Computational Neuroscience Scholar Analysis

Comprehensive analysis of top researchers in computational neuroscience, including citation metrics, h-index distribution, institutional affiliations, and research categories.

Data Source: OpenAlex API185 Scholars Analyzed

Overview Statistics

Total Scholars

185

In computational neuroscience

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Avg Citations

38,990

Median: 24,517

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Avg H-index

53.4

Max: 259

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Avg Publications

286

Median: 156

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Distribution Analysis

Citation Count Distribution

H-index Distribution

Citations vs H-index

Relationship between H-index and Total Citations (by Category)

Geographic & Institutional Distribution

Distribution by Country

Top Institutions

Research Category Distribution

Research Categories

Category Breakdown

Computational Neuroscience113 Scholars (61.1%)

AI & Machine Learning34 Scholars (18.4%)

Visual Neuroscience13 Scholars (7.0%)

Cognitive Neuroscience11 Scholars (5.9%)

Network Neuroscience7 Scholars (3.8%)

Motor Control7 Scholars (3.8%)

Key Insights

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Citation Power Law

Citations follow a strong power law distribution. The top 10% of scholars account for citations above 87,112, while the median is only 24,517.

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Geographic Concentration

The field is heavily concentrated in North America and Western Europe, with the US accounting for 36 scholars (19% of the sample).

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Interdisciplinary Nature

Many top scholars bridge AI/ML and neuroscience. The highest-cited researchers often develop widely-used methods or theoretical frameworks that cross disciplines.

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Early Career Impact Rankings

Ranking scholars by their citation impact during the first 5 years of their academic careers. This metric reveals early academic "explosion" potential and foundational contributions.

Top Early Citations

6,724

David Marr

Average Early Citations

2,137

Median Early Citations

1,595

Scholars Analyzed

Key Findings

David Marr's Legacy

David Marr leads with 6,724 early citations. His 1969-1973 works, especially 'A theory of cerebellar cortex', defined computational neuroscience's foundations.

Single paper: 3,291 citations

Early Burst Pattern

9 scholars have >20% of total citations from their first 5 years, indicating strong early-career impact in this field.

Average early citations: 2,137

Modern Rising Stars

7 scholars starting after 2005 made the top 20, showing the field's continued growth and new talent emergence.

Gershman, Scellier, Zenke lead the new generation

Sustained vs. Early Impact

Compare Warland (100% early) vs Paninski (7.5% early): some scholars peak early, others build influence over decades.

3 pre-1990 scholars still influential

Top 15 by Early Career Citations

Early Impact Pattern Analysis

The "Marr Effect"

David Marr's early works accumulated 6,724 citations in just 5 years (1969-1973), representing 23.2% of his total career citations. His theoretical frameworks became foundational texts cited for decades.

One-Hit Wonders vs. Sustained Growth

Davd Warland's single paper "Spikes" accounts for 100% of citations, while Liam Paninski's early 7.5% suggests continuous career growth. Both are valid paths to impact.

Modern AI-Neuro Crossover

Benjamin Scellier (2016 start) achieved 1,591 early citations largely from "A deep learning framework for neuroscience" - showing the field's growing intersection with AI.

Methodological Impact

Method developers like Paninski ("Instant neural control") often have lower early % because their tools gain adoption gradually over time.

Complete Early Career Rankings (Top 20)

#	Scholar	Institution	Career Start	Early Citations	Early %	Papers
1	David Marr A theory of cerebellar cortex	Massachusetts Institute of Technology	1969-1973	6,724	23.2%	8
2	Sander Nieuwenhuis Electrophysiological correlates of anterior cingulate function in a go/no-go task	Leiden University	1999-2003	4,446	18.6%	16
3	Samuel J. Gershman Model-Based Influences on Humans' Choices and Striatal Prediction Errors	Harvard University	2007-2011	3,746	18.5%	16
4	Michael Breakspear Synchronous Gamma activity: a review and contribution to an integrative neuroscience model	Hunter Medical Research Institute	2001-2005	3,044	9.5%	25
5	Davd Warland Spikes: Exploring the Neural Code	Harvard University	1996-2000	2,886	100%	1
6	Richard Miles Excitatory synaptic interactions between CA3 neurones in the guinea-pig hippocampus	Collège de France	1983-1987	2,591	17.2%	18
7	Panayiota Poirazi Pyramidal Neuron as Two-Layer Neural Network	FORTH Institute of Molecular Biology and Biotechnology	1999-2003	1,890	22.5%	6
8	Liam Paninski Instant neural control of a movement signal	Columbia University Irving Medical Center	1998-2002	1,683	7.5%	5
9	Jeffrey M. Beck Bayesian inference with probabilistic population codes	Duke University	2003-2007	1,652	29.4%	7
10	David G. Beiser Models of Information Processing in the Basal Ganglia	University of Chicago	1994-1998	1,599	43.2%	16
11	Benjamin Scellier A deep learning framework for neuroscience	Independent	2016-2020	1,591	96.9%	16
12	Adam Marblestone Rapid prototyping of 3D DNA-origami shapes with caDNAno	Massachusetts Institute of Technology	2009-2013	1,546	27.1%	12
13	Anna C. Schapiro Neural representations of events arise from temporal community structure	California University of Pennsylvania	2009-2013	1,448	25.9%	11
14	Eric Horvitz Decision theory in expert systems and artificial intelligence	Microsoft (United States)	1984-1988	1,208	3%	14
15	Viktor Jirsa Field Theory of Electromagnetic Brain Activity	Inserm	1994-1998	1,197	4.7%	9
16	Claudia Clopath Connectivity reflects coding: a model of voltage-based STDP with homeostasis	Imperial College London	2006-2010	1,188	7.9%	8
17	Archy O. de Berker Computations of uncertainty mediate acute stress responses in humans	Independent	2013-2017	1,136	42.5%	13
18	Wulfram Gerstner Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns	EPFL	1990-1994	1,130	3.5%	18
19	Nikolaus Kriegeskorte Cortical capacity constraints for visual working memory	Brain (Germany)	2001-2005	1,073	3.5%	8
20	Friedemann Zenke Inhibitory Plasticity Balances Excitation and Inhibition	Friedrich Miescher Institute	2008-2012	953	13.5%	5

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Rising Stars: Youngest Scholars

The 10 youngest computational neuroscientists by academic career start date. These emerging researchers represent the future of the field.

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Youngest Scholar

Scellier

Started in 2016, only 9 years in academia

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Most Efficient

Gershman

1127 citations/year average

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Average Stats

15 years

Avg age with 5,105 avg citations

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AI-Neuro Focus

70%

of young scholars work on AI + neuroscience intersection

Citations per Academic Year

Measuring research efficiency: total citations divided by years in academia

Academic Age vs H-Index

Bubble size represents total citations

Key Findings: The New Generation

Samuel Gershman Leads Efficiency

With 1,127 citations per year, Gershman demonstrates exceptional research productivity. His work on computational cognitive science has rapidly gained influence.

AI-Neuro Convergence

70% of the youngest scholars focus on the intersection of AI and neuroscience, including Scellier (equilibrium propagation), Zenke (spiking networks), and Marblestone (neural engineering).

Rapid H-Index Growth

Gershman achieved H-index 71 in just 18 years, while Schapiro and Zenke both reached 27 in under 17 years - indicating accelerating impact in modern academia.

Institutional Diversity

Young scholars are distributed across top institutions: Harvard, MIT, NYU, Imperial College, and research institutes like Friedrich Miescher - showing field-wide talent development.

Complete Youngest Scholars Rankings

#	Scholar	Institution	First Pub	Age	Citations	H-Index	Cites/Year
1	Benjamin Scellier A deep learning framework for neuroscience	Independent	2016	9 yrs	1,642	9	182
2	Grace W. Lindsay Parallel processing by cortical inhibition enables context-dependent behavior	New York University	2014	11 yrs	2,930	13	266
3	Archy O. de Berker Computations of uncertainty mediate acute stress responses in humans	Independent	2013	12 yrs	2,672	16	223
4	Garrett B. Goh Constant pH molecular dynamics of proteins	Pacific Northwest National Laboratory	2010	15 yrs	2,042	18	136
5	João Sacramento Dendritic cortical microcircuits	ETH Zurich	2010	15 yrs	1,665	15	111
6	Adam Marblestone Rapid prototyping of 3D DNA-origami shapes with caDNAno	Massachusetts Institute of Technology	2009	16 yrs	5,712	24	357
7	Anna C. Schapiro Neural representations of events arise from temporal community structure	University of Pennsylvania	2009	16 yrs	5,594	27	350
8	Friedemann Zenke Inhibitory Plasticity Balances Excitation and Inhibition	Friedrich Miescher Institute	2008	17 yrs	7,035	27	414
9	Colleen J. Gillon Learning from unexpected events in the neocortical microcircuit	Imperial College London	2008	17 yrs	1,472	8	87
10	Samuel J. Gershman Model-Based Influences on Humans' Choices and Striatal Prediction Errors	Harvard University	2007	18 yrs	20,281	71	1127

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Multi-Metric Ranking Matrix

Compare scholars across all metrics simultaneously. Each cell shows the scholar's rank for that specific metric. Hover over names for detailed profiles.

Scholar Ranking Matrix

Multi-dimensional evaluation of 185 scholars. Hover over names for details, click headers to sort.

Perspective:

Sort by:

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Current weights:Balanced evaluation of historical contributions and current activity

Rank colors:Top 5%Top 10%Top 25%Top 50%Bottom 50%Importance: *Primary +Secondary -Auxiliary

Scholar	Overallv	* H-Index	* 2Yr	* Eff	* M-Idx	+ Citations	- Pubs	- i10
1.Yoshua Bengio	1	2	3	5	-	1	2	2
2.Olaf Sporns	2	7	17	6	-	13	15	13
3.Zoubin Ghahramani	3	12	1	16	-	30	22	14
4.Terrence J. Sejnowski	4	4	22	11	-	5	5	3
5.Christof Koch	5	3	19	19	-	9	3	4
6.Karl Friston	6	1	28	15	-	2	1	1
7.Joshua B. Tenenbaum	7	6	21	14	-	8	7	6
8.Timothy Lillicrap	8	38	2	3	-	25	49	38
9.Michael Breakspear	9	16	12	37	2	51	21	15
10.Eric‐Jan Wagenmakers	10	8	33	33	-	23	9	9
11.Alexandre Pouget	11	27	8	12	-	73	46	33
12.Peter Dayan	12	5	39	38	-	19	6	7
13.Michael Häusser	13	18	11	25	-	80	37	28
14.James J. DiCarlo	14	26	15	13	-	62	42	36
15.Eric Horvitz	15	15	4	60	7	47	12	8
16.Michael J. Frank	16	14	43	28	-	39	17	18
17.Gustavo Deco	17	13	23	70	-	40	8	5
18.Nikolaus Kriegeskorte	18	25	34	30	3	66	29	32
19.Samuel J. Gershman	19	24	36	51	1	65	20	20
20.Mitsuo Kawato	20	11	45	58	-	42	11	12
21.Roger D. Traub	21	17	40	29	-	89	39	26
22.Konrad P. Körding	22	22	18	66	-	100	18	17
23.Viktor Jirsa	23	19	26	74	4	88	14	16
24.Christopher J. Honey	24	45	25	9	-	91	65	56
25.William Bialek	25	21	49	32	-	69	28	27
26.Liam Paninski	26	28	20	48	6	104	32	24
27.Danielle S. Bassett	27	9	64	56	-	37	10	11
28.Wulfram Gerstner	28	20	37	50	9	60	19	19
29.Daniel M. Wolpert	29	10	95	8	-	22	25	112
30.Pieter R. Roelfsema	30	23	30	55	-	101	26	23
31.Surya Ganguli	31	35	13	54	-	126	36	29
32.P. A. Robinson	32	29	9	87	-	124	13	10
33.Richard Miles	33	33	16	22	13	128	61	43
34.Greg Wayne	34	65	5	21	-	148	80	67
35.Robert C. Wilson	35	31	24	83	-	125	16	21
36.Claudia Clopath	36	49	27	41	8	108	35	42
37.Daniel Yamins	37	58	41	18	-	109	47	50
38.Sander Nieuwenhuis	38	30	47	95	5	96	4	35
39.Peter E. Latham	39	46	38	44	-	130	45	47
40.Rafał Bogacz	40	43	29	67	-	135	40	41
41.Ádám Kepecs	41	44	53	26	-	133	64	60
42.Henry D. I. Abarbanel	42	34	65	53	-	94	24	22
43.Kenneth D. Miller	43	47	46	34	-	134	58	53
44.Blake A. Richards	44	60	14	72	-	151	56	61
45.Birte U. Forstmann	45	32	67	68	-	127	31	31
46.Fred Rieke	46	36	62	71	-	129	30	34
47.Adam Marblestone	47	76	7	43	12	156	77	78
48.Grace W. Lindsay	48	92	6	40	-	172	91	91
49.Anne Collins	49	59	35	76	-	154	53	57
50.Danijar Hafner	50	83	10	61	-	170	85	83

Showing 50 / 185 scholars | M-Index data: 20 | Click headers to sort

Full Scholar Directory

Scholar Directory

Rank	Name ↕	Citations ↓	H-Index ↕	Publications ↕	Institution ↕	Category
1	Yoshua Bengio DZ	479,505	187	1290	Centre Universitaire de Mila	Computational Neuroscience
2	Karl Friston GB	296,123	259	2051	King's College London	Computational Neuroscience
3	Stephen M. Smith	263,905	0	0	WIN (FMRIB)	Network Neuroscience
4	Anders M. Dale	224,519	0	0	President	Computational Neuroscience
5	Terrence J. Sejnowski US	187,381	153	1002	Francis Crick Professor	Computational Neuroscience
6	Jonathon Shlens	175,314	0	0	Principal Scientist and Director	AI & Machine Learning
7	Klaus-Robert Müller	172,217	0	0	TU Berlin & Korea University & Google DeepMind	AI & Machine Learning
8	Joshua B. Tenenbaum US	139,379	114	932	MIT	Computational Neuroscience
9	Christof Koch US	137,783	160	1100	Ohio Northern University	AI & Machine Learning
10	Eero P Simoncelli	132,788	0	0	Professor of Neural Science	Visual Neuroscience
11	Tim Behrens	128,893	0	0	Professor of Computational Neuroscience	Computational Neuroscience
12	Edmund T Rolls	126,138	0	0	Oxford Centre for Computational Neuroscience	Visual Neuroscience
13	Olaf Sporns	125,492	112	501	Distinguished Professor	Computational Neuroscience
14	Vinod Menon	106,291	0	0	Professor of Psychiatry	Cognitive Neuroscience
15	Christos H Papadimitriou	102,049	0	0	Columbia University	Computational Neuroscience
16	Matthew Botvinick	101,163	0	0	Google DeepMind	AI & Machine Learning
17	Stephen Grossberg	89,143	0	0	Wang Professor	Cognitive Neuroscience
18	Mark Woolrich	88,364	0	0	Director	AI & Machine Learning
19	Peter Dayan DE	87,112	117	998	Max Planck Institute for Biological Cybernetics	Computational Neuroscience
20	Jean-Jacques Slotine	82,313	0	0	MIT	Motor Control

Showing 1 to 20 of 185 Scholars

Page 1 of 10

Methodology & Data Notes

Data Source

Scholar data retrieved from OpenAlex API, filtering by the Computational Neuroscience concept (ID: C15286952). Data includes citation counts, h-index, publication counts, and institutional affiliations.

Caveats

Cross-disciplinary researchers may have inflated metrics
Tool/method developers typically have higher citation counts
H-index varies significantly across sub-fields
Academic age is not factored into raw metrics