Zoltán Karádi

1.9k total citations
105 papers, 1.5k citations indexed

About

Zoltán Karádi is a scholar working on Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems and Nutrition and Dietetics. According to data from OpenAlex, Zoltán Karádi has authored 105 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Cellular and Molecular Neuroscience, 32 papers in Endocrine and Autonomic Systems and 30 papers in Nutrition and Dietetics. Recurrent topics in Zoltán Karádi's work include Biochemical Analysis and Sensing Techniques (30 papers), Regulation of Appetite and Obesity (29 papers) and Neuroscience and Neuropharmacology Research (28 papers). Zoltán Karádi is often cited by papers focused on Biochemical Analysis and Sensing Techniques (30 papers), Regulation of Appetite and Obesity (29 papers) and Neuroscience and Neuropharmacology Research (28 papers). Zoltán Karádi collaborates with scholars based in Hungary, Japan and Czechia. Zoltán Karádi's co-authors include László Lénárd, K. Miyashita, S. Miyachi, Miya K. Rand, Okihide Hikosaka, Hitoe Nishino, Yutaka Oomura, S. Aou, Thomas R. Scott and András Czurkó and has published in prestigious journals such as Journal of Neurophysiology, Scientific Reports and Brain Research.

In The Last Decade

Zoltán Karádi

102 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zoltán Karádi Hungary 20 631 493 360 357 232 105 1.5k
Yasunobu Yasoshima Japan 20 806 1.3× 461 0.9× 183 0.5× 430 1.2× 391 1.7× 32 1.4k
Amadeo Puerto Spain 24 885 1.4× 521 1.1× 454 1.3× 544 1.5× 248 1.1× 96 1.8k
Patrice Congar France 20 1.1k 1.7× 387 0.8× 160 0.4× 285 0.8× 445 1.9× 31 1.6k
Tatiana Lima Ferreira Brazil 16 380 0.6× 397 0.8× 324 0.9× 229 0.6× 269 1.2× 30 1.2k
Dolores E. López Spain 21 568 0.9× 555 1.1× 112 0.3× 195 0.5× 285 1.2× 68 1.4k
Ryuji Matsuo Japan 21 405 0.6× 250 0.5× 331 0.9× 482 1.4× 205 0.9× 70 1.2k
Zhen Fang Huang Cao China 13 410 0.6× 486 1.0× 811 2.3× 359 1.0× 169 0.7× 20 1.5k
G Plasse Netherlands 21 587 0.9× 379 0.8× 389 1.1× 173 0.5× 210 0.9× 28 1.5k
Joan F. Lorden United States 26 1.1k 1.8× 467 0.9× 283 0.8× 206 0.6× 415 1.8× 68 1.9k
Daniel C. Castro United States 10 758 1.2× 480 1.0× 338 0.9× 165 0.5× 361 1.6× 12 1.5k

Countries citing papers authored by Zoltán Karádi

Since Specialization
Citations

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

Fields of papers citing papers by Zoltán Karádi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zoltán Karádi

This figure shows the co-authorship network connecting the top 25 collaborators of Zoltán Karádi. A scholar is included among the top collaborators of Zoltán Karádi 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 Zoltán Karádi. Zoltán Karádi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Péczely, László, László Lénárd, Tamás Ollmann, et al.. (2024). The antipsychotic agent sulpiride microinjected into the ventral pallidum restores positive symptom-like habituation disturbance in MAM-E17 schizophrenia model rats. Scientific Reports. 14(1). 12305–12305. 1 indexed citations
2.
Miseta, Attila, Tamás Tornóczky, Péter Bogner, et al.. (2023). Novel Noninvasive Paraclinical Study Method for Investigation of Liver Diseases. Biomedicines. 11(9). 2449–2449. 4 indexed citations
3.
4.
László, Kristóf, László Péczely, Anita Kovács, et al.. (2020). The role of D2 dopamine receptors in oxytocin induced place preference and anxiolytic effect. Hormones and Behavior. 124. 104777–104777. 14 indexed citations
5.
Kertes, Erika, László Péczely, Tamás Ollmann, et al.. (2019). Ventromedial prefrontal cortex is involved in preference and hedonic evaluation of tastes. Behavioural Brain Research. 367. 149–157. 2 indexed citations
6.
Lénárd, László, László Péczely, Rita Gálosi, et al.. (2019). Cognitive performance of the MAM-E17 schizophrenia model rats in different age-periods. Behavioural Brain Research. 379. 112345–112345. 3 indexed citations
7.
Szabó, Ildikò, et al.. (2017). Food and water intake, body temperature and metabolic consequences of interleukin-1β microinjection into the cingulate cortex of the rat. Behavioural Brain Research. 331. 115–122. 3 indexed citations
8.
Lénárd, László, Kristóf László, Erika Kertes, et al.. (2017). Substance P and neurotensin in the limbic system: Their roles in reinforcement and memory consolidation. Neuroscience & Biobehavioral Reviews. 85. 1–20. 31 indexed citations
9.
Szabó, István, et al.. (2017). Multiple functional attributes of glucose-monitoring neurons in the medial orbitofrontal (ventrolateral prefrontal) cortex. Neuroscience & Biobehavioral Reviews. 85. 44–53. 3 indexed citations
10.
Lénárd, László, Tamás Ollmann, Kristóf László, et al.. (2017). Role of D2 dopamine receptors of the ventral pallidum in inhibitory avoidance learning. Behavioural Brain Research. 321. 99–105. 17 indexed citations
11.
12.
Karádi, Zoltán, et al.. (2007). Homeostatic significance of the forebrain glucose-monitoring neuronal network. 33–33. 1 indexed citations
13.
Karádi, Zoltán, et al.. (2005). Homeostatic alterations after intrapallidal microinjection of interleukin-1β in the rat. Appetite. 44(2). 171–180. 9 indexed citations
14.
Karádi, Zoltán. (2005). Involvement of Forebrain Glucose-monitoring Neurons in Taste Information Processing: Electrophysiological and Behavioral Studies. Chemical Senses. 30(Supplement 1). i168–i169. 21 indexed citations
15.
Hernádi, István, et al.. (2000). Alterations of conditioned taste aversion after microiontophoretically applied neurotoxins in the medial prefrontal cortex of the rat. Brain Research Bulletin. 53(6). 751–758. 39 indexed citations
16.
Hernádi, István, Zoltán Karádi, Béla Faludi, & László Lénárd. (1997). Disturbances of neophobia and taste-aversion learning after bilateral kainate microlesions in the rat pallidum.. Behavioral Neuroscience. 111(1). 137–146. 16 indexed citations
17.
Hajnal, A., et al.. (1991). Local and distant effects of amygdaloid kainate lesions in the rat: a silver impregnation study.. PubMed. 26(1-4). 71–3. 2 indexed citations
18.
Aou, S., et al.. (1991). Functional heterogeneity of the monkey lateral hypothalamus in the control of feeding. Brain Research Bulletin. 27(3-4). 451–455. 17 indexed citations
19.
Karádi, Zoltán, et al.. (1990). Complex attributes of lateral hypothalamic neurons in the regulation of feeding of alert rhesus monkeys. Brain Research Bulletin. 25(6). 933–939. 20 indexed citations
20.
Oomura, Yutaka, et al.. (1987). Odor responses of lateral hypothalamic glucosensitive (GS) and glucose-insensitive (GIS) neurons in the monkey. Neuroscience Research Supplements. 5. S87–S87. 2 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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