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Artificial intelligence can transform medicine in a myriad of ways, including its promise to act as a trusted diagnostic aide to busy clinicians.

Over the past two years, proprietary AI models, also known as closed-source models, have excelled at solving hard-to-crack medical cases that require complex clinical reasoning. Notably, these closed-source AI models have outperformed ones, so-called because their source code is publicly available and can be tweaked and modified by anyone.

Has open-source AI caught up?

The mass extinction that ended the Permian geological epoch, 252 million years ago, wiped out most animals living on Earth. Huge volcanoes erupted, releasing 100,000 billion metric tons of carbon dioxide into the atmosphere. This destabilized the climate and the carbon cycle, leading to dramatic global warming, deoxygenated oceans, and mass extinction.

However, many plants survived, leaving behind fossils which scientists have used to model a dramatic 10° rise in .

“While fossilized spores and pollen of plants from the Early Triassic do not provide strong evidence for a sudden and catastrophic biodiversity loss, both marine and terrestrial animals experienced the most severe mass extinction in Earth’s history,” explained Dr. Maura Brunetti of the University of Geneva, lead author of the article in Frontiers in Earth Science.

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00:00 Intro.
00:20 José Delgado’s beginnings with BCIs.
00:42 Use of BCI to reduce aggression.
00:57 How the brain and nerve cells work.
03:00 Stimulation of brain areas (motor cortex)
03:51 How Utah arrays works!
05:16 Measurement of voltage peaks (spikes)
06:06 How the Neuralink N1 works!
08:20 How the Stentrode by Synchron works!
09:40 The future of exoskeletons.
09:53 Are we becoming machines ourselves?

New in JNeurosci: Klein et al. characterized changes in the brain as people age and discovered that neural changes in teenagers may predict how decision-making and behavioral control develop.

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Seminal studies in animal neuroscience demonstrate that frontostriatal circuits exhibit a ventral-dorsal functional gradient to integrate neural functions related to reward processing and cognitive control. Prominent neurodevelopmental models posit that heightened reward-seeking and risk-taking during adolescence result from maturational imbalances between frontostriatal neural systems underlying reward processing and cognitive control. The present study investigated whether the development of ventral (VS) and dorsal (DS) striatal resting-state connectivity (rsFC) networks along this proposed functional gradient relates to putative imbalances between reward and executive systems posited by a dual neural systems theory of adolescent development. 163 participants aged 11–25 years (54% female, 90% white) underwent resting scans at baseline and biennially thereafter, yielding 339 scans across four assessment waves. We observed developmental increases in VS rsFC with brain areas implicated in reward processing (e.g., subgenual cingulate gyrus and medial orbitofrontal cortex) and concurrent decreases with areas implicated in executive function (e.g., ventrolateral and dorsolateral prefrontal cortices). DS rsFC exhibited the opposite pattern. More rapid developmental increases in VS rsFC with reward areas were associated with developmental improvements in reward-based decision making, whereas increases in DS rsFC with executive function areas were associated with improved executive function, though each network exhibited some crossover in function. Collectively, these findings suggest that typical adolescent neurodevelopment is characterized by a divergence in ventral and dorsal frontostriatal connectivity that may relate to developmental improvements in affective decision-making and executive function.

Significance Statement Anatomical studies in nonhuman primates demonstrate that frontostriatal circuits are essential for integration of neural functions underlying reward processing and cognition, with human neuroimaging studies linking alterations in these circuits to psychopathology. The present study characterized the developmental trajectories of frontostriatal resting state networks from childhood to young adulthood. We demonstrate that ventral and dorsal aspects of the striatum exhibit distinct age-related changes that predicted developmental improvements in reward-related decision making and executive function. These results highlight that adolescence is characterized by distinct changes in frontostriatal networks that may relate to normative increases in risk-taking. Atypical developmental trajectories of frontostriatal networks may contribute to adolescent-onset psychopathology.