Éva Csibri

828 total citations
23 papers, 614 citations indexed

About

Éva Csibri is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Physiology. According to data from OpenAlex, Éva Csibri has authored 23 papers receiving a total of 614 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 6 papers in Psychiatry and Mental health and 4 papers in Physiology. Recurrent topics in Éva Csibri's work include EEG and Brain-Computer Interfaces (9 papers), Functional Brain Connectivity Studies (9 papers) and Dementia and Cognitive Impairment Research (5 papers). Éva Csibri is often cited by papers focused on EEG and Brain-Computer Interfaces (9 papers), Functional Brain Connectivity Studies (9 papers) and Dementia and Cognitive Impairment Research (5 papers). Éva Csibri collaborates with scholars based in Hungary, Poland and United States. Éva Csibri's co-authors include Zoltán Hidasi, Pál Salacz, Gábor Csukly, Ádám Szabó, Zsófia Anna Gaál, Gábor Rudas, Éva Kiss, Márk Molnár, András Horváth and Márk Molnár and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of the Neurological Sciences.

In The Last Decade

Éva Csibri

23 papers receiving 605 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Éva Csibri Hungary	10	396	220	76	75	52	23	614
Zoltán Hidasi Hungary	10	367 0.9×	234 1.1×	106 1.4×	137 1.8×	53 1.0×	18	607
Lauren Nutile United States	6	238 0.6×	166 0.8×	109 1.4×	169 2.3×	62 1.2×	9	567
Christian Sandøe Musaeus Denmark	14	461 1.2×	170 0.8×	105 1.4×	138 1.8×	27 0.5×	41	725
Alexandra Roldán Spain	11	211 0.5×	353 1.6×	60 0.8×	56 0.7×	79 1.5×	24	652
Keiichiro Nishida Japan	15	555 1.4×	154 0.7×	63 0.8×	38 0.5×	28 0.5×	36	773
Anouk Schrantee Netherlands	15	301 0.8×	276 1.3×	100 1.3×	66 0.9×	122 2.3×	72	686
Thomas S. Harris United States	18	233 0.6×	176 0.8×	131 1.7×	119 1.6×	99 1.9×	38	657
Pál Salacz Hungary	8	295 0.7×	159 0.7×	37 0.5×	62 0.8×	45 0.9×	13	476
Anirban Dutt United Kingdom	12	369 0.9×	207 0.9×	41 0.5×	40 0.5×	105 2.0×	20	612
Cândida Helena Pires de Camargo Brazil	10	229 0.6×	334 1.5×	111 1.5×	100 1.3×	73 1.4×	15	558

Countries citing papers authored by Éva Csibri

Since Specialization

Citations

This map shows the geographic impact of Éva Csibri'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 Éva Csibri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éva Csibri more than expected).

Fields of papers citing papers by Éva Csibri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Éva Csibri. 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 Éva Csibri. The network helps show where Éva Csibri may publish in the future.

Co-authorship network of co-authors of Éva Csibri

This figure shows the co-authorship network connecting the top 25 collaborators of Éva Csibri. A scholar is included among the top collaborators of Éva Csibri based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Éva Csibri. Éva Csibri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Csukly, Gábor, Zoltán Hidasi, Éva Csibri, et al.. (2024). Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study. Translational Psychiatry. 14(1). 179–179. 3 indexed citations

Csukly, Gábor, et al.. (2024). Theta-burst rTMS in schizophrenia to ameliorate negative and cognitive symptoms: study protocol for a double-blind, sham-controlled, randomized clinical trial. Trials. 25(1). 269–269. 2 indexed citations

Hidasi, Zoltán, et al.. (2023). Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment. Scientific Reports. 13(1). 22285–22285. 5 indexed citations

Horváth, András Attila, Pál Salacz, Zoltán Hidasi, et al.. (2018). Decreased Event-Related Beta Synchronization During Memory Maintenance Marks Early Cognitive Decline in Mild Cognitive Impairment. Journal of Alzheimer s Disease. 63(2). 489–502. 18 indexed citations

Szabó, Ádám, Pál Salacz, Zoltán Hidasi, et al.. (2017). What can DTI tell about early cognitive impairment? – Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging. Psychiatry Research Neuroimaging. 272. 46–57. 34 indexed citations

Csukly, Gábor, András Horváth, Pál Salacz, et al.. (2016). The Differentiation of Amnestic Type MCI from the Non-Amnestic Types by Structural MRI. Frontiers in Aging Neuroscience. 8. 52–52. 125 indexed citations

Szabó, Ádám, et al.. (2015). Monitoring the Early Signs of Cognitive Decline in Elderly by Computer Games: An MRI Study. PLoS ONE. 10(2). e0117918–e0117918. 32 indexed citations

Tóth, Brigitta, Bálint File, Roland Boha, et al.. (2014). EEG network connectivity changes in mild cognitive impairment — Preliminary results. International Journal of Psychophysiology. 92(1). 1–7. 56 indexed citations

Hidasi, Zoltán, et al.. (2014). [Movement disorders is psychiatric diseases].. PubMed. 16(4). 205–11. 3 indexed citations

10.

Csukly, Gábor, et al.. (2014). [Pharmacological and other options in preventing dementia: a literature review].. PubMed. 16(3). 121–6. 1 indexed citations

11.

Csibri, Éva, et al.. (2013). [Differentiation between mild cognitive impairment and healthy elderly population using neuropsychological tests].. PubMed. 15(3). 139–46. 4 indexed citations

12.

Hidasi, Zoltán, et al.. (2012). [Depression in neuropsychiatric diseases].. PubMed. 65(1-2). 6–15. 2 indexed citations

13.

Salacz, Pál & Éva Csibri. (2011). Diabetes mellitus and Alzheimer’s disease. Orvosi Hetilap. 152(13). 512–515. 2 indexed citations

14.

Bódi, Nikoletta, Éva Csibri, Catherine E. Myers, Mark A. Gluck, & Szabolcs Kéri. (2009). Associative Learning, Acquired Equivalence, and Flexible Generalization of Knowledge in Mild Alzheimer Disease. Cognitive and Behavioral Neurology. 22(2). 89–94. 33 indexed citations

15.

Fehér, Ágnes, Anna Juhász, Ágnes Rimanóczy, et al.. (2009). Association between a Genetic Variant of the Alpha-7 Nicotinic Acetylcholine Receptor Subunit and Four Types of Dementia. Dementia and Geriatric Cognitive Disorders. 28(1). 56–62. 30 indexed citations

16.

Hidasi, Zoltán, et al.. (2007). Changes of EEG spectra and coherence following performance in a cognitive task in Alzheimer's disease. International Journal of Psychophysiology. 65(3). 252–260. 30 indexed citations

17.

Hidasi, Zoltán, Zsófia Anna Gaál, Éva Csibri, et al.. (2007). Quantitative EEG in early Alzheimer's disease patients — Power spectrum and complexity features. International Journal of Psychophysiology. 68(1). 75–80. 124 indexed citations

18.

Csibri, Éva, et al.. (2006). [Quantitative EEG analysis in Alzheimer's disease: spectral, coherence and complexity parameters].. PubMed. 21(4). 300–12. 3 indexed citations

19.

Rajna, Péter, et al.. (2003). Task related difference EEG spectrum – a new diagnostic method for neuropsychiatric disorders. Medical Hypotheses. 61(3). 390–397. 3 indexed citations

20.

Rajna, Péter, Béla Clemens, Éva Csibri, et al.. (1997). Hungarian multicentre epidemiologic study of the warning and initial symptoms (prodrome, aura) of epileptic seizures. Seizure. 6(5). 361–368. 85 indexed citations

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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