Magnetic resonance spectroscopy (MRS) measures the two most common inhibitory and excitatory neurotransmitters, GABA and glutamate, in the human brain. However, the role of MRS-derived GABA and glutamate signals in relation to system-level neural signaling and behavior is not fully understood. In this study, we investigated levels of GABA and glutamate in the visual cortex of healthy human participants (both genders) in three functional states with increasing visual input. Compared with a baseline state of eyes closed, GABA levels decreased after opening the eyes in darkness and Glx levels remained stable during eyes open but increased with visual stimulation. In relevant states, GABA and Glx correlated with amplitude of fMRI signal fluctuations. Furthermore, visual discriminatory performance correlated with the level of GABA, but not Glx. Our study suggests that differences in brain states can be detected through the contrasting dynamics of GABA and Glx, which has implications in interpreting MRS measurements.

Repeated display configurations improve visual search. Recently, the question has arisen whether this contextual cueing effect (Chun & Jiang, 1998) is itself mediated by attention, both in terms of selectivity and processing resources deployed. While it is accepted that selective attention modulates contextual cueing (Jiang & Leung, 2005), there is an ongoing debate whether the cueing effect is affected by a secondary working memory (WM) task, specifically at which stage WM influences the cueing effect: the acquisition of configural associations (e.g., Travis, Mattingley, & Dux, 2013) versus the expression of learned associations (e.g., Manginelli, Langer, Klose, & Pollmann, 2013). The present study re-investigated this issue. Observers performed a visual search in combination with a spatial WM task. The latter was applied on either early or late search trials--so as to examine whether WM load hampers the acquisition of or retrieval from contextual memory. Additionally, the WM and search tasks were performed either temporally in parallel or in succession--so as to permit the effects of spatial WM load to be dissociated from those of executive load. The secondary WM task was found to affect cueing in late, but not early, experimental trials--though only when the search and WM tasks were performed in parallel. This pattern suggests that contextual cueing involves a spatial WM resource, with spatial WM providing a workspace linking the current search array with configural long-term memory; as a result, occupying this workspace by a secondary WM task hampers the expression of learned configural associations.

Background Children’s literacy and mathematical competencies are a critical platform for their successful functioning as individuals in society. However, many children, in particular those with low socio-economic status (SES) backgrounds who may not receive the home support needed to develop to their full potential, are at risk of not reaching sufficient competence levels. The overall aim of this project is to develop innovative computer tablet applications (‘apps’) and test whether the apps support parents in the provision of high-quality home learning environments (HLEs) and impact positively on the short- and long-term development of children’s competencies. Altogether, “App-based learning for kindergarten children at home” (Learning4Kids) is a 5-year longitudinal study funded by the EU and designed to assess the potential impact of a tablet-based family intervention on children’s learning, development, social inclusion and well-being. Methods/design This study uses a multi-method intervention approach and draws on expertise from psychology, education, informatics, and didactics to evaluate the effectiveness of learning apps and the intervention approach. It also exploits new technological possibilities afforded by tablet computers that are very common nowadays in families. Learning4Kids sets out to measure the quality of the HLE, children’s early mathematical, literacy, and cognitive competencies and their behaviour. Here, data will be gathered via standardized tests, observations, and parental and educator surveys and checklists. Data collection also includes the assessment of app usage times via mobile sensing. In cohort 1, 190 families are assigned to one of four groups. One business-as-usual group will only participate in the child assessments, whereas the three remaining groups are provided with tablets for about 10 months. Two intervention groups will receive mathematical or literacy learning apps as well as parental information about these topics and the tablet-control-group will receive similar apps and information that focus on general child development, but not on mathematics or literacy. Discussion Whilst offering substantive advances for the scientific fields of psychology and education, the Learning4Kids study also has broad societal implications. Improving young children’s learning trajectories is both a social and economic imperative as it equips them to achieve greater individual success and to contribute to societal prosperity.

Repeated encounter of abstract target-distractor letter arrangements leads to improved visual search for such displays. This contextual-cueing effect is attributed to incidental learning of display configurations. Whether observers can consciously access the memory underlying the cueing effect is still a controversial issue. The current study uses a novel recognition task and eyetracking to tackle this question. Experiment 1 investigated observers’ ability to recognize or “generate” the display quadrant of the target in a previous search array when the target was now substituted by distractor element as well as where observers’ eye fixations would fall while they freely viewed the recognition display, examining the link between the fixation pattern and explicit recognition judgments. Experiment 2 tested whether eye fixations would serve a critical role for explicit retrieval from context memory. Experiment 3 asked whether eye fixations of the target region are critical for context-based facilitation of search reaction times to manifest. The results revealed longer fixational dwell times in the target quadrant for learned relative to foil displays. Further, explicit recognition was enhanced, and above chance level, when observers were made to fixate the target quadrant as compared to when they were prevented from doing so. However, the manifestation of contextual cueing of visual search did itself not require fixations of the target quadrant. Moreover, contextual-cueing of search reaction times was significantly correlated with both fixational dwell times and observers’ explicit generation performance. The results argue in favor of contextual cueing of visual search being the result of a single, explicit, memory system, though it could nevertheless receive support from separable—automatic versus controlled—retrieval processes. Fixational eye movements, that is, the directed overt allocation of visual attention, provide an interface between these processes in context cueing.

In everyday scenes, searched-for targets do not appear in isolation, but are embedded within configurations of non-target or distractor items. If the position of the target relative to the distractors is invariant, such spatial contingencies are implicitly learned and come to guide visual scanning ("contextual cueing"). However, the effectiveness of contextual cueing depends heavily on the consistency between bottom-up perceptual input and context memory:following configural learning, re-locating targets to an unexpected location within an unchanged distractor context completely abolishes contextual cueing, and gains deriving from the invariant context recover only very slowly with increasing exposure to the changed displays. The current study induces variations of the local target context, i.e., item density, to investigate the relation between this factor and contextual adaptation. The results showed that learned contextual cues can be adapted quickly if the target is re-positioned to a sparse local distractor context (consisting of 1 neighbouring non-target item), as compared to no adaptation with a dense context (with 3 surrounding non-targets). This suggests that contextual adaptation is modulated by spatial factors and is not per se limited by order effects in the learning process.