On the consequences of bilingualism: We need language and the brain to understand cognition

2014 ◽  
Vol 18 (1) ◽  
pp. 32-34 ◽  
Author(s):  
JUDITH F. KROLL
Keyword(s):  
Neural Networks ◽  
Learning Environments ◽  
Language Use ◽  
Neural Systems ◽  
Language Experience ◽  
Advantages And Disadvantages ◽  
The Mind ◽  
The Brain

In the last two decades there has been an explosion of research on bilingualism and its consequences for the mind and the brain (e.g., Kroll & Bialystok, 2013). One reason is that the use of two or more languages reveals interactions across cognitive and neural systems that are often obscured in monolingual speakers of a single language (e.g., Kroll, Dussias, Bogulski & Valdes Kroff, 2012). From this perspective, the interest in bilingualism is about developing a platform to ask questions about the ways that cognitive and neural networks are engaged during language use, in different learning environments, and across the lifespan. Another reason is that an emerging body of research on the consequences of bilingualism suggests that language experience changes cognition and the brain (e.g., Abutalebi, Della Rosa, Green, Hernandez, Scifo, Keim, Cappa & Costa, 2012; Bialystok, Craik, Green, & Gollan, 2009). Some of these changes have been claimed to produce cognitive advantages (see Bialystok et al., for a review of bilingual advantages and disadvantages).

Consciousness and the feeling body

2010 ◽  
Vol 18 (3) ◽  
pp. 607-616
Author(s):  
Julian Kiverstein
Keyword(s):  
Neural Systems ◽  
The Mind ◽  
Compare And Contrast ◽  
The Brain

In How the Mind Uses the Brain Ralph Ellis and Natika Newton develop a novel embodied, enactive theory of consciousness, according to which consciousness has its basis in neural systems that prepare the system to perform actions of emotional significance to the organism. Consciousness emerges out of self-organising processes which function in such a way as to contribute to, and maintain, the organism’s overall wellbeing. I’ll begin this review by reconstructing Ellis and Newton’s view of consciousness as a self-organising process, and then go on to compare and contrast the enactive theory with the model of consciousness Chris Frith has outlined in his lectures.

scholarly journals Using Diffusion Tensor Imaging to examine brain structural plasticity and language experience

2019 ◽  
Author(s):  
Gigi Luk ◽  
Christos Pliatsikas
Keyword(s):  
Language Processing ◽  
Brain Structure ◽  
Language Use ◽  
Diffusion Tensor ◽  
Brain Plasticity ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Language Experience ◽  
Brain Correlates ◽  
The Brain

Recent advances in neuroimaging methods have led to a renewed interest in the brain correlates of language processing. Most intriguing is how experiences of language use relates to variation in brain structure and how brain structure predicts language acquisition. These two lines of inquiry have important implications on considering language use as an experience-dependent mechanism that induces brain plasticity. This paper focuses on the structural connectivity of the brain, as delivered by white matter, i.e. the collections of the axons of the brain neurons that provide connectivity between brain regions. Tract-Based Spatial Statistics (TBSS), a method commonly used in the field, will be presented in detail. Readers will be introduced to procedures for the extraction of indices of variation in WM structure such as fractional anisotropy. Furthermore, the role of individual differences in WM and changes in WM pertaining to bilingual experience and language processing will be used as examples to illustrate the applicability of this method.

scholarly journals Emergence, a Universal Phenomenon which Connects Reality to Consciousness, Natural Sciences to Humanities

2018 ◽  
Vol 7 (2) ◽  
pp. 89-106
Author(s):  
Gabriel Crumpei ◽  
Alina Gavriluţ
Keyword(s):  
Neural Networks ◽  
Mathematical Models ◽  
Quantum Physics ◽  
Difficult Problem ◽  
Natural Sciences ◽  
Cognitive Neurosciences ◽  
Mathematical Formalization ◽  
The Difference ◽  
The Mind ◽  
The Brain

Abstract Progress in neuroscience has left a central question of psychism unanswered: what is consciousness? Modeling the psyche from a computational perspective has helped to develop cognitive neurosciences, but it has also shown their limits, of which the definition, description and functioning of consciousness remain essential. From Rene Descartes, who tackled the issue of psychism as the brain-mind dualism, to Chambers, who defined qualia as the tough, difficult problem of research in neuroscience, many hypotheses and theories have been issued to encompass the phenomenon of consciousness. Neuroscience specialists, such as Giulio Tononi or David Eagleman, consider consciousness as a phenomenon of emergence of all processes that take place in the brain. This hypothesis has the advantage of being supported by progress made in the study of complex systems in which the issue of emergence can be mathematically formalized and analyzed by physical-mathematical models. The current tendency to associate neural networks within the broad scope of network science also allows for a physical-mathematical formalization of phenomenology in neural networks and the construction of information-symbolic models. The extrapolation of emergence at the level of physical systems, biological systems and psychic systems can bring new models that can also be applied to the concept of consciousness. The meaning and significance that seem to structure the nature of consciousness is found as direction of evolution and teleological finality, of integration in the whole system and in any complex system at all scales. Starting from the wave-corpuscle duality in quantum physics, we can propose a model for structuring reality, based on the emergence of systems that contribute to the integration and coherence of the entire reality. Physical-mathematical models based mainly on (mereo)topology can provide a mathematical formalization path, and the paradigm of information could allow the development of a pattern of emergence, that is common to all systems, including the psychic system, the difference being given only by the degree of information complexity. Thus, the mind-brain duality, which has been dominating the representation on psychism for a few centuries, could be solved by an informational approach, describing the connection between object and subject, reality and human consciousness, between mind and brain, thus unifying the perspective on natural sciences and humanities.

scholarly journals DNNBrain: a unifying toolbox for mapping deep neural networks and brains

2020 ◽  
Author(s):  
Xiayu Chen ◽  
Ming Zhou ◽  
Zhengxin Gong ◽  
Wei Xu ◽  
Xingyu Liu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Cognitive Neuroscience ◽  
Deep Neural Networks ◽  
Learning Strategy ◽  
Neural Systems ◽  
Levels Of Abstraction ◽  
Internal Representations ◽  
High Level ◽  
The Brain

ABSTRACTDeep neural networks (DNNs) have attained human-level performance on dozens of challenging tasks through an end-to-end deep learning strategy. Deep learning gives rise to data representations with multiple levels of abstraction; however, it does not explicitly provide any insights into the internal operations of DNNs. Its success appeals to neuroscientists not only to apply DNNs to model biological neural systems, but also to adopt concepts and methods from cognitive neuroscience to understand the internal representations of DNNs. Although general deep learning frameworks such as PyTorch and TensorFlow could be used to allow such cross-disciplinary studies, the use of these frameworks typically requires high-level programming expertise and comprehensive mathematical knowledge. A toolbox specifically designed for cognitive neuroscientists to map DNNs and brains is urgently needed. Here, we present DNNBrain, a Python-based toolbox designed for exploring internal representations in both DNNs and the brain. By integrating DNN software packages and well-established brain imaging tools, DNNBrain provides application programming and command line interfaces for a variety of research scenarios, such as extracting DNN activation, probing DNN representations, mapping DNN representations onto the brain, and visualizing DNN representations. We expect that our toolbox will accelerate scientific research in applying DNNs to model biological neural systems and utilizing paradigms of cognitive neuroscience to unveil the black box of DNNs.

Does AI need symbols?

ITNOW ◽  
2021 ◽  
Vol 63 (2) ◽  
pp. 56-57
Author(s):  
Grace Lindsay
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural ◽  
The Mind ◽  
The Brain

Abstract Inspired by the brain, artificial neural networks are core to modern artificial intelligence. Grace Lindsay, author of Models of the Mind, explains concerns over the cognitive limits of these systems.

Lighting Up the Brain to Illuminate the Mind

2004 ◽  
Vol 49 (6) ◽  
pp. 713-716
Author(s):  
Ellen S. Berscheid
Keyword(s):  
The Mind ◽  
The Brain

How Does the Brain Make the Mind? We Do Not Know.

PsycCRITIQUES ◽  
2016 ◽  
Vol 61 (32) ◽  
Author(s):  
Christopher A. Was
Keyword(s):  
The Mind ◽  
The Brain

Big Heads title page

2019 ◽  
Author(s):  
vernon thornton
Keyword(s):  
Title Page ◽  
Language Of Thought ◽  
Correct Version ◽  
Evolutionary Context ◽  
The Mind ◽  
The Brain

A description of of the mind and its relationship to the brain, set in an evolutionary context. Introduction of a correct version of 'language-of-thought' called 'thinkish'.

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.

Implantable neural interfaces

2018 ◽  
Author(s):  
Stefano Vassanelli
Keyword(s):  
Brain Function ◽  
Large Scale ◽  
Ionic Channels ◽  
Patch Clamp Technique ◽  
Advantages And Disadvantages ◽  
Optogenetic Stimulation ◽  
Physical Interfaces ◽  
The Brain

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.

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