human brain
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Sowmya N. Sundaresh ◽  
John D. Finan ◽  
Benjamin S. Elkin ◽  
Andrew V. Basilio ◽  
Guy M. McKhann ◽  

2022 ◽  
Vol 20 (1) ◽  
Eva Matt ◽  
Lisa Kaindl ◽  
Saskia Tenk ◽  
Anicca Egger ◽  
Teodora Kolarova ◽  

Abstract Background With the high spatial resolution and the potential to reach deep brain structures, ultrasound-based brain stimulation techniques offer new opportunities to non-invasively treat neurological and psychiatric disorders. However, little is known about long-term effects of ultrasound-based brain stimulation. Applying a longitudinal design, we comprehensively investigated neuromodulation induced by ultrasound brain stimulation to provide first sham-controlled evidence of long-term effects on the human brain and behavior. Methods Twelve healthy participants received three sham and three verum sessions with transcranial pulse stimulation (TPS) focused on the cortical somatosensory representation of the right hand. One week before and after the sham and verum TPS applications, comprehensive structural and functional resting state MRI investigations and behavioral tests targeting tactile spatial discrimination and sensorimotor dexterity were performed. Results Compared to sham, global efficiency significantly increased within the cortical sensorimotor network after verum TPS, indicating an upregulation of the stimulated functional brain network. Axial diffusivity in left sensorimotor areas decreased after verum TPS, demonstrating an improved axonal status in the stimulated area. Conclusions TPS increased the functional and structural coupling within the stimulated left primary somatosensory cortex and adjacent sensorimotor areas up to one week after the last stimulation. These findings suggest that TPS induces neuroplastic changes that go beyond the spatial and temporal stimulation settings encouraging further clinical applications.

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Ashutosh Shankhdhar ◽  
Pawan Kumar Verma ◽  
Prateek Agrawal ◽  
Vishu Madaan ◽  
Charu Gupta

PurposeThe aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.Design/methodology/approachThis paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.FindingsAt the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.Originality/valueBCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.

2022 ◽  
Jimin Ren ◽  
Fang Yu ◽  
Benjamin M. Greenberg

Over the past four decades, ATP, the obligatory energy molecule for keeping all cells alive and functioning, was thought to contribute only one set of 31P MR signals in the human brain. Here we report for the first time the simultaneous detection of two pools of ATP in the human brain by high-resolution 3D 31P MRSI at ultrahigh field 7T. These two ATP pools differ in cytosolic Mg2+ concentration (1:0.5 ratio), with a resonance separation of 0.5 ppm at beta-ATP, a well-established imaging marker of intracellular Mg2+ concentration. Mg2+ is a cofactor of ATPase and its deficiency is associated with immune dysfunction, free radical damage, perturbations in Ca2+ homeostasis, development of atherosclerosis and dyslipidemia, and a number of neurological disorders, such as cerebral vasospasm, stroke, migraine, Alzheimer's disease, and Parkinson's disease. Our study documents reduced Mg levels in the brain of patients with myelin oligodendrocyte glycoprotein antibody disorders (MOGAD), which is an idiopathic, inflammatory, demyelinating condition of the central nervous system (CNS) more common in pediatric patients. Low-Mg2+ ATP signals in MOGAD were detected mostly in the white matter regions, which may suggest Mg2+ deficiency in oligodendrocytes, which are primarily responsible for maintenance and generation of the axonal myelin sheath. This preliminary study demonstrates the utility of the 7T 3D 31P MSRI for revealing altered energy metabolism with reduced Mg availability at a normal ATP level. The potential correlation between [Mg2+] and disease progression over time should be assessed in larger cohorts.

Science ◽  
2022 ◽  
Vol 375 (6577) ◽  
pp. 167-172
Yang Yang ◽  
Diana Arseni ◽  
Wenjuan Zhang ◽  
Melissa Huang ◽  
Sofia Lövestam ◽  

Hi-res view of human Aβ42 filaments Alzheimer’s disease is characterized by a loss of memory and other cognitive functions and the filamentous assembly of Aβ and tau in the brain. The assembly of Aβ peptides into filaments that end at residue 42 is a central event. Yang et al . used electron cryo–electron microscopy to determine the structures of Aβ42 filaments from human brain (see the Perspective by Willem and Fändrich). They identified two types of related S-shaped filaments, each consisting of two identical protofilaments. These structures will inform the development of better in vitro and animal models, inhibitors of Aβ42 assembly, and imaging agents with increased specificity and sensitivity. —SMH

2022 ◽  
Christopher J Playfoot ◽  
Shaoline Sheppard ◽  
Evarist Planet ◽  
Didier Trono

Transposable elements (TEs) contribute to the evolution of gene regulatory networks and are dynamically expressed throughout human brain development and disease. One gene regulatory mechanism influenced by TEs is the miRNA system of post-transcriptional control. miRNA sequences frequently overlap TE loci and this miRNA expression landscape is crucial for control of gene expression in adult brain and different cellular contexts. Despite this, a thorough investigation of the spatiotemporal expression of TE-embedded miRNAs in human brain development is lacking. Here, we identify a spatiotemporally dynamic TE-embedded miRNA expression landscape between childhood and adolescent stages of human brain development. These miRNAs sometimes arise from two apposed TEs of the same subfamily, such as for L2 or MIR elements, but in the majority of cases stem from solo TEs. They give rise to in silico predicted high-confidence pre-miRNA hairpin structures, likely represent functional miRNAs and have predicted genic targets associated with neurogenesis. TE-embedded miRNA expression is distinct in the cerebellum when compared to other brain regions, as has previously been described for gene and TE expression. Furthermore, we detect expression of previously non-annotated TE-embedded miRNAs throughout human brain development, suggestive of a previously undetected miRNA control network. Together, as with non-TE-embedded miRNAs, TE-embedded sequences give rise to spatiotemporally dynamic miRNA expression networks, the implications of which for human brain development constitute extensive avenues of future experimental research. To facilitate interactive exploration of these spatiotemporal miRNA expression dynamics, we provide the 'Brain miRTExplorer' web application freely accessible for the community.

Biology Open ◽  
2022 ◽  
Bilal M. Akhtar ◽  
Priyanka Bhatia ◽  
Shubhra Acharya ◽  
Sanjeev Sharma ◽  
Yojet Sharma ◽  

Human brain development is a complex process where multiple cellular and developmental events are co-ordinated to generate normal structure and function. Alteration in any of these events can impact brain development, manifesting clinically as neurodevelopmental disorders. Human genetic disorders of lipid metabolism often present with features of altered brain function. Lowe syndrome (LS), is a X-linked recessive disease with features of altered brain function. LS results from mutations in OCRL1 that encodes a phosphoinositide 5-phosphatase enzyme. However, the cellular mechanisms by which loss of OCRL1 leads to brain defects remain unknown. Human brain development involves several cellular and developmental features not conserved in other species and understanding such mechanisms remains a challenge. Rodent models of LS have been generated, but failed to recapitulate features of the human disease. Here we describe the generation of human stem cell lines from LS patients. Further, we present biochemical characterization of lipid metabolism in patient cell lines and demonstrate their use as a “disease-in-a-dish” model for understanding the mechanism by which loss of OCRL1 leads to altered cellular and physiological brain development.

2022 ◽  
Corentin Jacques ◽  
Jacques Jonas ◽  
Sophie Colnat-Coulbois ◽  
Louis Maillard ◽  
Bruno Rossion

In vivo intracranial recordings of neural activity offer a unique opportunity to understand human brain function. Intracranial electrophysiological (iEEG) activity related to sensory, cognitive or motor events manifests mostly in two types of signals: event-related local field potentials in lower frequency bands (<30 Hz, LF) and broadband activity in the higher end of the frequency spectrum (>30 Hz, High frequency, HF). While most current studies rely exclusively on HF, thought to be more focal and closely related to spiking activity, the relationship between HF and LF signals is unclear, especially in human associative cortex. Here we provide a large-scale in-depth investigation of the spatial and functional relationship between these 2 signals based on intracranial recordings from 121 individual brains (8000 recording sites). We measure selective responses to complex ecologically salient visual stimuli – human faces - across a wide cortical territory in the ventral occipito-temporal cortex (VOTC), with a frequency-tagging method providing high signal-to-noise ratio (SNR) and the same objective quantification of signal and noise for the two frequency ranges. While LF face-selective activity has higher SNR across the VOTC, leading to a larger number of significant electrode contacts especially in the anterior temporal lobe, LF and HF display highly similar spatial, functional, and timing properties. Specifically, and contrary to a widespread assumption, our results point to nearly identical spatial distribution and local spatial extent of LF and HF activity at equal SNR. These observations go a long way towards clarifying the relationship between the two main iEEG signals and reestablish the informative value of LF iEEG to understand human brain function.

2022 ◽  
Thomas I.-H. Park ◽  
Leon C. D. Smyth ◽  
Miranda Aalderink ◽  
Zoe R. Woolf ◽  
Justin Rustenhoven ◽  

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