Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7-19. doi:org/10.1093/analys/58.1.7

DeHaene, S. (2020). How we learn. Why brains learn better than any machine … for now. Viking.

Gibson, J. J. (1974). Overt and covert attention [Unpublished “Purple Peril”].

Pallier, C. (2013. Age effects in language acquisition and attrition. In J. J. Bolhuis, & M. Evereart, M. (Eds), Birdsong, Speech, and language exploring the evolution of mind and brain. MIT.

Pallier, C., Dehaene, S., Poline, J-B., LeBihan, D., Argenti, A-M., Dupoux, E. and Mehler, J. (2003). Brain imaging of language plasticity in adopted adults: can a second language replace the first?. Cerebral Cortex, 13(2), 155–161.
Do the neural circuits that subserve language acquisition lose plasticity as they become tuned to the maternal language?We tested adult subjects born in Korea and adopted by French families in childhood; they have become fluent in their second language and report no conscious recollection of their native language. In behavioral tests assessing their memory for Korean, we found that they do not perform better than a control group of native French subjects who have never been exposed to Korean. We also used event-related functional magnetic resonance imaging to monitor cortical activations while the Korean adoptees and native French listened to sentences spoken in Korean, French and other, unknown, foreign languages. The adopted subjects did not show any specific activations to Korean stimuli relative to unknown languages. The areas activated more by French stimuli than by foreign stimuli were similar in the Korean adoptees and in the French native subjects, but with relatively larger extents of activation in the latter group. We discuss these data in light of the critical period hypothesis for language acquisition.

Stanovich, K. E., & West R. F. (2000). Behavioral and brain sciences, 23,(5), 645-665.
Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (eg, the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors,(2) computational limitations,(3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.
System 1 an system 2. Table 3: The terms for the two systems used by a variety of theorists and the properties of dual-process theories of reasoning.