Comparative neuroanatomy: Integrating classic and modern methods to understand association fibers connecting dorsal and ventral visual cortex-Reference-Cited by-同舟云学术

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Comparative neuroanatomy: Integrating classic and modern methods to understand association fibers connecting dorsal and ventral visual cortex

Published:2019-09 Issue: Volume:146 Page:1-12
ISSN:0168-0102
Container-title:Neuroscience Research
language:en
Short-container-title:Neuroscience Research

Author:

Takemura Hiromasa^ORCID,Pestilli Franco,Weiner Kevin S.^ORCID

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

Grant-in-Aid for JSPS Fellows

NSF

NIH NIMH

Microsoft Research Award,

Indiana University Areas of Emergent Research initiative “Learning: Brains, Machines, Children,”

Indiana University Pervasive Technology Institute and Research Technologies Division

UC Berkeley

Publisher

Elsevier BV

Subject

General Medicine,General Neuroscience

Reference190 articles.

1. Architectonic mapping of the human brain beyond brodmann;Amunts;Neuron,2015

2. Retinotopic organization of scene areas in macaque inferior temporal cortex;Arcaro;J. Neurosci.,2017

3. The role of diffusion MRI in neuroscience;Assaf;NMR Biomed.,2017

4. A novel approach to the human connectome: ultra-high resolution mapping of fiber tracts in the brain;Axer;Neuroimage,2011

5. When tractography meets tracer injections: a systematic study of trends and variation sources of diffusion-based connectivity;Aydogan;Brain Struct. Funct.,2018

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1. A prominent vertical occipital white matter fasciculus unique to primate brains;Current Biology;2024-08

2. White matter connections of human ventral temporal cortex are organized by cytoarchitecture, eccentricity, and category-selectivity from birth;2024-07-30

3. White matter tracts adjacent to the human cingulate sulcus visual area (CSv);PLOS ONE;2024-04-05

4. Tractometry of Human Visual White Matter Pathways in Health and Disease;Magnetic Resonance in Medical Sciences;2024

5. Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data;NeuroImage;2022-11

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