Guntupalli, Haxby, and colleagues have proposed a new quantitative way to align whole-brain functional imaging data. The new technique, searchlight hyperalignment, allows transformations of a subject's brain activity into a latent common representational space and vice versa.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.tics.2016.06.001DOI Listing

Publication Analysis

Top Keywords

common representational
8
representational space
8
lining brains
4
brains common
4
space guntupalli
4
guntupalli haxby
4
haxby colleagues
4
colleagues proposed
4
proposed quantitative
4
quantitative align
4

Similar Publications

Intermodulation frequencies reveal common neural assemblies integrating facial and vocal fearful expressions.

Cortex

December 2024

Institute of Research in Psychology (IPSY) & Institute of Neuroscience (IoNS), Louvain Bionics Center, University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium; School of Health Sciences, HES-SO Valais-Wallis, The Sense Innovation and Research Center, Lausanne & Sion, Switzerland. Electronic address:

Effective social communication depends on the integration of emotional expressions coming from the face and the voice. Although there are consistent reports on how seeing and hearing emotion expressions can be automatically integrated, direct signatures of multisensory integration in the human brain remain elusive. Here we implemented a multi-input electroencephalographic (EEG) frequency tagging paradigm to investigate neural populations integrating facial and vocal fearful expressions.

View Article and Find Full Text PDF

This review article focuses on acral lentiginous melanoma (ALM), a rare cutaneous malignancy and the least common subtype of cutaneous malignant melanoma (CMM). ALM exhibits distinct characteristics, such as low overall mutation rates and increased chromosomal alterations. It is associated with worse prognosis, more advanced disease, and lower survival rates compared to other CMM subtypes.

View Article and Find Full Text PDF

Adhesive damage of class V restorations under shrinkage stress and occlusal forces using cohesive zone modeling.

J Mech Behav Biomed Mater

January 2025

Key Lab for Biomechanical Engineering of Sichuan Province, Sichuan University, Chengdu, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin, China. Electronic address:

Objective: This study aims to investigate adhesive damage caused by the synergistic effects of polymerization shrinkage and occlusal forces via finite element analysis (FEA), based on damage mechanics with the cohesive zone model (CZM). The objective is to obtain the adhesive damage distribution and investigate how the material properties of resin composite impact adhesive damage.

Methods: A 3D reconstruction model of an mandibular first molar was constructed through CBCT imaging, and a Class V cavity was prepared using computer-aided engineering (CAE) software.

View Article and Find Full Text PDF

Economic analysis of hemodialysis and urgent-start peritoneal dialysis therapies.

J Bras Nefrol

January 2025

Universidade Estadual Paulista, Faculdade de Medicina, Departamento de Clínica Médica, Botucatu, SP, Brazil.

Introduction: Unplanned initiation of renal replacement therapy (RRT) in chronic kidney disease (CKD) patients is a common situation worldwide. In this scenario, peritoneal dialysis (PD) has emerged as a therapeutic option compared to hemodialysis (HD). In planned RRT, the costs of PD are lower than those of HD; however, the literature lacks such analyses when initiation is urgent.

View Article and Find Full Text PDF

Machine Learning Algorithm-Based Prediction of Diabetes Among Female Population Using PIMA Dataset.

Healthcare (Basel)

December 2024

Department of Computer Science, School of Arts, Humanities and Social Sciences, University of Roehampton, London SW15 5PH, UK.

: Diabetes is a metabolic disorder characterized by increased blood sugar levels. Early detection of diabetes could help individuals to manage and delay the progression of this disorder effectively. Machine learning (ML) methods are important in forecasting the progression and diagnosis of different medical problems with better accuracy.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!