Welcome to the

Brain Science Laboratory

../../Brain%20Networks%20Project/*CCN/CCN_photo_crop.jpg    ../../Brain%20Networks%20Project/*fens/cocomac2.jpeg

@ Hobart & William Smith Colleges

Daniel J. Graham, PI

Associate Professor

Department of Psychology

Hobart and William Smith Colleges

Geneva, NY 14456 USA

Email: artstats  a@t  gmail  d0t  com   -or-   mylastname@hws.edu


CV (July 2018) available here


“The best thing that we're put here for's to see.”  - Robert Frost (from The Star-Splitter)

Research Summary


The research program of the Brain Science Laboratory at HWS investigates human and mammal brains from a variety of perspectives. We use computational, behavioral, and theoretical approaches and focus especially on vision coding. One ongoing strand of work focuses on natural, aesthetic, and artistic stimuli and their processing and creation. In tandem, I collaborate with Yan Hao (Math & CS) to investigate the fundamental principles of communication among neurons in mammal brains. In particular, my multiple strands of research focus on: 


(1)          principles of efficient processing of natural scenes, artwork, and faces in the visual stream

(2)          models and mechanisms in neuroaesthetics

(3)          network dynamics in the neocortex and at the whole brain level


Tying all of these strands together is the notion of efficiency: neural systems are shaped by evolutionary adaptation, which tends to produce solutions that are well matched to environmental demands. However, efficiency is not simply about using the smallest amount of resources; it also depends on handling and representing information in a way that is useful to the organism. Drawing on notions from information theory in physics, the encoding of environmental stimuli can be rigorously defined and implemented in physiological simulations and computer vision approaches.


·      Publications (click paper title for pdf)  **indicates HWS student co-author




Graham, D. J. and Hao, Y. 2018. A selective diffusion model of brain network activity. Proceedings of the Conference on Cognitive Computational Neuroscience, 1195.




Graham, D. J., 2017. Commentary: Building brains that communicate like machines. Behavioral and Brain Sciences e266, 37-38.


Pugach, C.** Leder, H. and Graham, D. J. 2017. How stable are human aesthetic preferences across the lifespan?. Frontiers in Human Neuroscience 11:289. doi: 10.3389/fnhum.2017.00289.

    This paper is part of a Research Topic I co-edited with Chris Redies and Ed Vessel for Frontiers in Human Neuroscience. See:
How Variable, Stable, or Universal are Aesthetic Preferences?




Graham, D. J., Schwarz, B., Chatterjee, A. and Leder, H. 2016. Preference for luminance histogram regularities in natural scenes Vision Research, 120, 11-21. Supplemental Data




Pugach, C.,** Daley, E.**, Leder, H. and Graham. D. J. 2014. Aesthetic stability in development. In: Proceedings of the International Association for Empirical Aesthetics Biennial Congress 2014, New York, NY. ISBN: 0-692-29396-5.


Graham, D. J. 2014. Routing in the brain. Frontiers in Computational Neuroscience 8:44.


Graham, D. J., Pallett, P. M., Meng, M. and Leder, H. 2014. Representation and aesthetics of the human face in portraiture. Art & Perception, 2(1-2), 75-98.




Graham, D. J. 2013. Integrating holism and reductionism in the science of art perception. Behavioral and Brain Sciences, 36(2), 145-146.


Graham, D. J., Stockinger, S. and Leder, H. 2013 An island of stability: art images and natural scenes—but not natural faces—show consistent aesthetic response in Alzheimer’s-related dementia. Frontiers in Psychology 4:107.




Graham, D. J. 2011. Visual Perception: Lightness in a High Dynamic Range World. Current Biology 21(22), R914-R916.


Graham, D. J. and Rockmore, D. N. 2011. The packet switching brain. Journal of Cognitive Neuroscience, 23 (2), 267-276.


Graham, D. J. and Meng, M. 2011. Artistic representations: clues to efficient coding in human vision. Visual Neuroscience 28, 371-379 [Special Issue on

comparative, ecological and developmental aspects of visual system design and function]


Graham, D. J. and Meng, M. 2011. Altered spatial frequency content in paintings by artists with schizophrenia. i-Perception 2 (1), 1-9.


Graham, D. J., Hughes, J. M., Leder, H. and Rockmore, D. N. 2011. Statistics, vision, and the analysis of artistic style. WIREs Comput. Stat. (Wiley Interdisciplinary Reviews-Computational Statistics) 4, 115–123. doi: 10.1002/wics.197.


Hughes, J. M., Graham, D. J., Jacobsen, C. R. and Rockmore, D. N. 2011. Comparing higher-order spatial statistics and perceptual judgments in the stylometric analysis of art. Proceedings of EUSIPCO 2011 (19th European Signal Processing Conference), Barcelona, ESP.




Graham, D. J. and Redies, C. 2010 Statistical regularities in art: Relations with visual coding and perception. Vision Research 50 (16) 1503-1509.


Hughes, J. M., Graham, D. J. and Rockmore, D. N. Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder. Proceedings of the National Academy of Sciences USA 107, 1279-1283.

MEDIA COVERAGE OF PNAS PAPER: Nature, NPR, BBC, Science News, IEEE Spectrum, Ars Technica, Physics World, NH Union Leader, Valley News, The Dartmouth, Press Release


Graham, D. J., Friedenberg, J. D., Rockmore, D. N. and Field, D. J. 2010. Mapping the similarity space of paintings: image statistics and visual perception. Visual Cognition 18 (4), 559-573.


Graham, D. J., Friedenberg, J. D., McCandless, C. H. and Rockmore, D. N. 2010. Preference for artwork: Similarity, statistics, and selling price. Proc. SPIE: Human Vision and Electronic Imaging 7527, 75271A.


Hughes, J. M., Graham, D. J. and Rockmore, D. N. 2010. Stylometrics of artwork: Uses and limitations. Proc. SPIE: Computer Vision and Image Analysis of Art 7531, 75310C.




Graham, D. J. 2009. Art statistics and visual processing: Insights for Picture Coding. Proceedings of the Picture Coding Symposium 2009, Chicago, IL.


Graham, D. J., Friedenberg, J. D. and Rockmore, D. N. 2009. Efficient visual system processing of spatial and luminance statistics in representational and non-representational art. Proc. SPIE: Human Vision and Electronic Imaging 7240, 72401N.




Graham, D. J. and Field, D. J. 2008. Global nonlinear luminance compression in painted art. Proc. SPIE: Computer Image Analysis in the Study of Art 6810, 68100K.


Graham, D. J. and Field, D. J. 2008. Variations in intensity statistics for representational and abstract art, and for art from the eastern and western hemispheres. Perception 37, 1341-1352.


Graham, D. J. and Field, D. J. 2008. Natural images: coding efficiency. In Encyclopedia of Neuroscience ed. Larry R. Squire. Academic Press, Oxford.



2004 - 2007


Graham, D. J. and Field, D. J. 2007. Statistical regularities of art images and natural scenes: Spectra, sparseness and nonlinearities. Spatial Vision 21, 149-164.


Graham, D. J., Chandler, D. M. and Field, D. J. 2006. Can the theory of "whitening" explain the center-surround properties of retinal ganglion cell receptive fields? Vision Research 46, 2901-2913.


Graham, D. J. and Field, D. J. 2006. Sparse coding in the neocortex. In Evolution of Nervous Systems ed. Jon H. Kaas and Leah A. Krubitzer. Elsevier, Vol. III, pp. 181-187.


Cuesta-Lopez, S., Peyrard, M. and Graham, D. J. 2005. Model for DNA hairpin denaturation. European Physical Journal E-Soft Matter 16, 235-246.



·      Theses


Graham, D. J. 2008. The relationship between efficient coding of natural scenes in the human visual system and statistical regularities in art. Doctoral Thesis, Department of Psychology, Cornell University.


Graham, D. J. 2004. Efficient retinal ganglion cell coding and the statistics of natural scenes. Master's Thesis, Department of Physics, Cornell University.



·      Book Reviews


Graham, D. J. 2012 Evolution’s Witness. Perception 41, 755-756.


Graham, D. J. 2012 The Evolution of the Eye from Algae and Jellyfish to Humans. Perception 41, 626-627.


Graham, D. J. 2004. In the Blink of an Eye. American Paleontologist 12, 13-17.


·      Selected Conference Abstracts


Graham, D. J. and Hao, Y. (2018, July). Sparseness and message loss in simulated packet-switching primate brain networks. Federation of European Neuroscience Societies Forum, Berlin, DE.


Hao, Y. and Graham, D. J. (2018, June). Simulating efficient routing protocols in primate brain networks. International Conference of Mathematical Neuroscience, Juan-les-Pins, FR.


Teceno, D.** and Graham, D. J. (2017, May) Aesthetic stability in non-elderly adults with brain injury: A pilot study. Association for Psychological Science, Boston, MA.


Prescott, N.** and Graham, D. J. (2017, March) The visual neuroscience of masks. Eastern Psychological Association, Boston, MA.


Graham, D. J., Schwarz, B., Chatterjee, A., and Leder, H. (2013, May). Preference for higher-order luminance regularities in natural scenes. Vision Sciences Society, Naples, FL.


Graham, D. J. and Meng, M. (2011, May). Lightness perception in artists. Vision Sciences Society 2011, Naples, FL.


Graham, D. J., Friedenberg, J. D. and Rockmore, D. N. (2009, August) Mathematics, Perception, and the Visual Arts: New Perspectives, talk at MathPsych 2009 (Society for Mathematical Psychology).


Graham, D. J., Friedenberg, J. D., Rockmore, D. N. and Field, D. J. (2008, August) Mapping the similarity space of paintings: Is there a role for image statistics? ECVP 2008 Utrecht, NL.


Graham, D. J. and Field, D. J. (2008, January) Global nonlinear compression of natural luminances in painted art. SPIE Electronic Imaging Conference on Computer Image Analysis in the Study of Art, San Jose CA.


Cutting, J. E., Graham, D. J. and Field, D. J. (2008, March) From a neuroesthetics to a neuroarthistory. Annual Conference of the College Art Association, Dallas TX.


Graham, D. J., Page, K. B. and Field, D. J. (2006, August) Relating nonlinearities to statistical regularities in paintings. Perception 35 supplement for ECVP.


Graham, D. J. Chandler, D. M. and Field, D. J. (2005, August) How alike are natural scenes and paintings? Characterizing the spatial statistical properties of a set of digitized, grey-scale images of painted art.  Perception 34 supplement for ECVP.


Graham, D. J., Chandler, D. M. and Field, D. J. 2004. Decorrelation and response equalization with center-surround receptive fields. Journal of Vision 4, 276a.



·      Invited Talks


Introduction to Visual Stylometry: A Neuroscientific Perspective, WAIVS (Workflows for Analysis of Images in Visual Stylometry), Fitchburg Art Museum, Fitchburg MA USA, May, 2017.


Face Representation in Portraiture and Masks, Eastern American Society for Aesthetics Annual Meeting, April 2016.


The Packet Switching Brain: A Hypothesis, Redwood Neuroscience Institute Seminar, University of California, Berkeley, Nov 2009.  VIDEO.


The Efficient Artist: Statistical Regularities in Art and Their Relationships with Visual Coding, Oxyopia Lecture Series, University of California, Berkeley, School of Optometry, Nov 2009. VIDEO.


Art and Efficient Visual Representation, Colloquium Speaker, Department of Mathematics, Middlebury College, Sept 2009.


Invited Panelist, Special Session on Visual Attention, Artistic Intent and Efficient Coding, Picture Coding Symposium, Chicago, IL, May 2009.


Stylometric analysis of Van Gogh using methods inspired by early visual system neural coding. Van Gogh Museum, Amsterdam, Netherlands, Oct 2008. (part of IP4AI)


Statistical Regularities in Paintings: Connections to Visual Coding and Perception, Friedrich-Schiller-University, Jena, Germany, Sept 2008.


Relationships Between Human Visual Coding and Painted Art, Applied and Computational Mathematics Seminar, Dartmouth College, Feb 2008.


The Illuminated World: Art and the Visual System, Art for Lunch, Herbert F. Johnson Museum of Art, Cornell University, April 2007.



·      Teaching


·       In Fall, I typically teach PSY 100: Introduction to Psychology and PSY 309: Topics in Sensory Perception (Focus on Art and Human Vision). In Spring, I typically teach Sensation and Perception (PSY 299) and Research in Sensory Perception (PSY 310).


·       We are always looking for motivated HWS students to work in the lab! Contact Prof. Graham if you are interested in an RA opportunity, independent study, or summer science.



·      Support and Awards


2008-2009: William H. Neukom 1964 Institute for Computational Science


2008-2010: National Science Foundation Small Grant for Exploratory Research DMS-0746667 (to D. Rockmore)


2007: Provost’s Diversity Fellowship, Cornell University


2004-2007: National Institutes of Health Kirschstein-NRSA Traineeship (Individual) EY015393


2002: NSF Locnet Fellowship, Ecole Normale Superieure, Lyon, France


2001-2004: NSF IGERT Program in Nonlinear Dynamics Fellowship, Cornell University



·      Writing for Non-scientists


I was the lead scientific researcher of a book for general audiences about e-mail and communication, Send, by David Shipley and Will Schwalbe (Knopf). See thinkbeforeyousend.com

Now in a revised edition.




·      Links


Noah Graham  (my brother) studies quantum mechanics and teaches physics at my alma mater, Middlebury College.



Updated 7 Sept 2018