The First Computational Theory of Cognition

2020 ◽  
pp. 107-127
Author(s):  
Gualtiero Piccinini
Keyword(s):  
Neural Networks ◽  
Body Problem ◽  
Digital Circuits ◽  
Finite Automata ◽  
Cognitive Activity ◽  
Logic Gates ◽  
Computer Design ◽  
Computational Theory ◽  
Modern Computer ◽  
The Mind

McCulloch and Pitts were the first to use and Alan Turing’s notion of computation to understand neural, and thus cognitive, activity. McCulloch and Pitts’s contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata, which is an important formalism in computability theory, (ii) a technique that inspired the notion of logic design, which is a fundamental part of modern computer design, (iii) the first use of computation to address the mind–body problem, and (iv) the first modern computational theory of cognition, which posits that neurons are equivalent to logic gates and neural networks are digital circuits.

The Mind-Body Problem Revisited

1975 ◽  
Vol 20 (8) ◽  
pp. 660-660
Author(s):  
MADGE SCHEIBEL ◽  
ARNOLD SCHEIBEL
Keyword(s):  
Body Problem ◽  
Mind Body Problem ◽  
The Mind

Zombies and Dolls

2018 ◽  
Author(s):  
Marcello Massimini ◽  
Giulio Tononi
Keyword(s):  
Body Problem ◽  
Thought Experiments ◽  
Turing Test ◽  
Hard Problem ◽  
Mind Body Problem ◽  
The Hard Problem ◽  
The Mind ◽  
The Brain

This chapter uses thought experiments and practical examples to introduce, in a very accessible way, the hard problem of consciousness. Soon, machines may behave like us to pass the Turing test and scientists may succeed in copying and simulating the inner workings of the brain. Will all this take us any closer to solving the mysteries of consciousness? The reader is taken to meet different kind of zombies, the philosophical, the digital, and the inner ones, to understand why many, scientists and philosophers alike, doubt that the mind–body problem will ever be solved.

Brute Necessity and the Mind–Body Problem

2018 ◽  
Author(s):  
James Van Cleve
Keyword(s):  
Body Problem ◽  
Necessary Truths ◽  
Mind Body Problem ◽  
The Mind

In a growing number of papers one encounters arguments to the effect that certain philosophical views are objectionable because they would imply that there are necessary truths for whose necessity there is no explanation. For short, they imply that there are brute necessities. Therefore, the arguments conclude, the views in question should be rejected in favor of rival views under which the necessities would be explained. This style of argument raises a number of questions. Do necessary truths really require explanation? Are they not paradigms of truths that either need no explanation or automatically have one, being in some sense self-explanatory? If necessary truths do admit of explanation or even require it, what types of explanation are available? Are there any necessary truths that are truly brute? This chapter surveys various answers to these questions, noting their bearing on arguments from brute necessity and arguments concerning the mind–body problem.

Metaphysics and the Mind-Body Problem. Michael E. Levin

Ethics ◽  
1981 ◽  
Vol 92 (1) ◽  
pp. 174-176
Author(s):  
Gilbert Harman
Keyword(s):  
Body Problem ◽  
Mind Body Problem ◽  
The Mind

scholarly journals Synthetic neural-like computing in microbial consortia for pattern recognition

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ximing Li ◽  
Luna Rizik ◽  
Valeriia Kravchik ◽  
Maria Khoury ◽  
Netanel Korin ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Gradient Descent ◽  
Biological Systems ◽  
Logic Gates ◽  
Structural Similarity ◽  
Microbial Consortia ◽  
Promoter Strength ◽  
Chemical Inducers ◽  
Artificial Neural

AbstractComplex biological systems in nature comprise cells that act collectively to solve sophisticated tasks. Synthetic biological systems, in contrast, are designed for specific tasks, following computational principles including logic gates and analog design. Yet such approaches cannot be easily adapted for multiple tasks in biological contexts. Alternatively, artificial neural networks, comprised of flexible interactions for computation, support adaptive designs and are adopted for diverse applications. Here, motivated by the structural similarity between artificial neural networks and cellular networks, we implement neural-like computing in bacteria consortia for recognizing patterns. Specifically, receiver bacteria collectively interact with sender bacteria for decision-making through quorum sensing. Input patterns formed by chemical inducers activate senders to produce signaling molecules at varying levels. These levels, which act as weights, are programmed by tuning the sender promoter strength Furthermore, a gradient descent based algorithm that enables weights optimization was developed. Weights were experimentally examined for recognizing 3 × 3-bit pattern.

The mind-body problem revisited

Neuroscience ◽  
1979 ◽  
Vol 4 (11) ◽  
pp. 1761
Author(s):  
A.R. Blight
Keyword(s):  
Body Problem ◽  
Mind Body Problem ◽  
The Mind

scholarly journals Deep learning-enabled medical computer vision

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andre Esteva ◽  
Katherine Chou ◽  
Serena Yeung ◽  
Nikhil Naik ◽  
Ali Madani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Medical Imaging ◽  
Real World ◽  
Recent Progress ◽  
Medical Applications ◽  
Modern Computer ◽  
Medical Computer

AbstractA decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

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