Carl F Craver
Dados Biográficos
| ID | 461797 |
|---|---|
| NOME | Carl F Craver |
| PRENOMES | Carl F |
| SOBRENOME | Craver |
| ASSINATURA | CRAVER C F |
| AFILIAÇÕES | Washington University in St. Louis |
| ORCID | 0000-0002-0289-1957 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 32 |
| TOTAL DE CITAÇÕES | 870 |
| TOTAL COMO AUTOR | 32 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2000 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 12 |
Examining temporal orientation without narrative construction in young and older adults
Defending levels by trading waves for trees
Phenomenological Laws and Mechanistic Explanations
In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal m…
Experimental Artefacts
Mind Design III
Cognitive ontology and the search for neural mechanisms
The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem , scientists often assess whether the tasks engage the same neural mechanisms…
Tools of Neuroscience Experiment
Constitutive relevance & mutual manipulability revisited
The Tools of Neuroscience Experiment
Remembering
Is it time? Episodic imagining and the discounting of delayed and probabilistic rewards in young and older adults
Gloomy Prospects and Roller Coasters
We address Turkheimer’s argument that genome-wide association studies of behaviors and psychiatric traits will fail to produce coherent explanations. We distinguish two major sources of potential incoherence (heterogeneity and complexity), showing how they independently threaten coherence and considering how they are being and might better be addressed with protein and other databases and network tools
Are More Details Better? On the Norms of Completeness for Mechanistic Explanations
Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific model…
Because without Cause
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
The directionality of distinctively mathematical explanations
The Explanatory Power of Network Models
Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as e…
In Search of Mechanisms
What kinds of things are psychiatric disorders?
This essay explores four answers to the question ‘What kinds of things are psychiatric disorders?’ Essentialist kinds are classes whose members share an essence from which their defining features arise. Although elegant and appropriate for some physical (e.g. atomic elements) and medical (e.g. Mendelian disorders) phenomena, this model is inappropriate for psychiatric disorders, which are multi-factorial and ‘fuzzy’. Socially constructed kinds ar…
Integrating psychology and neuroscience
The Explanatory Force of Dynamical and Mathematical Models in Neuroscience
We argue that dynamical and mathematical models in systems and cognitive neuroscience explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phenomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models includin…
Prosthetic Models
What are the relative epistemic merits of building prosthetic models versus building nonprosthetic models and simulations? I argue that prosthetic models provide a sufficient test of affordance validity, that is, of whether the target system affords mechanisms that can be commandeered by a prosthesis. In other respects, prosthetic models are epistemically on par with nonprosthetic models. I focus on prosthetics in neuroscience, but the results ar…
Mechanisms and natural kinds
It is common to defend the Homeostatic Property Cluster (HPC) view as a third way between conventionalism and essentialism about natural kinds (Boyd, 1989, 1991, 1997, 1999; Griffiths, 1997, 1999; Keil, 2003; Kornblith, 1993; Wilson, 1999, 2005; Wilson, Barker, & Brigandt, forthcoming). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a si…
Physical Law and Mechanistic Explanation in the Hodgkin and Huxley Model of the Action Potential
Hodgkin and Huxley's model of the action potential is an apparent dream case of covering-law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to exp…
Explaining the Brain
Top-down Causation Without Top-down Causes
Thinking about Mechanisms
The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change
When mechanistic models explain
Integrating psychology and neuroscience
The Explanatory Force of Dynamical and Mathematical Models in Neuroscience
We argue that dynamical and mathematical models in systems and cognitive neuroscience explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phenomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models includin…
Role Functions, Mechanisms, and Hierarchy
Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions—according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system—captures one important sense of “function” in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explan…
Are More Details Better? On the Norms of Completeness for Mechanistic Explanations
Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific model…
Strategies in the interfield discovery of the mechanism of protein synthesis
The directionality of distinctively mathematical explanations
The Explanatory Power of Network Models
Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as e…
Beyond reduction
Interlevel Experiments and Multilevel Mechanisms in the Neuroscience of Memory
The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. …
Physical Law and Mechanistic Explanation in the Hodgkin and Huxley Model of the Action Potential
Hodgkin and Huxley's model of the action potential is an apparent dream case of covering-law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to exp…
Constitutive relevance & mutual manipulability revisited
Dissociable Realization and Kind Splitting
It is a common assumption in contemporary cognitive neuroscience that discovering a putative realized kind to be dissociably realized (i.e., to be realized in each instance by two or more distinct realizers) mandates splitting that kind. Here I explore some limits on this inference using two deceptively similar examples: the dissociation of declarative and procedural memory and Ramachandran's argument that the self is an illusion
Prosthetic Models
What are the relative epistemic merits of building prosthetic models versus building nonprosthetic models and simulations? I argue that prosthetic models provide a sufficient test of affordance validity, that is, of whether the target system affords mechanisms that can be commandeered by a prosthesis. In other respects, prosthetic models are epistemically on par with nonprosthetic models. I focus on prosthetics in neuroscience, but the results ar…
Phenomenological Laws and Mechanistic Explanations
In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal m…
Experimental Artefacts
Cognitive ontology and the search for neural mechanisms
The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem , scientists often assess whether the tasks engage the same neural mechanisms…
Gloomy Prospects and Roller Coasters
We address Turkheimer’s argument that genome-wide association studies of behaviors and psychiatric traits will fail to produce coherent explanations. We distinguish two major sources of potential incoherence (heterogeneity and complexity), showing how they independently threaten coherence and considering how they are being and might better be addressed with protein and other databases and network tools
Because without Cause
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
Thinking about Mechanisms
The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change
Role Functions, Mechanisms, and Hierarchy
Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions—according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system—captures one important sense of “function” in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explan…
Strategies in the interfield discovery of the mechanism of protein synthesis
Interlevel Experiments and Multilevel Mechanisms in the Neuroscience of Memory
The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. …
Dissociable Realization and Kind Splitting
It is a common assumption in contemporary cognitive neuroscience that discovering a putative realized kind to be dissociably realized (i.e., to be realized in each instance by two or more distinct realizers) mandates splitting that kind. Here I explore some limits on this inference using two deceptively similar examples: the dissociation of declarative and procedural memory and Ramachandran's argument that the self is an illusion
Beyond reduction
When mechanistic models explain
Explaining the Brain
Top-down Causation Without Top-down Causes
Physical Law and Mechanistic Explanation in the Hodgkin and Huxley Model of the Action Potential
Hodgkin and Huxley's model of the action potential is an apparent dream case of covering-law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to exp…
Mechanisms and natural kinds
It is common to defend the Homeostatic Property Cluster (HPC) view as a third way between conventionalism and essentialism about natural kinds (Boyd, 1989, 1991, 1997, 1999; Griffiths, 1997, 1999; Keil, 2003; Kornblith, 1993; Wilson, 1999, 2005; Wilson, Barker, & Brigandt, forthcoming). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a si…
Prosthetic Models
What are the relative epistemic merits of building prosthetic models versus building nonprosthetic models and simulations? I argue that prosthetic models provide a sufficient test of affordance validity, that is, of whether the target system affords mechanisms that can be commandeered by a prosthesis. In other respects, prosthetic models are epistemically on par with nonprosthetic models. I focus on prosthetics in neuroscience, but the results ar…
What kinds of things are psychiatric disorders?
This essay explores four answers to the question ‘What kinds of things are psychiatric disorders?’ Essentialist kinds are classes whose members share an essence from which their defining features arise. Although elegant and appropriate for some physical (e.g. atomic elements) and medical (e.g. Mendelian disorders) phenomena, this model is inappropriate for psychiatric disorders, which are multi-factorial and ‘fuzzy’. Socially constructed kinds ar…
Integrating psychology and neuroscience
The Explanatory Force of Dynamical and Mathematical Models in Neuroscience
We argue that dynamical and mathematical models in systems and cognitive neuroscience explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phenomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models includin…
In Search of Mechanisms
The Explanatory Power of Network Models
Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as e…
The directionality of distinctively mathematical explanations
Because without Cause
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
Remembering
Is it time? Episodic imagining and the discounting of delayed and probabilistic rewards in young and older adults
Gloomy Prospects and Roller Coasters
We address Turkheimer’s argument that genome-wide association studies of behaviors and psychiatric traits will fail to produce coherent explanations. We distinguish two major sources of potential incoherence (heterogeneity and complexity), showing how they independently threaten coherence and considering how they are being and might better be addressed with protein and other databases and network tools
Are More Details Better? On the Norms of Completeness for Mechanistic Explanations
Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific model…
Constitutive relevance & mutual manipulability revisited
The Tools of Neuroscience Experiment
Epistemology (23 obras) · Psychology (21 obras) · Philosophy (18 obras) · Philosophy and History of Science (18 obras) · Computer Science (16 obras) · Cognitive science (15 obras) · Biomedical Text Mining and Ontologies (10 obras) · Cognitive psychology (9 obras) · Neuroscience (9 obras) · Artificial Intelligence (8 obras)