Danielle Ibarrola

2.8k citations
52 papers · 2.1k indexed · h-index 25

Impact in

Papers in

Danielle Ibarrola

50 papers receiving 2.0k citations

Peers

Danielle Ibarrola
Comparison fields: 5 of 107
  • Pathology and Forensic Medicine 740
  • Neurology 306
  • Cognitive Neuroscience 602
  • Radiology, Nuclear Medicine and Imaging 669
  • Anesthesiology and Pain Medicine 126
Replace Leighton P. Mark with:
Leighton P. Mark United States
Minoru Fujiki Japan
Ulrich Roelcke Switzerland
Mario Cirillo Italy
Mauro Bergui Italy
Shinsuke Ohta Japan
Dirk Van Roost Belgium
Emanuele Tinelli Italy
Francesca Caramia Italy
S. Blond France
Danielle Ibarrola relative to Leighton P. Mark United States Leighton P. Mark's profile →
Citations per field
00.5×2.8×
Leighton P. Mark · 1×
Citations per year

Countries citing papers authored by Danielle Ibarrola

Since Specialization
Citations

This map shows the geographic impact of Danielle Ibarrola's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Danielle Ibarrola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Ibarrola more than expected).

Fields of papers citing papers by Danielle Ibarrola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danielle Ibarrola. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Danielle Ibarrola. The network helps show where Danielle Ibarrola may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Danielle Ibarrola, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Danielle Ibarrola Line = papers co-authored together Danielle Ibarrola links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202320
3 20232
4 201611
5 201310
6 201259
7 201226
8 201129
9 201031
10 200988
11 200994
12 200813
13 200711
14 2005139
15 2004148
16 200474
17 200369
18 200144
19
[Practical role of functional MRI in neurosurgery].
20005
20 19989

About Danielle Ibarrola

Danielle Ibarrola is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine, Anesthesiology and Pain Medicine and Biophysics, having authored 52 papers that have together received 2.1k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (13 papers), Advanced MRI Techniques and Applications (12 papers), Advanced Neuroimaging Techniques and Applications (10 papers), Functional Brain Connectivity Studies (8 papers), Systemic Lupus Erythematosus Research (4 papers), Neural and Behavioral Psychology Studies (4 papers), Pain Management and Treatment (3 papers) and Transcranial Magnetic Stimulation Studies (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (740 citations), Neurology (306 citations), Cognitive Neuroscience (602 citations), Radiology, Nuclear Medicine and Imaging (669 citations) and Anesthesiology and Pain Medicine (126 citations). Danielle Ibarrola has collaborated with scholars based in France, Switzerland and United States. Frequent co-authors include Patrick J. Cozzone, Jean‐Philippe Ranjeva, Sylviane Confort‐Gouny, Jean Pelletier, Bertrand Audoin, Irina Malikova, I. Berry, A Alichérif, Y Lazorthes and Franck–Emmanuel Roux. Their work appears in journals such as Neurosurgery, Multiple Sclerosis Journal, Human Brain Mapping, PLoS ONE and NeuroImage.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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