Monaural right-ear advantage in a target-identification task

Subjects were monaurally presented with consonant—vowel syllables to the right or left ear, with or without simultaneous noise to the other ear. The subject's task on each trial was to indicate whether or not the item presented was the target item /ba/. A right-ear advantage in reaction time was obtained: 14 msec for target items, 6 msec for nontarget items. The size of this effect was comparable in the presence vs. absence of competing noise. No consistent individual differences were found in the size of the right-ear advantage for this task, although such differences were obtained in a dichotic-perception pretest.It is argued that data of this type do not permit inferences about the use of particular ear/hemisphere neural pathways.     

Language acquisition following hemidecortication: Linguistic superiority of the left over the right hemisphere

The language development of three 9- and 10-year-old children possessing only a right or a left hemisphere was studied. Surgical removal of one brain half antedated the beginning of speech, so each child has acquired speech and language with only one hemisphere. Different configurations of language skill have developed in the two isolated hemispheres: phonemic and semantic abilities are similarly developed but syntactic competence has been asymmetrically acquired. In relation to the left, the right brain half is deficient in understanding auditory language, especially when meaning is conveyed by syntactic diversity; detecting and correcting errors of surface syntactic structure; repeating stylistically permuted sentences; producing tag questions which match the grammatical features of a heard statement; determining sentence implication; integrating semantic and syntactic information to replace missing pronouns; and performing judgments of word interrelationships in sentences. Language development in an isolated right hemisphere, even under seizure-free conditions, results in incomplete language acquisition.     

Influence of linguistic complexity,rate of presentation,and interphrase pause time on auditory-verbal comprehension of adult aphasic patients

Among the variables affecting comprehension of linguistic stimuli by aphasic subjects are syntactic complexity and processing time. Comprehension performance of 15 aphasic adults was studied while altering the rate of speech presentation and varying the pause time between the major phrases within sentences of increasing grammatical complexity.Simple Active Affirmative Declarative Sentences, Negative, and Passive sentences were presented (1) at the rate of 150 words per minute (wpm) with 1-sec interphrase pause time (IPT); (2) 150 wpm with no pauses; (3) 120 wpm with 1-sec IPT; (4) 120 wpm with no pauses added.Performance was seen to vary with increasing syntactical complexity and as a function of processing time. Greater comprehension was seen with active affirmative than negative; greater with passive affirmative than with active negative. Clinical implications are discussed. Subjects demonstrated greater comprehension when sentences were presented at slower than normal rate; addition of interphrase pause time intervals aided comprehension. Combining slower rate of presentation and IPT intervals provided greatest increase in auditory processing time and showed concomitant increase in comprehension performance.     

Contralateral interference and ear advantages for identification of three-element patterns

Recent experience with attempts to test relatively simple patterns such as three-tone sequences in a traditional dichotic-listening paradigm indicates that when such sequences are used for both target and contralateral interference, performance tends to be low in both ears and not useful for measuring or comparing ear advantages in various target conditions. It is reported that tests with a variety of sounds presented contralaterally to three-element patterns show that several such sounds can (1) allow performance in at least one ear to remain above floor values, (2) result in performance in at least one ear that is below ceiling, and (3) reveal ear advantages that are similar in direction and magnitude to those seen with the traditional dichotic paradigm.     

Spread of Risk Information Through Microblogs: Twitter Users with More Mutual Connections Relay News That is More Dreadful1

In elucidating the spread of risk information through microblogging, it is important to understand the behaviors of numerous average users, in addition to the activities of authorities. We followed the transmission pathways of 10 actual widely spread tweets concerning several risk information topics, including natural disasters, nuclear disasters, and infectious diseases, and we identified the types of risk that affected retweeting by classifying each tweet based on Slovic's risk-perception model. Furthermore, we examined the types of users who did and did not retweet the information. Users with few connections in the form of followers (i.e., people who are following a user) or followees (people a user is following), or with a low ratio of mutual followers within their connections, had a tendency to retweet a large amount of risk information, regardless of the type of risk involved. On the other hand, users with a high ratio of mutual followers exhibited a greater tendency to retweet risk information when it was perceived as dreadful, though they did not retweet risk information much on the whole. These results suggest that there are two mechanisms by which risk information is spread within the Twitter network: information exchange and social sharing of personal reactions.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.