Mapping explanatory language in neuroscience

[1]  C. Pincock,et al.  On the Role of Erotetic Constraints in Non-causal Explanations , 2023, Philosophy of Science.

[2]  H. K. Andersen.  Leveraging Distortions: Explanation, Idealization, and Universality in Science , 2023, Philosophical Review.

[3]  Moti Mizrahi,et al.  Is Philosophy Exceptional? A Corpus-Based, Quantitative Study , 2022, Social Epistemology.

[4]  Kareem Khalifa,et al.  Decoupling Topological Explanations from Mechanisms , 2022, Philosophy of Science.

[5]  Moti Mizrahi,et al.  Philosophical reasoning about science: a quantitative, digital study , 2022, Synthese.

[6]  P. Maffezioli,et al.  When philosophy (of science) meets formal methods: a citation analysis of early approaches between research fields , 2022, Synthese.

[7]  Kareem Khalifa,et al.  Integrating Philosophy of Understanding With the Cognitive Sciences , 2022, Frontiers in Systems Neuroscience.

[8]  J. Knobe,et al.  Changing use of formal methods in philosophy: late 2000s vs. late 2010s , 2021, Synthese.

[9]  J. Bickle.  Tinkering in the Lab , 2021, The Tools of Neuroscience Experiment.

[10]  Kareem Khalifa,et al.  The directionality of topological explanations , 2021, Synthese.

[11]  Collin Rice.  Leveraging Distortions , 2021 .

[12]  Lauren N. Ross.  Causal Concepts in Biology: How Pathways Differ from Mechanisms and Why It Matters , 2020, The British Journal for the Philosophy of Science.

[13]  Luis H. Favela.  The dynamical renaissance in neuroscience , 2020, Synthese.

[14]  Luis H. Favela.  Dynamical systems theory in cognitive science and neuroscience , 2020 .

[15]  Daniel Kostić,et al.  General theory of topological explanations and explanatory asymmetry , 2020, Philosophical Transactions of the Royal Society B.

[16]  Claus C. Hilgetag,et al.  Unifying the essential concepts of biological networks: biological insights and philosophical foundations , 2020, Philosophical Transactions of the Royal Society B.

[17]  L. Lombardi,et al.  A State Space Approach to Dynamic Modeling of Mouse-Tracking Data , 2019, Front. Psychol..

[18]  Stiliyan Kalitzin,et al.  Epilepsy as a manifestation of a multistate network of oscillatory systems , 2019, Neurobiology of Disease.

[19]  Christophe Malaterre,et al.  What Is This Thing Called Philosophy of Science? A Computational Topic-Modeling Perspective, 1934–2015 , 2019, HOPOS: The Journal of the International Society for the History of Philosophy of Science.

[20]  Ewan Dunbar,et al.  Mouse tracking as a window into decision making , 2019, Behavior Research Methods.

[21]  Daniel Kostić.  Minimal Structure Explanations, Scientific Understanding and Explanatory Depth , 2019, Perspectives on Science.

[22]  Daniel Kostić.  Unifying the Debates: Mathematical and Non-Causal Explanations , 2019, Perspectives on Science.

[23]  Stiliyan Kalitzin,et al.  Expert system for pharmacological epilepsy treatment prognosis and optimal medication dose prescription: computational model and clinical application , 2019, APPIS.

[24]  Harish S. Bhat,et al.  Equations of mind: Data science for inferring nonlinear dynamics of socio-cognitive systems , 2018, Cognitive Systems Research.

[25]  Devika Narain,et al.  A Dynamical Systems Perspective on Flexible Motor Timing , 2018, Trends in Cognitive Sciences.

[26]  Olaf Sporns,et al.  Network-Based Asymmetry of the Human Auditory System , 2018, bioRxiv.

[27]  Alfredo Vernazzani,et al.  The structure of sensorimotor explanation , 2017, Synthese.

[28]  Fabian M. Suchanek,et al.  Relating Brain Structures To Open-Ended Descriptions Of Cognition , 2017 .

[29]  S. Glennan.  The New Mechanical Philosophy , 2017 .

[30]  M. Breakspear.  Dynamic models of large-scale brain activity , 2017, Nature Neuroscience.

[31]  Carl F. Craver,et al.  The Explanatory Power of Network Models , 2016, Philosophy of Science.

[32]  Daniel Kostic,et al.  Mechanistic and topological explanations: an introduction , 2016, Synthese.

[33]  D. Bassett,et al.  Mind Control: Frontiers in Guiding the Mind , 2016 .

[34]  A. Venturelli.  A Cautionary Contribution to the Philosophy of Explanation in the Cognitive Neurosciences , 2016, Minds and Machines.

[35]  Graham L. Baum,et al.  The modular organization of human anatomical brain networks: Accounting for the cost of wiring , 2016, Network Neuroscience.

[36]  Fabio Pasqualetti,et al.  Optimal trajectories of brain state transitions , 2016, NeuroImage.

[37]  D. Walsh.  Variance, Invariance and Statistical Explanation , 2015 .

[38]  Eve Marder,et al.  Understanding Brains: Details, Intuition, and Big Data , 2015, PLoS biology.

[39]  C. Hilgetag,et al.  Is the brain really a small-world network? , 2015, Brain Structure and Function.

[40]  Víctor M. Verdejo.  The systematicity challenge to anti-representational dynamicism , 2015, Synthese.

[41]  Robert W. Batterman,et al.  Minimal Model Explanations , 2014, Philosophy of Science.

[42]  Jean M. Vettel,et al.  Controllability of structural brain networks , 2014, Nature Communications.

[43]  Haim Sompolinsky,et al.  Computational neuroscience: beyond the local circuit , 2014, Current Opinion in Neurobiology.

[44]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[45]  S. Dehaene,et al.  How do we convert a number into a finger trajectory? , 2013, Cognition.

[46]  M. Corbetta,et al.  Dynamic functional connectivity: Promise, issues, and interpretations , 2013, NeuroImage.

[47]  L. Darden,et al.  In Search of Mechanisms: Discoveries across the Life Sciences , 2013 .

[48]  Marc Lange.  What Makes a Scientific Explanation Distinctively Mathematical? , 2013, The British Journal for the Philosophy of Science.

[49]  M. Sahani,et al.  Cortical control of arm movements: a dynamical systems perspective. , 2013, Annual review of neuroscience.

[50]  J. Woodward.  II—James Woodward: Mechanistic Explanation: Its Scope and Limits , 2013 .

[51]  J. Dupré.  I—John Dupré: Living Causes , 2013 .

[52]  James A. Overton.  “Explain” in scientific discourse , 2013, Synthese.

[53]  Xabier E. Barandiaran,et al.  A Dynamical Systems Account of Sensorimotor Contingencies , 2013, Front. Psychol..

[54]  S. Schaal,et al.  Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors , 2013, Neural Computation.

[55]  V. Hardcastle,et al.  Philosophy of Neuroscience , 2012 .

[56]  O. Sporns,et al.  Functional connectivity between anatomically unconnected areas is shaped by collective network-level effects in the macaque cortex. , 2012, Cerebral cortex.

[57]  Yuye Li,et al.  Coherence-Resonance-Induced Neuronal Firing near a Saddle-Node and Homoclinic Bifurcation Corresponding to Type-I Excitability , 2011 .

[58]  Daniel A. Weiskopf,et al.  Models and mechanisms in psychological explanation , 2011, Synthese.

[59]  Thomas A. Farmer,et al.  Hand in Motion Reveals Mind in Motion , 2011, Front. Psychology.

[60]  Michael T. Turvey,et al.  Philosophy for the Rest of Cognitive Science , 2011, Top. Cogn. Sci..

[61]  Gualtiero Piccinini,et al.  Integrating psychology and neuroscience: functional analyses as mechanism sketches , 2011, Synthese.

[62]  Edward T. Bullmore,et al.  Modular and Hierarchically Modular Organization of Brain Networks , 2010, Front. Neurosci..

[63]  Olaf Sporns,et al.  Can structure predict function in the human brain? , 2010, NeuroImage.

[64]  Andreas Daffertshofer,et al.  The relationship between structural and functional connectivity: Graph theoretical analysis of an EEG neural mass model , 2010, NeuroImage.

[65]  J. A. Scott Kelso,et al.  Instabilities and Phase Transitions in Human Brain and Behavior , 2010, Front. Hum. Neurosci..

[66]  Robert W. Batterman,et al.  On the Explanatory Role of Mathematics in Empirical Science , 2010, The British Journal for the Philosophy of Science.

[67]  Aravinthan D. T. Samuel,et al.  Caenorhabditis elegans: a model system for systems neuroscience , 2009, Current Opinion in Neurobiology.

[68]  Damian G. Stephen,et al.  The Self-Organization of Insight: Entropy and Power Laws in Problem Solving , 2009, J. Probl. Solving.

[69]  S. Epstein,et al.  Gamma oscillations mediate stimulus competition and attentional selection in a cortical network model , 2008, Proceedings of the National Academy of Sciences.

[70]  N. Logothetis.  What we can do and what we cannot do with fMRI , 2008, Nature.

[71]  Michael J. Spivey,et al.  Action Dynamics Reveal Parallel Competition in Decision Making , 2008, Psychological science.

[72]  A. Chemero,et al.  After the Philosophy of Mind: Replacing Scholasticism with Science* , 2008, Philosophy of Science.

[73]  W. K. Simmons,et al.  A common neural substrate for perceiving and knowing about color , 2007, Neuropsychologia.

[74]  Olaf Sporns,et al.  Network structure of cerebral cortex shapes functional connectivity on multiple time scales , 2007, Proceedings of the National Academy of Sciences.

[75]  C. Craver.  Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience , 2007 .

[76]  B. Bahrami,et al.  Attentional Load Modulates Responses of Human Primary Visual Cortex to Invisible Stimuli , 2007, Current Biology.

[77]  R. Passingham,et al.  Reading Hidden Intentions in the Human Brain , 2007, Current Biology.

[78]  Christopher L. Asplund,et al.  Isolation of a Central Bottleneck of Information Processing with Time-Resolved fMRI , 2006, Neuron.

[79]  Á. Pascual-Leone,et al.  Diminishing Reciprocal Fairness by Disrupting the Right Prefrontal Cortex , 2006, Science.

[80]  K. Yu,et al.  Attentional modulation of sensorimotor processes in the absence of perceptual awareness , 2006, Proceedings of the National Academy of Sciences.

[81]  Richard Henson,et al.  Forward inference using functional neuroimaging: dissociations versus associations , 2006, Trends in Cognitive Sciences.

[82]  Robert F. Port,et al.  The Dynamical Systems Hypothesis in Cognitive Science , 2006 .

[83]  E. Bullmore,et al.  A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs , 2006, The Journal of Neuroscience.

[84]  Olaf Sporns,et al.  The Human Connectome: A Structural Description of the Human Brain , 2005, PLoS Comput. Biol..

[85]  James S Magnuson,et al.  Moving hand reveals dynamics of thought. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[86]  Helen E. Fisher,et al.  Reward, motivation, and emotion systems associated with early-stage intense romantic love. , 2005, Journal of neurophysiology.

[87]  A. Cowey,et al.  Striate cortex (V1) activity gates awareness of motion , 2005, Nature Neuroscience.

[88]  Nikos K Logothetis,et al.  On the nature of the BOLD fMRI contrast mechanism. , 2004, Magnetic resonance imaging.

[89]  K. Swartz,et al.  Towards a structural view of gating in potassium channels , 2004, Nature Reviews Neuroscience.

[90]  H. Robinson,et al.  Threshold firing frequency-current relationships of neurons in rat somatosensory cortex: type 1 and type 2 dynamics. , 2004, Journal of neurophysiology.

[91]  Marcus Kaiser,et al.  Edge vulnerability in neural and metabolic networks , 2004, Biological Cybernetics.

[92]  Z. Oltvai,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[93]  L. Barsalou,et al.  Sensorimotor simulations underlie conceptual representations: Modality-specific effects of prior activation , 2004, Psychonomic bulletin & review.

[94]  Jonathan D. Cohen,et al.  The Neural Basis of Economic Decision-Making in the Ultimatum Game , 2003, Science.

[95]  Christopher Hitchcock,et al.  Explanatory generalizations, part II: Plumbing explanatory depth , 2003 .

[96]  Christopher Hitchcock,et al.  Explanatory Generalizations, Part I: A Counterfactual Account , 2003 .

[97]  Tim Lewens,et al.  The Trials of Life: Natural Selection and Random Drift* , 2002, Philosophy of Science.

[98]  J. Kelso,et al.  Cortical coordination dynamics and cognition , 2001, Trends in Cognitive Sciences.

[99]  P. Machamer,et al.  Thinking about Mechanisms , 2000, Philosophy of Science.

[100]  Stephan Kopp,et al.  RNA Shape Space Topology , 1999, Artificial Life.

[101]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[102]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[103]  J. Connor.  Neural repetitive firing: a comparative study of membrane properties of crustacean walking leg axons. , 1975, Journal of neurophysiology.

[104]  Richard F. Betzel,et al.  Supplement to : Optimally controlling the human connectome : the role of network topology , 2016 .

[105]  Daniel Kostić.  The topological realization , 2016, Synthese.

[106]  Raoul Gervais,et al.  Mechanistic and non-mechanistic varieties of dynamical models in cognitive science: explanatory power, understanding, and the ‘mere description’ worry , 2014, Synthese.

[107]  J. Rapoport,et al.  The anatomical distance of functional connections predicts brain network topology in health and schizophrenia. , 2013, Cerebral cortex.

[108]  M. Chirimuuta.  Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience , 2013, Synthese.

[109]  Y. Li 李,et al.  Coherence-Resonance-Induced Neuronal Firing near a Saddle-Node and Homoclinic Bifurcation Corresponding to Type-I Excitability , 2011 .

[110]  N. Ambady,et al.  When Two Become One: Temporally Dynamic Integration of the Face and Voice , 2011, CogSci.

[111]  L. Barsalou.  Grounded cognition. , 2008, Annual review of psychology.

[112]  Peter F. Stadler,et al.  The Topology of Evolutionary Biology , 2004 .

[113]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[114]  Lindley Darden,et al.  Discovering Complexity , 1996 .

[115]  Helen E. Longino,et al.  Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research , 1995 .