Weifu Wang, Devin Balkcom, Amit Chakrabarti: 
A fast online spanner for roadmap construction. 
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Matthew P. Bell, Weifu Wang, Jordan Kunzika, Devin Balkcom: 
Knot-tying with four-piece fixtures. 
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Jamshed Bharucha (2019). From passive to active learning. India Today (August).

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Bharucha, J. (2013). Education in South Asia: Time bomb or silver bullet? In A. Najam & M. Yusuf (Eds.), South Asia 2060: Envisioning Regional Futures. NY: Anthem Press.

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Bharucha, J. (2009). From frequency to pitch, and from pitch class to musical key: Shared principles of learning and perception. Connection Science, 21, 177-192.

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Songyun Tao, Yong Hoon Chung, Yijing Feng, Shirin Amouei, Michael Casey, Viola S. Stoermer, Elizabeth L. Murnane. MusicalPT: Augmenting Physical Therapy by Integrating Adaptive Musical Guidance to Enhance Exercise Quality and Patient Experience, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 9, Issue 3, 2025

Casey, M. Auditory Neural Decoding of Music Perception and Imagination, NSF Telluride Neuromorphic Cognition Engineering Workshop, July, 2025.

Feng, Y. and Casey, M., Phrase-Level Symbolic Music Generation, AI and Music Creativity (AIMC 2024), University of Oxford, Sep. 2024.

Keating, M. and Casey, M., Jazz Guitar Voice-Leading Chord Fingerings With Long Short-Term Memory, AI and Music Creativity (AIMC 2024), University of Oxford, Sep. 2024.

Bates, K., Kanishcheva, A., Casey, M., and Jobst, B. "Music and Epilepsy: Studying the Effects of Mozart's Sonata K. 448 on the Epileptic Brain", Ch. 20 in Neurobiology of Creativity, Cambridge University Press, 2024

Paulsen, S. and Casey, M., Self-Supervised Pretraining for Improved Downstream Decoding of Audio-Evoked fMRI Sequences, 4th Workshop on Self-Supervised Learning: Theory and Practice, Neural Information Processing Systems 2023, New Orleans, December 2023

Paulsen, S. and Casey, M., Improved Decoding of Audio-Evoked fMRI Sequences with Sequential Transfer Learning, Workshop: Neurips meets Medical Imaging, Neural Information Processing Systems 2023, New Orleans, December 2023

Quon, R.J., Strýček, O., Ettinger, A.B., Casey, M.A., Rektor, I., Jobst, B.C. (2023). "Music for Epilepsy". In: Devlin, K., Kang, K., Pantelyat, A. (eds) Music Therapy and Music-Based Interventions in Neurology. Current Clinical Neurology. Humana, Cham, 2023

May, L., Halpern, A., Paulsen, S., and Casey, M. Imagined Scale Relationships Decoded from Auditory Cortex. Journal of Cognitive Neuroscience, 34(8), July 1, 2022.

Feng, Y. and Casey, M. Evoked Responses to Note Onsets and Phrase Boundaries in Mozart's K448, Scientific Reports, 10 June, 2022.

Casey, M., Quon, R., and Jobst, B., Eliciting neural mechanisms of music medicine for epilepsy, Interdisciplinary Science Reviews, 47:1, March 24, 2022

Quon, R., Casey, M., Jobst, B., et al. Musical Components Important for the Mozart K448 Effect in Epilepsy, Scientific Reports, September 16, 2021.

Chew, E., ..., Casey, M., Lambiase, P., et al. How Music Can Literally Heal the Heart, Scientific American, September 18, 2021.

May, L. and Casey, M, Decoding Imagined Sound, in Paulo C. Chagas and Cecilia Wu (Eds.), Sounds From Within: Phenomenology and Practice, Springer Humanities, 2021.

Quon RJ, ..., Casey MA, Jobst BC. 40-Hz auditory stimulation for intracranial interictal activity: A pilot study. Clinical Trial, Acta Neurologica Scan. 2021

Jasinski, E.C., & Coch, D. (2012). ERPs across arithmetic operations in a delayed answer verification task. Psychophysiology, 49, 943-958. doi: 10.1111/j.1469-8986.2012.01378.x (Senior Honors Thesis, Emily Jasinski '10)

George, E., & Coch, D. (2011). Music training and working memory: an ERP study. Neuropsychologia, 49(5), 1083-1094. doi: 10.1016/j.neuropsychologia.2011.02.001 (Senior Honors Thesis, Elyse George '09)

Berger, N.I., & Coch, D. (2010). Do u txt? Event-related potentials to semantic anomalies in standard and texted English. Brain and Language, 113, 135-148. doi:10.1016/j.bandl.2010.02.002 (Senior Honors Thesis, Natalie Berger '09)

Mitra, P., & Coch, D. (2009). A masked priming ERP study of letter processing using single letters and false fonts. Cognitive, Affective, and Behavioral Neuroscience, 9, 216-228. doi: 10.3758/CABN.9.2.216 (Senior Honors Thesis, Priya Mitra '08)

Coch, D., Michlovitz, S.A., Ansari, D., & Baird, A. (2009). Building mind, brain, and education connections: the view from the Upper Valley. Mind, Brain, and Education, 3(1), 27-33. doi: 10.1111/j.1751-228X.2008.01050.x

Ansari, D., & Coch, D. (2006). Bridges over troubled waters: education and cognitive neuroscience. Trends in Cognitive Sciences, 10(4), 146-151. doi:10.1016/j.tics.2006.02.007

Hokenmaier W, Jurasek R, Bowen E, Granger R, Odom D (2024)  Co-design of a novel CMOS highly parallel, low-power, multi-chip neural network accelerator.  IEEE Microelectronics Design & Test Symposium (MDTS).    

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Pathak A, Brincat SL, Organtzidis H, Strey HH, Senneff S, Antzoulatos EG, Mujica-Parodi LR, Miller EK, Granger R  (2023) Biomimetic model of corticostriatal micro-assemblies discovers new neural code.  

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Bowen E, Granger R, Rodriguez A (2023)  A logical re-conception of neural networks: Hamiltonian bitwise part-whole architecture.  American Assoc Artificial Intelligence (AAAI)  https://openreview.net/forum?id=hP4dxXvvNc8 

Bowen E, Granger R (2023) Multi-core processing and memory arrangement. US Patent # 11,741,043 B2 (20 claims).  

Granger R, Bowen E, Rodriguez A, Felch A (2023) Computer-implemented perceptual apparatus.  US Patent # 11,693,372 B2 (6 claims). 

Bowen E, Rodriguez A, Sowinski D, Granger R (2022) Visual stream connectivity predicts assessments of image quality.  Journal of Vision, 22(11):4, 1-22.   https://doi.org/10.1167/jov.22.11.4   

Childers E, Bowen E, Rhodes CH, Granger R (2022) Immune-related genomic schizophrenic subtyping identified in DLPFC transcriptome.  Genes,   https://doi.org/10.3390/genes13071200     

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Rodriguez A, Granger R (2015) The grammar of mammalian brain capacity. Theoretical Computer Science C (TCS-C).  doi: 10.1016/j.tcs.2016.03.021

 Lee Y, Janata P, Frost C, Martinez Z, Granger R (2014) Melody recognition revisited: influence of melodic gestalt on the encoding of relational pitch information. Psychonomic Bulletin & Review, 1-7.  doi: 10.3758/ s13423-014-0653-y

Fogelson S, Kohler P, Miller K, Granger R, Tse P (2014) Unconscious neural processing differs with method used to render stimuli invisible. Frontiers in Psychol., 5: 601. doi: 10.3389/fpsyg.2014.00601

Chandrashekar A, Torresani L, Granger R (2013) Learning what is where from unlabeled images: joint localization and clustering of foreground objects. Machine Learning, doi: 10.1007/s10994-013-5330-2

Lee Y, Turkeltaub P, Granger R, Raizada R (2012) Categorical speech processing in Broca's area: An fMRI study using multivariate pattern-based analysis. J Neurosci, 32: 3942-3948.

Chandrashekar A, Granger R (2012) Derivation of a novel efficient supervised learning algorithm from cortical-subcortical loops. Frontiers Comput Neurosci., 5: 50. doi: 10.3389/fncom.2011.00050

Granger R (2011). How brains are built: Principles of computational neuroscience. Cerebrum; The Dana Foundation. http://dana.org/news/cerebrum/detail.aspx?id=30356

Moorkanikara J, Felch A, Chandrashekar A, Dutt N, Granger R, Nicolau A, Veidenbaum A. (2009) Brain-derived vision algorithm on high-performance architectures. Int'l Journal of Parallel Prog., 37: 345-369. 

Lee Y, Granger R, Raizada R (2009) Distributed and overlapping neural representations of the /ba/ - /da/ phonetic contiuum: Comparison of multivoxel pattern-based analysis against adaptation-fMRI. NeuroImage, 47: S129.

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Granger R (2006) Engines of the Brain: The computational instruction set of human cognition. AI Magazine 27:15-32. 

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Haxby, J. V. , Guntupalli, J. S. , Connolly, A. C. , Halchenko, Y. O. , Conroy, B. R., Gobbini, M. I. , Hanke, M. and Ramadge, P. J. (2011). A Common, High-Dimensional Model of the Representational Space in Human Ventral Temporal Cortex. Neuron, 72, 404–416. DOI: 10.1016/j.neuron.2011.08.026, cited by: 21

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Connolly, A. C. , Guntupalli, J. S. , Gors, J. , Hanke, M. , Halchenko, Y. O., Wu, Y. , Abdi, H. and Haxby, J. V. (2012). Representation of biological classes in the human brain. Journal of Neuroscience, 32, 2608–2618. DOI: 10.1523/JNEUROSCI.5547-11.2012,

Haxby, J.V., Connolly, A.C., Guntupalli, J.S. (2014). Decoding neural representational spaces using multivariate pattern analysis. Annual Review of Neuroscience, 37, 435-456.

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Haxby JV, Gobbini MI, Nastase SA.  (2020). Naturalistic stimuli reveal a dominant role for agentic action in visual representation.  Neuroimage, 216, 116561. https://doi.org/10.1016/j.neuroimage.2020.116561

Haxby JV, Guntupalli JS, Nastase SA, Feilong M.  (2020). Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies.  eLife, 9, e56601. doi: https://doi.org/10.7554/eLife.56601

Feilong M, Guntupalli JS, Haxby JV.  (2021). The neural basis of intelligence in fine-grained cortical topographies.  eLife, 10, e64058.  DOI: 10.7554/eLife.64058

Visconti di Oleggio Castello M, Haxby JV, Gobbini MI. (2021).Shared neural codes for visual and semantic information about familiar faces in a common representational space. Proceedings of the National Academy of Sciences, USA, 118, e2110474118. https://doi.org/10.1073/pnas.2110474118

Busch EL, Rapuano KM Anderson KM, Rosenberg MD, Watts R, Casey BJ, Haxby JV, Feilong M. (2023). Dissociation of reliability, heritability, and predictivity in coarse-and fine-scale functional connectomes during development. Journal of Neuroscience.  https://doi.org/10.1523/JNEUROSCI.0735-23.2023

Feilong M, Nastase SA, Jiahui G, Halchenko YO, Gobbini MI, Haxby JV.  (2023).The Individualized Neural Tuning Model: Precise and generalizable cartography of functional architecture in individual brains. Imaging Neuroscience, 1, 1-34. https://doi.org/10.1162/imag_a_00032

Jiahui G, Feilong M, Visconti di Oleggio Castello M, Nastase SA, Haxby JV, Gobbini MI. (2023). Modeling naturalistic face processing in humans with deep convolutional neural networks. Proceedings of the National Academy of Sciences, USA, 120, e2304085120. https://doi.org/10.1073/pnas.2304085120.

Jiahui G, Feilong M, Nastase SA, Haxby JV, Gobbini MI.  (2023). Cross-movie prediction of individualized functional topography. eLife, 12, e86037.  https://doi.org/10.7554/eLife.86037

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Saxe, R., & Houlihan, S. D. (2017). Formalizing emotion concepts within a Bayesian model of theory of mind. Current Opinion in Psychology, 17, 15–21. https://doi.org/10.1016/j.copsyc.2017.04.019.

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Xu X, Zhu Z, Zheng X, Manning JR (2024) The psychological arrow of time drives temporal asymmetries in inferring unobserved past and future events. Nature Communications: in press.

Fitzpatrick PC, Heusser AC, Manning JR (2024). Text embedding models yield high-resolution insights into conceptual knowledge from short multiple-choice quizzes. PsyArXiv: 10.31234/osf.io/dh3q2.

Manning (2023) Identifying stimulus-driven activity patterns in multi-patient intracranial recordings.  In Axmacher N, Ed. Intracranial EEG for Cognitive Neuroscience. New York, NY: Springer.  Chapter 48.

Manning JR, Notaro GM, Chen E, Fitzpatrick PC (2022) Fitness tracking reveals task-specific associations between memory, mental health, and exercise. Scientific Reports: 12(13822): doi.org/10.1038/s41598-022-17781-0.

Owen LLW, Chang TH, Manning JR (2021) High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns. Nature Communications, 12(5728): doi.org/10.1038/s41467-021-25876-x.

Manning JR (2021) Episodic memory: mental time travel or a quantum 'memory wave' function? Psychological Review, 128(4): 711—725.

Chang LJ, Jolly E, Cheong JH, Rapuano K, Greenstein N, Chen P-HA, Manning JR (2021) Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience. Science Advances, 7(17): doi.org/10.1126/sciadv.abf7129.

Heusser AC, Fitzpatrick PC, Manning JR (2021) Geometric models reveal behavioral and neural signatures of transforming naturalistic experiences into episodic memories. Nature Human Behaviour: https://doi.org/10.1038/s41562-021-01051-6.

Owen LLW, Muntianu TA, Heusser AC, Daly P, Scangos KW, Manning JR (2020) A Gaussian process model of human electrocorticographic data. Cerebral Cortex, 30(10): 5333—5345.

Heusser AC, Ziman K, Owen LW, Manning JR (2018) HyperTools: A Python toolbox for gaining geometric insights into high-dimensional data. Journal of Machine Learning Research, 18(152): 1 - 6.

Mills, T., & Phillips, J. (2023). Locating what comes to mind in empirically derived representational spaces. Cognition, 240, 105549.

Phillips, J., & Plunkett, D. (2023). Are there really any dual‐character concepts?. Philosophical Perspectives, 37(1), 340-369.

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