Subclinical inclination toward manic-depression and creative performance on the Remote Associates Test

An experiment examined manic-depressive inclination in college students as an influence on creativity. The Bipolar: Manic Disorder scale of the Millon Clinical Multiaxial Inventory determined manic-depressive inclination or its absence. The Remote Associates Test was the basis for assessing creativity. The experiment was a 2×2 factorial design with manic-depressive inclination (presence or absence) as the first factor, and a mood-enhancing experience as the second. The mood-enhancing experience required that students write an essay about an activity they once had performed superbly well. Students assigned to the control condition wrote an essay about how they organized and sequenced activities in an ordinary day. As hypothesized, students with high Bipolar scores who wrote about a peak performance obtained especially high Remote Associates Test scores in comparison with students in other conditions of the experiment (p<0.02). High Bipolar scores did not result in high Remote Associates Test scores in the control condition, suggesting that mood enhancement is a necessary prerequisite for manic-depressive inclination to potentiate creative performance.     

An evaluation of assumptions underlying the single-patient-only position in neuropsychological research: a reply.

This note challenges the position adopted by A. Caramazza and W. Badecker (1989, Brain and Cognition 10, 256-295) that, since the a priori classification of patients can only be theoretically arbitrary, the basic unit of analysis in cognitive neuropsychology must be the individual patient. We argue that even if there is no prior theory to justify patient classification, this does not preclude group studies; syndromes are what the world gives us--they constrain theory, permitting groups to be formed for research purposes. We also reexamine a particular example of group-based research that was extensively criticized by Caramazza and Badecker. We confront each of their criticisms, and, again, demonstrate the validity of group-based research.     

Parsing to Learn

Learning a language by parameter setting is almost certainly less onerous than composing a grammar from scratch. But recent computational modeling of how parameters are set has shown that it is not at all the simple mechanical process sometimes imagined. Sentences must be parsed to discover the properties that select between parameter values. But the sentences that drive learning cannot be parsed with the learner's current grammar. And there is not much point in parsing them with just one new grammar. They must apparently be parsed with all possible grammars, in order to find out which one is most successful at licensing the language. The research task is to reconcile this with the fact that the human sentence parsing mechanism, even in adults, has only very limited parallel parsing capacity. I have proposed that all possible grammars can be folded into one, if parameter values are fragments of sentential tree structures that the parser can make use of where necessary to assign a structure to an input sentence. However, the problem of capacity limitations remains. The combined grammar will afford multiple analyses for some sentences, too many to be computed on-line. I propose that the parser computes only one analysis per sentence but can detect ambiguity, and that the learner makes use of unambiguous input only. This provides secure information but relatively little of it, particularly at early stages of learning where few grammars have been excluded and ambiguity is rife. I consider three solutions: improving the parser's ability to extract unambiguous information from partially ambiguous sentences, assuming default parameter values to temporarily eliminate ambiguity, reconfiguring the parameters so that some are subordinate to others and do not present themselves to the learner until the others have been set. A more radical alternative is to give up the quest for error-free learning and permit parameters to be set without regard for whether the parser may have overlooked an alternative analysis of the sentence. If it can be assumed that the human parser keeps a running tally of the parameter values it has accessed, then the learner would do nothing other than parse sentences for comprehension, as adults do. The most useful parameter values would become more and more easily accessed; the noncontributors would drop out of the running. There would be no learning mechanism at all, over and above the parser. But how accurate this system would be remains to be established.     

Right-Wing Authoritarianism in Relation to Proposed Judicial Action, Electromyographic Response, and Affective Attitudes Toward a Schizophrenic Mother

Student participants who were high vs. low on Altemeyer's (1996) Right-Wing Authoritarianism (RWA) scale read background information and observed a videotaped interview concerning a schizophrenic woman who ostensibly killed her 2 young children in response to what she perceived as divine command. The woman now was functioning normally in response to medical treatment. High RWAs recommended harsher sentencing and expressed less sympathy than did low RWAs. High RWAs also evinced more facial electromyographic activity from the corrugator brow (i.e., frown) muscle while observing the interview than did low RWAs and gave the woman lower ratings on the Affective Attitudes Scale ( Crites, Fabrigar, & Petty, 1994 ).