Resurrecting an old idea about assessing school quality could allow schools to examine a broad range of data on performance and practices and lead to improvement.

In a small region of Vermont, a fierce debate raged over consolidating five tiny school districts into one.

State Education Secretary Rebecca Holcombe has been officiating over the state's politically thorny district consolidation process, and many are asking for it to be placed on hold until the state board replaces her.

In Kodiak, Alaska, a school district with deep ties to the U.S. Coast Guard has been walloped by the government shutdown with hundreds of families going without paychecks. And news of a deal to temporarily reopen the government was doing little to allay the community's anxieties.

Enrollment snags, head-count problems, and more home schooling could end up costing districts millions in funding based on the annual tally of how many students actually show up.

The supreme court put an end to five years of legal wrangling that landed the state's public school system with millions more dollars from the state and teachers with a pay raise.

A Greenville, Miss. teacher was fired and a superintendent placed on administrative leave after a video of a student being dragged by her hair surfaced on social media.

But some Democrats say that could make the selection process more political.

Pandemic-inflicted budget cuts have cost thousands of educators their jobs. Here’s how that’s playing out in five districts around the country.

The switch to remote learning in rural New Mexico has left some students profoundly isolated—cut off from others and the grid by sheer distance.

There’s a tussle over the right balance for who should pick up the tab for teacher retirements and how that affects wealthier and less-wealthy districts.

Campaigns to get rid of police in schools catch a wave of momentum in some communities, but activists still face deep resistance from educators nationally.

The state's decision indicates that U.S. Secretary of Education Betsy DeVos' push on COVID-19 and private school students is having an affect.

Confusion reigns when it comes to finding and reporting data on school-related coronavirus infections. That's a problem for school leaders weighing shutdowns.

The court declined to take up an appeal backed by school groups of a ruling allowing some property taxpayers challenge their assessments in federal court.

Holly Oakley
Oct 4, 2006; 26:10129-10140
Neurobiology of Disease

Yang Hu
Feb 24, 2021; 41:1699-1715
BehavioralSystemsCognitive

Bruce S. McEwen
Jan 2, 2020; 40:12-21
Viewpoints

Jesse J. Langille
Jul 3, 2019; 39:5244-5246
Journal Club

Randy L. Buckner
Aug 24, 2005; 25:7709-7717
Neurobiology of Disease

AP Georgopoulos
Nov 1, 1982; 2:1527-1537
Articles

Holly Oakley
Oct 4, 2006; 26:10129-10140
Neurobiology of Disease

Emerging research in nonhuman animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white matter connectivity in a cohort of men and women using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections between the cerebellum and VTA predominantly originate in the right cerebellar hemisphere, interposed nucleus, and paravermal cortex and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared with other lobules. We discovered a mediolateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socioaffective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socioaffective regulation.

Human sleep exhibits multiple, recurrent temporal regularities, ranging from circadian rhythms to sleep stage cycles and neuronal oscillations during nonrapid eye movement sleep. Moreover, recent evidence revealed a functional role of aperiodic activity, which reliably discriminates different sleep stages. Aperiodic activity is commonly defined as the spectral slope of the 1/frequency (1/f) decay function of the electrophysiological power spectrum. However, several lines of inquiry now indicate that the aperiodic component of the power spectrum might be better characterized by a superposition of several decay processes with associated timescales. Here, we determined multiple timescales, which jointly shape aperiodic activity using human intracranial electroencephalography. Across three independent studies (47 participants, 23 female), our results reveal that aperiodic activity reliably dissociated sleep stage-dependent dynamics in a regionally specific manner. A principled approach to parametrize aperiodic activity delineated several, spatially and state-specific timescales. Lastly, we employed pharmacological modulation by means of propofol anesthesia to disentangle state-invariant timescales that may reflect physical properties of the underlying neural population from state-specific timescales that likely constitute functional interactions. Collectively, these results establish the presence of multiple intrinsic timescales that define the electrophysiological power spectrum during distinct brain states.

Neural decoding is a tool for understanding how activities from a population of neurons inside the brain relate to the outside world and for engineering applications such as brain–machine interfaces. However, neural decoding studies mainly focused on different decoding algorithms rather than different neuron types which could use different coding strategies. In this study, we used two-photon calcium imaging to assess three auditory spatial decoders (space map, opponent channel, and population pattern) in excitatory and inhibitory neurons in the dorsal inferior colliculus of male and female mice. Our findings revealed a clustering of excitatory neurons that prefer similar interaural level difference (ILD), the primary spatial cues in mice, while inhibitory neurons showed random local ILD organization. We found that inhibitory neurons displayed lower decoding variability under the opponent channel decoder, while excitatory neurons achieved higher decoding accuracy under the space map and population pattern decoders. Further analysis revealed that the inhibitory neurons’ preference for ILD off the midline and the excitatory neurons’ heterogeneous ILD tuning account for their decoding differences. Additionally, we discovered a sharper ILD tuning in the inhibitory neurons. Our computational model, linking this to increased presynaptic inhibitory inputs, was corroborated using monaural and binaural stimuli. Overall, this study provides experimental and computational insight into how excitatory and inhibitory neurons uniquely contribute to the coding of sound locations.

Large-scale genome-wide association studies (GWASs) have associated intronic variants in PDE4B, encoding cAMP-specific phosphodiesterase-4B (PDE4B), with increased risk for post-traumatic stress disorder (PTSD), as well as schizophrenia and substance use disorders that are often comorbid with it. However, the pathophysiological mechanisms of genetic risk involving PDE4B are poorly understood. To examine the effects of PDE4B variation on phenotypes with translational relevance to psychiatric disorders, we focused on PDE4B missense variant M220T, which is present in the human genome as rare coding variant rs775201287. When expressed in HEK-293 cells, PDE4B1-M220T exhibited an attenuated response to a forskolin-elicited increase in the intracellular cAMP concentration. In behavioral tests, homozygous Pde4b^M220T male mice with a C57BL/6JJcl background exhibited increased reactivity to novel environments, startle hyperreactivity, prepulse inhibition deficits, altered cued fear conditioning, and enhanced spatial memory, accompanied by an increase in cAMP signaling pathway-regulated expression of BDNF in the hippocampus. In response to a traumatic event (10 tone–shock pairings), neuronal activity was decreased in the cortex but enhanced in the amygdala and hippocampus of Pde4b^M220T mice. At 24 h post-trauma, Pde4b^M220T mice exhibited increased startle hyperreactivity and decreased plasma corticosterone levels, similar to phenotypes exhibited by PTSD patients. Trauma-exposed Pde4b^M220T mice also exhibited a slower decay in freezing at 15 and 30 d post-trauma, demonstrating enhanced persistence of traumatic memories, similar to that exhibited by PTSD patients. These findings provide substantive mouse model evidence linking PDE4B variation to PTSD-relevant phenotypes and thus highlight how genetic variation of PDE4B may contribute to PTSD risk.

It is well established that holding information in working memory (WM) elicits sustained stimulus-specific patterns of neural activity. Nevertheless, here we provide evidence for a distinct class of neural activity that tracks the number of individuated items in working memory, independent of the type of visual features stored. We present two EEG studies of young adults of both sexes that provide robust evidence for a signal tracking the number of individuated representations in working memory, regardless of the specific feature values stored. In Study 1, subjects maintained either colors or orientations across separate blocks in a single session. We found near-perfect generalization of the load signal between these two conditions, despite being able to simultaneously decode which feature had been voluntarily stored. In Study 2, participants attended to two features with very distinct cortical representations: color and motion coherence. We again found evidence for a neural load signal that robustly generalized across these distinct visual features, even though cortically disparate regions process color and motion coherence. Moreover, representational similarity analysis provided converging evidence for a content-independent load signal, while simultaneously showing that unique variance in EEG activity tracked the specific features that were stored. We posit that this load signal reflects a content-independent "pointer" operation that binds objects to the current context while parallel but distinct neural signals represent the features that are stored for each item in memory.

Key event-related potentials (ERPs) of perceptual decision-making such as centroparietal positivity (CPP) elucidate how evidence is accumulated toward a given choice. Furthermore, this accumulation can be impacted by visual target selection signals such as the N2 contralateral (N2c). How these underlying neural mechanisms of perceptual decision-making are influenced by the spatial congruence of distractors relative to target stimuli remains unclear. Here, we used electroencephalography (EEG) in humans of both sexes to investigate the effect of distractor spatial congruency (same vs different hemifield relative to targets) on perceptual decision-making. We confirmed that responses for perceptual decisions were slower for spatially incongruent versus congruent distractors of high salience. Similarly, markers of target selection (N2c peak amplitude) and evidence accumulation (CPP slope) were found to be lower when distractors were spatially incongruent versus congruent. To evaluate the effects of congruency further, we applied drift diffusion modeling to participant responses, which showed that larger amplitudes of both ERPs were correlated with shorter nondecision times when considering the effect of congruency. The modeling also suggested that congruency's effect on behavior occurred prior to and during evidence accumulation when considering the effects of the N2c peak and CPP slope. These findings point to spatially incongruent distractors, relative to congruent distractors, influencing decisions as early as the initial sensory processing phase and then continuing to exert an effect as evidence is accumulated throughout the decision-making process. Overall, our findings highlight how key electrophysiological signals of perceptual decision-making are influenced by the spatial congruence of target and distractor.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multiomics datasets provide opportunities to use computational approaches for such studies. Here, we devised a novel disease gene identification (digID) computational framework that consists of a semi-supervised deep learning classifier to predict AD-associated genes and a protein–protein interaction (PPI) network-based analysis to prioritize the importance of these predicted genes in AD. digID predicted 1,529 AD-associated genes and revealed potentially new AD molecular mechanisms and therapeutic targets including GNAI1 and GNB1, two G-protein subunits that regulate cell signaling, and KNG1, an upstream modulator of CDC42 small G-protein signaling and mediator of inflammation and candidate coregulator of amyloid precursor protein (APP). Analysis of mRNA expression validated their dysregulation in AD brains but further revealed the significant spatial patterns in different brain regions as well as among different subregions of the frontal cortex and hippocampi. Super-resolution STochastic Optical Reconstruction Microscopy (STORM) further demonstrated their subcellular colocalization and molecular interactions with APP in a transgenic mouse model of both sexes with AD-like mutations. These studies support the predictions made by digID while highlighting the importance of concurrent biological validation of computationally identified gene clusters as potential new AD therapeutic targets.

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