Why the Brain Knows More than We Do: Non-Conscious Representations and Their Role in the Construction of Conscious Experience

Dresp-Langley, Birgitta

doi:10.3390/brainsci2010001

Cited by 22 publications

(18 citation statements)

References 99 publications

(128 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent research is beginning to illuminate what is taking place. According to Dresp-Langley (2012) and referring mainly to neuro-psychological investigations, ''… a large number of studies have shown that non-conscious brain processes influence perceptions and representations embedded in ongoing conscious experience'' (p. 2). She argues, therefore, that far more is ''known'' than our deliberative, mindful and immediate thinking would suggest.…”

Section: Neuroscience and Recent Ideas In Cognitionmentioning

confidence: 99%

Manipulating Models and Grasping the Ideas They Represent

Bryce

Blown

2016

Sci & Educ

View full text Add to dashboard Cite

This article notes the convergence of recent thinking in neuroscience and grounded cognition regarding the way we understand mental representation and recollection: ideas are dynamic and multi-modal, actively created at the point of recall. Also, neurophysiologically, re-entrant signalling among cortical circuits allows non-conscious processing to support our deliberative thoughts and actions. The qualitative research we describe examines the exchanges occurring during semi-structured interviews with 360 children age 3-13, including 294 from New Zealand (158 boys, 136 girls) and 66 from China (34 boys, 32 girls) concerning their understanding of the shape and motion of the Earth, Sun and Moon (ESM). We look closely at the relationships between what is revealed as children manipulate their own play-dough models and their apparent understandings of ESM concepts. In particular, we focus on the switching taking place between what is said, what is drawn and what is modelled. The evidence is supportive of Edelman's view that memory is non-representational and that concepts are the outcome of perceptual mappings, a view which is also in accord with Barsalou's notion that concepts are simulators or skills which operate consistently across several modalities. Quantitative data indicate that the dynamic structure of memory/concept creation is similar in both genders and common to the cultures/ethnicities compared (New Zealand European and Māori; Chinese Han) and that repeated interviews in this longitudinal research lead to more advanced modelling skills and/or more advanced shape and motion concepts, the results supporting hypotheses (Kolmogorov-Smirnov alpha levels .05; r s : p \ .001).

show abstract

Section: Neuroscience and Recent Ideas In Cognitionmentioning

confidence: 99%

Manipulating Models and Grasping the Ideas They Represent

Bryce

Blown

2016

Sci & Educ

View full text Add to dashboard Cite

show abstract

“…Our results will be of great interest to those involved in the application of biological and neurological structures to the computational domain [20,21]. The codification of non-conscious reasoning has many potential applications in artificial intelligence and complex systems, which are an increasingly ubiquitous component of modern life.…”

Section: Discussionmentioning

confidence: 83%

An Heuristic Framework for Non-Conscious Reasoning

Lara-Rosano

2017

Applied Sciences

View full text Add to dashboard Cite

Featured Application: This analysis of non-conscious reasoning can be applied in educational diagnostics and intervention, medical diagnostics and treatments, organizational and political decision making and design of artificial intelligence knowledge based systems, neuro-computers and similar devices for aiding people in the problem-solving process. Abstract: Human non-conscious reasoning is one of the most successful procedures evolved for the purposes of solving everyday problems in an efficient way. This is why the field of artificial intelligence should analyze, formalize and emulate the multiple ways of non-conscious reasoning with the purpose of applying them in human problem solving tasks, like medical diagnostics and treatments, educational diagnostics and intervention, organizational and political decision making, artificial intelligence knowledge based systems and neurocomputers, automatic control systems and similar devices for aiding people in the problem-solving process. In this paper, a heuristic framework for those non-conscious ways of reasoning is presented based on neurocognitive representations, heuristics, and fuzzy sets.

show abstract

“…The interactions between unconscious and conscious mental events were argued to be important by Freud [27], and this opinion is supported by recent neuroscientific study [28]. As only significant events within NARS enter the system's (conscious) experience, the same conclusion holds for NARS.…”

Section: Properties Of Narsmentioning

confidence: 82%

Conceptions of Artificial Intelligence and Singularity

Wang

Liu

Dougherty³

2018

Information

View full text Add to dashboard Cite

In the current discussions about "artificial intelligence" (AI) and "singularity", both labels are used with several very different senses, and the confusion among these senses is the root of many disagreements. Similarly, although "artificial general intelligence" (AGI) has become a widely used term in the related discussions, many people are not really familiar with this research, including its aim and status. We analyze these notions, and introduce the results of our own AGI research. Our main conclusions are that: (1) it is possible to build a computer system that follows the same laws of thought and shows similar properties as the human mind, but, since such an AGI will have neither a human body nor human experience, it will not behave exactly like a human, nor will it be "smarter than a human" on all tasks; and (2) since the development of an AGI requires a reasonably good understanding of the general mechanism of intelligence, the system's behaviors will still be understandable and predictable in principle. Therefore, the success of AGI will not necessarily lead to a singularity beyond which the future becomes completely incomprehensible and uncontrollable.Information 2018, 9, 79 2 of 15 the features that the leading article claimed to be impossible for AI. In the conclusion, we agree with the authors of the leading article [1] that the recent achievements of deep learning are still far from showing that the related techniques can give us AGI or singularity; however, we believe AGI can be achieved via paths outside the vision of mainstream AI researchers, as well as that of its critics. This conception of AGI is fundamentally different from that of the current mainstream conception of AI. As for "singularity", we consider it an ill-conceived notion, as it is based on an improper conception of intelligence. Notions Distinguished and ClarifiedLet us first analyze what people mean when talking about "AI" and "Singularity". Both notions have no widely accepted definitions, although there are common usages. Different Types of AIIn its broadest sense, AI is the attempt "to make a computer work like a human mind". Although it sounds plain, this description demands an AI to be similar (or even identical) to the human mind in certain aspects. On the other hand, because a computer is not a biological organism, nor does it live a human life, it cannot be expected to be similar to the human mind in all details. The latter is rarely mentioned but implicitly assumed, as it is self-evident. Consequently, by focusing on different aspects of the human mind, different paradigms of AI have been proposed and followed, with different objectives, desiderata, assumptions, road-maps, and applicabilities. They are each valid but distinct paradigms of scientific research [2].In the current discussion, there are at least three senses of "AI" involved:

show abstract

Why the Brain Knows More than We Do: Non-Conscious Representations and Their Role in the Construction of Conscious Experience

Cited by 22 publications

References 99 publications

Manipulating Models and Grasping the Ideas They Represent

Manipulating Models and Grasping the Ideas They Represent

An Heuristic Framework for Non-Conscious Reasoning

Conceptions of Artificial Intelligence and Singularity

Contact Info

Product

Resources

About