Neurotypical children have been shown to display a leftward visuospatial attention bias while children with dyslexia(i.e., children with a reading disorder characterized by slow and/or inaccurate word recognition) have been shown todisplay a relatively rightward visuospatial attention bias. Researchers have speculated that leftward bias in young childrenmay be driven by their beginning reading education in languages read from left to right. Here, we investigated whetherspatial bias may be related to the acquisition of reading skills among a sample of children in grades 1 to 3. We assessedthe relationship between spatial bias (measured using the landmark task) and performance on (1) a rapid automatizednaming test (a predictor of reading fluency) and (2) a word-identification test. We found that leftward bias predicts rapidautomatized naming but not word identification. This finding has implications for understanding the potential role ofspatial bias in reading and dyslexia.

Classic models of attention suggest that sustained neural firing constitutes a neural correlate of sustained attention. However, recent evidence indicates that behavioral performance fluctuates over time, exhibiting temporal dynamics that closely resemble the spectral features of ongoing, oscillatory brain activity. Therefore, it has been proposed that periodic neuronal excitability fluctuations might shape attentional allocation and overt behavior. However, empirical evidence to support this notion is sparse. Here, we address this issue by examining data from large-scale subdural recordings, using two different attention tasks that track perceptual ability at high temporal resolution. Our results reveal that perceptual outcome varies as a function of the theta phase even in states of sustained spatial attention. These effects were robust at the single-subject level, suggesting that rhythmic perceptual sampling is an inherent property of the frontoparietal attention network. Collectively, these findings support the notion that the functional architecture of top-down attention is intrinsically rhythmic.

The selection of behaviorally relevant information from cluttered visual scenes (often referred to as "attention") is mediated by a cortical large-scale network consisting of areas in occipital, temporal, parietal, and frontal cortex that is organized into a functional hierarchy of feedforward and feedback pathways. In the human brain, little is known about the temporal dynamics of attentional processing from studies at the mesoscopic level of electrocorticography (ECoG), that combines millisecond temporal resolution with precise anatomical localization of recording sites. We analyzed high-frequency broadband responses (HFB) responses from 626 electrodes implanted in 8 epilepsy patients who performed a spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system. HFB responses showed high spatial selectivity and tuning, constituting ECoG response fields (RFs), within and outside the topographic visual system. In accordance with monkey physiology studies, both RF widths and onset latencies increased systematically across the visual processing hierarchy. We used the spatial specificity of HFB responses to quantitatively study spatial attention effects and their temporal dynamics to probe a hierarchical top-down model suggesting that feedback signals back propagate the visual processing hierarchy. Consistent with such a model, the strengths of attentional modulation were found to be greater and modulation latencies to be shorter in posterior parietal cortex, middle temporal cortex and ventral extrastriate cortex compared with early visual cortex. However, inconsistent with such a model, attention effects were weaker and more delayed in anterior parietal and frontal cortex.SIGNIFICANCE STATEMENT In the human brain, visual attention has been predominantly studied using methods with high spatial, but poor temporal resolution such as fMRI, or high temporal, but poor spatial resolution such as EEG/MEG. Here, we investigate temporal dynamics and attention effects across the human visual system at a mesoscopic level that combines precise spatial and temporal measurements by using electrocorticography in epilepsy patients performing a classical spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system, thereby relating them to topography and processing hierarchy. We demonstrate regional differences in temporal dynamics across the attention network. Our findings do not fully support a top-down model that promotes influences on visual cortex by reversing the processing hierarchy.

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.