M. Mallar Chakravarty

32.8k total citations · 3 hit papers
347 papers, 12.6k citations indexed

About

M. Mallar Chakravarty is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, M. Mallar Chakravarty has authored 347 papers receiving a total of 12.6k indexed citations (citations by other indexed papers that have themselves been cited), including 166 papers in Cognitive Neuroscience, 126 papers in Radiology, Nuclear Medicine and Imaging and 95 papers in Psychiatry and Mental health. Recurrent topics in M. Mallar Chakravarty's work include Functional Brain Connectivity Studies (127 papers), Advanced Neuroimaging Techniques and Applications (110 papers) and Advanced MRI Techniques and Applications (39 papers). M. Mallar Chakravarty is often cited by papers focused on Functional Brain Connectivity Studies (127 papers), Advanced Neuroimaging Techniques and Applications (110 papers) and Advanced MRI Techniques and Applications (39 papers). M. Mallar Chakravarty collaborates with scholars based in Canada, United States and United Kingdom. M. Mallar Chakravarty's co-authors include D. Louis Collins, Aristotle N. Voineskos, Jason P. Lerch, Min Tae M Park, Gabriel A. Devenyi, Armin Raznahan, Jon Pipitone, Sandra E. Leh, Alain Ptito and Eric Plitman and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

M. Mallar Chakravarty

334 papers receiving 12.5k citations

Hit Papers

3 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases

2014 429 citations M. Mallar Chakravarty et al. profile →
Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity

2017 403 citations M. Mallar Chakravarty et al. profile →
neuromaps: structural and functional interpretation of brain maps

2022 164 citations Ross D. Markello, Golia Shafiei et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Mallar Chakravarty Canada	60	5.2k	3.4k	2.5k	2.0k	1.8k	347	12.6k
Núria Bargalló Spain	61	4.6k 0.9×	3.0k 0.9×	3.0k 1.2×	2.9k 1.5×	1.1k 0.6×	347	12.0k
Gary F. Egan Australia	72	5.3k 1.0×	3.3k 1.0×	1.7k 0.7×	2.1k 1.1×	2.5k 1.4×	362	14.7k
Gwenaëlle Douaud United Kingdom	45	5.3k 1.0×	4.1k 1.2×	1.5k 0.6×	2.2k 1.1×	1.0k 0.6×	66	10.8k
Philip A. Cook United States	37	5.1k 1.0×	5.7k 1.7×	1.5k 0.6×	1.2k 0.6×	964 0.5×	93	12.4k
Stefan Sunaert Belgium	69	7.5k 1.4×	4.2k 1.2×	2.2k 0.9×	1.7k 0.9×	847 0.5×	351	15.4k
Carme Junqué Spain	72	6.4k 1.2×	3.3k 1.0×	3.3k 1.3×	5.3k 2.7×	1.7k 0.9×	311	15.7k
Mara Cercignani United Kingdom	58	3.7k 0.7×	6.3k 1.8×	2.1k 0.8×	1.5k 0.8×	863 0.5×	230	11.6k
R. P. Maguire Switzerland	39	7.9k 1.5×	4.6k 1.4×	3.2k 1.3×	2.1k 1.1×	2.0k 1.2×	103	15.2k
Gerard R. Ridgway United Kingdom	44	4.2k 0.8×	4.0k 1.2×	2.4k 0.9×	1.6k 0.8×	741 0.4×	107	10.0k
David C. Reutens Australia	53	2.7k 0.5×	2.1k 0.6×	2.6k 1.0×	1.2k 0.6×	1.7k 0.9×	320	9.7k

Countries citing papers authored by M. Mallar Chakravarty

Since Specialization

Citations

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

Fields of papers citing papers by M. Mallar Chakravarty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Mallar Chakravarty. 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 M. Mallar Chakravarty. The network helps show where M. Mallar Chakravarty may publish in the future.

Co-authorship network of co-authors of M. Mallar Chakravarty

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Patel, Raihaan, Alyssa Salaciak, Saashi A. Bedford, et al.. (2025). Exploring morphological and microstructural signatures across the Alzheimer's spectrum and risk factors. Neurobiology of Aging. 149. 1–18.

Tullo, Stéphanie, Daniel Gallino, Raihaan Patel, et al.. (2025). Female mice exhibit resistance to disease progression despite early pathology in a transgenic mouse model inoculated with alpha-synuclein fibrils. Communications Biology. 8(1). 288–288.

Devenyi, Gabriel A., et al.. (2025). Similarities and differences in cerebellar alterations between youth born preterm and youth born with congenital heart disease. Scientific Reports. 15(1). 10420–10420.

Papadopoulou, Athina, Charidimos Tsagkas, Laura Gaetano, et al.. (2024). Visual evoked potentials in multiple sclerosis: P100 latency and visual pathway damage including the lateral geniculate nucleus. Clinical Neurophysiology. 161. 122–132. 3 indexed citations

Dhamala, Elvisha, Lucina Q. Uddin, Liisa A.M. Galea, et al.. (2024). Considering the interconnected nature of social identities in neuroimaging research. Nature Neuroscience. 28(2). 222–233. 5 indexed citations

Hughes, Colleen, Giulia Baracchini, Jennifer Tremblay‐Mercier, et al.. (2024). Iron Deposition and Distribution Across the Hippocampus Is Associated with Pattern Separation and Pattern Completion in Older Adults at Risk for Alzheimer's Disease. Journal of Neuroscience. 44(19). e1973232024–e1973232024. 8 indexed citations

Skorska, Malvina N., Gabriel A. Devenyi, Kenneth J. Zucker, et al.. (2023). Cortical Structure Differences in Relation to Age, Sexual Attractions, and Gender Dysphoria in Adolescents: An Examination of Mean Diffusivity and T1 Relaxation Time. Brain Sciences. 13(6). 963–963. 2 indexed citations

Papadopoulou, Athina, Frederike Cosima Oertel, Claudia Chien, et al.. (2021). Lateral geniculate nucleus volume changes after optic neuritis in neuromyelitis optica: A longitudinal study. NeuroImage Clinical. 30. 102608–102608. 9 indexed citations

Gouveia, Flavia Venetucci, Jürgen Germann, Erich Talamoni Fonoff, et al.. (2020). Longitudinal Changes After Amygdala Surgery for Intractable Aggressive Behavior: Clinical, Imaging Genetics, and Deformation-Based Morphometry Study—A Case Series. Neurosurgery. 88(2). E158–E169. 14 indexed citations

10.

Gallino, Daniel, et al.. (2020). Structural brain plasticity induced by early blindness. European Journal of Neuroscience. 53(3). 778–795. 14 indexed citations

11.

Kirschner, Matthias, Golia Shafiei, Ross D. Markello, et al.. (2020). Latent Clinical-Anatomical Dimensions of Schizophrenia. Schizophrenia Bulletin. 46(6). 1426–1438. 21 indexed citations

12.

Noda, Yoshihiro, Ryosuke Tarumi, Shiori Honda, et al.. (2020). White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 100. 109871–109871. 22 indexed citations

13.

Reardon, Paul K., Jakob Seidlitz, Simon Vandekar, et al.. (2018). Normative brain size variation and brain shape diversity in humans. Science. 360(6394). 1222–1227. 136 indexed citations

14.

Park, Min Tae M, Paul K. Reardon, Liv Clasen, et al.. (2017). Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization. Journal of Neuroscience. 37(21). 5221–5231. 50 indexed citations

15.

Schuetze, Manuela, et al.. (2016). Morphological Alterations in the Thalamus, Striatum, and Pallidum in Autism Spectrum Disorder. Neuropsychopharmacology. 41(11). 2627–2637. 118 indexed citations

16.

Treadway, Michael T., Michael Waskom, Daniel G. Dillon, et al.. (2014). Illness Progression, Recent Stress, and Morphometry of Hippocampal Subfields and Medial Prefrontal Cortex in Major Depression. Biological Psychiatry. 77(3). 285–294. 250 indexed citations

17.

Voineskos, Aristotle N., Daniel Felsky, Nataša Žunić Kovačević, et al.. (2012). Oligodendrocyte Genes, White Matter Tract Integrity, and Cognition in Schizophrenia. Cerebral Cortex. 23(9). 2044–2057. 59 indexed citations

18.

Dalby, Rikke Beese, Jesper Frandsen, M. Mallar Chakravarty, et al.. (2012). Correlations between Stroop task performance and white matter lesion measures in late-onset major depression. Psychiatry Research Neuroimaging. 202(2). 142–149. 19 indexed citations

19.

Dalby, Rikke Beese, Jesper Frandsen, M. Mallar Chakravarty, et al.. (2010). Depression severity is correlated to the integrity of white matter fiber tracts in late-onset major depression. Psychiatry Research Neuroimaging. 184(1). 38–48. 81 indexed citations

20.

Borghammer, Per, Karen Østergaard, Paul Cumming, et al.. (2009). A deformation‐based morphometry study of patients with early‐stage Parkinson’s disease. European Journal of Neurology. 17(2). 314–320. 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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