scholarly journals Hylomorphic Animalism, Emergentism, and the Challenge of the New Mechanist Philosophy of Neuroscience

2017 ◽  
Vol 5 (2) ◽  
pp. 9 ◽  
Author(s):  
Daniel D. De Haan
Keyword(s):  
Philosophy Of Neuroscience

Neuroscience and the explanation of psychological phenomena

1999 ◽  
Vol 22 (5) ◽  
pp. 847-849 ◽  
Author(s):  
Antti Revonsuo
Keyword(s):  
Cognitive Science ◽  
Cognitive Neuroscience ◽  
Actual Problem ◽  
Philosophy Of Neuroscience ◽  
Psychological Phenomena ◽  
Biological Explanations ◽  
Different Levels

Explanatory problems in the philosophy of neuroscience are not well captured by the division between the radical and the trivial neuron doctrines. The actual problem is, instead, whether mechanistic biological explanations across different levels of description can be extended to account for psychological phenomena. According to cognitive neuroscience, some neural levels of description at least are essential for the explanation of psychological phenomena, whereas, in traditional cognitive science, psychological explanations are completely independent of the neural levels of description. The challenge for cognitive neuroscience is to discover the levels of description appropriate for the neural explanation of psychological phenomena.

Philosophy of Neuroscience

2016 ◽  
Author(s):  
Adina L. Roskies ◽  
Carl F. Craver
Keyword(s):  
Experimental Study ◽  
Experimental Techniques ◽  
Central Research ◽  
Philosophy Of Neuroscience ◽  
The Past ◽  
Research Areas ◽  
Potential Impact ◽  
Rich Material ◽  
The Mind ◽  
The Brain

The experimental study of the brain has exploded in the past several decades, providing rich material for both philosophers of science and philosophers of mind. In this chapter, the authors summarize some central research areas in philosophy of neuroscience. Some of these areas focus on the internal practice of neuroscience, that is, on the assumptions underlying experimental techniques, the accepted structures of explanations, the goals of integrating disciplines, and the possibility of a unified science of the mind-brain. Other areas focus outwards on the potential impact that neuroscience is having on our conception of the mind and its place in nature.

Levels, Individual Variation, and Massive Multiple Realization in Neurobiology

2009 ◽  
Author(s):  
Kenneth Aizawa ◽  
Carl Gillett
Keyword(s):  
Nervous System ◽  
Individual Variation ◽  
Multiple Realization ◽  
Philosophy Of Psychology ◽  
Philosophy Of Neuroscience

This article examines massive multiple realization (MMR) in the context of neurobiology. It highlights the differences in the conception of multiple realization and its methodological implications by researchers in the philosophy of psychology and those in the philosophy of neuroscience. It discusses neurobiological findings about MMR and shows that there is plausibly important individual variation at every physiologically significant level of organization in the nervous system. It explores philosophical concerns about the MMR hypothesis and proposes a framework for realization and multiple realization.

The logic of interests in neuroscience

1999 ◽  
Vol 22 (5) ◽  
pp. 831-832
Author(s):  
Leslie Brothers
Keyword(s):  
Popular Culture ◽  
Social Analysis ◽  
Philosophy Of Neuroscience ◽  
Freudian Theory ◽  
Target Article ◽  
Social Interests

Logical problems inherent in claims that biological neuroscience can ultimately explain mind are not anomalous: They result from underlying social interests. Neuroscientists are currently making a successful bid to fill a vacuum of authority created by the demise of Freudian theory in popular culture. The conflations described in the Gold & Stoljar target article are the result of alliances between certain apologist-philosophers, neuroscientists, and institutions, for the purpose of commanding authority and resources. Social analysis has a role to play in addressing logical issues in the philosophy of neuroscience.

Philosophy of Neuroscience

2016 ◽  
Author(s):  
Adina L. Roskies ◽  
Carl F. Craver
Keyword(s):  
Experimental Study ◽  
Experimental Techniques ◽  
Central Research ◽  
Philosophy Of Neuroscience ◽  
The Past ◽  
Research Areas ◽  
Potential Impact ◽  
Rich Material ◽  
The Mind ◽  
The Brain

The experimental study of the brain has exploded in the past several decades, providing rich material for both philosophers of science and philosophers of mind. In this chapter, the authors summarize some central research areas in philosophy of neuroscience. Some of these areas focus on the internal practice of neuroscience, that is, on the assumptions underlying experimental techniques, the accepted structures of explanations, the goals of integrating disciplines, and the possibility of a unified science of the mind-brain. Other areas focus outwards on the potential impact that neuroscience is having on our conception of the mind and its place in nature.

The Development and Application of Efficient Coding Explanation in Neuroscience

2018 ◽  
Author(s):  
Mazviita Chirimuuta
Keyword(s):  
Applied Sciences ◽  
Explanatory Models ◽  
Therapeutic Interventions ◽  
Philosophy Of Neuroscience ◽  
Theoretical Virtues ◽  
Causal Explanations ◽  
Efficient Coding ◽  
Efficient Code ◽  
Unifying Principles ◽  
The Brain

In the philosophy of neuroscience, much attention has been paid to mechanistic causal explanations, both in terms of their theoretical virtues, and their application in potential therapeutic interventions. Non-mechanistic, non-causal explanatory models, it is often assumed, would have no role to play in any practical endeavors. This assumption ignores the fact that many of the non-mechanistic explanatory models which have been successfully employed in neuroscience have their origins in engineering and applied sciences, and are central to many new neuro-technologies. This chapter examines the development of explanations of lateral inhibition in the early visual system as implementing an efficient code for converting photoreceptor input into a data-compressed output from the eye to the brain. Two applications of the efficient coding approach are considered: in streamlining the vast datasets of current neuroscience by offering unifying principles, and in building artificial systems that replicate vision and other cognitive functions.

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