumors (p< 0.05), correlating well with elevated Caspase-3 staining of apoptotic cells. T1-w contrast enhanced images of tumors after treatment revealed no differences in the population of contrast-enhanced tumors between the WBRT and sham radiation groups. However, quantitative DCE MRI showed higher Ktrans in WBRT treated tumors relative to sham treated lesions, and an increase in Ktrans of WBRT tumors (p< 0.05), despite high permeability heterogeneity both inter- and intra-tumorally, indicating remaining impermeable BBB. In addition to monitoring tumor volume, longitudinal MRI provided non-invasive assessments of temporal and spatial changes in cellularity and vascular permeability of brain metastasis in response to WBRT, which may prove to be useful for defining an ideal treatment window for potential combination BCBM treatments.

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Neville, Kathryn E., Timothy L. Bosse, Mia Klekos, John F. Mills, Steven E. Weicksel, James S. Waters, and Marla Tipping. "A novel ex vivo method for measuring whole brain metabolism in model systems." Journal of Neuroscience Methods 296 (February 2018): 32–43. http://dx.doi.org/10.1016/j.jneumeth.2017.12.020.

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Ruiz Vargas, E., D. G. V. Mitchell, S. G. Greening, and L. M. Wahl. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model." Physica A: Statistical Mechanics and its Applications 405 (July 2014): 151–58. http://dx.doi.org/10.1016/j.physa.2014.03.025.

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Zhu, QiaoYun, YuHang Sun, Yi Wu, HuoBiao Zhu, GuoYe Lin, YuJia Zhou, and QianJin Feng. "Whole‐brain functional MRI registration based on a semi‐supervised deep learning model." Medical Physics 48, no. 6 (April 15, 2021): 2847–58. http://dx.doi.org/10.1002/mp.14777.

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Handayani, Baiq Sri, Aloysius Duran Corebima, Herawati Susilo, and Susriyati Mahanal. "Developing Brain Based Learning (BBL) Model Integrated with Whole Brain Teaching (WBT) Model on Science Learning in Junior High School in Malang." Universal Journal of Educational Research 8, no. 4A (April 2020): 59–69. http://dx.doi.org/10.13189/ujer.2020.081809.

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Kirstein, Marina, and Rolien Kunz. "A Whole Brain® learning approach to an undergraduate auditing initiative – an exploratory study." Meditari Accountancy Research 24, no. 4 (October 3, 2016): 527–44. http://dx.doi.org/10.1108/medar-02-2014-0029.

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Purpose Individual students have different learning styles, and lecturers can no longer afford to ignore this. Lecturers have a responsibility to accommodate students’ different learning styles by including learning style flexibility in the offered learning opportunities. The purpose of this study is to map a teaching case study against the Herrmann Whole Brain® model to determine whether learning style flexibility has been incorporated in the teaching case study. Design/methodology/approach A teaching case study was developed and delivered as part of an undergraduate level course at a South African residential university. The case study’s primary intention was to illustrate the practical evaluation of general controls in an information technology environment. The teaching case study was analysed in terms of the Herrmann Whole Brain® model to determine whether learning style flexibility had been accommodated in the learning opportunity. Findings Based on an analysis of the teaching case study against the Herrmann Whole Brain® model, it is evident that the teaching case study incorporated activities that addressed all four quadrants of the Whole Brain® model. It can therefore be concluded that the learning opportunity incorporated learning style flexibility. Originality/value This paper contributes to the literature in accounting education by focusing on learning style flexibility specifically using the Herrmann Whole Brain® model, as it appears that limited examples of the use of this model in accounting education have yet been published. Although this paper discusses the use of an auditing case study, the results may be of interest to lecturers in other subject areas across the academic spectrum.

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Kaboodvand, Neda, Martijn P. van den Heuvel, and Peter Fransson. "Adaptive frequency-based modeling of whole-brain oscillations: Predicting regional vulnerability and hazardousness rates." Network Neuroscience 3, no. 4 (January 2019): 1094–120. http://dx.doi.org/10.1162/netn_a_00104.

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Whole-brain computational modeling based on structural connectivity has shown great promise in successfully simulating fMRI BOLD signals with temporal coactivation patterns that are highly similar to empirical functional connectivity patterns during resting state. Importantly, previous studies have shown that spontaneous fluctuations in coactivation patterns of distributed brain regions have an inherent dynamic nature with regard to the frequency spectrum of intrinsic brain oscillations. In this modeling study, we introduced frequency dynamics into a system of coupled oscillators, where each oscillator represents the local mean-field model of a brain region. We first showed that the collective behavior of interacting oscillators reproduces previously shown features of brain dynamics. Second, we examined the effect of simulated lesions in gray matter by applying an in silico perturbation protocol to the brain model. We present a new approach to map the effects of vulnerability in brain networks and introduce a measure of regional hazardousness based on mapping of the degree of divergence in a feature space.

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Eth, Daniel, Juan-Carlos Foust, and Brandon Whale. "The Prospects of Whole Brain Emulation within the next Half- Century." Journal of Artificial General Intelligence 4, no. 3 (December 1, 2013): 130–52. http://dx.doi.org/10.2478/jagi-2013-0008.

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Abstract Whole Brain Emulation (WBE), the theoretical technology of modeling a human brain in its entirety on a computer-thoughts, feelings, memories, and skills intact-is a staple of science fiction. Recently, proponents of WBE have suggested that it will be realized in the next few decades. In this paper, we investigate the plausibility of WBE being developed in the next 50 years (by 2063). We identify four essential requisite technologies: scanning the brain, translating the scan into a model, running the model on a computer, and simulating an environment and body. Additionally, we consider the cultural and social effects of WBE. We find the two most uncertain factors for WBE’s future to be the development of advanced miniscule probes that can amass neural data in vivo and the degree to which the culture surrounding WBE becomes cooperative or competitive. We identify four plausible scenarios from these uncertainties and suggest the most likely scenario to be one in which WBE is realized, and the technology is used for moderately cooperative ends

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Bálentová, Soňa, Petra Hnilicová, Dagmar Kalenská, Peter Murín, Eva Hajtmanová, Ján Lehotský, and Marian Adamkov. "Effect of whole-brain irradiation on the specific brain regions in a rat model: Metabolic and histopathological changes." NeuroToxicology 60 (May 2017): 70–81. http://dx.doi.org/10.1016/j.neuro.2017.03.005.

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Zwergal, Andreas, Julia Schlichtiger, Guoming Xiong, Roswitha Beck, Lisa Günther, Roman Schniepp, Florian Schöberl, et al. "Sequential [18F]FDG µPET whole-brain imaging of central vestibular compensation: a model of deafferentation-induced brain plasticity." Brain Structure and Function 221, no. 1 (October 1, 2014): 159–70. http://dx.doi.org/10.1007/s00429-014-0899-1.

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Yu, L. J., B. Riordan, P. Hatsis, A. Brockman, S. Daniels, N. Stagliano, S. Finklestein, J. Ren, M. Milton, and G. Miwa. "Study of brain and whole blood PK/PD of bortezomib in rat models." Journal of Clinical Oncology 24, no. 18_suppl (June 20, 2006): 12036. http://dx.doi.org/10.1200/jco.2006.24.18_suppl.12036.

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12036 Background: Bortezomib (Btz) is the first in class proteasome inhibitor and has been approved for treatment of multiple myeloma patients who have received at least 1 prior therapy. The potential for Btz to penetrate the CNS was examined in the rat under two conditions: intact blood brain barrier (BBB) and compromised BBB induced by middle cerebral artery occlusion (MCAO). Methods: Intact BBB: healthy rats received an iv bolus followed by a constant infusion of Btz to steady-state (SS). The blood and brain samples were collected for determination of concentration (Conc) of Btz (PK) and of 20S proteasome activity (PD). The brain samples were collected after a perfusion with saline. Inulin was included in the study in order to determine blood contamination in brain tissues. Compromised BBB: rats underwent MCAO surgery and 1 h later were administered Btz via an iv bolus of 0, 0.1, 0.2 or 0.35 mg/kg. The blood and brain samples were collected through 24 h postdose. Conc of Btz was determined by an LC/MS/MS method. The 20S proteasome activity was measured using an ex vivo assay. Results: 1) Intact BBB: at SS the mean blood Conc of Btz was 140 ng/mL, and proteasome activity in the blood was inhibited by ∼80% compared to the vehicle group (p < 0.0001). In contrast, the brain Conc of Btz was extremely low (∼3 ng/g) with the brain-to-blood ratio of ∼0.02. No difference was observed in brain proteasome activity between the vehicle and Btz-treated groups. 2)The MCAO rat: the PK/PD relationship in the blood was best described by a sigmoid Emax model with an EC50 of 110 ng/mL and gamma factor of 3.8. The model also suggests that there is no proteasome inhibition (PI) when the blood Conc is <40 ng/mL (no effective blood Conc, NOEBC). In the brain, the Cmax of Btz was 22.0 ng/g from the highest dose group, in contrast to the blood Cmax of 164 ng/mL. The increased exposure in the brain of a MCAO rat relative to a normal rat was anticipated as its BBB is impaired. However, the brain Concs were all below the NOEBC. No significant PI was observed in all brain tissues (P>0.1). Conclusion: Very poor brain penetration was observed for Btz in rats. Btz showed PI in whole blood but not in the brain either of normal or MCAO rats following administration of Btz. [Table: see text]

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Lester-Coll, Nataniel H., Arie P. Dosoretz, William J. Magnuson, Maxwell S. Laurans, Veronica L. Chiang, and James B. Yu. "Cost-effectiveness of stereotactic radiosurgery versus whole-brain radiation therapy for up to 10 brain metastases." Journal of Neurosurgery 125, Supplement_1 (December 2016): 18–25. http://dx.doi.org/10.3171/2016.7.gks161499.

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OBJECTIVEThe JLGK0901 study found that stereotactic radiosurgery (SRS) is a safe and effective treatment option for treating up to 10 brain metastases. The purpose of this study is to determine the cost-effectiveness of treating up to 10 brain metastases with SRS, whole-brain radiation therapy (WBRT), or SRS and immediate WBRT (SRS+WBRT).METHODSA Markov model was developed to evaluate the cost effectiveness of SRS, WBRT, and SRS+WBRT in patients with 1 or 2–10 brain metastases. Transition probabilities were derived from the JLGK0901 study and modified according to the recurrence rates observed in the Radiation Therapy Oncology Group (RTOG) 9508 and European Organization for Research and Treatment of Cancer (EORTC) 22952–26001 studies to simulate the outcomes for patients who receive WBRT. Costs are based on 2015 Medicare reimbursements. Health state utilities were prospectively collected using the Standard Gamble method. End points included cost, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). The willingness-to-pay (WTP) threshold was $100,000 per QALY. One-way and probabilistic sensitivity analyses explored uncertainty with regard to the model assumptions.RESULTSIn patients with 1 brain metastasis, the ICERs for SRS versus WBRT, SRS versus SRS+WBRT, and SRS+WBRT versus WBRT were $117,418, $51,348, and $746,997 per QALY gained, respectively. In patients with 2–10 brain metastases, the ICERs were $123,256, $58,903, and $821,042 per QALY gained, respectively. On the sensitivity analyses, the model was sensitive to the cost of SRS and the utilities associated with stable post-SRS and post-WBRT states. In patients with 2–10 brain metastases, SRS versus WBRT becomes cost-effective if the cost of SRS is reduced by $3512. SRS versus WBRT was also cost effective at a WTP of $200,000 per QALY on the probabilistic sensitivity analysis.CONCLUSIONSThe most cost-effective strategy for patients with up to 10 brain metastases is SRS alone relative to SRS+WBRT. SRS alone may also be cost-effective relative to WBRT alone, but this depends on WTP, the cost of SRS, and patient preferences.

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Cho, Moo. "Development and Evaluation of an Education Program Based on Whole Brain Model for Novice Nurses." Journal of Korean Academic Society of Nursing Education 26, no. 1 (February 28, 2020): 36–46. http://dx.doi.org/10.5977/jkasne.2020.26.1.36.

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Purpose: This study was conducted to develop and implement an education program based on the Whole Brain Model for novice nurses, and to evaluate its effects on work performance, interpersonal skills and self-efficacy. Methods: A pretest-posttest quasi-experimental design was used with an experimental group (n=20) and a control group (n=21). The experimental group participated in an education program based on the Whole Brain Model for seven sessions over 4 weeks. An independent t-test, χ2-test, and Mann-Whitney U test were performed to analyze the data. Results: There were statistically significant differences in work performance (p=.015), interpersonal skills (p=.014) and self-efficacy (p=.021) between the experimental and the control group. Conclusion: This program was an effective learning strategy to enhance nursing competence for novice nurses. The novice nurses who participated this program were able to reflect deeply on themselves, improve interpersonal skills, and induce whole-brain integrated thinking in learning how to solve the problems caused by changes in patient conditions that can be experienced in clinical practice. Therefore, this program can be recommended for regular continuing education for novice nurses.

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Wijaya, Elita Mega Selvia, and Nathasa Pramudita Irianti. "Whole Brain Teaching sebagai Desain Pembelajaran Matematika yang Kreatif." MUST: Journal of Mathematics Education, Science and Technology 2, no. 2 (December 28, 2017): 196. http://dx.doi.org/10.30651/must.v2i2.839.

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Penelitian bertujuan untuk memperoleh desain pembelajaran berbasis karakter kreatif melalui pendekatan Whole Brain Teaching pada materi grafik garis lurus yang valid, praktis dan efektif. Pengembangan desain pembelajaran ini didasarkan pada model pengembangan Plomp, yang terdiri dari empat fase, yaitu: (1) investigasi awal, (2) desain atau perancangan, (3) realisasi atau konstruksi, dan (4) tes, evaluasi, revisi. Fase investigasi awal meliputi investigasi pengetahuan prasyarat, mengamati dan analisis perilaku siswa, mengkaji kurikulum dan silabus, serta investigasi sumber pendukung. Fase perancangan diantaranya merancang pengorganisasian materi menjadi unit-unit yang utuh, berdasarkan karakteristik materi dan alokasi waktu, membuat pemetaan materi dan aktivitas PBM yang relevan, serta membuat rancangan RPP dan LKS. Dalam fase realisasi, dikembangkan dua perangkat yaitu RPP dan LKS. Di fase terakhir, yaitu tes evaluasi, dilakukan validasi dan uji coba lapangan. Berdasarkan hasil analisis data, desain pembelajaran matematika berdasarkan Whole Brain Teaching dapat diterapkan dan terlaksana dengan baik. Hal ini ditunjukkan dari tingkat keterlaksanaan lebih dari 75% dan masing-masing aktivitas terlaksana di atas 61%. Hasil ini diperkuat dengan hasil wawancara yang berpendapat bahwa pembelajaran persamaan garis lurus menggunakan Whole Brain Teaching cukup baik dan menyenangkan, secara umum menyampaikan gesture yang dipakai pada pembelajaran dapat membantu dalam memahami konsep persamaan dan grafik garis lurus dan meningkatkan daya ingat.

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Degtyaruk, Oleksiy, Benedict Mc Larney, Xosé Deán-Ben, Shy Shoham, and Daniel Razansky. "Optoacoustic Calcium Imaging of Deep Brain Activity in an Intracardially Perfused Mouse Brain Model." Photonics 6, no. 2 (June 12, 2019): 67. http://dx.doi.org/10.3390/photonics6020067.

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One main limitation of established neuroimaging methods is the inability to directly visualize large-scale neural dynamics in whole mammalian brains at subsecond speeds. Optoacoustic imaging has advanced in recent years to provide unique advantages for real-time deep-tissue observations, which have been exploited for three-dimensional imaging of both cerebral hemodynamic parameters and direct calcium activity in rodents. Due to a lack of suitable calcium indicators excitable in the near-infrared window, optoacoustic imaging of neuronal activity at deep-seated areas of the mammalian brain has been impeded by the strong absorption of blood in the visible range of the light spectrum. To overcome this, we have developed and validated an intracardially perfused mouse brain preparation labelled with genetically encoded calcium indicator GCaMP6f that closely resembles in vivo conditions. By overcoming the limitations of hemoglobin-based light absorption, this new technique was used to observe stimulus-evoked calcium dynamics in the brain at penetration depths and spatio-temporal resolution scales not attainable with existing neuroimaging techniques.

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Li, Dao, Chunsheng Ma, Ming Shen, Peiyu Li, and Jinhuan Zhang. "Brain Injury Differences in Frontal Impact Crash Using Different Simulation Strategies." Computational and Mathematical Methods in Medicine 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/348947.

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In the real world crashes, brain injury is one of the leading causes of deaths. Using isolated human head finite element (FE) model to study the brain injury patterns and metrics has been a simplified methodology widely adopted, since it costs significantly lower computation resources than a whole human body model does. However, the degree of precision of this simplification remains questionable. This study compared these two kinds of methods: (1) using a whole human body model carried on the sled model and (2) using an isolated head model with prescribed head motions, to study the brain injury. The distribution of the von Mises stress (VMS), maximum principal strain (MPS), and cumulative strain damage measure (CSDM) was used to compare the two methods. The results showed that the VMS of brain mainly concentrated at the lower cerebrum and occipitotemporal region close to the cerebellum. The isolated head modelling strategy predicted higher levels of MPS and CSDM 5%, while the difference is small in CSDM 10% comparison. It suggests that isolated head model may not equivalently reflect the strain levels below the 10% compared to the whole human body model.

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Roldan-Valadez, Ernesto, Camilo Rios, David Cortez-Conradis, Rafael Favila, and Sergio Moreno-Jimenez. "Global diffusion tensor imaging derived metrics differentiate glioblastoma multiforme vs. normal brains by using discriminant analysis: introduction of a novel whole-brain approach." Radiology and Oncology 48, no. 2 (June 1, 2014): 127–36. http://dx.doi.org/10.2478/raon-2014-0004.

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Abstract Background. Histological behavior of glioblastoma multiforme suggests it would benefit more from a global rather than regional evaluation. A global (whole-brain) calculation of diffusion tensor imaging (DTI) derived tensor metrics offers a valid method to detect the integrity of white matter structures without missing infiltrated brain areas not seen in conventional sequences. In this study we calculated a predictive model of brain infiltration in patients with glioblastoma using global tensor metrics. Methods. Retrospective, case and control study; 11 global DTI-derived tensor metrics were calculated in 27 patients with glioblastoma multiforme and 34 controls: mean diffusivity, fractional anisotropy, pure isotropic diffusion, pure anisotropic diffusion, the total magnitude of the diffusion tensor, linear tensor, planar tensor, spherical tensor, relative anisotropy, axial diffusivity and radial diffusivity. The multivariate discriminant analysis of these variables (including age) with a diagnostic test evaluation was performed. Results. The simultaneous analysis of 732 measures from 12 continuous variables in 61 subjects revealed one discriminant model that significantly differentiated normal brains and brains with glioblastoma: Wilks’ λ = 0.324, χ2 (3) = 38.907, p < .001. The overall predictive accuracy was 92.7%. Conclusions. We present a phase II study introducing a novel global approach using DTI-derived biomarkers of brain impairment. The final predictive model selected only three metrics: axial diffusivity, spherical tensor and linear tensor. These metrics might be clinically applied for diagnosis, follow-up, and the study of other neurological diseases.

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Feng, Guoping, Frances E. Jensen, Henry T. Greely, Hideyuki Okano, Stefan Treue, Angela C. Roberts, James G. Fox, et al. "Opportunities and limitations of genetically modified nonhuman primate models for neuroscience research." Proceedings of the National Academy of Sciences 117, no. 39 (August 19, 2020): 24022–31. http://dx.doi.org/10.1073/pnas.2006515117.

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The recently developed new genome-editing technologies, such as the CRISPR/Cas system, have opened the door for generating genetically modified nonhuman primate (NHP) models for basic neuroscience and brain disorders research. The complex circuit formation and experience-dependent refinement of the human brain are very difficult to model in vitro, and thus require use of in vivo whole-animal models. For many neurodevelopmental and psychiatric disorders, abnormal circuit formation and refinement might be at the center of their pathophysiology. Importantly, many of the critical circuits and regional cell populations implicated in higher human cognitive function and in many psychiatric disorders are not present in lower mammalian brains, while these analogous areas are replicated in NHP brains. Indeed, neuropsychiatric disorders represent a tremendous health and economic burden globally. The emerging field of genetically modified NHP models has the potential to transform our study of higher brain function and dramatically facilitate the development of effective treatment for human brain disorders. In this paper, we discuss the importance of developing such models, the infrastructure and training needed to maximize the impact of such models, and ethical standards required for using these models.

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Roy, Abhijit Guha, Sailesh Conjeti, Nassir Navab, and Christian Wachinger. "Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control." NeuroImage 195 (July 2019): 11–22. http://dx.doi.org/10.1016/j.neuroimage.2019.03.042.

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Chansel‐Debordeaux, Lucie, and Erwan Bezard. "Local transgene expression and whole‐body transgenesis to model brain diseases in nonhuman primate." Animal Models and Experimental Medicine 2, no. 1 (January 29, 2019): 9–17. http://dx.doi.org/10.1002/ame2.12055.

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Robbins, Mike E., J. Daniel Bourland, J. Mark Cline, Kenneth T. Wheeler, and Sam A. Deadwyler. "A Model for Assessing Cognitive Impairment after Fractionated Whole-Brain Irradiation in Nonhuman Primates." Radiation Research 175, no. 4 (April 2011): 519–25. http://dx.doi.org/10.1667/rr2497.1.

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Spiegler, A., M. Mohajerani, and V. K. Jirsa. "Dynamics in response to focal stimulation in a whole-brain network model of mice." Brain Stimulation 10, no. 2 (March 2017): 536. http://dx.doi.org/10.1016/j.brs.2017.01.557.

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Irsyadi, Mohamad Khafid, and Ayu Silvi Lisvian Sari. "Penerapan Metode Pembelajaran Whole Brain Teaching pada Materi Maple." Jurnal Tadris Matematika 3, no. 1 (July 3, 2020): 31–42. http://dx.doi.org/10.21274/jtm.2020.3.1.31-42.

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This research is a Classroom Action Research which aims to describe the application of Whole Brain Teaching learning method to Maple material. The steps of the learning model are as follows: (1) Yes-Class, the lecturer observes the readiness of students in starting the lecture by saying "Class" and if the students are ready to respond by answering "Yes", (2) Micro-Lecture, the lecturer delivers Maple material in Computer course I, (3) Okay-Teach, students repeat the explanations that have been delivered by the lecturer, (4) Scoreboard, the lecturer give an assessment of students responses in repeating lecturers' explanations, (5) Hand and Eyes, the lecturer condition the class when the classroom becomes noisy, and (6) Comprehension Check, lecturer gives exercise. The subjects of this study are students of the second semester, Department of Mathematics Education, Academic year 2018/2019 at STKIP PGRI Blitar. The research instrument was the final cycle test, observation sheet and questionnaire. Based on the results of the end of the cycle test, out of 5 students it was found that 5 students had completed 100% learning with very good criteria. This is in accordance with the success criteria ≥ 80%. From the overall percentage, the average observation of lecturer activities reached 87.09% with good criteria. Meanwhile the overall average percentage of completeness of observations of student activities is 83.46% with good criteria. Based on the questionnaire responses of students obtained an average percentage of 83% with a good success rate. Thus it can be concluded that the research carried out was successful.

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Deco, Gustavo, Joana Cabral, Mark W. Woolrich, Angus B. A. Stevner, Tim J. van Hartevelt, and Morten L. Kringelbach. "Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data." NeuroImage 152 (May 2017): 538–50. http://dx.doi.org/10.1016/j.neuroimage.2017.03.023.

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Hormuth, David A., Jared A. Weis, Stephanie L. Barnes, Michael I. Miga, Vito Quaranta, and Thomas E. Yankeelov. "Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer." International Journal of Radiation Oncology*Biology*Physics 100, no. 5 (April 2018): 1270–79. http://dx.doi.org/10.1016/j.ijrobp.2017.12.004.

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Bálentová, Soňa, Petra Hnilicová, Dagmar Kalenská, Eva Baranovičová, Peter Muríň, Eva Hajtmanová, and Marian Adamkov. "Effect of fractionated whole-brain irradiation on brain and plasma in a rat model: Metabolic, volumetric and histopathological changes." Neurochemistry International 145 (May 2021): 104985. http://dx.doi.org/10.1016/j.neuint.2021.104985.

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NIEDER, CARSTEN, BÅRD MANNSÅKER, and ROSALBA YOBUTA. "Validation of a Graded Prognostic Model in Patients With Brain Metastases Treated With Whole-brain Radiotherapy Instead of Radiosurgery." In Vivo 35, no. 3 (2021): 1569–72. http://dx.doi.org/10.21873/invivo.12412.

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Moore, Jordan M., and Timothy J. DeVoogd. "Concerted and mosaic evolution of functional modules in songbird brains." Proceedings of the Royal Society B: Biological Sciences 284, no. 1854 (May 10, 2017): 20170469. http://dx.doi.org/10.1098/rspb.2017.0469.

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Vertebrate brains differ in overall size, composition and functional capacities, but the evolutionary processes linking these traits are unclear. Two leading models offer opposing views: the concerted model ascribes major dimensions of covariation in brain structures to developmental events, whereas the mosaic model relates divergent structures to functional capabilities. The models are often cast as incompatible, but they must be unified to explain how adaptive changes in brain structure arise from pre-existing architectures and developmental mechanisms. Here we show that variation in the sizes of discrete neural systems in songbirds, a species-rich group exhibiting diverse behavioural and ecological specializations, supports major elements of both models. In accordance with the concerted model, most variation in nucleus volumes is shared across functional domains and allometry is related to developmental sequence. Per the mosaic model, residual variation in nucleus volumes is correlated within functional systems and predicts specific behavioural capabilities. These comparisons indicate that oscine brains evolved primarily as a coordinated whole but also experienced significant, independent modifications to dedicated systems from specific selection pressures. Finally, patterns of covariation between species and brain areas hint at underlying developmental mechanisms.

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