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Category: neuroscience – Page 476

Circa 2018 face_with_colon_three

“This data set—and the opportunities it creates—are … arguably one of the most important things to have happened in neurobiology recently,” says Rachel Wilson, a neurobiologist at Harvard University who was not involved in the new work. “Anyone in the world who is interested can download the data set and determine whether any two neurons … talk to each other.”

The 100,000-neuron fruit fly brain is elementary compared with the roughly 100 billion neurons in our own skulls. But the fly is still “much more than this little speck that you swat away from your wine glass over dinner,” says Davi Bock, a neuroscientist at the Howard Hughes Medical Institute’s Janelia Research Campus in Ashburn, Virginia. Some systems in the fly brain—like those responsible for detecting and remembering smells—likely share “common principles” with those in humans, he says.

Continue reading “In a ‘tour de force,’ researchers image an entire fly brain in minute detail” | >

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This is not a knock on caffeine by any means. There’s a reason people have been consuming it for thousands of years. It works by blocking the neurotransmitters in the brain that produce drowsiness. This keeps your neurons firing at full speed, which makes you feel awake. And studies show it is very effective at boosting mood. But what if you could do more for your brain than simply tricking it into being awake? What if you could give your brain nutrients that help it work better all the time? Well, with a well-designed nootropics supplement, you can.

Nootropics are often marketed as “smart drugs,” which gives the impression that they’re going to boost your IQ and turn you into a rocket scientist or brain surgeon. But that is not actually the case. Nootropics are simply chemical compounds that help create the biological conditions necessary for optimal brain function. They include things like amino acids, vitamins, minerals, nutrients, and even stimulants such as caffeine. Some of these compounds serve as fuel for cognition. Others modulate various processes involved in neurotransmission.

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Short cycles of a low-calorie diet that mimics fasting appeared to lower inflammation and delay cognitive decline in Alzheimer’s.

Alzheimer’s disease is a disease that attacks the brain, causing a decline in mental ability that worsens over time. It is the most common form of dementia and accounts for 60 to 80 percent of dementia cases. There is no current cure for Alzheimer’s disease, but there are medications that can help ease the symptoms.

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Self-organizing lumps of human brain tissue grown in the laboratory have been successfully transplanted into the nervous systems of newborn rats in a step towards finding new ways to treat neuropsychiatric disorders.

The 3D organoids, developed from stem cells to resemble a simplified model of the human cortex, connected and integrated with the surrounding tissue in each rat’s cortex to form a functional part of the rodent’s own brain, displaying activity related to sensory perception.

This, according to a team of researchers led by neuroscientist Sergiu Pașca of Stanford University, overcomes the limitations of dish-grown organoids, and gives us a new platform for modeling human brain development and disease in a living system.

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In The Analysis of Matter (1927) Bertrand Russell defended a couple of theses that amounted to a novel approach to the mind-body problem. Similar claims were defended by Eddington in his Gifford lectures of the same year. This approach was forgotten about in the latter half of the twentieth century, perhaps because it didn’t fit with the physicalist predilections of the period. However, it has recently been rediscovered, leading to a view – or better a school of views – known as ‘Russellian monism.’ Russellian monism is increasingly seen as a promising middle way between dualism and physicalism, avoiding the problems associated with either of these extremes. In this lecture, I explain the basic idea.

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Fluid intelligence (gf) refers to abstract reasoning and problem solving abilities. It is considered a human higher cognitive factor central to general intelligence (g). The regions of the cortex supporting gf have been revealed by recent bioimaging studies and valuable hypothesis on the neural correlates of individual differences have been proposed. However, little is known about the interaction between individual variability in gf and variation in cortical activity following task complexity increase. To further investigate this, two samples of participants (high-IQ, N = 8; low-IQ, N = 10) with significant differences in gf underwent two reasoning (moderate and complex) tasks and a control task adapted from the Raven progressive matrices. Functional magnetic resonance was used and the recorded signal analyzed between and within the groups. The present study revealed two opposite patterns of neural activity variation which were probably a reflection of the overall differences in cognitive resource modulation: when complexity increased, high-IQ subjects showed a signal enhancement in some frontal and parietal regions, whereas low-IQ subjects revealed a decreased activity in the same areas. Moreover, a direct comparison between the groups’ activation patterns revealed a greater neural activity in the low-IQ sample when conducting moderate task, with a strong involvement of medial and lateral frontal regions thus suggesting that the recruitment of executive functioning might be different between the groups. This study provides evidence for neural differences in facing reasoning complexity among subjects with different gf level that are mediated by specific patterns of activation of the underlying fronto-parietal network.

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In an effort to clarify how deductive reasoning is accomplished, an fMRI study was performed to observe the neural substrates of logical reasoning and mathematical calculation. Participants viewed a problem statement and three premises, and then either a conclusion or a mathematical formula. They had to indicate whether the conclusion followed from the premises, or to solve the mathematical formula. Language areas of the brain (Broca’s and Wernicke’s area) responded as the premises and the conclusion were read, but solution of the problems was then carried out by non-language areas. Regions in right prefrontal cortex and inferior parietal lobe were more active for reasoning than for calculation, whereas regions in left prefrontal cortex and superior parietal lobe were more active for calculation than for reasoning. In reasoning, only those problems calling for a search for counterexamples to conclusions recruited right frontal pole. These results have important implications for understanding how higher cognition, including deduction, is implemented in the brain. Different sorts of thinking recruit separate neural substrates, and logical reasoning goes beyond linguistic regions of the brain.

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The spatiotemporal analysis of brain activation during syllogistic reasoning, and the execution of 1 baseline task (BST) were performed in 14 healthy adult participants using high-density event-related brain potentials (ERPs). The following results were obtained: First, the valid syllogistic reasoning task (VSR) elicited a greater positive ERP deflection than the invalid syllogistic reasoning task (ISR) and BST between 300 and 400 ms after the onset of the minor premise. Dipole source analysis of the difference waves (VSR-BST and VSR-ISR) indicated that the positive components were localized in the vicinity of the occipito-temporal cortex, possibly related to visual premise processing. Second, VSR and ISR demonstrated greater negativity than BST developed at 600–700 ms. Dipole source analysis of difference waves (VSR-BST and ISR-BST) indicated that the negative components were mainly localized near the medial frontal cortex/the anterior cingulate cortex, possibly related to the manipulation and integration of premise information. Third, both VSR and ISR elicited a more positive ERP deflection than BST between 2,500 and 3,000 ms. Voltage maps of the difference waves (VSR-BST and VSR-ISR) demonstrated strong activity in the right frontal scalp regions. Results indicate that the reasoning tasks may require more mental effort to spatial processing of working memory.

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Working memory for order information is mediated by different cognitive mechanisms that rely on different neural circuits. Here we discuss evidence that order memory involves mechanisms that range from general supervisory processes to process that maintenance fine-grained temporal position information. We suggest that neural regions-including the prefrontal cortex, motor cortex, parietal cortex and medial temporal structures-operate at different levels and processing stages to give rise to working memory for order information.

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