M. Berk Mirza

1.9k total citations · 1 hit paper
13 papers, 1.3k citations indexed

About

M. Berk Mirza is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Health. According to data from OpenAlex, M. Berk Mirza has authored 13 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 7 papers in Computer Vision and Pattern Recognition and 1 paper in Health. Recurrent topics in M. Berk Mirza's work include Neural dynamics and brain function (7 papers), Visual perception and processing mechanisms (4 papers) and Embodied and Extended Cognition (4 papers). M. Berk Mirza is often cited by papers focused on Neural dynamics and brain function (7 papers), Visual perception and processing mechanisms (4 papers) and Embodied and Extended Cognition (4 papers). M. Berk Mirza collaborates with scholars based in United Kingdom, United States and Switzerland. M. Berk Mirza's co-authors include Katherine L. Narr, David W. Shattuck, Vitria Adisetiyo, Arthur W. Toga, Georges Salamon, Russell A. Poldrack, Cornelius Hojatkashani, Robert M. Bilder, Karl Friston and Rick A. Adams and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

M. Berk Mirza

13 papers receiving 1.2k citations

Hit 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.

Construction of a 3D probabilistic atlas of human cortical structures

2007 850 citations David W. Shattuck, M. Berk Mirza et al. NeuroImage profile →

Peers

Countries citing papers authored by M. Berk Mirza

Since Specialization

Citations

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

Fields of papers citing papers by M. Berk Mirza

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Berk Mirza

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

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	Structure learning enhances concept formation in synthetic Active Inference agents 2022 ·PLoS ONE ·(unknown), M. Berk Mirza, Rick A. Adams, Karl Friston	8
2	Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions 2022 ·Comprehensive Psychiatry ·Adam Hampshire, William Trender, Jon E. Grant, M. Berk Mirza, Rosalyn Moran, Peter J. Hellyer, Samuel R. Chamberlain	16
3	Contextual perception under active inference 2021 ·Scientific Reports ·M. Berk Mirza, (unknown), Thomas Parr, Sukhwinder S. Shergill, Rosalyn Moran	8
4	Generative Models for Active Vision 2021 ·Frontiers in Neurorobotics ·Thomas Parr, Noor Sajid, Lancelot Da Costa, M. Berk Mirza, Karl Friston	21
5	Deep Active Inference and Scene Construction 2020 ·Frontiers in Artificial Intelligence ·(unknown), M. Berk Mirza, Thomas Parr, Karl Friston, Igor Kagan, Arezoo Pooresmaeili	14
6	Dynamic causal modelling of active vision 2019 ·Oxford University Research Archive (ORA) (University of Oxford) ·(unknown), M. Berk Mirza, (unknown), (unknown)	11
7	Introducing a Bayesian model of selective attention based on active inference 2019 ·Scientific Reports ·M. Berk Mirza, Rick A. Adams, Karl Friston, Thomas Parr	49
8	Human visual exploration reduces uncertainty about the sensed world 2018 ·PLoS ONE ·M. Berk Mirza, Rick A. Adams, Christoph Mathys, Karl Friston	55
9	Impulsivity and Active Inference 2018 ·Journal of Cognitive Neuroscience ·M. Berk Mirza, Rick A. Adams, Thomas Parr, Karl Friston	8
10	Scene Construction, Visual Foraging, and Active Inference 2016 ·Frontiers in Computational Neuroscience ·M. Berk Mirza, Rick A. Adams, Christoph Mathys, Karl Friston	104
11	Online resource for validation of brain segmentation methods 2008 ·NeuroImage ·David W. Shattuck, Gautam Prasad, M. Berk Mirza, Katherine L. Narr, Arthur W. Toga	127
12	Construction of a 3D probabilistic atlas of human cortical structures breakdown → 2007 ·NeuroImage ·David W. Shattuck, M. Berk Mirza, Vitria Adisetiyo, Cornelius Hojatkashani, Georges Salamon, Katherine L. Narr, Russell A. Poldrack, Robert M. Bilder, Arthur W. Toga	850
13	Automatic Caudate Segmentation by Hybrid Generative/Discriminative Models 2007 ·Zhuowen Tu, M. Berk Mirza, Ivo D. Dinov, Arthur W. Toga	1

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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