Sylvain Sirois

Modeling developmental cognitive neuroscience

In the past few years connectionist models have greatly contributed to formulating theories of cognitive development. Some of these models follow the approach of developmental cognitive neuroscience in exploring interactions between brain development and cognitive development by integrating structural change into learning. We describe two classes of these models. The first focuses on experience-dependent structural elaboration within a brain region by adding or deleting units and connections during learning. The second models the gradual integration of different brain areas based on combinations of experience-dependent and maturational factors. These models provide new theories of the mechanisms of cognitive change in various domains and they offer an integrated framework to study normal and abnormal development, and normal and impaired adult processing.

An Interacting Systems Model of Infant Habituation

Habituation and related procedures are the primary behavioral tools used to assess perceptual and cognitive competence in early infancy. This article introduces a neurally constrained computational model of infant habituation. The model combines the two leading process theories of infant habituation into a single functional system that is grounded in functional brain circuitry. The HAB model (for Habituation, Autoassociation, and Brain) proposes that habituation behaviors emerge from the opponent, complementary processes of hippocampal selective inhibition and cortical long-term potentiation. Simulations of a seminal experiment by Fantz Visual experience in infants: Decreased attention familiar patterns relative to novel ones. Science, 146, 668670, 1964 are reported. The ability of the model to capture the fine detail of infant data (especially age-related changes in performance) underlines the useful contribution of neurocomputational models to our understanding of behavior in general, and of early cognition in particular.

Precis of neuroconstructivism: how the brain constructs cognition

Neuroconstructivism: How the Brain Constructs Cognition proposes a unifying framework for the study of cognitive development that brings together (1) constructivism (which views development as the progressive elaboration of increasingly complex structures), (2) cognitive neuroscience (which aims to understand the neural mechanisms underlying behavior), and (3) computational modeling (which proposes formal and explicit specifications of information processing). The guiding principle of our approach is context dependence, within and (in contrast to Marr [1982]) between levels of organization. We propose that three mechanisms guide the emergence of representations: competition, cooperation, and chronotopy; which themselves allow for two central processes: proactivity and progressive specialization. We suggest that the main outcome of development is partial representations, distributed across distinct functional circuits. This framework is derived by examining development at the level of single neurons, brain systems, and whole organisms. We use the terms encellment, embrainment, and embodiment to describe the higher-level contextual influences that act at each of these levels of organization. To illustrate these mechanisms in operation we provide case studies in early visual perception, infant habituation, phonological development, and object representations in infancy. Three further case studies are concerned with interactions between levels of explanation: social development, atypical development and within that, developmental dyslexia. We conclude that cognitive development arises from a dynamic, contextual change in embodied neural structures leading to partial representations across multiple brain regions and timescales, in response to proactively specified physical and social environment.

Social cognition in infancy: A critical review of research on higher order abilities

This paper reviews early precursors to social cognition in infancy, then critically reviews infancy work suggesting goal attribution to human agents in the first year of life and theory of mind (ToM) abilities (assessed through a modified false belief task) in the second year of life. Overall, methodological problems and statistical limitations compound data interpretation, which would be equivocal despite these limitations. The authors find no support for high-order social cognitive abilities in infancy. The discussion focuses on how the field of social cognition in infancy should build theories from the bottom up, assessing how simpler precursors change over time and combine to give rise to socially competent individuals.

Hebbian motor control in a robot-embedded model of habituation

Two experiments using a mobile robot examine the performance of a neural network model of habituation. The input to the network is the video feed from the robots camera, preprocessed to model the visual system. Images, after retinal processing, are translated in the frequency domain and Gabor-filtered. The output of the network controls the robots motors and thus where it looks. In one condition, network output directly controls the motors. In a second condition, network outputs are connected to control units via weights that are modified with simple Hebbian learning. In both cases, the robots behavior reproduces the important familiarity-to-novelty shift observed in human infants. Hebbian learning, however, helps to increase and stabilize novelty preference.

Preschoolers out of adults: Discriminative learning with a cognitive load

This paper explores novel predictions from the spontaneous overtraining interpretation of human discrimination shift learning (Sirois & Shultz, 1998a). Results from six experiments where adults perform a discrimination shift task with or without a cognitive distractor are reported. In three experiments with a concurrent distractor task (Experiments 1A, 2A, and 3A), performance of adults is comparable to what would be expected from preschoolers performing only the learning task. These adults show no dimensional transfer from initial learning, unless new attributes are introduced in shift learning. On the same tasks without a cognitive load (Experiments 1B, 2B, and 3B), performance is typical of normal adults. The discussion focuses on the relative ability of competing theoretical models (i.e., levels of processing, attentional mediation, and perceptual differentiation) to account for these data.

Studying development in the 21(st) century

In this response, we consider four main issues arising from the commentaries to the target article. These include further details of the theory of interactive specialization, the relationship between neuroconstructivism and selectionism, the implications of neuroconstructivism for the notion of representation, and the role of genetics in theories of development. We conclude by stressing the importance of multidisciplinary approaches in the future study of cognitive development and by identifying the directions in which neuroconstructivism can expand in the Twenty-first Century.

Pupil dilation and infant cognition

Looking time data provide the main window into early cognitive abilities of human infants. With respect to advanced conceptual capabilities, research findings supporting such skills in infants using Violation-of-Expectations (VOE) methods have been met with sustained criticism. This paper proposes the introduce pupil dilation data as a complement to looking time measures. Pupil dilation is an autonomous response to arousal, and should be observed if and when infants are surprised by conceptually unusual events, as typically used in VOE tasks. This paper reports on analyses of pupil dilation data to VOE events involving an implausible change of object identity. The data show that while some aspects of pupil responses show fluctuations across trials, some important features that help in the interpretation looking time data remain stable. The discussion stresses the potential benefits of including pupil data analyses in the study of infant cognition.

Lessons from atypical development

All parents have asked themselves why some children grow up to excel at mathematics, others to excel at languages and yet others to excel at sports. Occasionally, there are clear events that demarcate why one child has developed a strength in a particular area, but even without such obvious markers, individual children differ enormously in what they grow into. Our aim in this chapter is to introduce the notion of developmental tra-jectory (e. This is the idea that to fully understand a biological system such as the growing child, we need to consider each developmental step that the child has taken before. That is, we need to view the child as positioned on a continuous developmental trajectory rather than as simply passing through discrete stages of performance. An individual childs current position on this continuum is the outcome of a common developmental process that operates under slightly differing constraints. Children whose development follows a trajectory that is very different from the typical trajectory expected of the majority of other children offer a unique opportunity to examine how these constraints operate. Developmental disorders , then, strike at the heart of the issues we are considering in this book. What are the constraints that shape development? In this chapter, we will examine how development occurs in children with developmental disorders (see Box 11.1 What are developmental disorders?). The aim of this exercise is to explore how constraints at the genetic, neural, physical and social levels of description operate to guide cognitive development. We begin by asking what role, if any, development actually has in understanding children who follow atypical developmental trajectories. We then ask how the interactivity of brain systems constrains development, and the extent to which the timing of developmental events plays a significant role. Next, we ask what role differences in input encoding and motor abilities have on cognitive development. Finally, we ask how the childs social context can constrain development.