Mental representation in the brain remains an unresolved issue. However, there has been significant research in a variety of fields in the last four decades - from various forms of neuroscience to theoretical computer science - which can provide new insights on the issue of representation. Our conjectures and analysis of the representational issue has been mainly focused at the level of the neurons. At the neuron level, the fundamental dispute has been between local and distributed representation. However, there are also theories that claim that the brain is representation less and that representation exist in other forms and levels.
Approaching the representation issue from the modeling side, the question of neural basis of cognitive phenomena and intelligent behavior has recently received renewed interest in cognitive science, cognitive modelling, and artificial intelligence. Significant efforts are being dedicated to unraveling the appropriate forms of biologically-adequate representation as the basis for cognitively-adequate models and to the bridging from observed high-level structures and behavior to low-level implementations (and vice versa). At the same time, technological advances inspired by theories about representation in the brain (such as, e.g., hierarchically-structured Deep Neural Networks) are receiving the attention of entire research communities.
Representational and modeling issues also arise in a broad range of other contexts and in addressing computational complexity challenges. For example, of particular interest are interactions between bottom-up and top-down signals and how they overcome combinatorial complexity, which since the 1960s inhibited modeling cognitive functions and developing cognitive algorithms. Some related questions are: What are the similarities and differences between cognitive representations and language ones, and how they interact. What is the function of emotions in learning representations and in language. Which aspects of representations are accessible to consciousness and which remain unconscious.
This Research Topic in Frontiers in Psychology welcomes articles that can provide significantly new insights on these decade’s long questions about mental representation and how it relates to various cognitive functions. Specifically, articles that are comprehensive and take into account the theoretical and experimental evidence of the last few decades are encouraged.
Mental representation in the brain remains an unresolved issue. However, there has been significant research in a variety of fields in the last four decades - from various forms of neuroscience to theoretical computer science - which can provide new insights on the issue of representation. Our conjectures and analysis of the representational issue has been mainly focused at the level of the neurons. At the neuron level, the fundamental dispute has been between local and distributed representation. However, there are also theories that claim that the brain is representation less and that representation exist in other forms and levels.
Approaching the representation issue from the modeling side, the question of neural basis of cognitive phenomena and intelligent behavior has recently received renewed interest in cognitive science, cognitive modelling, and artificial intelligence. Significant efforts are being dedicated to unraveling the appropriate forms of biologically-adequate representation as the basis for cognitively-adequate models and to the bridging from observed high-level structures and behavior to low-level implementations (and vice versa). At the same time, technological advances inspired by theories about representation in the brain (such as, e.g., hierarchically-structured Deep Neural Networks) are receiving the attention of entire research communities.
Representational and modeling issues also arise in a broad range of other contexts and in addressing computational complexity challenges. For example, of particular interest are interactions between bottom-up and top-down signals and how they overcome combinatorial complexity, which since the 1960s inhibited modeling cognitive functions and developing cognitive algorithms. Some related questions are: What are the similarities and differences between cognitive representations and language ones, and how they interact. What is the function of emotions in learning representations and in language. Which aspects of representations are accessible to consciousness and which remain unconscious.
This Research Topic in Frontiers in Psychology welcomes articles that can provide significantly new insights on these decade’s long questions about mental representation and how it relates to various cognitive functions. Specifically, articles that are comprehensive and take into account the theoretical and experimental evidence of the last few decades are encouraged.
