Neurosciences

Article Computer Science, Artificial Intelligence

Star algorithm for neural network ensembling

Sergey Zinchenko, Dmitrii Lishudi

Summary: This paper proposes a new neural network ensemble algorithm based on Audibert's empirical star algorithm and provides theoretical and empirical analysis of its performance on regression and classification tasks.

NEURAL NETWORKS (2024)

Article Endocrinology & Metabolism

New fraternine analogues: Evaluation of the antiparkinsonian effect in the model of Parkinson's disease

Andreia Biolchi Mayer, Henrique de Oliveira Amaral, Danilo Gustavo R. de Oliveira, Gabriel Avohay Alves Campos, Priscilla Galante Ribeiro, Solange Cristina Rego Fernandes, Adolfo Carlos Barros de Souza, Raffael Hinio Araijo de Castro, Anamelia Lorenzetti Bocca, Marcia Renata Mortari

Summary: This study synthesized three bioinspired peptides based on fraternine and tested their effects in a Parkinson's disease model. The peptides fra-10 and fra-14 improved motor coordination, but most of the peptides were toxic at the applied doses. All three peptides reduced the intensity of lesion-induced rotations. The peptide fra-24 increased the number of TH+ neurons in the substantia nigra and reduced the concentration of the cytokine TNF-alpha, suggesting it has neuroprotective effects in Parkinson's disease.

NEUROPEPTIDES (2024)

Article Behavioral Sciences

Bayesian multi-level modelling for predicting single and double feature visual search

Anna E. Hughes, Anna Nowakowska, Alasdair D. F. Clarke

Summary: This study examines the relationship between search slopes and search efficiency in visual search tasks, introduces the Target Contrast Signal (TCS) Theory, and extends it to a Bayesian multi-level framework. The findings demonstrate that TCS can predict data well, but distinguishing between contrast combination models proves to be difficult.

CORTEX (2024)

Article Neurosciences

Spontaneity competes with intention to influence the coordination dynamics of interpersonal performance tendencies

John J. Buchanan, Alberto Cordova

Summary: Research has shown that spontaneous visual coupling supports frequency entrainment, phase attraction, and intermittent interpersonal coordination during the switch from a novision (NV) to vision (V) context among co-actors. The experiments demonstrate that similar self-paced frequencies result from same amplitude movements, while different amplitudes lead to disparate frequencies. In experiment 1, co-actors were instructed to maintain amplitude without explicit instructions for coordination, which limited frequency and phase entrainment in the V context. In experiment 2, co-actors were instructed to maintain amplitude and intentionally coordinate together, resulting in significant frequency modulations and the production of various stable relative phase patterns.

HUMAN MOVEMENT SCIENCE (2024)

Article Neurosciences

Biomechanical changes identified during a marathon race among high-school aged runners

Alexandra F. Dejong Lempke, Danielle L. Hunt, Sarah B. Willwerth, Pierre A. d'Hemecourt, William P. Meehan III, Kristin E. Whitney

Summary: Adolescent athletes alter their gait patterns throughout a marathon race, and there are correlations between biomechanical features and race performance among young marathoners.

GAIT & POSTURE (2024)

Article Behavioral Sciences

Functional and representational differences between bilateral inferior temporal numeral areas

Darren J. Yeo, Courtney Pollack, Benjamin N. Conrad, Gavin R. Price

Summary: The processing of numerals as visual objects is supported by an Inferior Temporal Numeral Area (ITNA) in the bilateral inferior temporal gyri (ITG). Extant findings suggest some degree of hemispheric asymmetry in how the bilateral ITNAs process numerals. The study found that digit sensitivity did not differ between ITNAs, and digit sensitivity in both left and right ITNAs was associated with calculation skills. The study also revealed a right lateralization in engagement in alphanumeric categorization, and that the right ITNA showed greater discriminability between digits and letters.

CORTEX (2024)

Article Computer Science, Artificial Intelligence

Hierarchical attention network with progressive feature fusion for facial expression recognition

Huanjie Tao, Qianyue Duan

Summary: In this paper, a hierarchical attention network with progressive feature fusion is proposed for facial expression recognition (FER), addressing the challenges posed by pose variation, occlusions, and illumination variation. The model achieves enhanced performance by aggregating diverse features and progressively enhancing discriminative features.

NEURAL NETWORKS (2024)

Article Linguistics

Pupil size shows diminished increases on verbal fluency tasks in patients with behavioral-variant-frontotemporal dementia

Mohamad El Haj, Dimitrios Kapogiannis, Claire Boutoleau-Bretonniere

Summary: This study assessed linguistic processing in patients with behavioral variant frontotemporal dementia (bvFTD) using pupillometry. The results showed that patients with bvFTD had smaller pupil size during verbal fluency tasks and counting compared to control participants. However, larger pupil size was observed during verbal fluency tasks compared to counting in both groups. Moreover, patients with bvFTD performed poorer in verbal fluency tasks compared to control participants.

JOURNAL OF NEUROLINGUISTICS (2024)

Article Computer Science, Artificial Intelligence

AdjointBackMapV2: Precise reconstruction of arbitrary CNN unit's activation via adjoint operators

Qing Wan, Siu Wun Cheung, Yoonsuck Choe

Summary: This study applies adjoint operators to convolutional neural networks, overcomes the limitations of previous unbiased assumptions by embedding input images into an extended normed space, and proposes a new algorithm. Experimental results demonstrate that the proposed method achieves near-zero reconstruction error in the reconstruction process of activation values.

NEURAL NETWORKS (2024)

Article Computer Science, Artificial Intelligence

Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing

Alexander Wikner, Joseph Harvey, Michelle Girvan, Brian R. Hunt, Andrew Pomerance, Thomas Antonsen, Edward Ott

Summary: Recent research has shown that machine learning models can accurately predict the dynamics of unknown chaotic systems by employing feedback loops and adding noise to the training process. This study introduces a new regularization technique called Linearized Multi-Noise Training (LMNT), which improves the stability and accuracy of the models. Machine learning models trained with LMNT produce long-term climate predictions that are indefinitely stable and similar to the true system, while also achieving more accurate short-term forecasts than other regularization techniques.

NEURAL NETWORKS (2024)

Article Neurosciences

The interaction effect of different footwear types and static navicular drop or dynamic ankle pronation on the joint stiffness of the lower limb during running

Ali Esmaeili, Sayed Esmaeil Hosseininejad, Amirali Jafarnezhadgero, Valdeci Carlos Dionisio

Summary: This study investigates the effects of footwear type, navicular drop and ankle pronation on lower limb joint stiffness during running. The results show that navicular drop and dynamic ankle pronation do not affect joint stiffness, but footwear type significantly affects joint stiffness. Conventional footwear increases ankle and hip joint stiffness while reducing knee joint stiffness, which may have implications for injury risk.

GAIT & POSTURE (2024)

Article Computer Science, Artificial Intelligence

Exploiting nonlinear dendritic adaptive computation in training deep Spiking Neural Networks

Guobin Shen, Dongcheng Zhao, Yi Zeng

Summary: Inspired by the information transmission process in the brain, this study introduces the Dendritic Spatial Gating Module (DSGM) and the Dendritic Temporal Adjust Module (DTAM) to improve the performance of Spiking Neural Networks (SNNs). This approach achieves state-of-the-art performance on various datasets and demonstrates competitive performance compared to current state-of-the-art methods.

NEURAL NETWORKS (2024)

Article Computer Science, Artificial Intelligence

Mental image reconstruction from human brain activity: Neural decoding of mental imagery via deep neural network-based Bayesian estimation

Naoko Koide-Majima, Shinji Nishimoto, Kei Majima

Summary: Visual images observed by humans can be reconstructed from brain activity, and the visualization of arbitrary natural images from mental imagery has been achieved through an improved method. This study provides a unique tool for directly investigating the subjective contents of the brain.

NEURAL NETWORKS (2024)

Article Endocrinology & Metabolism

Effects of menstrual cycle phase and ovulation on the salivary cortisol awakening response

Lisa Haase, Antonia Vehlen, Julia Strojny, Gregor Domes

Summary: This study found no significant changes in the cortisol awakening response (CAR) over the menstrual cycle, and no significant association with variations in estradiol and progesterone. These results suggest that CAR is largely robust against hormonal variations across the menstrual cycle.

PSYCHONEUROENDOCRINOLOGY (2024)

Article Behavioral Sciences

How neural representations of newly learnt faces change over time: Event-related brain potential evidence for overnight consolidation

Holger Wiese, Tsvetomila Popova, Maya Schipper, Deni Zakriev, Mike Burton, Andrew W. Young

Summary: Previous experiments have shown that brief exposure to unfamiliar individuals leads to the formation of new facial representations, which undergo changes and consolidation within the first day after learning.

CORTEX (2024)

Article Behavioral Sciences

Temperament and probabilistic predictive coding in visual-spatial attention

Stefano Lasaponara, Gabriele Scozia, Silvana Lozito, Mario Pinto, David Conversi, Marco Costanzi, Tim Vriens, Massimo Silvetti, Fabrizio Doricchi

Summary: Cholinergic (Ach), Noradrenergic (NE), and Dopaminergic (DA) pathways are crucial in regulating spatial attention and determining inter-individual differences in temperamental traits. This study found that temperamental traits predict individual differences in the ability to orient spatial attention based on the probabilistic association between cues and targets. These findings highlight the importance of considering temperamental and personality traits in social and professional environments where attention control is essential.

CORTEX (2024)

Article Neurosciences

Pathology of Primary Angiitis of the Central Nervous System

Selima Siala, Nabil Rahoui, Benjamin Cho, Carlos A. Zamora

NEUROIMAGING CLINICS OF NORTH AMERICA (2024)

Article Neurosciences

Usefulness of Different Imaging Methods in the Diagnosis of Cerebral Vasculopathy

Carlos A. Zamora, Mahmud Mossa-Basha, Mauricio Castillo

Summary: Assessment of cerebral vasculopathies can be challenging, but a comprehensive understanding of different imaging methods can facilitate the process. There are various angiographic techniques with unique advantages and disadvantages, such as bolus-based methods that enhance arterial depiction and non-contrast techniques that show high-resolution arteries. MRI can assess vessel wall pathology and aid in diagnosing vasculitis and non-inflammatory vasculopathies.

NEUROIMAGING CLINICS OF NORTH AMERICA (2024)

Article Neurosciences

Effects of propofol on presynaptic synapsin phosphorylation in the mouse brain in vivo

Li-Min Mao, Khyathi Thallapureddy, John Q. Wang

Summary: Propofol can enhance synapsin phosphorylation and modulate synaptic transmission in the mouse brain. The study reveals the potential role of synapsin as a substrate of propofol and its effects on neurotransmitter release machinery.

BRAIN RESEARCH (2024)

Article Neurosciences

Structural and functional changes in the brain after chronic complete thoracic spinal cord injury

Jing Li, Yi Shan, Xiaojing Zhao, Guixiang Shan, Peng-Hu Wei, Lin Liu, Changming Wang, Hang Wu, Weiqun Song, Yi Tang, Guo-Guang Zhao, Jie Lu

Summary: This study investigates changes in brain anatomical structures and functional network connectivity after chronic complete thoracic spinal cord injury (cctSCI) and their impact on clinical outcomes. The findings reveal alterations in gray matter volume and functional connectivity in specific brain regions, indicating potential therapeutic targets and methods for tracking treatment outcomes.

BRAIN RESEARCH (2024)