The Nature-Nurture controversy has been with us since it was first outlined by Plato and Aristotle. Nobody likes it anymore. All reasonable scholars today agree that genes and environment interact to determine complex cognitive outcomes. So why does the controversy persist? First, it persists because it has practical implications that cannot be postponed (i.e., what can we do to avoid bad outcomes and insure better ones?), a state of emergency that sometimes tempts scholars to stake out claims they cannot defend. Second, the controversy persists because we lack a precise, testable theory of the process by which genes and environment interact. In the absence of a better theory, innateness is often confused with (1) domain specificity (Outcome X is so peculiar that it must be innate), (2) species specificity (we are the only species who do X, so X must lie in the human genome), (3) localization (Outcome X is mediated by a particular part of the brain, so X must be innate), and (4) learnability (we cannot figure out how X could be learned, so X must be innate). We believe that an explicit and plausible theory of interaction is now around the corner, and that many of the classic maneuvers to defend or attack innateness will soon disappear. In the interim, some serious errors can be avoided if we keep these confounded issues apart. That is the major goal of this paper, i.e., not to attack innateness but to clarify what

Developmental psychology and developmental neuropsychology have traditionally focused on the study of children. But these two fields are also supposed to be about the study of change, i.e. changes in behavior, changes in the neural structures that underlie behavior, and changes in the relationship between mind and brain across the course of development. Ironically, there has been relatively little interest in the mechanisms responsible for change in the last 15–20 years of developmental research. The reasons for this de-emphasis on change have a great deal to do with a metaphor for mind and brain that has influenced most of experimental psychology, cognitive science and neuropsychology for the last few decades, i.e. the metaphor of the serial digital computer. We will refer to this particu-

Aphasia (defined as the loss or impairment of language abilities following acquired brain injury) is strongly associated with damage to the left hemisphere in adults. This well-known finding has led to the hypothesis that the left hemisphere is innately specialized for language, and may be the site of a specific "language organ". However, for over a century we have known that young children with left-hemisphere damage (LHD) do not suffer from aphasia, and in most studies do not differ significantly from children with right-hemisphere damage (RHD). This result provides strong evidence for plasticity, i.e., brain reorganization in response to experience, and constitutes a serious challenge to the language organ hypothesis. This chapter reviews the history of research on language outcomes in children vs. adults with unilateral brain injury, addressing some discrepancies in the literature to date, including methodological confounds that may be responsible for those discrepancies. It also reviews recent prospective studies of children with unilateral injury as they pass through the first stages of language development. Prospective studies have demonstrated specific correlations between lesion site and profiles of language delay, but they look quite different from lesionsymptom correlations in adults, and gradually disappear across the course of language development. The classic pattern of brain organization for language observed in normal adults may be the product rather than the cause of language learning, emerging out of regional biases in information processing that are relevant for language, but only indirectly related to language itself. If those

A simple model of self-organised learning with no classical (Hebbian) reinforcement is presented. Synaptic connections involved in mistakes are depressed. The model operates at a highly adaptive, probably critical, state reached by extremal dynamics similar to that of recent evolution models. Thus, one might think of the mechanism as synaptic Darwinism. It is widely believed that learning in the brain resides in alterations of synaptic efficacy. Without exception, contemporary formulations of such learning follows Hebb’s ideas [1] of reinforcement: synaptic connections among neurons excited during a a given firing pattern are strengthened by a process of long term potentiation (LTP). However, long term synaptic depression (LTD) in the mammalian brain is almost as prevalent as potentiation, but there appears to be little or no understanding of its functional role. Working hypotheses covers a wide range, where depression is given always an auxiliary function to potentiation [2]. A recent review [3], reflecting the current variety of ideas regarding the functional role of LTD, speculates: “Although it is conceivable that LTP is

The Nature-Nurture controversy has been with us since it was first outlined by Plato and Aristotle. Nobody likes it anymore. All reasonable scholars today agree that genes and environment interact to determine complex cognitive outcomes. So why does the controversy persist? First, it persists because it has practical implications that cannot be postponed (i.e., what can we do to avoid bad outcomes and insure better ones?), a state of emergency that sometimes tempts scholars to stake out claims they cannot defend. Second, the controversy persists because we lack a precise, testable theory of the process by which genes and environment interact. In the absence of a better theory, innateness is often confused with (1) domain specificity (Outcome X is so peculiar that it must be

We present the first direct comparison of language production in brain-injured children and adults, using agecorrected z scores for multiple lexical and grammatical measures. Spontaneous speech samples were elicited in a structured biographical interview from 38 children (5-8 years of age), 24 with congenital left-hemisphere damage (LHD) and 14 with congenital right-hemisphere damage (RHD), compared with 38 age- and gender-matched controls, 21 adults with unilateral injuries (14 LHD, 7 RHD), and 12 adult controls. Adults with LHD showed severe and contrasting profiles of impairment across all measures (including classic differences between fluent and nonfluent aphasia). Adults with RHD (and three nonaphasic adults with LHD) showed fluent but disinhibited and sometimes empty speech. None of these qualitative or quantitative deviations were observed in children with unilateral brain injury, who were in the normal range for their age on all measures. There were no significant differences between children with LHD and RHD on any measure. When LHD children were compared directly with LHD adults using age-corrected z scores, the children scored far better than their adult counterparts on structural measures. These results provide the first systematic confirmation of differential free-speech outcomes in children and adults, and offer strong evidence for neural and behavioral plasticity following early brain damage. For more than 3000 years, we have known that

Abstract. A viable evolutionary cognitive psychology requires that specific cognitive capacities be (a) heritable and (b) ‘quasi-independent ’ from other heritable traits. They must be heritable because there can be no selection for traits that are not. They must be quasi-independent from other heritable traits, since adaptive variations in a specific cognitive capacity could have no distinctive consequences for fitness if effecting those variations required widespread changes in other unrelated traits and capacities as well. These requirements would be satisfied by innate cognitive modules, as the dominant paradigm in evolutionary cognitive psychology assumes. However, those requirements would also be satisfied by heritable learning biases, perhaps in the form of architectural or chronotopic constraints, that operated to increase the canalization of specific cognitive capacities in the ancestral environment (Cummins and Cummins 1999). As an organism develops, cognitive capacities that are highly canalized as the result of heritable learning biases might result in an organism that is behaviourally quite similar to an organism whose innate modules come on line as the result of various environmental triggers. Taking this possibility seriously is increasingly important as the case against innate cognitive modules becomes increasingly strong.

Developmental cognitive neuroscience necessar- ily begins with a characterization of the developing mind. One cannot discover the neural underpinnings of cognition with- out detailed understanding of the representational Capacities that underlie thought. Characterizing the developing mind nvolves specifying the evolutionarily given building blocks from which human conceptual abilities are constructed. de- scribing what develops, and discovering the computational mechanisms that underlie the process of change. Here, 1 pres- ent the current state of the art with respect to one example of conceptual understanding: the representation of number.

A review of the Chialvo-Bak model is presented, for the two-layer neural network topology. A novel Markov Chain representation is proposed that yields several important analytical quantities and supports a learning convergence argument. The power law regime is re-examined under this new representation and is found to be limited to learning under small mapping changes. A parallel between the power law regime and the biological neural avalanches is proposed. A mechanism to avoid the permanent tagging of synaptic weights of the selective punishment rule is proposed. i Acknowledgements I wish to thank Dr. Mark van Rossum for his tireless support and attentive guidance, and for having accepted to supervise me in the first place. To Dr. J. Michael Herrmann I wish to thank the very creative and rewarding discussions on the holistic merits of the Chialvo-Bak model. To Dr. Wolfgang Maass and his team at the Institute for Theoretical Computer Science at T.U. Graz, I wish to thank the precious feedback and fruitful discussions received after the first

A study to enhance understanding of causal pathways as a step towards improving prevention and treatment.