Visual field size necessary for length comparison

Influence of visual field size upon acuity for comparing lengths of two lines was investigated. The visual field was effectively narrowed to any desired size by use of a TV display system. The TV screen presented a portion of the test stimulus, the position of which was controlled by the subject’s eye movement so that his fixation point always coincided with the center of the portion. The test stimulus was composed of two lines arranged horizontally, one of which had a length of 81 mm and the other a slightly different value. Sizes of the narrowed visual field were 20, 40, 70, 100, 150, and 340 mm wide. The comparison acuity dropped rapidly as the visual field was narrowed to and below 70 mm which was about the same extent as one of the two lines. The implication is that our excellent ability for length comparison is only possible when we can observe the whole line at one time.     

Influence of foveal load on the functional visual field

Attention, Perception, & Psychophysics - The functional visual field defined in terms of a discrimination task of a target presented peripherally among ambiguous background patterns was...     

Brain mechanisms for predictive control by switching internal models: implications for higher-order cognitive functions

Humans can guide their actions toward the realization of their intentions. Flexible, rapid and precise realization of intentions and goals relies on the brain learning to control its actions on external objects and to predict the consequences of this control. Neural mechanisms that mimic the input–output properties of our own body and other objects can be used to support prediction and control, and such mechanisms are called internal models. We first summarize functional neuroimaging, behavioral and computational studies of the brain mechanisms related to acquisition, modular organization, and the predictive switching of internal models mainly for tool use. These mechanisms support predictive control and flexible switching of intentional actions. We then review recent studies demonstrating that internal models are crucial for the execution of not only immediate actions but also higher-order cognitive functions, including optimization of behaviors toward long-term goals, social interactions based on prediction of others’ actions and mental states, and language processing. These studies suggest that a concept of internal models can consistently explain the neural mechanisms and computational principles needed for fundamental sensorimotor functions as well as higher-order cognitive functions. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Spatiotemporal variations of alpha and sigma band EEG in the waking-sleeping transition period

The aim of this study is to evaluate the spatiotemporal variation of alpha and sigma band EEGs during the waking-sleeping transition or hypnagogic period. Power and coherence from 7 EEG channels (Fp1, F7, Fz, C3, Pz, T5, O1) were studied using EEG records of the period of 5 min. before the onset of Stage 1 to 24 min. after the onset of Stage 1. The EEG spectra were computed for 4 frequency bands (alpha 1: 8.0-9.0 Hz, alpha 2: 9.5-11.0 Hz, alpha 3: 11.5-12.5 Hz, and sigma: 13.0-15.0 Hz). The power of alpha 1 and 2 bands initially started to decrease before the onset of Stage 1. Principal component analysis of the coherence yielded Generalized and Localized Components in each band. The Generalized Component was widespread across scalp areas, while the Localized Component was a restricted local area. The Generalized Components of alpha 1 and 2 bands reached stable levels of NREM sleep about 1 min. after the onset of Stage 1. The component of sigma band reached a stable level of NREM sleep about 0.6 min. before the onset of Stage 2, while the component of alpha 3 band reached a stable level of NREM sleep about 3.4 min. after the onset of Stage 2. These results suggest that the alpha-sigma band EEG structures during the waking-sleeping transition period may not be uniform across EEG bands and that the hypnagogic EEG changes may start before the onset of Stage 1 and continue for several minutes after the onset of Stage 2.