In the quest to unravel the complexities of neural circuits, scientists are beginning to use genetically encoded voltage indicators (GEVIs) to visualize electrical activity in the brain. These indicators are crucial for understanding how neurons communicate and process information. However, the effectiveness of one-photon (1P) versus two-photon (2P) voltage imaging has remained a topic of debate. A recent study by researchers at Harvard University sheds light on the relative merits and limitations of these two imaging techniques, providing valuable insights for the scientific community.
Category: neuroscience – Page 94
Bracha et al.
Toxoplasma gondii culture and maintenance.
Type I RH and type II Pru and ME49 strain T. gondii were grown in HFF in high-glucose Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 4 mM l-glutamine, 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin or 20 μg ml−1 gentamicin antibiotics (‘complete DMEM’) at 37 °C with 5% CO2. Cultures were monitored daily and T. gondii were passaged by transferring 1–3 drops (20–100 μl) of the supernatant of a lysed dish (containing extracellular parasites) into a fresh dish with confluent HFF cells. Type I RH and type II Pru strains were validated by PCR–restriction-fragment length polymorphism (primers described in Supplementary Table 1)81 or by passage into Cre Reporter cell lines to confirm Cre recombination as previously described16.
This explores how the human brain forms abstract concepts and adapts to changing environments, specifically looking at how neurons in certain brain regions contribute to complex thinking.
It takes brains to infer how any two things in the world relate to each other, whether it’s the way bad weather links to commuting delays or how environmental conditions lead to the evolution of species. A new study based on recordings in the brains of people has yielded a pathbreaking trove of data that researchers now have used to reveal, with more clarity than ever, the neural incarnations of inferential reasoning.
In a recent study in Nature Communications, researchers increased synaptic serotonin through a selective serotonin-releasing agent (SSRA), fenfluramine, to investigate its impact on human behavior.
Neuroscience research concentrates on the function of central serotonin (5HT) in human behavior, specifically the impact of selective serotonin reuptake inhibitors (SSRIs). Serotonin is necessary for several actions, including eating, sexual function, and goal-directed cognition.
It is difficult to determine the causal relationship between increased synaptic 5-HT and behavior in humans via SSRIs due to SSRIs’ complicated effects on 5-HT and colocalized neurotransmitter systems. A low dose of fenfluramine, approved for the treatment of Dravet epilepsy in 2020, directly and swiftly elevates synaptic 5-HT without altering extracellular dopamine concentrations in mood control areas.
Ivanti releases critical security updates for vTM and Neurons for ITSM to fix vulnerabilities allowing unauthorized access. Update immediately.
A new method of detecting criticality from time-series data outperforms conventional metrics in the presence of variable noise levels for both simulated systems and real neural recordings.
Engineers have tried for decades to develop bionic eyes to reverse blindness. But the brain is far more complex than a computer.
Preclinical study investigates neuron-targeted partial cellular reprogramming in the hippocampus to mitigate age-related cognitive impairments.
A silent symphony is playing inside your brain right now as neurological pathways synchronize in an electromagnetic chorus that’s thought to give rise to consciousness.
Yet how various circuits throughout the brain align their firing is an enduring mystery, one some theorists suggest might have a solution that involves quantum entanglement.
The proposal is a bold one, not least because quantum effects tend to blur into irrelevance on scales larger than atoms and molecules. Several recent findings are forcing researchers to put their doubts on hold and reconsider whether quantum chemistry might be at work inside our minds after all.
Theories of computation and theories of the brain have close historical interrelations, the best-known examples being Turing’s introspective use of the brain’s operation as a model for his idealized computing machine (Turing 1936), McCulloch’s and Pitts’ use of ideal switching elements to model the brain (McCulloch and Pitts 1943), and von Neumann’s comparison of the logic and physics of both brains and computers (von Neumann 1958).