The Quality of Home Environment in Brazil: An Ecological Model

Based on Bronfenbrenner's (1999) ecological perspective, a longitudinal, prospective model of individual differences in the quality of home environment (Home Observation for Measurement of the Environment—HOME) was tested in a sample of 179 Brazilian children and their families. Perinatal measures of family socioeconomic status (SES) and child birth weight had direct effects on HOME at preschool age. As either family SES or child birth weight increased, HOME also increased through diminished emotional distress in the mother a month following childbirth. SES had a negative effect on number of children in the household, which in turn had a long-term negative impact on HOME. Compared to mothers who had reported not to plan their pregnancy, those who did were more likely to have fewer children, to report more spouse support during childbearing, and to show less emotional distress a month after childbirth, all of which also influenced HOME at preschool age. These findings are discussed in light of the broader socio-ecological Brazilian context, with direct implications to clinical practice aimed at improving the quality of home environment.     

Neural Computation and the Computational Theory of Cognition

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non‐neural notions of computation ought to be replaced or reinterpreted in terms of neural computation.     

A priori entailment and conceptual analysis: Making room for type-C physicalism 1

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.     

The First Computational Theory of Mind and Brain: A Close Look at Mcculloch and Pitts's “Logical Calculus of Ideas Immanent in Nervous Activity”

Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in computability theory), (ii) a technique that inspired the notion of logic design (a fundamental part of modern computer design), (iii) the first use of computation to address the mind–body problem, and (iv) the first modern computational theory of mind and brain.     

Crying as a Form of Parent–Infant Communication in the Context of Maternal Depression

In cases of maternal depression certain complex factors interfere with communication with the child. The present study sought to investigate forms of parent–infant communication in families in which the mother was experiencing postpartum depression. Particular emphasis was placed on analysis of crying patterns and on methods employed by parents to soothe the child. The study sample comprised 15 families in which the mother had a diagnosis of postpartum depression. Semi-structured interviews were performed, followed by qualitative content analysis. Results showed that depressed mothers—and, at times, their husbands—reported difficulties in communication with their child, particularly in distinguishing different types of cries and in ways of soothing the infant. Postpartum depression is discussed as a specific diagnosis, beyond its relational aspect, which affects the family as a whole.     

Computation without Representation

The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational states are individuated within computability theory and computer science. A secondary purpose is to show that existing arguments for the semantic view are defective.     

Integrating psychology and neuroscience: functional analyses as mechanism sketches

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms, in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated with multilevel mechanistic explanations.     

Computational explanation in neuroscience

According to some philosophers, computational explanation is proprietary to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that are being developed by a number of authors.     

Religiosity/Spirituality and Mental Health and Quality of Life of Early Pregnant Women

Journal of Religion and Health - The present study aims to investigate how religious/spiritual (R/S) beliefs are associated with depressive, anxious and stress symptoms and quality of life (QOL) of...