Outline of a theory of thought-processes and thinking machines

Caianiello, E. R.

doi:10.1016/0022-5193(61)90046-7

Cited by 454 publications

(68 citation statements)

References 4 publications

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“…The streams of research TABLE 1 Hartline- Ratliff-Miller (1963) Grossberg (1967. 1968) Sperling-Sondhi (1968 Wilson-Cowan (1972) McCulloch-Pitts (1943) Caianiello (1961) Rosenblatt (1962 Kohonen (1971) made his transition from linear algebra concepts such as the Moore-Penrose pseudoinverse to more biologically motivated studies which he has summarized in his influential books (Kohonen, 1977(Kohonen, , 1984. These workers thus began to develop their intuitions within a mathematically familiar engineering framework which was progressively developed to include more biologically motivated nonlinear interactions.…”

Section: A Binarymentioning

confidence: 99%

Nonlinear neural networks: Principles, mechanisms, and architectures

1988

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Abstract-An historical discussion is provided of the intellectual trends that caused nineteenth century interdisciplinary studies of physics and psychobiology by leading scientists such as Helmholtz, Maxwell, and Mach to splinter into separate twentieth-century scientific movements. The nonlinear, nonstationary, and nonlocal nature of behavioral and brain data are emphasized. Three sources of contemporary neural network research-the binary, linear, and continuous-nonlinear models-are noted. The remainder of the article describes results about continuous-nonlinear models: Many models of content-addressable memory are shown to be special cases of the Cohen-Grossberg model and global Liapunov function, including the additive, brain-state-in-a-box, McCulloch-Pitts, Boltzmann machine, Hartline-Ratliff-Millet; shunting, maskingfield, bidirectional associative memory, Volterra-Lotka, Gilpin-Ayala, and Eigen-Schuster models. A Liapunov functional method is described for proving global limit or oscillation theorems for nonlinear competitive systems when their decision schemes are globally consistent or inconsistent, respectively. The former case is illustrated by a model of a globally stable economic market, and the latter case is illustrated by a model of the voting paradox. Key properties of shunting competitive feedback networks are summarized, including the role of sigmoid signalling, automatic gain control, competitive choice and quantization, tunable filtering, total activity normalization, and noise suppression in pattern transformation and memory storage applications. Connections to models of competitive learning, vector quantization, and categorical perception are noted. Adaptive resonance theory (ART) models for selJstabilizing adaptive pattern recognition in response to complex real-time nonstationary input environments are compared with off-line models such as autoassociators, the Boltzmann machine, and back propagation. Special attention is paid to the stability and capacity of these models, and to the role of top-down expectations and attentional processing in the active regulation of both learning and fast information processing. Models whose performance and learning are regulated by internal gating and matching signals, or by external environmentally generated error signals, are contrasted with models whose learning is regulated by external teacher signals that have no analog in natural real-time environments. Examples from sensory-motor control of adaptive vector encoders, adaptive coordinate transformations. adaptive gain control by visual error signals. and automatic generation of synchronous multijoint movement trajectories illustrate the former model types. Internal matching processes are shown capable of discovering several different types of inyariant environmental properties. These include ART mechanisms which discover recognition invariants. adaptive vector encoder mechanisms which discover movement invariants. and autoreceptive associative mechanisms which discover invariants of selJregulating t...

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Section: A Binarymentioning

confidence: 99%

Nonlinear neural networks: Principles, mechanisms, and architectures

1988

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“…For instance, imagine a person, who has memorized some parts of a book. Then, if he is asked to transform all the information into an interesting and understandable chart, he will start thinking and using his imagination in order to figure out a perfect description over his saved senses (25).…”

Section: The First Phase Of Thought Is Transforming Sense Into Imaginmentioning

confidence: 99%

What Is Thought: Take a Look at the Holy Quran and the Principles of Neuroscience

Tekieh

Nikbin

Sahraei

et al. 2017

Iran Red Crescent Med J

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Background: Human beings firmly obtain a better understanding of the creator, its aims and destination, natural phenomena as well as the surrounding concepts with the help of thoughts. Invitation towards contemplation is one of the principles of Holy Quran's teachings. Thought is one of the best activities of the human being's brain from the neuroscience point of view, which occurs in specific parts of the cerebral cortex. These areas consist of parts of the cerebral cortex, which either does not exist in other creatures or is not highly developed. Objectives: The purpose of this study was to investigate the importance of thought from the Holy Quran's point of view and the Foundations of Neuroscience. Methods: This research was carried out during year 2015 in the city of Tehran (the capital city of Iran). In this qualitative study, data were collected based on the Holy Quran and the interpretation of authentic books of the Quran and matching interpretation of these verses with neuroscience articles and books in the field of thought. Results: Careful consideration of the data led to the identification of 18 verses of the Holy Quran that pointed directly to thinking, which were consistent with accepted principles in neuroscience. Conclusions: Scientific secrets of the Holy Quran can be easily revealed by making a connection between a medical sciences, basic sciences, and Quranic sciences. There is hope of greater connection between the community of researchers in different fields with Quranic scientists, which might lead to the discovery of the secrets of this scripture and deep realization of the mystery of permanence.

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“…The simplest statistics-based concept available for use in the nervous system, and one often used in the literature, ignores individual neuronal spikes and confines the discussion to the average spike rates of neurons (see for example Caianiello, 1961;Wilson and Cowan, 1972;Bienenstock et al, 1982). However, the spike-rate-based events and changes predicted in neuronal networks are relatively slow, and their functional relevance to learning is at best obscure.…”

Section: The Linkage Between Ltp and Surprising Eventsmentioning

confidence: 99%

Synaptic and extrasynaptic traces of long-term memory: the ID molecule theory

Legéndy

2016

Reviews in the Neurosciences

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AbstractIt is generally assumed at the time of this writing that memories are stored in the form of synaptic weights. However, it is now also clear that the synapses are not permanent; in fact, synaptic patterns undergo significant change in a matter of hours. This means that to implement the long survival of distant memories (for several decades in humans), the brain must possess a molecular backup mechanism in some form, complete with provisions for the storage and retrieval of information. It is found below that the memory-supporting molecules need not contain a detailed description of mental entities, as had been envisioned in the ‘memory molecule papers’ from 50 years ago, they only need to contain unique identifiers of various entities, and that this can be achieved using relatively small molecules, using a random code (‘ID molecules’). In this paper, the logistics of information flow are followed through the steps of storage and retrieval, and the conclusion reached is that the ID molecules, by carrying a sufficient amount of information (entropy), can effectively control the recreation of complex multineuronal patterns. In illustrations, it is described how ID molecules can be made to revive a selected cell assembly by waking up its synapses and how they cause a selected cell assembly to ignite by sending slow inward currents into its cells. The arrangement involves producing multiple copies of the ID molecules and distributing them at strategic locations at selected sets of synapses, then reaching them through small noncoding RNA molecules. This requires the quick creation of entropy-rich messengers and matching receptors, and it suggests that these are created from each other by small-scale transcription and reverse transcription.

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Outline of a theory of thought-processes and thinking machines

Cited by 454 publications

References 4 publications

Nonlinear neural networks: Principles, mechanisms, and architectures

Nonlinear neural networks: Principles, mechanisms, and architectures

What Is Thought: Take a Look at the Holy Quran and the Principles of Neuroscience

Synaptic and extrasynaptic traces of long-term memory: the ID molecule theory

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