Timing the “magical number seven”: Presentation rate and regularity affect verbal working memory performance

The informative value of time and temporal structure often remains neglected in cognitive assessments. However, next to information about stimulus identity we can exploit temporal ordering principles, such as regularity, periodicity, or grouping to generate predictions about the timing of future events. Such predictions may improve cognitive performance by optimising adaptation to dynamic stimuli. Here, we investigated the influence of temporal structure on verbal working memory by assessing immediate recall performance for aurally presented digit sequences (forward digit span) as a function of standard (1000 ms stimulus-onset-asynchronies, SOAs), short (700 ms), long (1300 ms) and mixed (700–1300 ms) stimulus timing during the presentation phase. Participant's digit spans were lower for short and mixed SOA presentation relative to standard SOAs. This confirms an impact of temporal structure on the classic “magical number seven,” suggesting that working memory performance can in part be regulated through the systematic application of temporal ordering principles.     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Talking Points: A Modulating Circle Increases Listening Effort Without Improving Speech Recognition in Young Adults

Psychonomic Bulletin & Review - Speech recognition is improved when the acoustic input is accompanied by visual cues provided by a talking face (Erber in Journal of Speech and Hearing Research,...     

Correction to: Effects of reward magnitude and training frequency on the learning rates and memory retention of the Port Jackson shark Heterodontus portusjacksoni

Animal Cognition - In the original publication of the article, the Fig. 4 was erroneously published.     

Neighborhood Stress and Life Satisfaction: Is there a Relationship for African American Adolescents?

Applied Research in Quality of Life - This study identified associations between perceived neighborhood stress and adolescents’ perceptions of life satisfaction. African American adolescents...     

Separate verbal memory and naming deficits in attention deficit disorder and reading disability

In this study, verbal memory and naming abilities were investigated in reading disabled (RD) and control children who were characterized according to the presence or absence of attention deficit disorder (ADD). Results indicate that deficits in learning and memory for recently acquired information occur as a function of ADD rather than RD while deficits in naming are specific to RD rather than ADD. We conclude that ADD is a major source of additional and separate cognitive morbidity in RD children.     

Correlations between glucose metabolic rates in brain regions of healthy male adults at rest and during language stimulation

This study examines the effect of different behavioral conditions on patterns of correlation between regional cerebral metabolic rates for glucose. Cerebral glucose metabolism was determined with positron emission tomography and (11C)-deoxyglucose in 29 normal subjects between the ages of 23 and 55. Seventeen subjects were studied in an unstimulated (resting) condition and 12 subjects during a phoneme monitoring language stimulation. Partial correlation coefficients, controlling for whole brain glucose metabolism, were calculated for pairs of metabolic rates in 14 cortical and 2 subcortical regions. Both stimulated and unstimulated subjects showed statistically significant correlations between left and right hemisphere homologs. The stimulated subjects also showed significant within-hemisphere correlations between left but not right hemisphere regions. These included left perisylvian regions classically associated with language functions (left inferior frontal, left superior temporal and left transverse temporal cortical regions) as well as other regions. Significant correlations between left regions and a right superior temporal region were also found. In general, these findings show a pattern of cross-hemisphere symmetry at rest and of hemisphere asymmetry during stimulation. Moreover, the asymmetry observed during stimulation appears to be superimposed upon a pattern of cross-hemisphere symmetry similar to that observed in the unstimulated state.