NT/New AI turns brain activity into text

Paradigm
Paradigm
Published in
26 min readApr 3, 2020

Neuroscience biweekly, 20th March — 3rd April

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Articles

Machine translation of cortical activity to text with an encoder–decoder framework

by Joseph G. Makin, David A. Moses & Edward F. Chang in Nature Neuroscience

US Scientists develop AI that can turn brain activity into text. They tracked the neural data from people while they were speaking.

A decade after speech was first decoded from human brain signals, accuracy and speed remain far below that of natural speech. Researchers show how to decode the electrocorticogram with high accuracy and at natural-speech rates. Taking a cue from recent advances in machine translation, they train a recurrent neural network to encode each sentence-length sequence of neural activity into an abstract representation, and then to decode this representation, word by word, into an English sentence. For each participant, data consist of several spoken repeats of a set of 30–50 sentences, along with the contemporaneous signals from ~250 electrodes distributed over peri-Sylvian cortices. Average word error rates across a held-out repeat set are as low as 3%. Finally, they show how decoding with limited data can be improved with transfer learning, by training certain layers of the network under multiple participants’ data.

Dr. Christian Herff an expert in the field from Maastricht University who was not involved in the study said the research was exciting because the system used less than 40 minutes of training data for each participant, and a limited collection of sentences, rather than the millions of hours typically needed.

“By doing so they achieve levels of accuracy that haven’t been achieved so far,” he said.

However, he noted the system was not yet usable for many severely disabled patients as it relied on the brain activity recorded from people speaking a sentence out loud.

“Of course this is fantastic research but those people could just use ‘OK Google’ as well,” he said. “This is not translation of thought [but of brain activity involved in speech].”

Herff said people should not worry about others reading their thoughts just yet: the brain electrodes must be implanted, while imagined speech is very different to inner voice.

But Dr. Mahnaz Arvaneh, an expert in brain machine interfaces at Sheffield University, said it was important to consider ethical issues now. “We [are still] very, very far away from the point that machines can read our minds,” she said. “But it doesn’t mean that we should not think about it and we should not plan about it.”

Dual-process contributions to creativity in jazz improvisations: An SPM-EEG study

by David S. Rosen, Yongtaek Oh, Brian Erickson Fengqing (Zoe) Zhang, Youngmoo E. Kim, John Kounios in NeuroImage

Professional jazz guitarists do improvisation without active work of the frontal lobes, which provide cognitive control — unlike their less experienced colleagues

  • Neural and behavioral evidence for an expertise-dependent, dual-process model of creativity.
  • Performance quality/creativity a function of right-hemispheric activity.
  • Superior creative production is associated with hypofrontality and the inhibition of executive Type-2 processes.
  • Sophisticated EEG analysis (SPM12; surface-Laplacian transformations) and machine-learning (k-fold validation) techniques.
  • Collection of high-density EEG during live guitar improvisation.

Conflicting theories identify creativity either with frontal-lobe mediated (Type-2) executive control processes or (Type-1) associative processes that are disinhibited when executive control is relaxed. Musical (jazz) improvisation is an ecologically valid test-case to distinguish between these views because relatively slow, deliberate, executive-control processes should not dominate during high-quality, real-time improvisation. In the present study, jazz guitarists (n ​= ​32) improvised to novel chord sequences while 64-channel EEGs were recorded. Jazz experts rated each improvisation for creativity, technical proficiency and aesthetic appeal. Surface-Laplacian-transformed EEGs recorded during the performances were analyzed in the scalp-frequency domain using SPM12. Significant clusters of high-frequency (beta-band and gamma-band) activity were observed when higher-quality versus lower-quality improvisations were compared. Higher-quality improvisations were associated with predominantly posterior left-hemisphere activity; lower-quality improvisations were associated with right temporo-parietal and fronto-polar activity. However, after statistically controlling for experience (defined as the number of public performances previously given), performance quality was a function of right-hemisphere, largely right-frontal, activity. These results support the notion that superior creative production is associated with hypofrontality and right-hemisphere activity thereby supporting a dual-process model of creativity in which experience influences the balance between executive and associative processes. This study also highlights the idea that the functional neuroanatomy of creative production depends on whether creativity is defined in terms of the quality of products or the type of cognitive processes involved.

A jazz guitarist performing while EEG is recorded

A neuroimaging biomarker for striatal dysfunction in schizophrenia

by Ang Li, Andrew Zalesky, Bing Liu et al. in Nature Medicine

Scientists have developed an algorithm that, based on the characteristics of the striatum activity, diagnoses schizophrenia with an accuracy of more than 80 percent

Mounting evidence suggests that function and connectivity of the striatum is disrupted in schizophrenia. Researchers has developed a new hypothesis-driven neuroimaging biomarker for schizophrenia identification, prognosis and subtyping based on functional striatal abnormalities (FSA). FSA scores provide a personalized index of striatal dysfunction, ranging from normal to highly pathological. Using inter-site cross-validation on functional magnetic resonance images acquired from seven independent scanners (n = 1,100), FSA distinguished individuals with schizophrenia from healthy controls with an accuracy exceeding 80% (sensitivity, 79.3%; specificity, 81.5%). In two longitudinal cohorts, inter-individual variation in baseline FSA scores was significantly associated with antipsychotic treatment response. FSA revealed a spectrum of severity in striatal dysfunction across neuropsychiatric disorders, where dysfunction was most severe in schizophrenia, milder in bipolar disorder, and indistinguishable from healthy individuals in depression, obsessive-compulsive disorder and attention-deficit hyperactivity disorder. Loci of striatal hyperactivity recapitulated the spatial distribution of dopaminergic function and the expression profiles of polygenic risk for schizophrenia. In conclusion, scientists has developed a new biomarker to index striatal dysfunction and established its utility in predicting antipsychotic treatment response, clinical stratification and elucidating striatal dysfunction in neuropsychiatric disorders.

Fundamental bounds on the fidelity of sensory cortical coding

by Oleg I. Rumyantsev, Jérôme A. Lecoq, Oscar Hernandez, Yanping Zhang, Joan Savall, Radosław Chrapkiewicz, Jane Li, Hongkui Zeng, Surya Ganguli & Mark J. Schnitzer in Nature

Scientists found that noise bursts that are born simultaneously in different neurons limit the coding of information in populations of thousands or more cells in the visual cortex of mice

How the brain processes information accurately despite stochastic neural activity is a longstanding question. For instance, perception is fundamentally limited by the information that the brain can extract from the noisy dynamics of sensory neurons. Seminal experiments, suggest that correlated noise in sensory cortical neural ensembles is what limits their coding accuracy, although how correlated noise affects neural codes remains debated. Recent theoretical work proposes that how a neural ensemble’s sensory tuning properties relate statistically to its correlated noise patterns is a greater determinant of coding accuracy than is absolute noise strength. However, without simultaneous recordings from thousands of cortical neurons with shared sensory inputs, it is unknown whether correlated noise limits coding fidelity. The authors present a 16-beam, two-photon microscope to monitor activity across the mouse primary visual cortex, along with analyses to quantify the information conveyed by large neural ensembles. They found that, in the visual cortex, correlated noise constrained signalling for ensembles with 800–1,300 neurons. Several noise components of the ensemble dynamics grew proportionally to the ensemble size and the encoded visual signals, revealing the predicted information-limiting correlations. Notably, visual signals were perpendicular to the largest noise mode, which therefore did not limit coding fidelity. The information-limiting noise modes were approximately ten times smaller and concordant with mouse visual acuity. Therefore, cortical design principles appear to enhance coding accuracy by restricting around 90% of noise fluctuations to modes that do not limit signalling fidelity, whereas much weaker correlated noise modes inherently bound sensory discrimination.

a — visual cortex of the mouse, b — visual stimuli

3D printing of conducting polymers

by Hyunwoo Yuk, Baoyang Lu, Shen Lin, Kai Qu, Jingkun Xu, Jianhong Luo & Xuanhe Zhao in Nature Communications

MIT engineers are working on developing soft, flexible neural implants that can gently conform to the brain’s contours and monitor activity over longer periods, without aggravating surrounding tissue. Such flexible electronics could be softer alternatives to existing metal-based electrodes designed to monitor brain activity, and may also be useful in brain implants that stimulate neural regions to ease symptoms of epilepsy, Parkinson’s disease, and severe depression.

Conducting polymers are promising material candidates in diverse applications including energy storage, flexible electronics, and bioelectronics. However, the fabrication of conducting polymers has mostly relied on conventional approaches such as ink-jet printing, screen printing, and electron-beam lithography, whose limitations have hampered rapid innovations and broad applications of conducting polymers. Researchers introduce a high-performance 3D printable conducting polymer ink based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for 3D printing of conducting polymers. The resultant superior printability enables facile fabrication of conducting polymers into high resolution and high aspect ratio microstructures, which can be integrated with other materials such as insulating elastomers via multi-material 3D printing. The 3D-printed conducting polymers can also be converted into highly conductive and soft hydrogel microstructures. They further demonstrate fast and streamlined fabrications of various conducting polymer devices, such as a soft neural probe capable of in vivo single-unit recording.

3D printing of conducting polymer devices

Sequential snapshots for 3D printing of high-density flexible electronic circuit patterns by the conducting polymer ink. b Lighting up of LED on the 3D-printed conducting polymer circuit. PETE indicates polyethylene terephthalate. c Bending of the 3D-printed conducting polymer circuit without failure. d Image of the 3D-printed soft neural probe with 9-channels by the conducting polymer ink and the PDMS ink. e Image of the 3D-printed soft neural probe in magnified view. f Images of the implanted 3D-printed soft neural probe (top) and a freely moving mouse with the implanted probe (bottom). g, h Representative electrophysiological recordings in the mouse dHPC by the 3D-printed soft neural probe. Local field potential (LFP) traces (0.5 to 250 Hz) under freely moving conditions (g). Continuous extracellular action potential (AP) traces (300 to 40 kHz) recorded under freely moving conditions (h). i Principal component analysis of the recorded single-unit potentials from (h). j Average two units spike waveforms recorded over time corresponding to clusters in (i). Scale bars, 5 mm (a–c); 1 mm (d, e); 2 mm (f).

Local and global consequences of reward-evoked striatal dopamine release

by Nan Li and Alan Jasanoff in Nature

Using a specialized MRI sensor, neuroscientists have uncovered how dopamine released deep within the brain influences both nearby and distant brain regions

The neurotransmitter dopamine is required for the reinforcement of actions by rewarding stimuli. Neuroscientists have tried to define the functions of dopamine in concise conceptual terms, but the practical implications of dopamine release depend on its diverse brain-wide consequences. Although molecular and cellular effects of dopaminergic signalling have been extensively studied, the effects of dopamine on larger-scale neural activity profiles are less well-understood. Researchers combine dynamic dopamine-sensitive molecular imaging and functional magnetic resonance imaging to determine how striatal dopamine release shapes local and global responses to rewarding stimulation in rat brains. They find that dopamine consistently alters the duration, but not the magnitude, of stimulus responses across much of the striatum, via quantifiable postsynaptic effects that vary across subregions. Striatal dopamine release also potentiates a network of distal responses, which they delineate using neurochemically dependent functional connectivity analyses. Hot spots of dopaminergic drive notably include cortical regions that are associated with both limbic and motor function. The results reveal distinct neuromodulatory actions of striatal dopamine that extend well beyond its sites of peak release, and that result in enhanced activation of remote neural populations necessary for the performance of motivated actions. Researchers findings also suggest brain-wide biomarkers of dopaminergic function and could provide a basis for the improved interpretation of neuroimaging results that are relevant to learning and addiction.

MIT biological engineers have created a specialized sensor that allows them to track dopamine in the brain using magnetic resonance imaging (MRI), as shown in the bottom row. Images in the top row show overall brain activity, as measured by functional MRI.

Presymptomatic Increase of an Extracellular RNA in Blood Plasma Associates with the Development of Alzheimer’s Disease

by Zhangming Yan, Zixu Zhou, Qiuyang Wu, Zhen Bouman Chen, Edward H. Koo, Sheng Zhong in Current Biology

Researchers discovered that high blood levels of RNA produced by the PHGDH gene could serve as a biomarker for early detection of Alzheimer’s disease. The work could lead to the development of a blood test to identify individuals who will develop the disease years before they show symptoms.

  • Blood plasma exRNAs from a 15-year clinical follow-up are sequenced by SILVER-seq
  • Brain expression levels of brain-specific genes correlate with presence of exRNA
  • PHGDH exhibits AD-associated mRNA and protein increase in brain and exRNA increase
  • Presymptomatic increase of plasma PHGDH exRNA predicts the clinical diagnosis of AD

The extracellular RNAs (exRNAs) from human biofluid have recently been systematically characterized. However, the correlations of biofluid exRNA levels and human diseases remain largely untested. Here, considering the unmet need for presymptomatic biomarkers of sporadic Alzheimer’s disease (AD), researchers leveraged the recently developed SILVER-seq (small-input liquid volume extracellular RNA sequencing) technology to generate exRNA profiles from a longitudinal collection of human plasma samples. These 164 plasma samples were collected from research subjects 70 years or older with up to 15 years of clinical follow-up prior to death and whose clinical diagnoses were confirmed by pathological analysis of their post mortem brains. The exRNAs of AD-activated genes and transposons in the brain exhibited a concordant trend of increase in AD plasma in comparison with age-matched control plasma. However, when they required statistical significance with multiple testing adjustments, phosphoglycerate dehydrogenase (PHGDH) was the only gene that exhibited consistent upregulation in AD brain transcriptomes from 3 independent cohorts and an increase in AD plasma as compared to controls. Researchers validated PHGDH’s serum exRNA and brain protein expression increases in AD by using 5 additional published cohorts. Finally, they compared the time-course exRNA trajectories between “converters” and controls. Plasma PHGDH exRNA exhibited presymptomatic increases in each of the 11 converters during their transitions from normal to cognitive impairment but remained stable over the entire follow-up period in 8 out of the 9 control elderly subjects. These data suggest the potential utilities of plasma exRNA levels for screening and longitudinal exRNA changes as a presymptomatic indication of sporadic AD.

Longitudinal Changes of Plasma PHGDH

(A) PHGDH exRNA levels (y axis) across time (x axis) in each converter (C1–C11). The time of clinical diagnosis of cognitive impairment is set as year 0. Negative and positive years correspond to the years before and after diagnosis. The regression coefficient (β) from a linear regression (line) summarizes the overall change over time for each converter. A positive β corresponds to exRNA increase over time.

(B) The β (y axis) of longitudinal changes of plasma PHGDH for every participant (dot) in controls (blue), AD (red), and converters (green). The p values of t test between each two groups are reported. *p < 0.05.

(C ) β (dot) and its standard deviation (whisker) for controls (blue) and converters (green). Arrows: participants with the lower whisker above 0 are shown (β − standard deviation of β > 0).

The genetic architecture of the human cerebral cortex

by Katrina L. Grasby et al. in Science

More 360 scientists from 184 different institutions have contributed to a global effort to find more than 200 regions of the genome and more than 300 specific genetic variations that affect the structure of the cerebral cortex and likely play important roles in psychiatric and neurological conditions

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, researchers conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. They analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. Researchers identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Identifying genetic influences on human cortical structure

(A) Measurement of cortical surface area and thickness from MRI. (B) Genomic locations of common genetic variants that influence global and regional cortical structure. © The results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. (D) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE.

The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium

by Laurena Holleran, Sinead Kelly, Clara Alloza, Ingrid Agartz, Ole A. Andreassen, Celso Arango in The American Journal of Psychiatry

An international collaborative study provides findings on the neural basis of intelligence, otherwise known as general cognitive ability (IQ).

The new research uses an imaging technique called diffusion tensor imaging (DTI) to provide an insight into how small variations in this wiring system is associated with differences in IQ in both the general population and how disorders such as schizophrenia manifest.

Over 40 scientists from around the world were involved in analysing brain MRI scans and measures of cognitive function of 1,717 participants, with both healthy functions and patients with schizophrenia. This resulted in a new method to harmonise data collection and analysis as part of the Enhancing Neuroimaging Genetics through Meta-Analysis project (ENIGMA), Schizophrenia Working Group.

Commenting on the findings, lead author Dr. Laurena Holleran, stated that:

“To date, this is the largest meta-analysis study of brain structure and cognitive function in schizophrenia. Understanding the neural basis of cognitive function is essential so that effective therapies that address difficulties associated with disorders like schizophrenia, which aren’t targeted by current treatments. This is important because cognitive deficits associated with the disorder strongly predict social and functional outcomes, such as employment or social relationships.

Previous literature suggested that general intelligence relies on specific grey matter areas of the brain, including temporal, parietal and frontal regions. However, the results from this study indicate that efficient connection pathways across the entire brain provide a neural network that supports general cognitive function.”

According to the study’s senior author Professor Gary Donohoe: “These results advance our knowledge in a number of ways. Firstly, we have demonstrated that the relationship between brain structure and intelligence not only involves grey matter, but also white matter — the brain’s wiring system. Secondly, it’s not just one part of this wiring system that is important for intelligence, but rather the wiring system as a whole. And finally, the relationship between intelligence and the brain’s wiring system is basically the same in patients with schizophrenia and healthy people, in that the lack of pattern explains their cognitive abilities. This suggests that cognitive function in patients is the same as the general population, at least as far as white matter is concerned.”

Massively parallel microwire arrays integrated with CMOS chips for neural recording

by Abdulmalik Obaid, Mina-Elraheb Hanna, Yu-Wei Wu, Mihaly Kollo, Romeo Racz, Matthew R. Angle, Jan Müller, Nora Brackbill et al. Science Advances

A new device enables researchers to observe hundreds of neurons in the brain in real-time. The system is based on modified silicon chips from cameras, but rather than taking a picture, it takes a movie of the neural electrical activity.

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Scientists present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

Neural bundle design

(A) Schematic of the CMOS chip integrated with the microwire bundle. The bundle consists of a proximal (chip) end (B) designed for contact to the CMOS pixels, and a distal (brain) end (C )designed to record in tissue. The proximal end has partially exposed metal wires to contact the chip, while the distal end wires are separated to limit tissue damage upon insertion. (D) A bundle of 800 microwires spaced 100 μm apart, with a device form factor less than 0.6 cm wide appropriate for small-animal studies.

Tripping on nothing: placebo psychedelics and contextual factors

by Olson, J.A., Suissa-Rocheleau, L., Lifshitz, M., Raz, A., & Veissière, S.P.L. in Psychopharmacology

There has been a lot of recent interest in the use of psychedelic drugs to treat depression. A new study suggests that, in the right context, some people may experience psychedelic-like effects from placebos alone.

Is it possible to have a psychedelic experience from a placebo alone? Most psychedelic studies find few effects in the placebo control group, yet these effects may have been obscured by the study design, setting, or analysis decisions. Scientists examined individual variation in placebo effects in a naturalistic environment resembling a typical psychedelic party. Thirty-three students completed a single-arm study ostensibly examining how a psychedelic drug affects creativity. The 4-h study took place in a group setting with music, paintings, coloured lights, and visual projections. Participants consumed a placebo that they described as a drug resembling psilocybin, which is found in psychedelic mushrooms. To boost expectations, confederates subtly acted out the stated effects of the drug and participants were led to believe that there was no placebo control group. The participants later completed the 5-Dimensional Altered States of Consciousness Rating Scale, which measures changes in conscious experience. There was considerable individual variation in the placebo effects; many participants reported no changes while others showed effects with magnitudes typically associated with moderate or high doses of psilocybin. In addition, the majority (61%) of participants verbally reported some effect of the drug. Several stated that they saw the paintings on the walls “move” or “reshape” themselves, others felt “heavy… as if gravity [had] a stronger hold”, and one had a “come down” before another “wave” hit her. Understanding how context and expectations promote psychedelic-like effects, even without the drug, will help researchers to isolate drug effects and clinicians to maximise their therapeutic potential.

A Cluster of Autism-Associated Variants on X-Linked NLGN4X Functionally Resemble NLGN4Y

by Thien A. Nguyen, Kunwei Wu, Saurabh Pandey, Mahim Jain, Wei Lu, Katherine W. Roche in Neuron

A new study offers clues to why autism is more common in boys

  • Despite sharing ∼97% amino acid identity, NLGN4X and NLGN4Y are differentially regulated
  • NLGN4Y cannot traffic to the surface due to one amino difference from NLGN4X
  • A cluster of autism-associated variants in NLGN4X surrounds the critical amino acid
  • NLGN4X autism-associated variants display a deficit in trafficking similar to NLGN4Y

Autism spectrum disorder (ASD) is more prevalent in males; however, the etiology for this sex bias is not well understood. Many mutations on X-linked cell adhesion molecule NLGN4X result in ASD or intellectual disability. NLGN4X is part of an X-Y pair, with NLGN4Y sharing ∼97% sequence homology. Using biochemistry, electrophysiology, and imaging, researchers show that NLGN4Y displays severe deficits in maturation, surface expression, and synaptogenesis regulated by one amino acid difference with NLGN4X. Furthermore, they identify a cluster of ASD-associated mutations surrounding the critical amino acid in NLGN4X, and these mutations phenocopy NLGN4Y. Researchers show that NLGN4Y cannot compensate for the functional deficits observed in ASD-associated NLGN4X mutations. Altogether, their data reveal a potential pathogenic mechanism for male bias in NLGN4X-associated ASD.

Application of optogenetic Amyloid-β distinguishes between metabolic and physical damage in neurodegeneration

by Lim et al. in eLife

Amyloid plaque formation directly causes brain tissue loss in animals, but a drug called lithium reduces the life-shortening effects of this loss, shows a new study published in eLife

The brains of Alzheimer’s Disease patients show a decrease in brain mass and a preponderance of extracellular Amyloid-β plaques. These plaques are formed by aggregation of polypeptides that are derived from the Amyloid Precursor Protein (APP). Amyloid-β plaques are thought to play either a direct or an indirect role in disease progression, however the exact role of aggregation and plaque formation in the aetiology of Alzheimer’s Disease is subject to debate as the biological effects of soluble and aggregated Amyloid-β peptides are difficult to separate in vivo. To investigate the consequences of formation of Amyloid-β oligomers in living tissues, reserchers developed a fluorescently tagged, optogenetic Amyloid-β peptide that oligomerizes rapidly in the presence of blue light. They applied this system to the crucial question of how intracellular Amyloid-β oligomers underlie the pathologies of Alzheimer’s Disease. Researchers use Drosophila, C. elegans and D. rerio to show that, although both expression and induced oligomerization of Amyloid-β were detrimental to lifespan and healthspan, they were able to separate the metabolic and physical damage caused by light-induced Amyloid-β oligomerization from Amyloid-β expression alone. The physical damage caused by Amyloid-β oligomers also recapitulated the catastrophic tissue loss that is a hallmark of late AD. They show that the lifespan deficit induced by Amyloid-β oligomers was reduced with Li+ treatment. The results present the first model to separate different aspects of disease progression.

Combining HF rTMS over the Left DLPFC with Concurrent Cognitive Activity for the Offline Modulation of Working Memory in Healthy Volunteers: A Proof-of-Concept Study

by Ilya Bakulin, Alfiia Zabirova, Dmitry Lagoda, Alexandra Poydasheva, Anastasiia Cherkasova, Nikolay Pavlov, Peter Kopnin, Dmitry Sinitsyn et al. in Brain Sciences

New research shows that human working memory can be tweaked with non-invasive magnetic stimulation

A group of scientists from the Research Center of Neurology and Skoltech showed that human working memory can be tweaked using non-invasive magnetic stimulation of the brain. Also, they discovered that the effect of magnetic stimulation weakens as the brain works on a cognitive task under stimulation.

Working memory (WM) stores and processes the information we need for daily use. The WM mechanisms get activated when, for example, we memorize a phone number until we find a scrap of paper or a smartphone to write it down. WM disorders are a frequent occurrence in many nervous system diseases, whereas in healthy people, the WM capacity is associated with an individual’s learning ability and general intelligence level.

The transcranial magnetic stimulation (TMS) is regarded as one of the promising non-pharmacological WM enhancement methods leveraging the effect of the alternating magnetic field which painlessly penetrates through the scalp and skull bones, with an electric field forming in the cortex. As TMS can influence the mechanisms of neuroplasticity, it is used as a therapeutic method for various nervous system diseases. The TMS effects are known to depend both on the stimulation parameters and the brain activity during stimulation. Combining TMS with concurrent cognitive activity has evolved into a cognitive enhancement technique for patients with Alzheimer’s disease. However, data are still lacking on how exactly the brain activity influences the TMS efficiency.

The researchers compared the effects of TMS on WM when stimulation was applied with and without a cognitive load. The WM performance was evaluated before and after a 20-minute stimulation session. The stimulation area was selected based on the individual brain activation pattern which formed during a WM-engaging task. The results suggest that WM does not respond to any stimulation other than TMS with no cognitive load.

Spatially regulated editing of genetic information within a neuron

by Isabel C Vallecillo-Viejo, Noa Liscovitch-Brauer, Juan F Diaz Quiroz, Maria F Montiel-Gonzalez, Sonya E Nemes, Kavita J Rangan, Simon R Levinson, Eli Eisenberg, Joshua J C Rosenthal in Nucleic Acids Research

Revealing yet another super-power in the skillful squid, scientists have discovered that squid massively edit their own genetic instructions not only within the nucleus of their neurons, but also within the axon — the long, slender neural projections that transmit electrical impulses to other neurons. This is the first time that edits to genetic information have been observed outside of the nucleus of an animal cell.

In eukaryotic cells, with the exception of the specialized genomes of mitochondria and plastids, all genetic information is sequestered within the nucleus. This arrangement imposes constraints on how the information can be tailored for different cellular regions, particularly in cells with complex morphologies like neurons. Although messenger RNAs (mRNAs), and the proteins that they encode, can be differentially sorted between cellular regions, the information itself does not change. RNA editing by adenosine deamination can alter the genome’s blueprint by recoding mRNAs; however, this process too is thought to be restricted to the nucleus. In this work, we show that ADAR2 (adenosine deaminase that acts on RNA), an RNA editing enzyme, is expressed outside of the nucleus in squid neurons. Furthermore, purified axoplasm exhibits adenosine-to-inosine activity and can specifically edit adenosines in a known substrate. Finally, a transcriptome-wide analysis of RNA editing reveals that tens of thousands of editing sites (>70% of all sites) are edited more extensively in the squid giant axon than in its cell bodies. These results indicate that within a neuron RNA editing can recode genetic information in a region-specific manner.

Onset of Regular Cannabis Use & Young Adult Insomnia: An Analysis of Shared Genetic Liability

by Winiger EA, Huggett SB, Hatoum AS, Friedman NP, Drake CL, Wright KP, Hewitt JK

Smoke a lot of weed as a teenager, and when you reach adulthood you’ll be more likely to have trouble falling or staying asleep, according to a new CU Boulder study of more than 1,800 twins

The study, published in the journal Sleep, comes at a time when cannabis — in everything from THC-infused gummies to prerolled joints and high-potency vape pens — is increasingly being marketed as a sleep aid in states where marijuana is legal. It adds to a growing body of evidence suggesting that while it may help some users fall asleep occasionally, chronic use can have negative long-term consequences, particularly for the young.

“People tend to think that cannabis helps with sleep, but if you look closely at the studies, continued or excessive use is also associated with a lot of sleep deficits,” said lead author Evan Winiger, a graduate student in the Institute for Behavioral Genetics. “Our study adds to that literature, showing for the first time that early use is associated with increased rates of insomnia later on.”

For the study, Winiger analyzed data from 1,882 young adults from the Colorado Twin Registry, which has been following twins for research since 1968. Each had completed surveys about their sleep habits, marijuana use and mental health.

They found that about one-third of subjects who started using marijuana regularly before age 18 had insomnia in adulthood, compared to less than 20% among those who didn’t use cannabis regularly as teens. The same pattern held true for a particularly hazardous form of insomnia known as “short sleep” (sleeping fewer than six hours per night on a regular basis). About one in 10 subjects who used cannabis regularly as teens grew up to be short-sleepers, while only about 5% of non-users did.

People who started using marijuana after they turned 18 also had slightly higher rates of insomnia in young adulthood. And these patterns persisted when controlling for depression, anxiety and shift work (which can all also impair sleep).

Dissociable roles of ventral pallidum neurons in the basal ganglia reinforcement learning network

by Alexander Kaplan, Aviv D. Mizrahi-Kliger, Zvi Israel, Avital Adler & Hagai Bergman in Nature Neuroscience

Reinforcement learning models treat the basal ganglia (BG) as an actor–critic network. The ventral pallidum (VP) is a major component of the BG limbic system. However, its precise functional roles within the BG circuitry, particularly in comparison to the adjacent external segment of the globus pallidus (GPe), remain unexplored. Researchers recorded the spiking activity of VP neurons, GPe cells (actor) and striatal cholinergic interneurons (critic) while monkeys performed a classical conditioning task. They report that VP neurons can be classified into two distinct populations. The persistent population displayed sustained activation following visual cue presentation, was correlated with monkeys’ behavior and showed uncorrelated spiking activity. The transient population displayed phasic synchronized responses that were correlated with the rate of learning and the reinforcement learning model’s prediction error. Scientists’ results suggest that the VP is physiologically different from the GPe and identify the transient VP neurons as a BG critic.

Facial expressions of emotion states and their neuronal correlates in mice

by Nejc Dolensek, Daniel A. Gehrlach, Alexandra S. Klein, Nadine Gogolla in Science

Researchers at the Max Planck Institute of Neurobiology are the first to describe different emotional facial expressions for mice

Understanding the neurobiological underpinnings of emotion relies on objective readouts of the emotional state of an individual, which remains a major challenge especially in animal models. Researchers found that mice exhibit stereotyped facial expressions in response to emotionally salient events, as well as upon targeted manipulations in emotion-relevant neuronal circuits. Facial expressions were classified into distinct categories using machine learning and reflected the changing intrinsic value of the same sensory stimulus encountered under different homeostatic or affective conditions. Facial expressions revealed emotion features such as intensity, valence, and persistence. Two-photon imaging uncovered insular cortical neuron activity that correlated with specific facial expressions and may encode distinct emotions. Facial expressions thus provide a means to infer emotion states and their neuronal correlates in mice.

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