Release Date: 2024-06-19

Cerebral Cortex Anatomy

Turan Koc (Author)

Release Date: 2024-06-19

Approximately 10-20% of idiopathic pulmonary fibrosis cases have a familial component, suggesting a strong genetic influence. While most cases are sporadic, familial cases provide critical insights into genetic predispositions and mechanisms. TERT and TERC mutations which encode components of telomerase, are among the most common in familial idiopathic pulmonary fibrosis. They lead to shortened telomeres [...]

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Work TypeMonograph
Internal ReferenceNBL72
Edition1
DOIhttps://doi.org/10.69860/nobel.9786053359470
ISBN978-605-335-947-0 (PAPERBACK)
Page Count168
Print Lenghtvi+162
PlaceIstanbul
Copyright HolderNobel Tıp Kitabevleri
Licensehttps://nobelpub.com/publish-with-us/copyright-and-licensing
BICMFC
BISACMED005000
THEMAMFC
Approximately 10-20% of idiopathic pulmonary fibrosis cases have a familial component, suggesting a strong genetic influence. While most cases are sporadic, familial cases provide critical insights into genetic predispositions and mechanisms. TERT and TERC mutations which encode components of telomerase, are among the most common in familial idiopathic pulmonary fibrosis. They lead to shortened telomeres and premature cellular aging. SFTPC and SFTPA2 mutations in genes encoding surfactant proteins can disrupt normal lung function and homeostasis, leading to increased fibrosis. MUC5B is a common polymorphism in the promoter region of the MUC5B gene is strongly associated with both familial and sporadicidiopathic pulmonary fibrosis. This variant increases the expression of mucin, which may contribute to aberrant wound healing and fibrosis.
1. Cerebral Cortex
2. Lobes of the Brain
3. Functional Areas
4. Association Areas
5. Limbic System
6. Components of Basal Nuclei
7. Brief Clinical Syndromes

    Turan Koc (Author)
    Assistant Professor, Kahramanmaraş Sütçü İmam University
    https://orcid.org/0000-0001-6970-3351
    3Dr. Koç is a fresh-young writer and researcher passionate about neuroanatomy and neuroscience. Holding a MsC and Ph.D. in Anatomy from Mersin University Medical Faculty, Dr. Koç has contributed extensively to the field through numerous publications, including book chapters, journal articles, and industry reports. With a keen eye for detail and a talent for clear and engaging writing, Dr. Koç brings complex concepts to life for a diverse audience. When not immersed in writing, Dr. Koç enjoys 3D neuronal imaging, dissection, painting, and reading anime, further enriching their perspective and creativity. Dr. Koç was awarded the second-best oral presentation award for his master’s thesis, "Early cranial irradiation alters epigenetics parallel to reduced hippocampal neurogenesis in adult mice," at the 13th National Neuroscience Congress he attended in 2015.In addition to receiving good traditional gross anatomy training, Dr. Koç has been involved in experimental studies in neuroscience, especially cognitive and behavioral sciences. In 2019, he studied the cognitive ability and hemisphere dominance of the motor cortex in mice in the Neuronal Plasticity department at the Max Planck Institute für Physichatrie. He also examined the sexual behavior of mice in deprivation states and evaluated ultrasonic vocalization and social interaction. He has been a visiting scientist at Coimbra University, Center for Neuroscience and Cell Biology since 2024 to conduct neuroscience-related experiments, especially optogenetics and prosocial behavior. Dr. Koç currently works as an assistant professor at Kahramanmaraş Sütçü İmam Faculty of Medicine, Department of Anatomy.

    • Crick, F., & Asanuma, C. (1986). Certain aspects of the anatomy and physiology of the cerebral cortex. Parallel distributed processing, 2, 333-371.

    • Shipp, S. (2007). Structure and function of the cerebral cortex. Current Biology, 17(12), R443-R449.

    • Zilles, K., Palomero‐Gallagher, N., & Schleicher, A. (2004). Transmitter receptors and functional anatomy of the cerebral cortex. Journal of anatomy, 205(6), 417-432.

    • McCulloch, W. S. (1944). The functional organization of the cerebral cortex. Physiological reviews, 24(3), 390-407.

    • Kiloh, L. G., McComas, A. J., & Osselton, J. W. (1972). Anatomy and physiology of cerebral cortex. Clinical electroencephalography. London: Butterworths, 1-20.

    • Sporns, O., Tononi, G., & Edelman, G. M. (2002). Theoretical neuroanatomy and the connectivity of the cerebral cortex. Behavioural brain research, 135(1-2), 69-74.

    • Bartels, A., & Zeki, S. (2005). The chronoarchitecture of the cerebral cortex. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1456), 733-750.

    • Abeles, M. (1991). Corticonics: Neural circuits of the cerebral cortex. Cambridge University Press.

    • Swenson, R. S., & Gulledge, A. T. (2017). The cerebral cortex. In Conn's Translational Neuroscience (pp. 263-288). Academic Press.

    • Pathak, A., N. Menon, S., & Sinha, S. (2020). Mesoscopic architecture enhances communication across the Macaque connectome revealing structure-function correspondence in the brain.

    • Ma, Y., Zhou, X., & Wu, W. (2022). A Stochastic Process Model for Time Warping Functions.

    • Hjelm, M. (2019). Human Visual Understanding for Cognition and Manipulation -- A primer for the roboticist.

    • M. Innocenti, G., Schmidt, K., Milleret, C., Fabri, M., G. Knyazeva, M., Battaglia-Mayer, A., Aboitiz, F., Ptito, M., Caleo, M., A. Marzi, C., Barakovic, M., Lepore, F., & Caminiti, R. (2022). The functional characterization of callosal connections.

    • J. Bintrim, S. & C. Berkelbach, T. (2021). Full-frequency dynamical Bethe-Salpeter equation without frequency and a study of double excitations.

    • Pessoa, L. (2014). Understanding brain networks and brain organization.

    • Pessoa, L. (2019). Intelligent architectures for robotics: The merging of cognition and emotion.

    • Saini, F., Dell’Acqua, F., & Strydom, A. (2022). Structural Connectivity in Down Syndrome and Alzheimer’s Disease.

    • W. Swanson, L., D. Hahn, J., & Sporns, O. (2017). Organizing principles for the cerebral cortex network of commissural and association connections.

    • Ghulam‐Jelani, Z., Barrios‐Martinez, J., Eguiluz‐Melendez, A., Gomez, R., Anania, Y., & Yeh, F. C. (2021). Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

    • Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R., Yeh, C. H., Zhao, T., & J. O'Donnell, L. (2021). Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review.

    • Yang, Y., Zheng, Z., Liu, L., Zheng, H., Zhen, Y., Zheng, Y., Wang, X., & Tang, S. (2022). Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes.

    • S. Buyanova, I. & Arsalidou, M. (2021). Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review.

    • Zhao, Y., Li, L., & S. Caffo, B. (2019). Multimodal Neuroimaging Data Integration and Pathway Analysis.

    • W. Bohland, J., Wu, C., Barbas, H., Bokil, H., Bota, M., C. Breiter, H., T. Cline, H., C. Doyle, J., J. Freed, P., J. Greenspan, R., N. Haber, S., Hawrylycz, M., G. Herrera, D., C. Hilgetag, C., Josh Huang, Z., Jones, A., G. Jones, E., J. Karten, H., Kleinfeld, D., Kotter, R., A. Lester, H., M. Lin, J., D. Mensh, B., Mikula, S., Panksepp, J., L. Price, J., Safdieh, J., B. Saper, C., D. Schiff, N., D. Schmahmann, J., W. Stillman, B., Svoboda, K., W. Swanson, L., W. Toga, A., C. Van Essen, D., D. Watson, J., & P. Mitra, P. (2009). A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale.

    • Islam, R. & Kaffman, A. (2021). White-Matter Repair as a Novel Therapeutic Target for Early Adversity.

    • Pasquini, L., Di Napoli, A., Camilla Rossi-Espagnet, M., Visconti, E., Napolitano, A., Romano, A., Bozzao, A., K. Peck, K., & I. Holodny, A. (2022). Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications.

    • Piras, F., Vecchio, D., Kurth, F., Piras, F., Banaj, N., Ciullo, V., Luders, E., & Spalletta, G. (2021). Corpus callosum morphology in major mental disorders: a magnetic resonance imaging study.

    • Thomas, F., Gallea, C., Moulier, V., Bouaziz, N., Valero-Cabré, A., & Januel, D. (2022). Local alterations of left arcuate fasciculus and transcallosal white matter microstructure in schizophrenia patients with medication-resistant auditory verbal hallucinations: A pilot study.

    • Svoboda, W., McManamon, B., & Schwartz, S. (2021). Replication of SARS-CoV-2 mutation analysis suggests differences in per-protein mutation characteristics.

    • Parkes, L., M. Moore, T., E. Calkins, M., Cieslak, M., R. Roalf, D., H. Wolf, D., C. Gur, R., E. Gur, R., D. Satterthwaite, T., & S. Bassett, D. (2020). Network controllability in transmodal cortex predicts psychosis spectrum symptoms.

    • Tang, H., Ma, G., Guo, L., Fu, X., Huang, H., & Zhang, L. (2022). Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model.

    • D. Neacsiu, A., Szymkiewicz, V., T. Galla, J., Li, B., Kulkarni, Y., & W. Spector, C. (2022). The neurobiology of misophonia and implications for novel, neuroscience-driven interventions.

    • Pessoa, L. (2010). Emergent processes in cognitive-emotional interactions.

    • Ventura, P., Dell'Agli, F., Lugaro, M., Romano, D., Tailo, M., & Yague, A. (2020). Gas and dust from metal-rich AGB stars.

    • Monticelli, M., Zeppa, P., Mammi, M., Penner, F., Melcarne, A., Zenga, F., & Garbossa, D. (2021). Where We Mentalize: Main Cortical Areas Involved in Mentalization.

    • J. Jackson, D. (2023). Generalised Proper Time and the Universal Bootstrap.

    • Mishra, S. & S. Tiwary, U. (2019). A Cognition-Affect Integrated Model of Emotion.

    • Van Mao, C., F. P. Araujo, M., Nishimaru, H., Matsumoto, J., Hai Tran, A., Hori, E., Ono, T., & Nishijo, H. (2017). Pregenual Anterior Cingulate Gyrus Involvement in Spontaneous Social Interactions in Primates—Evidence from Behavioral, Pharmacological, Neuropsychiatric, and Neurophysiological Findings.

    • J. Wanger, T. (2018). An ALE meta-analytic comparison of verbal working memory tasks.

    • Yu, X., Ruan, Y., Zhang, Y., Wang, J., Liu, Y., Zhang, J., & Zhang, L. (2021). Cognitive Neural Mechanism of Social Anxiety Disorder: A Meta-Analysis Based on fMRI Studies.

    • Barttfeld, P., Wicker, B., Cukier, S., Navarta, S., Lew, S., Leiguarda, R., & Sigman, M. (2012). State-dependent changes of connectivity patterns and functional brain network topology in Autism Spectrum Disorder.

    • Dai, W., Liu, R. H., Qiu, E., Liu, Y., Chen, Z., Chen, X., Ao, R., Zhuo, M., & Yu, S. (2021). Cortical mechanisms in migraine.

    • J. Pondelis, N. & A. Moulton, E. (2022). Supraspinal Mechanisms Underlying Ocular Pain.

    • S. Chester, D., S. Pond, R., B. Richman, S., & Nathan DeWall, C. (2012). The optimal calibration hypothesis: how life history modulates the brain's social pain network.

    • Vadovičová, K. & Gasparotti, R. (2013). Reward and adversity processing circuits, their competition and interactions with dopamine and serotonin signaling.

    • D. Medaglia, J. (2018). Clarifying Cognitive Control and the Controllable Connectome.

    • Tang, E., Giusti, C., Baum, G., Gu, S., Pollock, E., E. Kahn, A., Roalf, D., M. Moore, T., Ruparel, K., C. Gur, R., E. Gur, R., D. Satterthwaite, T., & S. Bassett, D. (2016). Developmental increases in white matter network controllability support a growing diversity of brain dynamics.

    • Upadhyay, J., Patra, J., Tiwari, N., Salankar, N., Nazam Ansari, M., & Ahmad, W. (2021). Dysregulation of Multiple Signaling Neurodevelopmental Pathways during Embryogenesis: A Possible Cause of Autism Spectrum Disorder.

    • P. Singh, S. & Karkare, S. (2017). Stress, Depression and Neuroplasticity.

    • Wang, Y., Vantieghem, I., Dong, D., Nemegeer, J., De Mey, J., Van Schuerbeek, P., Marinazzo, D., & Vandekerckhove, M. (2022). Approaching or Decentering? Differential Neural Networks Underlying Experiential Emotion Regulation and Cognitive Defusion.

    • Banwinkler, M., Theis, H., Prange, S., & van Eimeren, T. (2022). Imaging the Limbic System in Parkinson’s Disease—A Review of Limbic Pathology and Clinical Symptoms.

    • Ji, X., Cheng, W., Zhang, J., Ge, T., Sun, L., Wang, Y., & Feng, J. (2011). Increased Coupling in the Saliency Network is the main cause/effect of Attention Deficit Hyperactivity Disorder.

    • Kabbara, A., Robert, G., Khalil, M., Verin, M., Benquet, P., & Hassan, M. (2021). An Electroencephalography connectome predictive model of major depressive disorder severity.

    • Adams, R. & S David, A. (2007). Patterns of anterior cingulate activation in schizophrenia: a selective review.

    • Bowirrat, A., J.H. Chen, T., Blum, K., Madigan, M., A. Bailey, J., Lih Chuan Chen, A., William Downs, B., R. Braverman, E., Radi, S., L. Waite, R., Kerner, M., Giordano, J., Morse, S., Oscar-Berman, M., & Gold, M. (2010). Neuro-psychopharmacogenetics and Neurological Antecedents of Posttraumatic Stress Disorder: Unlocking the Mysteries of Resilience and Vulnerability.

    • Mandic Ferreira Furtado, L., Morais Bernardes, H., Alexandre de Souza Félix Nunes, F., Alberto Gonçalves, C., Aloysio Da Costa Val Filho, J., & Silva de Miranda, A. (2022). The Role of Neuroplasticity in Improving the Decision-Making Quality of Individuals With Agenesis of the Corpus Callosum: A Systematic Review.

    • Shoeibi, A., Ghassemi, N., Khodatars, M., Moridian, P., Khosravi, A., Zare, A., M. Gorriz, J., Hossein Chale-Chale, A., Khadem, A., & Rajendra Acharya, U. (2022). Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression.

    • Misra, R. & K. Gandhi, T. (2023). Functional Connectivity Dynamics show Resting-State Instability and Rightward Parietal Dysfunction in ADHD.

    • Dehghani, A., Soltanian-Zadeh, H., & Hossein-Zadeh, G. A. (2020). Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback.

    • Palomero-Gallagher, N., Hoffstaedter, F., Mohlberg, H., B Eickhoff, S., Amunts, K., & Zilles, K. (2019). Human Pregenual Anterior Cingulate Cortex: Structural, Functional, and Connectional Heterogeneity.

    • Zhuang, P., Li, H., Yang, R., & Huang, J. (2022). ReLoc: A Restoration-Assisted Framework for Robust Image Tampering Localization.

    • Dean, T., Fan, C., E. Lewis, F., & Sano, M. (2019). Biological Blueprints for Next Generation AI Systems.

    • Reck Miranda, E. (2020). On Interfacing the Brain with Quantum Computers: An Approach to Listen to the Logic of the Mind.

    • Lu, H. Y., S Lorenc, E., Zhu, H., Kilmarx, J., Sulzer, J., Xie, C., N Tobler, P., J Watrous, A., L Orsborn, A., Lewis-Peacock, J., & R Santacruz, S. (2021). Multi-scale neural decoding and analysis.

    • Llorens, A., Trébuchon, A., Liégeois-Chauvel, C., & Alario, F. X. (2011). Intra-Cranial Recordings of Brain Activity During Language Production.

    • Onoda, K., Kawagoe, T., Zheng, H., & Yamaguchi, S. (2017). Theta band transcranial alternating current stimulations modulates network behavior of dorsal anterior cingulate cortex.

    • Ting To, W., Eroh, J., Hart, J., & Vanneste, S. (2018). Exploring the effects of anodal and cathodal high definition transcranial direct current stimulation targeting the dorsal anterior cingulate cortex.

    • K Rao, A., K Menon, V., Bhavsar, A., Roy Chowdhury, S., Negi, R., & Dutt, V. (2024). Classification of attention performance post-longitudinal tDCS via functional connectivity and machine learning methods.

    • Höistad, M., Segal, D., Takahashi, N., Sakurai, T., D. Buxbaum, J., & R. Hof, P. (2009). Linking White and Grey Matter in Schizophrenia: Oligodendrocyte and Neuron Pathology in the Prefrontal Cortex.

    • Pessoa, L. (2014). Understanding brain networks and brain organization.

    • Pessoa, L. (2019). Intelligent architectures for robotics: The merging of cognition and emotion.

    • Saini, F., Dell’Acqua, F., & Strydom, A. (2022). Structural Connectivity in Down Syndrome and Alzheimer’s Disease.

    • W. Swanson, L., D. Hahn, J., & Sporns, O. (2017). Organizing principles for the cerebral cortex network of commissural and association connections.

    • Ghulam‐Jelani, Z., Barrios‐Martinez, J., Eguiluz‐Melendez, A., Gomez, R., Anania, Y., & Yeh, F. C. (2021). Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

    • Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R., Yeh, C. H., Zhao, T., & J. O'Donnell, L. (2021). Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review.

    • Yang, Y., Zheng, Z., Liu, L., Zheng, H., Zhen, Y., Zheng, Y., Wang, X., & Tang, S. (2022). Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes.

    • Pessoa, L. (2014). Understanding brain networks and brain organization.

    • Pessoa, L. (2019). Intelligent architectures for robotics: The merging of cognition and emotion.

    • Saini, F., Dell’Acqua, F., & Strydom, A. (2022). Structural Connectivity in Down Syndrome and Alzheimer’s Disease.

    • W. Swanson, L., D. Hahn, J., & Sporns, O. (2017). Organizing principles for the cerebral cortex network of commissural and association connections.

    • Ghulam‐Jelani, Z., Barrios‐Martinez, J., Eguiluz‐Melendez, A., Gomez, R., Anania, Y., & Yeh, F. C. (2021). Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

    • Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R., Yeh, C. H., Zhao, T., & J. O'Donnell, L. (2021). Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review.

    • Y., Zheng, Z., Liu, L., Zheng, H., Zhen, Y., Zheng, Y., Wang, X., & Tang, S. (2022). Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes.

    • Pessoa, L. (2014). Understanding brain networks and brain organization.

    • Pessoa, L. (2019). Intelligent architectures for robotics: The merging of cognition and emotion.

    • Saini, F., Dell’Acqua, F., & Strydom, A. (2022). Structural Connectivity in Down Syndrome and Alzheimer’s Disease.

    • W. Swanson, L., D. Hahn, J., & Sporns, O. (2017). Organizing principles for the cerebral cortex network of commissural and association connections.

    • Ghulam‐Jelani, Z., Barrios‐Martinez, J., Eguiluz‐Melendez, A., Gomez, R., Anania, Y., & Yeh, F. C. (2021). Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

    • Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R., Yeh, C. H., Zhao, T., & J. O'Donnell, L. (2021). Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review.

    • Yang, Y., Zheng, Z., Liu, L., Zheng, H., Zhen, Y., Zheng, Y., Wang, X., & Tang, S. (2022). Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes.

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