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Past research suggests that meditation and exposure to art or nature can positively impact people’s well-being and brain health, in some cases even reducing stress and supporting the processing of emotions. Yet most past studies focused on each of these experiences individually, rather than comparing their effects on brain activity.

Researchers at University of California Los Angeles set out to examine the brain activation patterns associated with a visualization-based of connecting to the cosmic soul and compare them to those from people watching evocative digital art or nature videos.

Their findings, published in Frontiers in Human Neuroscience, suggest that these different types of transcending experiences prompt different brain activation patterns.

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A study from Tel Aviv University could reshape our scientific understanding of how humans learn and form memories, particularly through classical and operant conditioning.

The research team found that our brain engages in a fierce competition between these two learning systems, and that only one can prevail at any given time. This means that if we try to learn two conflicting actions for the same situation simultaneously, the result will be confusion, making it difficult to perform either action when encountering the situation again.

In their study, the researchers demonstrate this phenomenon in fruit flies. When the flies were trained to associate a smell with a randomly delivered electric shock (classical conditioning) and also to connect their own actions to the smell and shock (operant conditioning), the flies became confused and failed to exhibit a clear response to the shock.

Alzheimer’s disease (AD) is defined by synaptic and neuronal degeneration and loss accompanied by amyloid beta (Aβ) plaques and tau neurofibrillary tangles (NFTs)1,2,3. In vivo animal experiments indicate that both Aβ and tau pathologies synergistically interact to impair neuronal circuits4. For example, the hypersynchronous epileptiform activity observed in over 60% of AD cases5 may be generated by surrounding Aβ and/or tau deposition yielding neuronal network hyperactivity5,6. Cortical and hippocampal network hyperexcitability precedes memory impairment in AD models7,8. In an apparent feedback loop, endogenous neuronal activity, in turn, regulates Aβ aggregation, in both animal models and computational simulations9,10. Multiple other factors involved in AD pathogenesis-remarkably, neuroinflammatory dysregulations-also seemingly influence neuronal firing and act on hypo/hyperexcitation patterns11,12,13. Thus, mounting evidence suggest that neuronal excitability changes are a key mechanistic event appearing early in AD and a tentative therapeutic target to reverse disease symptoms3,4,7,14. However, the exact patterns of Aβ, tau and other disease factors’ neuronal activity alterations in AD’s neurodegenerative progression are unclear as in vivo and non-invasive measuring of neuronal excitability in human subjects remains impractical.

Brain imaging and electrophysiological monitoring constitute a reliable readout for brain network degeneration likely associating with AD’s neuro-functional alterations3,15,16,17,18. Patients present distinct resting-state blood-oxygen-level-dependent (BOLD) signal content in the low frequency fluctuations range (0.01–0.08 Hz)16,19. These differences increase with disease progression, from cognitively unimpaired (CU) controls to mild cognitive impairment (MCI) to AD, correlating with performance on cognitive tests16. Another characteristic functional change is the slowing of the electro-(magneto-) encephalogram (E/MEG), with the signal shifting towards low frequency bands15,18. Electrophysiological spectral changes associate with brain atrophy and with losing connections to hub regions including the hippocampus, occipital and posterior areas of the default mode network20. All these damages are known to occur in parallel with cognitive impairment20. Disease processes also manifest differently given subject-specific genetic and environmental conditions1,21. Models of multiple pathological markers and physiology represent a promising avenue for revealing the connection between individual AD fingerprints and cognitive deficits3,18,22.

In effect, large-scale neuronal dynamical models of brain re-organization have been used to test disease-specific hypotheses by focusing on the corresponding causal mechanisms23,24,25. By considering brain topology (the structural connectome18) and regional profiles of a pathological agent24, it is possible to recreate how a disorder develops, providing supportive or conflicting evidence on the validity of a hypothesis23. Generative models follow average activity in relatively large groups of excitatory and inhibitory neurons (neural masses), with large-scale interactions generating E/MEG signals and/or functional MRI observations26. Through neural mass modeling, personalized virtual brains were built to describe Aβ pathology effects on AD-related EEG slowing25 and several hypotheses for neuronal hyperactivation have been tested27. Simulated resting-state functional MRI across the AD spectrum was used to estimate biophysical parameters associated with cognitive deterioration28. In addition, different intervention strategies to counter neuronal hyperactivity in AD have been tested10,22. Notably, comprehensive computational approaches combining pathophysiological patterns and functional network alterations allow the quantification of non-observable biological parameters29 like neuronal excitability values in a subject-specific basis1,3,18,21,23,24, facilitating the design of personalized treatments targeting the root cause(s) of functional alterations in AD.

Do speakers of different languages build sentence structure in the same way? In a neuroimaging study published in PLOS Biology, scientists from the Max Planck institute for Psycholinguistics, Donders Institute and Radboud University in Nijmegen recorded the brain activity of participants listening to Dutch stories. In contrast to English, sentence processing in Dutch was based on a strategy for predicting what comes next rather than a “wait-and-see” approach, showing that strategies may differ across languages.

While listening to spoken , people need to link abstract knowledge of grammar to the words they actually hear. Theories on how people build grammatical structure in real time are often based on English. In sentences such as “I have watched a documentary,” the noun “documentary” immediately follows the verb. However, in Dutch sentences, the may be reversed: “Ik heb een documentaire gezien” (“I have a documentary watched.”).

“To find out whether speakers of different languages build grammatical structure in the same way, it is important to look at languages that differ from English in such interesting respects,” says first author Cas Coopmans. “Findings based on English may not generalize to languages that have different grammatical properties, such as Dutch.”

It’s become increasingly clear that the gut microbiome can affect human health, including mental health. Which bacterial species influence the development of disease and how they do so, however, is only just starting to be unraveled.

For instance, some studies have found compelling links between one species of gut bacteria, Morganella morganii, and major depressive disorder. But until now, no one could tell whether this bacterium somehow helps drive the disorder, the disorder alters the microbiome, or something else is at play.

Harvard Medical School researchers have now pinpointed a biologic mechanism that strengthens the evidence that M. morganii influences brain health and provides a plausible explanation for how it does so.

Surprise is a key human emotion that is typically felt when something that we are witnessing or experiencing differs from our expectations. This natural human response to the unexpected has been the focus of numerous psychology studies, which uncovered some of its underlying neural processes.

Researchers at the University of Chicago have developed a brain network model that can predict people’s surprise. In a paper published in Nature Human Behaviour, they showed that this model generalized well across various tasks, predicting the surprise of individuals who were performing a task or watching different videos containing unexpected elements.

The study carried out by these researchers builds on previous research focusing on surprise. Earlier work found that humans experience surprise when reality clashes with their expectations in many different situations. Some of these past works discovered patterns of brain activity associated with each specific experience of surprise.

Specialized extracellular matrix structures known as perineuronal nets surround the soma and dendrites of many CNS neurons. Fawcett and colleagues provide an update on our current understanding of perineuronal net composition, formation and functional roles in brain function and disease.