Inhibition of the LH Surge by Restraint Stress in Cyclic Rats: Studies on the Role of GABAA and GABAB Receptors

There is evidence that stress can alter the activity in the brain of gamma-aminobutyricacid (GABA), a neurotransmitter that has been implicated in the regulation of LH secretion. In the present study the role of GABA in the restraint stress-induced inhibition of the LH surge was investigated in the intact cyclic rat. Intracerebroventricular (icv) administration of the GABAA receptor agonist muscimol (0.1, 0.5 or 1 μg) 5 min before the presumed onset of the pro-oestrous LH surge (at 0900 h) caused a dose dependent suppression of the surge. A single dose of the GABAB receptor agonist baclofen (1 μg; icv) injected at 0855 h postponed the onset of the LH surge, and repeated injections at 0855 and 1130 h suppressed the surge. These data indicate that GABA-ergic activity in the brain can inhibit the LH surge in the cyclic rat via GABAA and GABAB receptors. Pro-oestrous rats were subjected to 5 hrs of restraint starting at 0855 h. Pretreatment with the GABAA receptor antagonist bicuculine (1 μg; icv) at 0840, 0940 and 1040 h or pretreatment with the GABAB receptor antagonist phaclofen (10 μg; icv) at 0840 h were ineffective in preventing the restraint-induced inhibition of the LH surge. The results suggest that GABAA and GABAB receptors are not involved in the inhibitory effect of restraint stress on the LH surge.     

A Semantics and Methodology for Ceteris Paribus Hypotheses

Taking seriously the arguments of Earman, Roberts and Smith that ceteris paribus laws have no semantics and cannot be tested, I suggest that ceteris paribus claims have a kind of formal pragmatics, and that at least some of them can be verified or refuted in the limit. This revised version was published online in July 2006 with corrections to the Cover Date.     

A theory of causal learning in children: causal maps and Bayes nets

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.     

Causal inference

Conclusion We have examined only a few of the basic questions about causal inference that result from Reichenbach's two principles. We have not considered what happens when the probability distribution is a mixture of distributions from different causal structures, or how unmeasured common causes can be detected, or what inferences can reliably be drawn about causal relations among unmeasured variables, or the exact advantages that experimental control offers. A good deal is known about these questions, and there is a good deal more to find out.We thank the Office of Naval Research and the Navy Personnel Research and Development Center for supporting this research. Proofs of theorems will be found in Spirtes, Glymour, and Scheines (1991).     

Causal learning mechanisms in very young children: two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation

Three studies investigated whether young children make accurate causal inferences on the basis of patterns of variation and covariation. Children were presented with a new causal relation by means of a machine called the "blicket detector." Some objects, but not others, made the machine light up and play music. In the first 2 experiments, children were told that "blickets make the machine go" and were then asked to identify which objects were "blickets." Two-, 3-, and 4-year-old children were shown various patterns of variation and covariation between two different objects and the activation of the machine. All 3 age groups took this information into account in their causal judgments about which objects were blickets. In a 3rd experiment, 3- and 4-year-old children used the information when they were asked to make the machine stop. These results are related to Bayes-net causal graphical models of causal learning.     

Preschool children learn about causal structure from conditional interventions

The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of experimental design and the causal Bayes net formalism. Two studies suggest that preschoolers can use the conditional intervention principle to distinguish causal chains, common cause and interactive causal structures even in the absence of differential spatiotemporal cues and specific mechanism knowledge. Children were also able to use knowledge of causal structure to predict the patterns of evidence that would result from interventions. A third study suggests that children's spontaneous play can generate evidence that would support such accurate causal learning.     

Lifecourse Social Conditions and Racial and Ethnic Patterns of Cognitive Aging

A lifecourse perspective is key for understanding and interpreting racial and ethnic patterns in neuropsychological test performance. In this article, we discuss contextual factors that shape the environmental conditions encountered by racial and ethnic minorities in the United States, in particular African-Americans. These conditions include geographic segregation at the level of regions, metropolitan areas, and neighborhoods; intra- and inter-national migration patterns; socioeconomic position, including financial resources, and occupational and educational opportunities; discrimination; and group resources. Each of these exposures sets in course a cascade of individual mediators that ultimately manifest in neuropsychological outcomes. The physiological and behavioral consequences of these pathways likely accumulate across the lifecourse. We focus on cognitive aging, although the processes discussed here begin in infancy and likely influence cognitive outcomes throughout life from childhood into old age. A lifecourse framework can help inform clinical encounters, neuropsychological research, and surveillance regarding the population prevalence of cognitive impairments.