Multispecies migratory connectivity indicates hemispheric-scale risk to bird populations from global change
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Latent circuit inference from heterogeneous neural responses during cognitive tasks
Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity and task variables leave unknown how heterogeneous responses arise from connectivity to drive behavior. We develop the latent circuit model, a dimensionality reduction approach in which task variables interact via low-dimensional recurrent connectivity to produce behavioral output. We apply the latent circuit inference to recurrent neural networks trained to perform a context-dependent decision-making task and find a suppression mechanism in which contextual representations inhibit irrelevant sensory responses. We validate this mechanism by confirming the behavioral effects of patterned connectivity perturbations predicted by the latent circuit model. We find similar suppression of irrelevant sensory responses in the prefrontal cortex of monkeys performing the same task. We show that incorporating causal interactions among task variables is critical for identifying behaviorally relevant computations from neural response data.
Simultaneous tACS-fMRI reveals state- and frequency-specific modulation of hippocampal-cortical functional connectivity
Non-invasive indirect hippocampal-targeted stimulation is of broad scientific and clinical interest. Transcranial alternating current stimulation (tACS) is appealing because it allows oscillatory stimulation to study hippocampal theta (3–8 Hz) activity. We found that tACS administered during functional magnetic resonance imaging yielded a frequency-, mental state- and topologically-specific effect of theta stimulation (but not other frequencies) enhancing right (but not left) hippocampal-cortical connectivity during resting blocks but not during task blocks. Control analyses showed that this effect was not due to possible stimulation-induced changes in signal quality or head movement. Our findings are promising for targeted network modulations of deep brain structures for research and clinical intervention.
Dopaminergic modulation and dosage effects on brain state dynamics and working memory component processes in Parkinson’s disease
Parkinson’s disease (PD) is primarily diagnosed through its characteristic motor deficits, yet it also encompasses progressive cognitive impairments that profoundly affect quality of life. While dopaminergic medications are routinely prescribed to manage motor symptoms in PD, their influence extends to cognitive functions as well. Here we investigate how dopaminergic medication influences aberrant brain circuit dynamics associated with encoding, maintenance and retrieval working memory (WM) task-phases processes. PD participants, both on and off dopaminergic medication, and healthy controls, performed a Sternberg WM task during fMRI scanning. We employ a Bayesian state-space computational model to delineate brain state dynamics related to different task phases. Importantly, a within-subject design allows us to examine individual differences in the effects of dopaminergic medication on brain circuit dynamics and task performance. We find that dopaminergic medication alters connectivity within prefrontal-basal ganglia-thalamic circuits, with changes correlating with enhanced task performance. Dopaminergic medication also restores engagement of task-phase-specific brain states, enhancing task performance. Critically, we identify an “inverted-U-shaped” relationship between medication dosage, brain state dynamics, and task performance. Our study provides valuable insights into the dynamic neural mechanisms underlying individual differences in dopamine treatment response in PD, paving the way for more personalized therapeutic strategies.
Coastal wetland resilience through local, regional and global conservation
Coastal wetlands, including tidal marshes, mangrove forests and tidal flats, support the livelihoods of millions of people. Understanding the resilience of coastal wetlands to the increasing number and intensity of anthropogenic threats (such as habitat conversion, pollution, fishing and climate change) can inform what conservation actions will be effective. In this Review, we synthesize anthropogenic threats to coastal wetlands and their resilience through the lens of scale. Over decades and centuries, anthropogenic threats have unfolded across local, regional and global scales, reducing both the extent and quality of coastal wetlands. The resilience of existing coastal wetlands is driven by their quality, which is modulated by both physical conditions (such as sediment supply) and ecological conditions (such as species interactions operating from local through to global scales). Protection and restoration efforts, however, are often localized and focus on the extent of coastal wetlands. The future of coastal wetlands will depend on an improved understanding of their resilience, and on society’s actions to enhance both their extent and quality across different scales.
The role of rivers in the origin and future of Amazonian biodiversity
The rich biodiversity of Amazonia is shaped geographically and ecologically by its rivers and their cycles of seasonal flooding. Anthropogenic effects, such as deforestation, infrastructure development and extreme climatic events, threaten the ecological processes sustaining Amazonian ecosystems. In this Review, we explore the coupled evolution of Amazonian rivers and biodiversity associated with terrestrial and seasonally flooded environments, integrating geological, climatic, ecological and genetic evidence. Amazonia and its fluvial environments are highly heterogeneous, and the drainage system is historically dynamic and continually evolving; as a result, the discharge, sediment load and strength of rivers as barriers to biotic dispersal has changed through time. Ecological affinities of taxa, drainage rearrangements and variations in riverine landscape caused by past climate changes have mediated the evolution of the high diversity found in modern-day Amazonia. The connected history of the region’s biodiversity and landscape provides fundamental information for mitigating current and future impacts. However, incomplete knowledge about species taxonomy, distributions, habitat use, ecological interactions and occurrence patterns limits our understanding. Partnerships with Indigenous peoples and local communities, who have close ties to land and natural resources, are key to improving knowledge generation and dissemination, enabling better impact assessments, monitoring and management of the riverine systems at risk from evolving pressures.
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