Notice bibliographique
Résumé
Networks of the Brain, by Olaf Sporns. The MIT Press, 2010, 375 pages (ISBN 978-0-262-01469-4, CA $40.00 Hardcover) Reviewed by MARK DALEY and JODY C. CULHAM DOI: 10.1037/00025503 The history of psychology and neuroscience is filled with a tension between theories emphasising localization of brain functions versus holistic processing. A third way has been emerging - viewing brain and mind in terms of dynamic, interacting networks. In his recent book Networks of the Brain, Olaf Sporns provides a much-welcomed synthesis of the network perspective. This perspective is not entirely new. First, as indicated by the well-selected quotes from eminent historical figures - Golgi, Cajal, Broca, James, and Hebb included - that Sporns employs to introduce each chapter, network ideas have been considered for some time. Second, the core tools used to analyse networks, primarily graph theory (which dates back to 1 8th century mathematician Leonhard Euler), are well-established. Graph theory has revealed common principles that define small-world networks - in which clusters of sparse connections allow short paths between any two nodes - in applications as diverse as social circles, epidemiology and transportation routes. What is new - and exciting - is the application of network analytic approaches to neuroscience: over the past decade, graph theory has been applied to the wiring diagrams or connectomes within brains. Specific neuroscience applications span a range of scales: thousands of connections between hundreds of neurons in the simple roundworm, Caenorhabditis elegans; hundreds of connections between dozens of functional areas of the human brain; and potentially even the trillions of connections between billions of neurons in the human brain. Sporns provides a comprehensive, tour-de-force overview of the cutting edge of the application of network science to neuroscience. This is a book that everyone with an interest in brain function should read. It provides a grand overview of a field that will undoubtedly hold a central position in the future of neuroscience - if it has not already taken that position now. The scope of the book is enormous, yet relatively self-contained. Sporns masterfully reviews and explains core concepts from many neuroscientific, psychological, mathematical, physical, and engineering disciplines in a way which is at once accessible to nonspecialists and, in most cases, does not sacrifice correctness or rigour to achieve that goal. The use of clear, natural language explanations in place of mathematical in order to appeal to a broader authence is commendable. Despite the inherent difficulty of such an undertaking, it is exactly the authence members who might be put off by too many equations who are most likely to benefit immediately from considering the approaches reviewed by Sporns. Chapter 1 provides an appetizer of sorts, briefly and clearly outlining a compelling argument for why one might wish to read the rest of the book. Chapters 2 and 3 provide the necessary background in network theory and neuroscience methods, respectively, to make sense of the rest of the book. The exposition of this material is clear, well written, and given in a wonderfully informal style - as though being guided through a new field over drinks by a very patient and knowledgeable colleague. Chapters 4-7 outline the application of network theoretic approaches to connections within anatomical circuits in the brain. Sporns is at the top of his game here and writes as one who has masterful knowledge of both the current state of the field and where it is likely to go. Particularly impressive is Sporns' very careful treatment of evolution in Chapter 7; he provides a network-theoretic framework for thinking about structural evolution in the brain by calling on a deep, broad range of supporting literature and making the full argument in terms of modern evolutionary theory. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».