Summary: Study reveals how the element of surprise helps facilitate learning and memory retrieval.
Source: University of Manchester.
A study by University of Manchester neuroscientists into the effect of surprise on our memory has inadvertently discovered a method which might help us to perform better in exams.
Summary: Researchers have identified human-specific cell types in the prefrontal cortex. These unique cells may explain why humans are more susceptible to neuropsychiatric diseases than other primate species.
Source: Yale.
What makes the human brain distinct from that of all other animals—including even our closest primate relatives?
Due to a rare genetic mutation, Aliria Rosa Piedrahita de Villegas should have had 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.
The flow of time from the past to the future is a central feature of how we experience the world. But precisely how this phenomenon, known as the arrow of time, arises from the microscopic interactions among particles and cells is a mystery—one that researchers at the CUNY Graduate Center Initiative for the Theoretical Sciences (ITS) are helping to unravel with the publication of a new paper in the journal Physical Review Letters. The findings could have important implications in a variety of disciplines, including physics, neuroscience, and biology.
Fundamentally, the arrow of time arises from the second law of thermodynamics: the principle that microscopic arrangements of physical systems tend to increase in randomness, moving from order to disorder. The more disordered a system becomes, the more difficult it is for it to find its way back to an ordered state, and the stronger the arrow of time. In short, the universe’s tendency toward disorder is the fundamental reason why we experience time flowing in one direction.
“The two questions our team had were, if we looked at a particular system, would we be able to quantify the strength of its arrow of time, and would we be able to sort out how it emerges from the micro scale, where cells and neurons interact, to the whole system?” said Christopher Lynn, the paper’s first author and a postdoctoral fellow with the ITS program. “Our findings provide the first step toward understanding how the arrow of time that we experience in daily life emerges from these more microscopic details.”
Someone taps your shoulder. The organized touch receptors in your skin send a message to your brain, which processes the information and directs you to look left, in the direction of the tap. Now, Penn State and U.S. Air Force researchers have harnessed this processing of mechanical information and integrated it into engineered materials that ‘think.’
In a report this week from the science journal SciTechDaily, we learn of a scientific breakthrough that it clearly intended to be exciting and startling, but potentially worrisome as well. Scientists at the University of Cambridge have created a series of “model embryos” that include a functioning brain, a beating heart, and the foundation for all of the other bodily organs you would expect.
We have arrived at Aldous Huxleys Brave new world.
Scientists from the University of Cambridge have created model embryos from mouse stem cells that form a brain, a beating heart, and the foundations of all the other organs of the body. It represents a new avenue for recreating the first stages of life.
The team of researchers, led by Professor Magdalena Zernicka-Goetz, developed the embryo model without eggs or sperm. Instead, they used stem cells – the body’s master cells, which can develop into almost any cell type in the body.
Motor skills learning is classically associated with brain regions including cerebral and cerebellar cortices and basal ganglia nuclei. Less is known about the role of the hippocampus in the acquisition and storage of motor skills. Here, we show that mice receiving a long-term training in the accelerating rotarod display marked hippocampal transcriptional changes and reduced pyramidal neurons activity in the CA1 region when compared with naive mice. Then, we use mice in which neural ensembles are permanently labeled in an Egr1 activity-dependent fashion. Using these mice, we identify a subpopulation of Egr1-expressing pyramidal neurons in CA1 activated in short-term (STT) and long-term (LTT) trained mice in the rotarod task. When Egr1 is downregulated in the CA1 or these neuronal ensembles are depleted, motor learning is improved whereas their chemogenetic stimulation impairs motor learning performance. Thus, Egr1 organizes specific CA1 neuronal ensembles during the accelerating rotarod task that limit motor learning. These evidences highlight the role of the hippocampus in the control of this type of learning and we provide a possible underlying mechanism.
SIGNIFICANCE STATEMENT It is a major topic in neurosciences the deciphering of the specific circuits underlying memory systems during the encoding of new information. However, the potential role of the hippocampus in the control of motor learning and the underlying mechanisms has been poorly addressed. In the present work we show how the hippocampus responds to motor learning and how the Egr1 molecule is one of the major responsible for such phenomenon controlling the rate of motor coordination performances.
Though we are often friends with people similar to ourselves, it is unclear if neural responses to perceptual stimuli are also similar. Here, authors show that the similarity of neural responses evoked by a range of videos was highest for close friends and decreased with increasing social distance.
Using electrocorticography (ECoG), we probed the neurocognitive substrates of mentalizing at the level of neuronal populations. We found that mentalizing about the self and others recruited near-identical cortical sites (Fig. 5a, b) in a common spatiotemporal sequence (Figs. 5 c and 6). Within our ROIs, activations began in visual cortex, followed by temporoparietal DMN regions (TPJ, ATL, and PMC), and lastly in mPFC regions (amPFC, dmPFC, and vmPFC; Fig. 3e, f). Critically, regions with later activations exhibited greater functional specialization for mentalizing as measured by three metrics: functional specificity for mentalizing versus arithmetic (Figs. 3 c, d and 4b), self/other differentiation in activation timing (Fig. 5c, d), and temporal associations with behavioral responses (Fig. 4D and Table 1). Taken together, these results reveal a common neurocognitive sequence28,29,30,31 for self-and other-mentalizing, beginning in visual cortex (low specialization), ascending through temporoparietal DMN areas (intermediate specialization), then reaching its apex in mPFC regions (high specialization).
Our results are consistent with gradient-based models of brain function, which posit that concrete sensorimotor processing in unimodal regions (e.g., visual cortex) gradually yields to increasingly abstract and inferential processing in ‘high-level’ transmodal regions like mPFC41,42. We found that the strength of self/other differences in activation timing increased along a gradient from visual cortex to mPFC. Specifically, other-mentalizing evoked slower (Fig. 5c) and lengthier (Fig. 5d) activations than self-mentalizing throughout successive DMN ROIs. These self/other functional differences corresponded with self/other differences in RTBehav (Supplementary Fig. 4), although the two were often dissociable (Table 1). Thus, perhaps because we know ourselves better than others, other-mentalizing may require lengthier processing at more abstract and inferential levels of representation, ultimately resulting in slower behavioral responses.
What might our results imply about extant fMRI findings? Hundreds of fMRI studies consistently suggest that: TPJ and dmPFC are most crucial for mentalizing6,8,11,12,43,44,45,46, and dmPFC is selective for thinking about others over oneself 32,33,34,35. However, when examined with ECoG, we found that both pieces of received wisdom are not what they seem. Below, we discuss both issues before moving onto our peculiar vmPFC results, and then conclude with systems-level discussion.
