Saturday, April 03, 2010

Research Bytes 4-3-10: Gf, Gs, Gv, Ga, working memory, exec function, orthography plus more

Nettelbeck, T., & Burns, N. R. (2010). Processing speed, working memory and reasoning ability from childhood to old age. Personality and Individual Differences, 48(4), 379-384.

The study investigated whether theoretical causative relations among declining cognitive abilities during adulthood and old age conform to a literal reversal of improving cognitive development during childhood. Children aged 8–14 years (n = 240) and adults aged 18–87 (n = 238) completed the same battery of psychometric tests, which defined latent traits for processing speed, working memory, and reasoning ability. Speeded performance improved during childhood and slowed across the adult range. Childhood performance was well described by a developmental cascade, whereby increasing chronological age is accompanied by faster processing speed, which influences improved working memory, which in turn influences improving reasoning ability. However, although adult performance resembled a cascade with diminishing reasoning ability mediated by processing speed and working memory, this was not a mirror image of the cascade for children. The main difference with adults was a direct causal path between age and working memory. Post hoc analysis located this among adults aged 55 years and over. This suggests that, whereas childhood cognitive development is substantially mediated by processing speed, declining reasoning ability in old age is influenced by slower processing speed but also by age-related change(s) influencing working memory that are independent from processing speed.
Article Outline

1. Introduction
2. Method

2.1. Participants
2.2. Materials

2.2.1. Processing speed (PS)
2.2.2. Digit Symbol
2.2.3. Visual Matching
2.2.4. Inspection time (IT, Nettelbeck (2001))
2.2.5. Simple reaction time (RT)
2.2.6. Odd man out – decision time (DT, Frearson & Eysenck (1986))
2.2.7. Working memory (WM)
2.2.8. Picture Swaps (Stankov (2000))
2.2.9. Picture Recognition (modelled on the test from WJ – R)
2.2.10. Digit Span (modelled on the test from WAIS-IV)
2.2.11. Reasoning ability (RA)

2.3. Procedure
2.4. Statistical analyses

3. Results
4. Discussion

Wolbers, T., & Hegarty, M., (2010). What determines our navigational abilities? Trends in Cognitive Sciences, 14(2), 138-146
The ability to find one's way in our complex environments represents one of the most fundamental cognitive functions. Although involving basic perceptual and memory related processes, spatial navigation is particularly complex because it is a multisensory process in which information needs to be integrated and manipulated over time and space. Not surprisingly, humans differ widely in this ability, and recent animal and human work has begun to unveil the underlying mechanisms. Here, we consider three interdependent domains that have been related to navigational abilities: cognitive and perceptual factors, neural information processing and variability in brain microstructure. Together, the findings converge into an emerging model of how different factors interact to produce individual patterns of navigational performance.
Article Outline

Spatial navigation – a complex behavior with large individual differences
Variability in perceptual and cognitive processing
Variability in structure and function of critical brain circuits
Concluding remarks

Booth, J. N., Boyle, J. M. E., & Kelly, S. W. (2010). Do tasks make a difference? Accounting for heterogeneity of performance of children with reading difficulties on tasks of executive function: Findings from a meta-analysis. British Journal of Developmental Psychology, 28(1), 133-176.
Research studies have implicated executive functions in reading difficulties (RD). But while some studies have found children with RD to be impaired on tasks of executive function other studies report unimpaired performance. A meta-analysis was carried out to determine whether these discrepant findings can be accounted for by differences in the tasks of executive function that are utilized. A total of 48 studies comparing the performance on tasks of executive function of children with RD with their typically developing peers were included in the meta-analysis, yielding 180 effect sizes. An overall effect size of 0.57 (SE .03) was obtained, indicating that children with RD have impairments on tasks of executive function. However, effect sizes varied considerably suggesting that the impairment is not uniform. Moderator analysis revealed that task modality and IQ-achievement discrepancy definitions of RD influenced the magnitude of effect; however, the age and gender of participants and the nature of the RD did not have an influence. While the children's RD were associated with executive function impairments, variation in effect size is a product of the assessment task employed, underlying task demands, and definitional criteria.

Jordan, J. A., Wylie, J., & Mulhern, G. (2010). Phonological awareness and mathematical difficulty: A longitudinal perspective. British Journal of Developmental Psychology, 28(1), 89-107.

The present longitudinal study sought to investigate the impact of poor phonology on children's mathematical status. From a screening sample of 256 five-year-olds, 82 children were identified as either typically achieving (TA; N=31), having comorbid poor phonology and mathematical difficulties (PDMD; N=31), or having only poor phonology (phonological difficulty, PD; N=20). Children were assessed on eight components of informal and formal mathematics achievement at ages 5-7 years. PD children were found to have significant impairments in some, mainly formal, components of mathematics by age 7 compared to TA children. Analysis also revealed that, by age 7, approximately half of the PD children met the criteria for PDMD, while the remainder exhibited less severe deficits in some components of formal mathematics. Children's mathematical performance at age 5, however, did not predict which PD children were more likely to become PDMD at age 7, nor did they differ in terms of phonological awareness at age 5. However, those PD children who later became PDMD had lower scores on verbal and non-verbal tests of general ability.

Newton, E. J., Roberts, M. J., & Donlan, C. (2010). Deductive reasoning in children with specific language impairment. British Journal of Developmental Psychology, 28(1), 71-87.
The diagnosis of specific language impairment (SLI) requires non-verbal ability to be in the normal range, but little is known regarding the extent to which general reasoning skills are preserved during development. A total of 122 children were tested; 40 SLI, 42 age-matched controls, and 40 younger language-matched controls. Deductive reasoning tasks were given in both verbal and pictorial presentation types, namely the relational inference task and the reduced array selection task (RAST). Pictorial presentation facilitated all groups for all tasks equally. For the relational inference task, SLI performance was below both age and language matches. For the RAST, contextual information facilitated all groups equally. SLI performance was intermediate between age and language matches. It is concluded that the non-verbal versus verbal distinction is a complex one and that non-verbal reasoning can draw upon linguistic processes. It is also suggested that SLI reasoning depends upon precise task demands, here the need to sequence information in working memory, and the need for explicit reasoning with conditional rules. Reasoning processes may not be equivalent to normally developing children, even when tasks appear non-verbal.

Damian, M. F., & Bowers, J. S. (2010). Orthographic effects in rhyme monitoring tasks: Are they automatic? European Journal of Cognitive Psychology, 22(1), 106-116.

Over the last 30 years or so, various findings have been reported which suggest that the perception of spoken words may involve the automatic coactivation of orthographic properties. Here we assessed this possibility in auditory rhyme judgement tasks and replicated a classic finding reported by Seidenberg and Tanenhaus (1979), showing that orthographic similarity between stimuli facilitated responses on rhyming pairs, but had the opposite effect on nonrhyming pairs. However, Experiments 2 and 3 showed that manipulating the nature of the nonrhymes, or adding a large proportion of filler items, eliminated the effects of orthographic match or mismatch. These findings suggest the involvement of strategic factors in the emergence of orthographic effects in rhyme judgement tasks.
Keywords: Speech perception; Orthographic effects; Rhyme monitoring

Cowan, N. (2010). The Magical Mystery Four: How Is Working Memory Capacity Limited, and Why? Current Directions in Psychological Science, 19(1), 51-57.
Working memory storage capacity is important because cognitive tasks can be completed only with sufficient ability to hold information as it is processed. The ability to repeat information depends on task demands but can be distinguished from a more constant, underlying mechanism: a central memory store limited to 3 to 5 meaningful items for young adults. I discuss why this central limit is important, how it can be observed, how it differs among individuals, and why it may exist.

Hubbard, T. (2010). Auditory imagery:  Empircal findings.  Psychological Bulletin, 136(2), 302-329
The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d) auditory imagery’s relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia) are considered. It is concluded that auditory imagery (a) preserves many structural and temporal properties of auditory stimuli, (b) can facilitate auditory discrimination but interfere with auditory detection, (c) involves many of the same brain areas as auditory perception, (d) is often but not necessarily influenced by subvocalization, (e) involves semantically interpreted information and expectancies, (f) involves depictive components and descriptive components, (g) can function as a mnemonic but is distinct from rehearsal, and (h) is related to musical ability and experience (although the mechanisms of that relationship are not clear

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