To be successful, the research agenda for a novel control view of cognition should foresee more detailed, computationally specified process models of cognitive operations including higher cognition. These models should cover all domains of cognition, including those cognitive abilities that can be characterized as online interactive loops and detached forms of cognition that depend on internally generated neuronal processing.

Despite countless anecdotes and the historical significance of insight as a problem solving mechanism, its nature has long remained elusive. The conscious experience of insight is notoriously difficult to trace in non-verbal animals. Although studying insight has presented a significant challenge even to neurobiology and psychology, human neuroimaging studies have cleared the theoretical landscape, as they have begun to reveal the underlying mechanisms. The study of insight in non-human animals has, in contrast, remained limited to innovative adjustments to experimental designs (...) within the classical approach of judging cognitive processes in animals, based on task performance. This leaves no apparent possibility of ending debates from different interpretations emerging from conflicting schools of thought. We believe that comparative cognition has thus much to gain by embracing advances from neuroscience and human cognitive psychology. We will review literature on insight and discuss the consequences of these findings to comparative cognition. (shrink)

Characterizing the cultural evolution of imaginary worlds as a hedonic but non-adaptive exaptation from evolved exploratory tendencies, Dubourg and Baumard defend too narrow a conception of the adaptive evolution of imaginary worlds. Imagination and its imaginary worlds are ancient and adaptive, allowing deliberation over actions, consequences, and futures worth aspiring to, often engendering the world we see around us.

In today’s society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with “consciousness” and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a (...) multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain’s capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable properties? Instead of proposing criteria that would each define a “hard” threshold for consciousness, we outline six indicators: goal-directed behavior and model-based learning; anatomic and physiological substrates for generating integrative multimodal representations; psychometrics and meta-cognition; episodic memory; susceptibility to illusions and multistable perception; and specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience. (shrink)