How to build a brain: from function to implementation

To have a fully integrated understanding of neurobiological systems, we must address two fundamental questions: 1. What do brains do (what is their function)? and 2. How do brains do whatever it is that they do (how is that function implemented)? I begin by arguing that these questions are necessarily inter-related. Thus, addressing one without consideration of an answer to the other, as is often done, is a mistake. I then describe what I take to be the best available approach to addressing both questions. Specifically, to address 2, I adopt the Neural Engineering Framework (NEF) of Eliasmith &; Anderson [Neural engineering: Computation representation and dynamics in neurobiological systems. Cambridge, MA: MIT Press, 2003] which identifies implementational principles for neural models. To address 1, I suggest that adopting statistical modeling methods for perception and action will be functionally sufficient for capturing biological behavior. I show how these two answers will be mutually constraining, since the process of model selection for the statistical method in this approach can be informed by known anatomical and physiological properties of the brain, captured by the NEF. Similarly, the application of the NEF must be informed by functional hypotheses, captured by the statistical modeling approach.     

How to build a baby: On the development of an accessible representational system

The notion of a sensorimotor stage in infancy is called into question. First, some of the recent experimental literature on cognitive development in infancy is examined to determine the kinds of representational capacity that these data require. It is concluded that most of the recent work on perceptual development and the object concept in infancy is compatible with the notion of a sensorimotor stage but that other work showing imitation, motor recognition, the acquisition of manual signs, and recall of absent objects is not, requiring, instead, a conceptual form of representation. Such a system is apparent early in development. It is suggested that there is a viable alternative to Piaget's theory that conceptual representation consists of a transformation of sensorimotor schemas into a new, more advanced code. It is proposed that an accessible conceptual system develops simultaneously and in parallel with the sensorimotor system, with neither system being derivative from the other. It is further proposed that the mechanism by which infants encode information into an accessible system consists of a process of perceptual analysis.     

Learning to perceive object unity: a connectionist account

To explore questions of how human infants begin to perceive partly occluded objects, we devised two connectionist models of perceptual development. The models were endowed with an existing ability to detect several kinds of visual information that have been found important in infants’ and adults’ perception of object unity (motion, co‐motion, common motion, relatability, parallelism, texture and T‐junctions). They were then presented with stimuli consisting of either one or two objects and an occluding screen. The models’ task was to determine whether the object or objects were joined when such a percept was ambiguous, after specified amounts of training with events in which a subset of possible visual information was provided. The model that was trained in an enriched environment achieved superior levels of performance and was able to generalize veridical percepts to a wide range of novel stimuli. Implications for perceptual development in humans, current theories of development and origins of knowledge are discussed.     

Learning to attend: a connectionist model of situated language comprehension

Evidence from numerous studies using the visual world paradigm has revealed both that spoken language can rapidly guide attention in a related visual scene and that scene information can immediately influence comprehension processes. These findings motivated the coordinated interplay account ( Knoeferle & Crocker, 2006 ) of situated comprehension, which claims that utterance-mediated attention crucially underlies this closely coordinated interaction of language and scene processing. We present a recurrent sigma-pi neural network that models the rapid use of scene information, exploiting an utterance-mediated attentional mechanism that directly instantiates the CIA. The model is shown to achieve high levels of performance (both with and without scene contexts), while also exhibiting hallmark behaviors of situated comprehension, such as incremental processing, anticipation of appropriate role fillers, as well as the immediate use, and priority, of depicted event information through the coordinated use of utterance-mediated attention to the scene.     

Acquiring contextualized concepts: a connectionist approach

Conceptual knowledge is acquired through recurrent experiences, by extracting statistical regularities at different levels of granularity. At a fine level, patterns of feature co-occurrence are categorized into objects. At a coarser level, patterns of concept co-occurrence are categorized into contexts. We present and test CONCAT, a connectionist model that simultaneously learns to categorize objects and contexts. The model contains two hierarchically organized CALM modules (Murre, Phaf, & Wolters, 1992). The first module, the Object Module, forms object representations based on co-occurrences between features. These representations are used as input for the second module, the Context Module, which categorizes contexts based on object co-occurrences. Feedback connections from the Context Module to the Object Module send activation from the active context to those objects that frequently occur within this context. We demonstrate that context feedback contributes to the successful categorization of objects, especially when bottom-up feature information is degraded or ambiguous.     

How to Define Your (Mental) Terms

The discovery that the universe is fine-tuned for life ? a discovery to which the phrase ?the anthropic principle? is often applied ? has prompted much extra-cosmic speculation by philosophers, theologians, and theoretical physicists. Such speculation is referred to as extra-cosmic because an inference is made to the existence either of one unobservable entity that is distinct from the cosmos and any of its parts (God) or of many such entities (multiple universes). In this article a case is mounted for the sceptical position that cosmic fine-tuning does not support an inference to anything extra-cosmic. To that end three definitions of ?fine-tuned for life? are proposed: the ?slight difference? definition, the (unconditional) probability definition, and John Leslie?s conditional probability definition. These three definitions are the only ones suggested by the relevant literature on fine-tuning and the anthropic principle. Since on none of them do claims of fine-tuning warrant an inference to something extracosmic, it is concluded that there is no definition of ?fine-tuned for life? serving this function.     

How to do things with (recorded) words

The aim of this paper is to evaluate which context determines the illocutionary force of written or recorded utterances—those involved in written texts, films and images, conceived as recordings that can be seen or heard in different occasions. More precisely, my paper deals with the “metaphysical” or constitutive role of context—as opposed to its epistemic or evidential role: my goal is to determine which context is semantically relevant in order to fix the illocutionary force of a speech act, as distinct from the information the addressee uses to ascertain the semantically relevant context. In particular I will try to assess two different perspectives on this problem, a Conventionalist Perspective and an Intentionalist Perspective. Drawing on the literature on indexicals in written texts and recorded messages, I will argue in favor of the Intentionalist Perspective: the relevant context is the one intended by the speaker. Bringing intentions into the picture, however, requires qualification; in particular, I will distinguish my Weak Intentionalist proposal from a Strong Intentionalist one. I will show that the Weak Intentionalist Perspective is flexible enough to deal with cases of delayed communication, but not so unrestricted as to yield counter-intuitive consequences.     

How (not) to think about mental action

I examine Galen Strawson's recent work on mental action in his paper, ‘Mental Ballistics or The Involuntariness of Spontaneity’. I argue that his account of mental action is too restrictive. I offer a means of testing tokens of mental activity types to determine if they are actional. The upshot is that a good deal more mental activity than Strawson admits is actional.     

Talking nets: a multiagent connectionist approach to communication and trust between individuals

A multiagent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other and, as such, is a network of networks. The individual recurrent networks simulate the process of information uptake, integration, and memorization within individual agents, and the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents' existing beliefs and results in changes of the connections between individual networks, called trust weights. These weights lead to a selective propagation and thus to the filtering out of less reliable information, and they implement H. P. Grice's (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intrapersonal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions.     

Using connectionist models to guide assessment of psychological disorder

Connectionist models are introduced as promising tools for understanding the nature of psychological disorders and guiding their assessment. Specifically, ways in which connectionist models can guide the following aspects of the assessment process are described: understanding what constructs are relevant to assess, designing approaches to assessing these constructs, and understanding individual differences in data from assessments. Two extended examples are given based on the authors' research on cognitive aspects of depression and Alzheimer's disease.     

Using context to build semantics

Latent semantic analysis (LSA) is a model of knowledge representation for words. It works by applying dimension reduction to local co-occurrence data from a large collection of documents after performing singular value decomposition on it. When the reduction is applied, the system forms condensed representations for the words that incorporate higher order associations. The higher order associations are primarily responsible for any semantic similarity between words in LSA. In this article, a memory model is described that creates semantic representations for words that are similar in form to those created by LSA. However, instead of applying dimension reduction, the model builds the representations by using a retrieval mechanism from a well-known account of episodic memory.     

意气风发 共谋社会和谐——热烈祝贺两会胜利闭幕

春风送暖,大地披绿,我们又一次迎来了一个阳光明媚的春天。一年一度的全国人民代表大会和全国政协会议在世界各国人民的关注下胜利闭幕了,我们和全国各族人民一样满怀喜悦的心情,热烈祝贺两会的圆满成功。刚刚闭幕的十届全国人大三次会议是在我国改革发展的关键时期召开的一次重要会议,是一次团结奋进、昂扬向上、开拓创新、求真务实的会议。会议听取并审议了温家宝总理做的《政府工作报告》和其他几个重要报告;表决同意江泽民同志辞去国家军委主席职务的请求,对江泽民同志为国家、为人民、为国防事业所作的杰出贡献给予了高度评价,同时一致…     

Evaluation and development of a connectionist theory of configural learning

A configural theory of associative learning is described that is based on the assumption that conditioning results in associations between the unconditioned stimulus and a representation of the entire pattern of stimulation that was present prior to its delivery. Configural theory was formulated originally to account for generalization and discrimination in Pavlovian conditioning. The first part of the article demonstrates how this theory can be used to explain results from studies of overshadowing, blocking, summation, and discrimination learning. The second part of the article shows how the theory can be developed to explain a broader range of phenomena, including mediated conditioning, reinforcer devaluation effects, the differential outcomes effect, acquired equivalence, sensory preconditioning, and structural discriminations.