找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Lesion-to-Symptom Mapping; Principles and Tools Dorian Pustina,Daniel Mirman Book 2022 Springer Science+Business Media, LLC, part of Spring

[復(fù)制鏈接]
查看: 33149|回復(fù): 52
樓主
發(fā)表于 2025-3-21 19:31:41 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Lesion-to-Symptom Mapping
副標(biāo)題Principles and Tools
編輯Dorian Pustina,Daniel Mirman
視頻videohttp://file.papertrans.cn/586/585208/585208.mp4
概述Includes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts
叢書(shū)名稱(chēng)Neuromethods
圖書(shū)封面Titlebook: Lesion-to-Symptom Mapping; Principles and Tools Dorian Pustina,Daniel Mirman Book 2022 Springer Science+Business Media, LLC, part of Spring
描述Recent developments in lesion-symptom mapping (LSM) have spurred rapid growth. This volume provides comprehensive coverage of the steps and considerations involved in LSM. The chapters cover the definition and types of brain lesions, how to prepare them for analysis, standard LSM methods, network-based LSM methods, and approaches of transient lesions induced by brain stimulation. These chapters are supplemented by practical, hands-on mini tutorials on implementing the different analyses using freely-available software. In the .Neuromethods. series style, chapters include the kind of detail and key advice from the specialists needed to get started using LSM in your laboratory.?.Cutting-edge and thorough, .Lesion-to-Symptom Mapping: Principles and Tools. connects core conceptual issues with available tools, making it a valuable resource for experienced and new researchers.?.
出版日期Book 2022
關(guān)鍵詞TBI; behavior mapping; segmentation; Voxel-based lesion-behavior mapping; VLBM approach
版次1
doihttps://doi.org/10.1007/978-1-0716-2225-4
isbn_softcover978-1-0716-2227-8
isbn_ebook978-1-0716-2225-4Series ISSN 0893-2336 Series E-ISSN 1940-6045
issn_series 0893-2336
copyrightSpringer Science+Business Media, LLC, part of Springer Nature 2022
The information of publication is updating

書(shū)目名稱(chēng)Lesion-to-Symptom Mapping影響因子(影響力)




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping被引頻次




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping被引頻次學(xué)科排名




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping年度引用




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping年度引用學(xué)科排名




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping讀者反饋




書(shū)目名稱(chēng)Lesion-to-Symptom Mapping讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 21:34:16 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:21:05 | 只看該作者
https://doi.org/10.1007/978-1-0716-2225-4TBI; behavior mapping; segmentation; Voxel-based lesion-behavior mapping; VLBM approach
地板
發(fā)表于 2025-3-22 05:26:12 | 只看該作者
5#
發(fā)表于 2025-3-22 12:39:01 | 只看該作者
Neuromethodshttp://image.papertrans.cn/l/image/585208.jpg
6#
發(fā)表于 2025-3-22 15:21:40 | 只看該作者
7#
發(fā)表于 2025-3-22 20:51:45 | 只看該作者
Book 2022ions involved in LSM. The chapters cover the definition and types of brain lesions, how to prepare them for analysis, standard LSM methods, network-based LSM methods, and approaches of transient lesions induced by brain stimulation. These chapters are supplemented by practical, hands-on mini tutoria
8#
發(fā)表于 2025-3-22 23:51:18 | 只看該作者
9#
發(fā)表于 2025-3-23 03:51:37 | 只看該作者
Mapping the Spatial Distribution of Lesions in Stroke: Effect of Diffeomorphic Registration Strategso confounded with the general difficulty of intersubject brain mapping. We review and compare image registration strategies for mapping T1-weighted neuroimaging of stroke patients into a single common coordinate system.
10#
發(fā)表于 2025-3-23 08:41:25 | 只看該作者
Lesion Network Mapping Using Resting-State Functional Connectivity MRI,l and psychiatric symptoms to brain networks. These lesion network mapping results are reproducible across independent datasets and show promise for identifying therapeutic targets for neuromodulation. Here, we review the methodology for lesion network mapping using functional connectivity MRI.
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 11:18
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
门头沟区| 河南省| 宜兴市| 闻喜县| 闸北区| 佛教| 黎川县| 峨眉山市| 图片| 花莲市| 榆树市| 澜沧| 裕民县| 云浮市| 新龙县| 沂水县| 巢湖市| 甘南县| 永和县| 中西区| 彭州市| 大石桥市| 庐江县| 周至县| 阳信县| 吉木萨尔县| 南昌县| 滦南县| 岳阳市| 塘沽区| 云霄县| 蒲城县| 柳河县| 三明市| 开江县| 汉阴县| 古田县| 都江堰市| 崇州市| 井冈山市| 南通市|