Federico Calesella

553 total citations
21 papers, 240 citations indexed

About

Federico Calesella is a scholar working on Psychiatry and Mental health, Cognitive Neuroscience and Biological Psychiatry. According to data from OpenAlex, Federico Calesella has authored 21 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Psychiatry and Mental health, 8 papers in Cognitive Neuroscience and 7 papers in Biological Psychiatry. Recurrent topics in Federico Calesella's work include Functional Brain Connectivity Studies (8 papers), Bipolar Disorder and Treatment (8 papers) and Tryptophan and brain disorders (7 papers). Federico Calesella is often cited by papers focused on Functional Brain Connectivity Studies (8 papers), Bipolar Disorder and Treatment (8 papers) and Tryptophan and brain disorders (7 papers). Federico Calesella collaborates with scholars based in Italy, Switzerland and Germany. Federico Calesella's co-authors include Francesco Benedetti, Benedetta Vai, Sara Poletti, Cristina Lorenzi, Cristina Colombo, Raffaella Zanardi, Mario Gennaro Mazza, Roberto Furlan, Igor Branchi and Elisa Melloni and has published in prestigious journals such as International Journal of Molecular Sciences, Neuroscience & Biobehavioral Reviews and Human Brain Mapping.

In The Last Decade

Federico Calesella

18 papers receiving 238 citations

Peers

Federico Calesella

PMH

ECP

Zhen Tang China

Inge Winter-van Rossum Netherlands

Suheyla Cetin‐Karayumak United States

Rocco Hoekstra Netherlands

Supaksorn Thika Thailand

Christian Núñez Spain

Mihnea Costin Manea Romania

Cristina Oliveira Spain

Samuel Leighton United Kingdom

Jennifer L. Kruse United States

Zhen Tang China

Federico Calesella

137 ×1.5

50 ×0.6

PMH

92 ×1.6

40 ×0.8

47 ×1.3

ECP

Citations per year, relative to Federico Calesella Federico Calesella (= 1×) peers Zhen Tang

Countries citing papers authored by Federico Calesella

Since Specialization

Citations

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

Fields of papers citing papers by Federico Calesella

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federico Calesella

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

Calesella, Federico, Emanuela Serra, Mariagrazia Palladini, et al.. (2025). Differences in resting-state functional connectivity between depressed bipolar and major depressive disorder patients: A machine learning study. European Neuropsychopharmacology. 97. 28–37. 2 indexed citations

Paolini, Marco, Anna Verri, Federico Calesella, et al.. (2025). Cardiovascular Risk Predicts White Matter Hyperintensities, Brain Atrophy and Treatment Resistance in Major Depressive Disorder: Role of Genetic Liability. Acta Psychiatrica Scandinavica. 151(6). 709–718. 1 indexed citations

Acconcia, Maria Cristina, Federica Colombo, Federico Calesella, et al.. (2025). Spontaneous neural activity mediates the effect of adverse childhood experiences on negative cognitive styles in mood disorders: a multivariate approach. Psychiatry Research Neuroimaging. 352. 112038–112038.

Cavicchioli, Marco, Federico Calesella, Ilaria Carretta, et al.. (2025). A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study. Journal of Clinical Psychology. 81(4). 222–236. 1 indexed citations

Bianchi, Anna Maria, Federico Calesella, Benedetta Vai, et al.. (2024). Assessment of ComBat Harmonization Performance on Structural Magnetic Resonance Imaging Measurements. Human Brain Mapping. 45(18). e70085–e70085. 2 indexed citations

Palladini, Mariagrazia, Mario Gennaro Mazza, Veronica Aggio, et al.. (2024). Circulating inflammatory markers predict depressive symptomatology in COVID-19 survivors. Cytokine. 186. 156839–156839. 2 indexed citations

Vai, Benedetta, et al.. (2024). Adverse childhood experiences differently affect Theory of Mind brain networks in schizophrenia and healthy controls. Journal of Psychiatric Research. 172. 81–89. 1 indexed citations

Melloni, Elisa, Marco Paolini, Mariagrazia Palladini, et al.. (2023). Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines. Brain Behavior and Immunity. 116. 52–61. 23 indexed citations

Raffaelli, L., Federica Colombo, Federico Calesella, et al.. (2023). Predicting unipolar and bipolar depression using inflammatory markers, neuroimaging and neuropsychological data: a machine learning study. European Psychiatry. 66(S1). S621–S621.

10.

Calesella, Federico, Federico Colombo, Emanuela Maggioni, et al.. (2023). Predicting Suicide Attempts among Major Depressive Disorder Patients with Structural Neuroimaging: A Machine Learning Approach. European Psychiatry. 66(S1). S1111–S1112.

11.

Calesella, Federico, Federica Colombo, Sara Poletti, et al.. (2023). A machine learning pipeline for efficient differentiation between bipolar and major depressive disorder based on multimodal structural neuroimaging. Neuroscience Applied. 3. 103931–103931. 3 indexed citations

12.

Vai, Benedetta, Federico Calesella, Paola Di Fiore, et al.. (2023). Reduced corticolimbic habituation to negative stimuli characterizes bipolar depressed suicide attempters. Psychiatry Research Neuroimaging. 331. 111627–111627. 3 indexed citations

13.

Mazza, Elena, Federico Calesella, Marco Paolini, et al.. (2022). Insulin resistance disrupts white matter microstructure and amplitude of functional spontaneous activity in bipolar disorder. Bipolar Disorders. 25(1). 32–42. 11 indexed citations

14.

Poletti, Sara, Marco Paolini, Irene Bollettini, et al.. (2022). Long-term effect of childhood trauma: Role of inflammation and white matter in mood disorders. Brain Behavior & Immunity - Health. 26. 100529–100529. 14 indexed citations

15.

Colombo, Federica, Federico Calesella, Mario Gennaro Mazza, et al.. (2022). Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews. 135. 104552–104552. 26 indexed citations

16.

Poletti, Sara, Federico Calesella, Benedetta Vai, et al.. (2021). Circulating inflammatory markers impact cognitive functions in bipolar depression. Journal of Psychiatric Research. 140. 110–116. 29 indexed citations

17.

Cavicchioli, Marco, Federico Calesella, Mariagrazia Movalli, et al.. (2021). Investigating predictive factors of dialectical behavior therapy skills training efficacy for alcohol and concurrent substance use disorders: A machine learning study. Drug and Alcohol Dependence. 224. 108723–108723. 10 indexed citations

18.

Calesella, Federico, Alberto Testolin, Michele De Filippo De Grazia, & Marco Zorzi. (2021). A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients. Brain Informatics. 8(1). 8–8. 20 indexed citations

19.

Vai, Benedetta, Mario Gennaro Mazza, Federico Calesella, et al.. (2021). Higher Interleukin 13 differentiates patients with a positive history of suicide attempts in major depressive disorder. Journal of Affective Disorders Reports. 6. 100254–100254. 9 indexed citations

20.

Poletti, Sara, Benedetta Vai, Mario Gennaro Mazza, et al.. (2020). A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 105. 110136–110136. 81 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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