Isabella Premoli

2.0k total citations
24 papers, 992 citations indexed

About

Isabella Premoli is a scholar working on Cognitive Neuroscience, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Isabella Premoli has authored 24 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 15 papers in Neurology and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Isabella Premoli's work include Transcranial Magnetic Stimulation Studies (14 papers), EEG and Brain-Computer Interfaces (8 papers) and Functional Brain Connectivity Studies (8 papers). Isabella Premoli is often cited by papers focused on Transcranial Magnetic Stimulation Studies (14 papers), EEG and Brain-Computer Interfaces (8 papers) and Functional Brain Connectivity Studies (8 papers). Isabella Premoli collaborates with scholars based in United Kingdom, Italy and Germany. Isabella Premoli's co-authors include Ulf Ziemann, Paolo Belardinelli, Davide Rivolta, Florian Müller‐Dahlhaus, Nazareth P. Castellanos, Carl Moritz Zipser, Svenja Espenhahn, Tonio Heidegger, Andrea Biondi and Ricardo Bajo and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and NeuroImage.

In The Last Decade

Isabella Premoli

24 papers receiving 988 citations

Peers

Isabella Premoli

NEURO

CMN

NEURO

Zsolt Turi Germany

Leo Tomasevic Denmark

Shane Fresnoza Austria

Tonio Heidegger Germany

Alain Dagher Canada

Andrea Cancelli Italy

Valentina Bellina Italy

Greg Kronberg United States

R. Jarrett Rushmore United States

Michele Maiella Italy

Zsolt Turi Germany

Isabella Premoli

715 ×1.0

548 ×0.8

NEURO

183 ×1.4

CMN

99 ×1.0

59 ×0.6

NEURO

Citations per year, relative to Isabella Premoli Isabella Premoli (= 1×) peers Zsolt Turi

Countries citing papers authored by Isabella Premoli

Since Specialization

Citations

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

Fields of papers citing papers by Isabella Premoli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabella Premoli

This figure shows the co-authorship network connecting the top 25 collaborators of Isabella Premoli. A scholar is included among the top collaborators of Isabella Premoli 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 Isabella Premoli. Isabella Premoli 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

Biondi, Andrea, et al.. (2022). Spontaneous and TMS-related EEG changes as new biomarkers to measure anti-epileptic drug effects. Scientific Reports. 12(1). 1919–1919. 16 indexed citations

Brown, Katlyn E., Jaime Ibáñez, Vishal Rawji, et al.. (2021). Transcranial Evoked Potentials Can Be Reliably Recorded with Active Electrodes. Brain Sciences. 11(2). 145–145. 37 indexed citations

Belardinelli, Paolo, Isabella Premoli, Debora Desideri, et al.. (2021). TMS-EEG signatures of glutamatergic neurotransmission in human cortex. Scientific Reports. 11(1). 8159–8159. 82 indexed citations

Greene, Barry R., et al.. (2021). Predicting Fall Counts Using Wearable Sensors: A Novel Digital Biomarker for Parkinson’s Disease. Sensors. 22(1). 54–54. 18 indexed citations

Shergill, Sukhwinder S., et al.. (2021). TMS-EEG indexes abnormal GABAergic signalling in patients with schizophrenia. BJPsych Open. 7(S1). S52–S52. 2 indexed citations

Bossi, Francesco, et al.. (2020). Theta- and Gamma-Band Activity Discriminates Face, Body and Object Perception. Frontiers in Human Neuroscience. 14. 74–74. 19 indexed citations

Premoli, Isabella, et al.. (2019). Tensor decomposition of TMS-induced EEG oscillations reveals data-driven profiles of antiepileptic drug effects. Scientific Reports. 9(1). 17057–17057. 7 indexed citations

Premoli, Isabella, et al.. (2019). TMS-induced oscillations to evaluate pharmacodynamics properties of a newly developed anti-epileptic drug (XEN1101). Brain stimulation. 12(2). 459–460. 1 indexed citations

Premoli, Isabella, et al.. (2019). TMS-EEG and TMS-EMG to assess the pharmacodynamic profile of a novel potassium channel opener (XEN1101) on human cortical excitability. Brain stimulation. 12(2). 459–459. 3 indexed citations

10.

Premoli, Isabella, Florian Müller‐Dahlhaus, Carl Moritz Zipser, et al.. (2018). Short-interval and long-interval intracortical inhibition of TMS-evoked EEG potentials. Brain stimulation. 11(4). 818–827. 47 indexed citations

11.

Zipser, Carl Moritz, Isabella Premoli, Paolo Belardinelli, et al.. (2018). Cortical Excitability and Interhemispheric Connectivity in Early Relapsing–Remitting Multiple Sclerosis Studied With TMS-EEG. Frontiers in Neuroscience. 12. 393–393. 32 indexed citations

12.

Bossi, Francesco, et al.. (2017). Preliminary Evidence of “Other-Race Effect”-Like Behavior Induced by Cathodal-tDCS over the Right Occipital Cortex, in the Absence of Overall Effects on Face/Object Processing. Frontiers in Neuroscience. 11. 661–661. 14 indexed citations

13.

Premoli, Isabella, Til Ole Bergmann, Matteo Fecchio, et al.. (2017). The impact of GABAergic drugs on TMS-induced brain oscillations in human motor cortex. NeuroImage. 163. 1–12. 69 indexed citations

14.

Premoli, Isabella, et al.. (2017). Neurophysiological Correlates of Featural and Spacing Processing for Face and Non-face Stimuli. Frontiers in Psychology. 8. 333–333. 23 indexed citations

15.

Fecchio, Matteo, Andrea Pigorini, Angela Comanducci, et al.. (2017). The spectral features of EEG responses to transcranial magnetic stimulation of the primary motor cortex depend on the amplitude of the motor evoked potentials. PLoS ONE. 12(9). e0184910–e0184910. 97 indexed citations

16.

Premoli, Isabella, Alyssa Costantini, Davide Rivolta, Andrea Biondi, & Mark P. Richardson. (2017). The Effect of Lamotrigine and Levetiracetam on TMS-Evoked EEG Responses Depends on Stimulation Intensity. Frontiers in Neuroscience. 11. 585–585. 26 indexed citations

17.

Premoli, Isabella, et al.. (2016). Characterization of GABAA-receptor mediated neurotransmission in the human cortex by paired-pulse TMS-EEG. Clinical Neurophysiology. 127(3). e45–e45. 2 indexed citations

18.

Premoli, Isabella, Nazareth P. Castellanos, Davide Rivolta, et al.. (2014). TMS-EEG Signatures of GABAergic Neurotransmission in the Human Cortex. Journal of Neuroscience. 34(16). 5603–5612. 269 indexed citations

19.

Premoli, Isabella, Davide Rivolta, Svenja Espenhahn, et al.. (2014). Characterization of GABAB-receptor mediated neurotransmission in the human cortex by paired-pulse TMS–EEG. NeuroImage. 103. 152–162. 126 indexed citations

20.

Chebib, Mary, Navnath S. Gavande, Anna Park, et al.. (2009). Guanidino Acids Act as ρ1 GABAC Receptor Antagonists. Neurochemical Research. 34(10). 1704–1711. 19 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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