Sleep spindles and intelligence: evidence for a sexual dimorphism.

Sleep spindles are thalamocortical oscillations in nonrapid eye movement sleep, which play an important role in sleep-related neuroplasticity and offline information processing. Sleep spindle features are stable within and vary between individuals, with, for example, females having a higher number of spindles and higher spindle density than males. Sleep spindles have been associated with learning potential and intelligence; however, the details of this relationship have not been fully clarified yet. In a sample of 160 adult human subjects with a broad IQ range, we investigated the relationship between sleep spindle parameters and intelligence. In females, we found a positive age-corrected association between intelligence and fast sleep spindle amplitude in central and frontal derivations and a positive association between intelligence and slow sleep spindle duration in all except one derivation. In males, a negative association between intelligence and fast spindle density in posterior regions was found. Effects were continuous over the entire IQ range. Our results demonstrate that, although there is an association between sleep spindle parameters and intellectual performance, these effects are more modest than previously reported and mainly present in females. This supports the view that intelligence does not rely on a single neural framework, and stronger neural connectivity manifesting in increased thalamocortical oscillations in sleep is one particular mechanism typical for females but not males.

Super-Memorizers Are Not Super-Recognizers.

Humans have a natural expertise in recognizing faces. However, the nature of the interaction between this critical visual biological skill and memory is yet unclear. Here, we had the unique opportunity to test two individuals who have had exceptional success in the World Memory Championships, including several world records in face-name association memory. We designed a range of face processing tasks to determine whether superior/expert face memory skills are associated with distinctive perceptual strategies for processing faces. Superior memorizers excelled at tasks involving associative face-name learning. Nevertheless, they were as impaired as controls in tasks probing the efficiency of the face system: face inversion and the other-race effect. Super memorizers did not show increased hippocampal volumes, and exhibited optimal generic eye movement strategies when they performed complex multi-item face-name associations. Our data show that the visual computations of the face system are not malleable and are robust to acquired expertise involving extensive training of associative memory.

A comparison of two sleep spindle detection methods based on all night averages: individually adjusted vs. fixed frequencies.

Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (FixF) (11-13 Hz for slow spindles, 13-15 Hz for fast spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.