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Category: neuroscience – Page 276

Latent circuit inference from heterogeneous neural responses during cognitive tasks

The latent circuit model captures task-related neural activity in the low-dimensional subspace spanned by the columns of Q, with dynamics within this subspace generated by the neural circuit Eq. (2). We infer the latent circuit parameters (Q, wrec, win and wout) from neural activity y by minimizing the loss function L = ∑k,t ∥ y − Qx ∥ 2 + ∥ z − woutx ∥ 2, where k and t index trials and time within a trial, respectively (Methods).

In the latent circuit model, the heterogeneity of single-neuron responses has three possible sources: mixing of task inputs to the latent circuit via win, recurrent interactions among latent nodes via wrec and linear mixing of representations in single neurons via the embedding Q. The orthonormality constraint on Q implies that the projection defined by the transpose matrix QT is a dimensionality reduction in which projection onto the i th column of Q correlates with the activity of the i th node in the latent circuit. Conversely, the image of each latent node i is a high-dimensional activity pattern given by the column qi of the matrix Q. Thus, the latent circuit provides a dimensionality reduction that incorporates an explicit mechanistic hypothesis for how the resulting low-dimensional dynamics are generated.

In general, it is not obvious under what circumstances we can satisfactorily fit a latent circuit model to the responses of a high-dimensional system. If, for example, solutions to cognitive tasks that emerge in large systems are qualitatively different from mechanisms operating in small circuits, then we should not be able to adequately fit task-related dynamics of the large system with a low-dimensional circuit model. However, the existence of a low-dimensional circuit solution that accurately captures dynamics of the large system would suggest that this circuit mechanism may be latent in the high-dimensional system.

Alzheimer’s scientist resigns after university finds ‘data integrity concerns’ in papers

Sylvain Lesné, a neuroscientist accused of image manipulation in a seminal Alzheimer’s disease paper in, resigned last week from his tenured professorship at the University of Minnesota Twin Cities (UMN). The move follows a 2.5-year investigation in which the university found problems with several other papers on which Lesné is an author. The study has already been pulled, but the school has asked that four more of Lesné’s papers be retracted.

The resignation, effective 1 March, was first reported by the. Lesné did not respond to a request for comment. UMN spokesperson Jake Ricker said, “The university has identified data integrity concerns impacting several publications and has been in touch with those journals to recommend retraction of the publications, where appropriate.”

As a postdoc, Lesné worked in the lab of neuroscientist Karen Ashe. In 2006, they published a study in that seemed to show a cause-effect relationship between a protein—amyloid-beta *56—and memory loss in rats. Those symptoms seemed to resemble the memory problems that afflict Alzheimer’s patients.

Quantum Entanglement and the Connected Mind: Unraveling the Neural Web

Imagine a world where your thoughts aren’t confined to the boundaries of your skull, where your consciousness is intimately connected to the universe around you, and where the neurons in your brain communicate instantly across vast distances.

This isn’t science fiction — it’s the intriguing possibility suggested by applying the principle of quantum entanglement to the realm of consciousness.

Quantum entanglement, often described as the “spooky action at a distance,” is a phenomenon that baffled even Einstein. In essence, it describes a scenario where two particles become so deeply linked that they share the same fate, regardless of the distance separating them. Measuring the state of one instantly reveals the state of its partner, even if they are light-years apart.

Yale Scientists Just Cracked the DNA Code That Built the Human Brain

Scientists explored Human Accelerated Regions (HARs), genetic regulators that tweak existing genes rather than introducing new ones. Using cutting-edge techniques, they mapped nearly all HAR interactions, revealing their role in brain development and neurological disorders like autism and schizophrenia.

Decoding the Genetic Evolution of the Human Brain

A new Yale study offers a deeper understanding of the genetic changes that shaped human brain evolution and how this process differed from that of chimpanzees.

Gut bacteria can alter brain proteins: New glycosylation method uncovers link

Our guts are home to trillions of bacteria, and research over the last few decades has established how essential they are to our physiology—in health and disease. A new study from EMBL Heidelberg researchers shows that gut bacteria can bring about profound molecular changes in one of our most critical organs—the brain.

The new study, published in the journal Nature Structural & Molecular Biology, is the first to show that bacteria living in the gut can influence how proteins in the brain are modified by carbohydrates—a process called glycosylation. The study was made possible by a new method the scientists developed—DQGlyco—which allows them to study glycosylation at a much higher scale and resolution than previous studies.

Dr. Wang joined the Max Planck Florida Institute for Neuroscience (MPFI) in February 2018 leading the Neuronal Mechanisms of Episodic Memory research group

Before joining MPFI, Wang was a research scientist at the Janelia Research Campus of Howard Hughes Medical Institute, working with Dr. Jeffery Magee and previously with Dr. Eva Pastalkova. At Janelia, she studied the hippocampal neuronal activities that represent memory traces. In particular, she employed memory tasks that can reversibly toggle the influence of sensory inputs on and off and isolated neuronal activities associated with internally stored memory.

Wang was trained as an electrical engineer. She completed her graduate study under the mentorship of Drs. Shih-Chii Liu, Tobi Delbruck and Rodney Douglas at the Swiss Federal Institute of Technology Zurich (ETHZ). During her Ph.D. training, she designed brain-inspired computational systems on silicon chips. These fully reconfigurable systems incorporated electronic circuits of a network of neurons with dendrites and synapses. Using these systems as simulation tools, she also investigated the computational principles native to a neuron with active dendrites.

Gardenia Plants may hold Chemical Key to Regenerating Diseased Human Nerves

Gardenias are known for their rich, earthy fragrance, waxy petals and brilliant white color that contrasts with the deep emerald green of their leaves. The plant has long been prized by herbalists, seekers of food and fabric dyes, and even pharmaceutical companies.

Now, a collaborative team of scientists at several research centers in the United States has found that a compound known as genipin, derived from the gardenia plant called Cape jasmine, can prompt nerve regeneration. Neurons damaged and stunted by disease find new life in the lab when exposed to the plant-derived compound.

The chemical comes from the fruit of this extraordinarily versatile plant. Gardenia shrubs, in general, are native to tropical and subtropical regions of Asia. But the plants are propagated globally by horticulturists and amateur gardeners who are most familiar with the flower’s beauty and the intoxicating scent of their perfume.

Cerebrospinal biomarker test can detect Alzheimer’s pathology earlier, study shows

Years before tau tangles show up in brain scans of patients with Alzheimer’s disease, a biomarker test developed at the University of Pittsburgh School of Medicine can detect small amounts of the clumping-prone tau protein and its misfolded pathological forms that litter the brain, cerebrospinal fluid and potentially blood, new research published today in Nature Medicine suggests.

The biomarker test correlates with the severity of cognitive decline, independent of other factors, including brain amyloid deposition, thereby opening doors for early-stage disease diagnosis and intervention.

Since amyloid-beta pathology often precedes tau abnormalities in Alzheimer’s disease, most biomarker efforts have focused on early detection of amyloid-beta changes. However, the clumping of tau protein into well-ordered structures referred to by pathologists as “” is a more defining event for Alzheimer’s disease as it is more strongly associated with the cognitive changes seen in affected people.

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