The TD drive - A parametric, open-source implant for multi-area electrophysiological recordings in behaving and sleeping rats DOI Creative Commons
Tim Schröder, Jacqueline van der Meij, Paul van Heumen

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Март 4, 2024

ABSTRACT Intricate interactions between multiple brain areas underlie most functions attributed to the brain. The process of learning, as well formation and consolidation memories are two examples that rely heavily on functional connectivity across In addition, investigating hemispheric similarities and/or differences goes hand in with these multi-area interactions. Electrophysiological studies trying further elucidate complex processes thus depend recording activity at locations simultaneously often a bilateral fashion. Presented here is 3D-printable implant for rats, named TD drive, capable symmetric, wire electrode recordings, currently up ten distributed simultaneously. open-source design was created employing parametric principles, allowing prospective users easily adapt drive their needs by simply adjusting high-level parameters, such anterior-posterior medio-lateral coordinates locations. validated n = 20 Lister Hooded rats performed different tasks. compatible tethered sleep recordings open field (Object Exploration) wireless large maze (HexMaze 9×5 m) using commercial systems headstages. sum, presented adaptable assembly new electrophysiological facilitating fast preparation implantation.

Язык: Английский

Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations DOI Creative Commons
Constantinos Halkiopoulos, Evgenia Gkintoni,

Anthimos Aroutzidis

и другие.

Diagnostics, Год журнала: 2025, Номер 15(4), С. 456 - 456

Опубликована: Фев. 13, 2025

Background/Objectives: The following systematic review integrates neuroimaging techniques with deep learning approaches concerning emotion detection. It, therefore, aims to merge cognitive neuroscience insights advanced algorithmic methods in pursuit of an enhanced understanding and applications recognition. Methods: study was conducted PRISMA guidelines, involving a rigorous selection process that resulted the inclusion 64 empirical studies explore modalities such as fMRI, EEG, MEG, discussing their capabilities limitations It further evaluates architectures, including neural networks, CNNs, GANs, terms roles classifying emotions from various domains: human-computer interaction, mental health, marketing, more. Ethical practical challenges implementing these systems are also analyzed. Results: identifies fMRI powerful but resource-intensive modality, while EEG MEG more accessible high temporal resolution limited by spatial accuracy. Deep models, especially CNNs have performed well emotions, though they do not always require large diverse datasets. Combining data behavioral features improves classification performance. However, ethical challenges, privacy bias, remain significant concerns. Conclusions: has emphasized efficiencies detection, technical were highlighted. Future research should integrate advances, establish innovative enhance system reliability applicability.

Язык: Английский

Процитировано

4
The Paradox of the Self-Studying Brain DOI Creative Commons
Simone Battaglia, Philippe Servajean, Karl Friston

и другие.

Physics of Life Reviews, Год журнала: 2025, Номер 52, С. 197 - 204

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

2
In vivo imaging of the human brain with the Iseult 11.7-T MRI scanner DOI Creative Commons
Nicolas Boulant, Franck Mauconduit,

Vincent Gras

и другие.

Nature Methods, Год журнала: 2024, Номер 21(11), С. 2013 - 2016

Опубликована: Окт. 17, 2024

Язык: Английский

Процитировано

9
Noninvasive intervention by transcranial ultrasound stimulation: Modulation of neural circuits and its clinical perspectives DOI Creative Commons
Takahiro Osada, Seiki Konishi

Psychiatry and Clinical Neurosciences, Год журнала: 2024, Номер 78(5), С. 273 - 281

Опубликована: Март 20, 2024

Low‐intensity focused transcranial ultrasound stimulation (TUS) is an emerging noninvasive technique capable of stimulating both the cerebral cortex and deep brain structures with high spatial precision. This method recognized for its potential to comprehensively perturb various regions, enabling modulation neural circuits, in a manner not achievable through conventional magnetic or electrical techniques. The underlying mechanisms neuromodulation are based on phenomenon where mechanical waves kinetically interact neurons, specifically affecting neuronal membranes mechanosensitive channels. interaction induces alterations excitability neurons within stimulated region. In this review, we briefly present fundamental principles physics physiological TUS neuromodulation. We explain experimental apparatus procedures humans. Due focality, integration methods, including resonance imaging resonance–guided neuronavigation systems, important perform experiments precise targeting. then review current state literature neuromodulation, particular focus human subjects, targeting subcortical structures. Finally, outline future perspectives clinical applications psychiatric neurological fields.

Язык: Английский

Процитировано

5
A neurofunctional signature of subjective disgust generalizes to oral distaste and socio-moral contexts DOI
Xianyang Gan, Feng Zhou, Ting Xu

и другие.

Nature Human Behaviour, Год журнала: 2024, Номер 8(7), С. 1383 - 1402

Опубликована: Апрель 19, 2024

Язык: Английский

Процитировано

5
The pathobiology of neurovascular aging DOI
Monica M. Santisteban, Costantino Iadecola

Neuron, Год журнала: 2025, Номер 113(1), С. 49 - 70

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Toward a functional future for the cognitive neuroscience of human aging DOI Creative Commons

Zoya Mooraj,

Alireza Salami, Karen L. Campbell

и другие.

Neuron, Год журнала: 2025, Номер 113(1), С. 154 - 183

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Neural electrodes for brain‐computer interface system: From rigid to soft DOI Creative Commons
Dan Yang, Gongwei Tian, Jianhui Chen

и другие.

BMEMat, Год журнала: 2025, Номер unknown

Опубликована: Янв. 12, 2025

Abstract Brain‐computer interface (BCI) is an advanced technology that establishes a direct connection between the brain and external devices, enabling high‐speed real‐time information exchange. In BCI systems, electrodes are key devices responsible for transmitting signals including recording electrophysiological electrically stimulating nerves. Early were mainly composed of rigid materials. The mismatch in Young's modulus soft biological tissue can lead to rejection reactions within system, resulting electrode failure. Furthermore, prone damaging tissues during implantation use. Recently, flexible have garnered attention field science research due their better adaptability softness curvature brain. design effectively reduce mechanical damage neural improve accuracy stability signal transmission, providing new tools methods exploring function mechanisms developing novel technologies. Here, we review advancements systems. This paper emphasizes importance discusses limitations traditional electrodes, introduces various types detail. addition, also explore practical application scenarios future development trends technology, aiming offer valuable insights enhancing performance user experience

Язык: Английский

Процитировано

0
Alice in Wonderland Syndrome in dementia with Lewy bodies: a case report exploring visual cognition dysfunction DOI Creative Commons
Alexis Demas

Frontiers in Neurology, Год журнала: 2025, Номер 16

Опубликована: Март 27, 2025

Background Alice in Wonderland Syndrome (AIWS) is characterized by transient distortions visual perception—alterations size, shape, and spatial relationships—typically described migraine or encephalitis. Its occurrence neurodegenerative conditions, particularly dementia with Lewy bodies (DLB), remains exceedingly rare. Case description This article reports a case of 68-year-old patient (DLB; limbic-early subtype) who presented typical DLB features alongside brief episode misperception—reporting that his bed had “shrunk.” Neuroimaging revealed diffuse cortical atrophy prominent bi-hippocampal parietal lobe involvement, hypoperfusion on HMPAO SPECT. Conclusion the first reported AIWS DLB. We hypothesize selective dysfunction high-level networks—particularly right extrastriate cortex responsible for canonical storage object size—may lead to an agnosia size. underscores importance considering within spectrum disturbances Theoretical implications These findings provide novel insights into neurobiology cognition, aligning Husserl’s concept “primordial body” (Urleib) intuition. They suggest disruptions integration sensory inputs properties may critically influence conscious reconstruction reality.

Язык: Английский

Процитировано

0
Prediction of antipsychotic drug efficacy for schizophrenia treatment based on neural features of the resting-state functional connectome DOI Creative Commons

Song Liu,

Meng Wang, Wei Han

и другие.

Translational Psychiatry, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 10, 2025

Neuroimaging studies have identified a large number of biomarkers associated with schizophrenia (SZ), but there is still lack that can predict the efficacy antipsychotic medication in SZ patients. The aim this study was to identify neuroimaging drug response among features resting-state connectome. Resting-state functional magnetic resonance scans were acquired from discovery cohort 105 patients at baseline and after 8 weeks treatment. Baseline clinical status post-treatment outcome assessed using Positive Negative Symptom Scale (PANSS), improvement rated by total score reduction. Based on imaging data, connectivity matrix constructed for each patient, connectome-based predictive model subsequently established trained individual PANSS Model performance calculating Pearson correlation coefficients between predicted true reduction leave-one-out cross-validation. Finally, generalizability tested an independent validation 52 incorporating connectome characteristics treatment outcomes both (prediction vs. truth r = 0.59, mean squared error (MSE) 0.021) (r 0.41, MSE 0.036). four positive eight negative features, which respectively correlated positively negatively Among these specific connections within parietal lobe played crucial role model's performance. As they included frontoparietal control network cerebello-thalamo-cortical connections. This discovered validated set based connectome, where higher lower rate better therapeutic effect. These be used through model. Clinical doctors potentially infer results.

Язык: Английский

Процитировано

0