Read Montague

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Pendleton Read Montague, Jr.
Born1960 (age 63–64)
Education Auburn University
University of Alabama at Birmingham
Known for Temporal difference learning
Parents
  • Pendleton Read Montague, Sr. [1] (father)
  • Ann Montague (mother)
Scientific career
Fields Neuroscience
Institutions Baylor College of Medicine
Virginia Tech
University College London
Thesis An application of fractal sets to the analysis of neuritic patterns of cultured cat retinal ganglion cells  (1988)
Doctoral advisor Michael Friedlander
Other academic advisors Terry Sejnowski
Gerald Edelman
Doctoral students David Eagleman

Pendleton Read Montague, Jr. (born 1960) is an American neuroscientist and popular science author. He is the director of the Human Neuroimaging Lab and Computational Psychiatry Unit at the Fralin Biomedical Research Institute at VTC in Roanoke, Virginia, where he also holds the title of the inaugural Virginia Tech Carilion Vernon Mountcastle Research Professor. Montague is also a professor in the department of physics at Virginia Tech in Blacksburg, Virginia and professor of Psychiatry and Behavioral Medicine at Virginia Tech Carilion School of Medicine.

Contents

Education

In 1978 Montague graduated high school from The Lovett School in Atlanta, Georgia. From 1978–1979, Montague studied electrical engineering at Georgia Tech. He then continued his undergraduate education at Auburn University, graduating in 1983 with a bachelor's degree in mathematics. In 1988, he earned a Ph.D. in biophysics from the University of Alabama at Birmingham School of Medicine. He continued his training with a fellowship in theoretical neurobiology at The Neurosciences Institute at Rockefeller University. After completion of that fellowship, he completed another fellowship in the Computational Neurobiology Lab at The Salk Institute for Biological Studies.

Career

Montague is the director of the Center for Human Neuroscience Research, the Human Neuroimaging Lab, the Human Magnetometry Lab, and the Computational Psychiatry Unit at the Fralin Biomedical Research Institute in Roanoke, Virginia, where he also holds the title of the inaugural Virginia Tech Carilion Vernon Mountcastle Research Professor. Montague is also a professor in the department of physics at Virginia Tech in Blacksburg, Virginia, a professor of Psychiatry and Behavioral Medicine at Virginia Tech Carilion School of Medicine and holds an appointment as Honorary Professor at The Wellcome Trust Centre for Neuroimaging at University College London.

From 2011-2018, Montague was a Wellcome Trust Principal Research Fellow at The Wellcome Centre for Human Neuroimaging, University College London. Before moving to the Fralin Biomedical Research Institute, Montague was the Brown Foundation Professor of neuroscience at Baylor College of Medicine, founding director of the Human Neuroimaging Lab, and founding director in 2006 of the Computational Psychiatry Unit. He was also a professor in the Menninger Department of Psychiatry and Behavioral Sciences at Baylor College of Medicine.

Research

Montague’s work has long focused on computational neuroscience – the connection between physical mechanisms present in real neural tissue and the computational functions that these mechanisms embody. His early theoretical work focused on the hypothesis that dopaminergic systems encode a particular kind of computational process, a reward prediction error signal, similar to those used in areas of artificial intelligence like optimal control. This work, carried out in collaboration with Peter Dayan and Terry Sejnowski, focused on prediction as a guiding concept in terms of synaptic learning rules that would underlie learning, [2] [3] [4] [5] [6] valuation, [7] and choice. [8] This work proposed a modification to the then dominant idea of Hebbian or correlational learning. [2] In particular, it was shown that dopamine neurons and homologous octopaminergic neurons in bees display a reward prediction error signal exactly consonant with the temporal difference error signal [7] [6] familiar from models of conditioning proposed by Sutton and Barto during the 1980s.

In pursuit of testing these prediction error ideas in humans, Montague founded the Human Neuroimaging Lab at Baylor College of Medicine in Houston, Texas, and pursued functional neuroimaging experiments analogous to those used in other model species. This work tested the reward prediction error model in human subjects using simple conditioning experiments directly analogous to those used in rodents and non-human primates. [9] [10] [11] [12] [13] His group then tested the reward prediction error idea during an abstract task of social exchange between two interacting humans [14] and showed striatal BOLD signals that changed their timing consistent with a prediction error signal, but in the context of a social exchange. They also tested the idea of cultural brand identity and its impact on reward prediction error signals. [15] With Brooks King-Casas and colleagues, Montague later applied the same social exchange approach in participants with Autism [16] Borderline Personality Disorder [17] . These and other papers [18] [19] [20] helped establish the field of computational psychiatry [21] [22] .

Montague and colleagues have further investigated the computational nature of dopamine as well as serotonin signals by making the first measurements of sub-second dopamine, serotonin, and noradrenaline fluctuations in the striatum of conscious human subjects. [23] [24] [25] [26] [27] [28]

Montague has written a nonfiction work aimed at lay audiences entitled Why Choose This Book?: How We Make Decisions. The book discusses with (mostly) non-technical language the neuroscience and psychology of decision making.

Montague also gave a TED Global Talk [29]  in 2012 where he explained how functional MRI has opened a window on the neural basis of human social interaction and how such approaches may open a window on the neural basis of social disorders. He specifically spoke about how real-time imaging allows researchers to examine the complicated neural underpinnings of human interaction.

Awards and honors

Writings

Related Research Articles

<span class="mw-page-title-main">Striatum</span> Nucleus in the basal ganglia of the brain

The striatum or corpus striatum is a nucleus in the subcortical basal ganglia of the forebrain. The striatum is a critical component of the motor and reward systems; receives glutamatergic and dopaminergic inputs from different sources; and serves as the primary input to the rest of the basal ganglia.

<span class="mw-page-title-main">Dopamine</span> Organic chemical that functions both as a hormone and a neurotransmitter

Dopamine is a neuromodulatory molecule that plays several important roles in cells. It is an organic chemical of the catecholamine and phenethylamine families. Dopamine constitutes about 80% of the catecholamine content in the brain. It is an amine synthesized by removing a carboxyl group from a molecule of its precursor chemical, L-DOPA, which is synthesized in the brain and kidneys. Dopamine is also synthesized in plants and most animals. In the brain, dopamine functions as a neurotransmitter—a chemical released by neurons to send signals to other nerve cells. Neurotransmitters are synthesized in specific regions of the brain, but affect many regions systemically. The brain includes several distinct dopamine pathways, one of which plays a major role in the motivational component of reward-motivated behavior. The anticipation of most types of rewards increases the level of dopamine in the brain, and many addictive drugs increase dopamine release or block its reuptake into neurons following release. Other brain dopamine pathways are involved in motor control and in controlling the release of various hormones. These pathways and cell groups form a dopamine system which is neuromodulatory.

<span class="mw-page-title-main">Basal ganglia</span> Group of subcortical nuclei involved in the motor and reward systems

The basal ganglia (BG) or basal nuclei are a group of subcortical nuclei found in the brains of vertebrates. In humans and other primates, differences exist, primarily in the division of the globus pallidus into external and internal regions, and in the division of the striatum. Positioned at the base of the forebrain and the top of the midbrain, they have strong connections with the cerebral cortex, thalamus, brainstem and other brain areas. The basal ganglia are associated with a variety of functions, including regulating voluntary motor movements, procedural learning, habit formation, conditional learning, eye movements, cognition, and emotion.

Computational neuroscience is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.

The mesolimbic pathway, sometimes referred to as the reward pathway, is a dopaminergic pathway in the brain. The pathway connects the ventral tegmental area in the midbrain to the ventral striatum of the basal ganglia in the forebrain. The ventral striatum includes the nucleus accumbens and the olfactory tubercle.

Neuroeconomics is an interdisciplinary field that seeks to explain human decision-making, the ability to process multiple alternatives and to follow through on a plan of action. It studies how economic behavior can shape our understanding of the brain, and how neuroscientific discoveries can guide models of economics.

<span class="mw-page-title-main">Nucleus accumbens</span> Region of the basal forebrain

The nucleus accumbens is a region in the basal forebrain rostral to the preoptic area of the hypothalamus. The nucleus accumbens and the olfactory tubercle collectively form the ventral striatum. The ventral striatum and dorsal striatum collectively form the striatum, which is the main component of the basal ganglia. The dopaminergic neurons of the mesolimbic pathway project onto the GABAergic medium spiny neurons of the nucleus accumbens and olfactory tubercle. Each cerebral hemisphere has its own nucleus accumbens, which can be divided into two structures: the nucleus accumbens core and the nucleus accumbens shell. These substructures have different morphology and functions.

<span class="mw-page-title-main">Dopaminergic pathways</span> Projection neurons in the brain that synthesize and release dopamine

Dopaminergic pathways in the human brain are involved in both physiological and behavioral processes including movement, cognition, executive functions, reward, motivation, and neuroendocrine control. Each pathway is a set of projection neurons, consisting of individual dopaminergic neurons.

<span class="mw-page-title-main">Ventral tegmental area</span> Group of neurons on the floor of the midbrain

The ventral tegmental area (VTA), also known as the ventral tegmental area of Tsai, or simply ventral tegmentum, is a group of neurons located close to the midline on the floor of the midbrain. The VTA is the origin of the dopaminergic cell bodies of the mesocorticolimbic dopamine system and other dopamine pathways; it is widely implicated in the drug and natural reward circuitry of the brain. The VTA plays an important role in a number of processes, including reward cognition and orgasm, among others, as well as several psychiatric disorders. Neurons in the VTA project to numerous areas of the brain, ranging from the prefrontal cortex to the caudal brainstem and several regions in between.

Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods, and perform updates based on current estimates, like dynamic programming methods.

<span class="mw-page-title-main">Habenula</span> Small bilateral neuronal structure in the brain of vertebrates

The habenula is a small bilateral neuronal structure in the brain of vertebrates, that has also been called a microstructure since it is no bigger than a pea. The naming as little rein describes its elongated shape in the epithalamus, where it borders the third ventricle, and lies in front of the pineal gland.

<span class="mw-page-title-main">Orbitofrontal cortex</span> Region of the prefrontal cortex of the brain

The orbitofrontal cortex (OFC) is a prefrontal cortex region in the frontal lobes of the brain which is involved in the cognitive process of decision-making. In non-human primates it consists of the association cortex areas Brodmann area 11, 12 and 13; in humans it consists of Brodmann area 10, 11 and 47.

<span class="mw-page-title-main">Peter Dayan</span> Researcher in computational neuroscience

Peter Dayan is a British neuroscientist and computer scientist who is director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, along with Ivan De Araujo. He is co-author of Theoretical Neuroscience, an influential textbook on computational neuroscience. He is known for applying Bayesian methods from machine learning and artificial intelligence to understand neural function and is particularly recognized for relating neurotransmitter levels to prediction errors and Bayesian uncertainties. He has pioneered the field of reinforcement learning (RL) where he helped develop the Q-learning algorithm, and made contributions to unsupervised learning, including the wake-sleep algorithm for neural networks and the Helmholtz machine.

<span class="mw-page-title-main">Reward system</span> Group of neural structures responsible for motivation and desire

The reward system is a group of neural structures responsible for incentive salience, associative learning, and positively-valenced emotions, particularly ones involving pleasure as a core component. Reward is the attractive and motivational property of a stimulus that induces appetitive behavior, also known as approach behavior, and consummatory behavior. A rewarding stimulus has been described as "any stimulus, object, event, activity, or situation that has the potential to make us approach and consume it is by definition a reward". In operant conditioning, rewarding stimuli function as positive reinforcers; however, the converse statement also holds true: positive reinforcers are rewarding.

Cultural neuroscience is a field of research that focuses on the interrelation between a human's cultural environment and neurobiological systems. The field particularly incorporates ideas and perspectives from related domains like anthropology, psychology, and cognitive neuroscience to study sociocultural influences on human behaviors. Such impacts on behavior are often measured using various neuroimaging methods, through which cross-cultural variability in neural activity can be examined.

Gregory Scott Berns is an American neuroeconomist, neuroscientist, professor of psychiatry, psychologist and writer. He lives with his family in Atlanta, Georgia, US.

In neuroscience, predictive coding is a theory of brain function which postulates that the brain is constantly generating and updating a "mental model" of the environment. According to the theory, such a mental model is used to predict input signals from the senses that are then compared with the actual input signals from those senses. With the rising popularity of representation learning, the theory is being actively pursued and applied in machine learning and related fields.

Ilana B. Witten is an American neuroscientist and professor of psychology and neuroscience at Princeton University. Witten studies the mesolimbic pathway, with a focus on the striatal neural circuit mechanisms driving reward learning and decision making.

Yael Niv is a neuroscientist who studies human and animal reinforcement learning and decision making. She is Professor of Psychology and Neuroscience at Princeton University. Niv is known for her research contributions and for her visible advocacy work fighting against gender bias in neuroscience. Niv is founder of biaswatchneuro.com, a website that tracks statistics in an effort to combat sexism in science.

Wolfram Schultz, is a German professor of Neuroscience at the University of Cambridge known for his research that dopamine neurons signal errors in reward prediction.

References

  1. ↑ "Montague, Pendleton". The Atlanta Journal-Constitution. ISSN   1539-7459 . Retrieved 27 November 2022.
  2. 1 2 Montague, PR; Dayan, P; Nowlan, SJ; Pouget, A; Sejnowski, TJ (1993). "Using Aperiodic Reinforcement for Directed Self-Organization During Development" (PDF). Advances in Neural Information Processing Systems. 5: 969–976.
  3. ↑ Montague, PR; Dayan, P; Sejnowski, TJ (1994a). Foraging in an Uncertain Environment Using Predictive Hebbian Learning (PDF). Vol. 6. pp. 598–605.
  4. ↑ Montague, PR; Sejnowski, TJ. (1994b). "The predictive brain: Temporal coincidence and temporal order in synaptic learning mechanisms" (PDF). Learning and Memory. 1 (1): 1–33. doi:10.1101/lm.1.1.1. PMID   10467583. S2CID   44560099.
  5. ↑ Montague, PR; Gancayco, CD; Winn, MJ; Marchase, RB; Friedlander, MJ. (18 February 1994). "Role of NO production in NMDA receptor-mediated neurotransmitter release in cerebral cortex" (PDF). Science. 263 (5149): 973–977. doi:10.1126/science.7508638. ISSN   0036-8075. PMID   7508638.
  6. 1 2 Montague, PR; Dayan, P; Sejnowski, TJ. (1 March 1996). "A framework for mesencephalic dopamine systems based on predictive Hebbian learning" (PDF). The Journal of Neuroscience. 16 (5): 1936–1947. doi: 10.1523/JNEUROSCI.16-05-01936.1996 . ISSN   0270-6474. PMC   6578666 . PMID   8774460.
  7. 1 2 Montague, PR; Dayan, P; Person, C; Sejnowski, TJ. (26 October 1995). "Bee foraging in uncertain environments using predictive hebbian learning" (PDF). Nature. 377 (6551): 725–728. Bibcode:1995Natur.377..725M. doi:10.1038/377725a0. ISSN   0028-0836. PMID   7477260. S2CID   4324169.
  8. ↑ Schultz, W; Dayan, P; Montague, PR. (14 March 1997). "A neural substrate of prediction and reward" (PDF). Science. 275 (5306): 1593–1599. CiteSeerX   10.1.1.133.6176 . doi:10.1126/science.275.5306.1593. ISSN   0036-8075. PMID   9054347. S2CID   220093382.
  9. ↑ Berns, GS; McClure, SM; Pagnoni, G; Montague, PR. (15 April 2001). "Predictability modulates human brain response to reward" (PDF). The Journal of Neuroscience. 21 (8): 2793–2798. doi: 10.1523/JNEUROSCI.21-08-02793.2001 . ISSN   1529-2401. PMC   6762527 . PMID   11306631.
  10. ↑ Montague, PR; Berns, GS. (10 October 2002). "Neural economics and the biological substrates of valuation" (PDF). Neuron. 36 (2): 265–284. doi:10.1016/s0896-6273(02)00974-1. ISSN   0896-6273. PMID   12383781. S2CID   1814617.
  11. ↑ McClure, SM; Daw, ND; Montague, PR. (1 August 2003). "A computational substrate for incentive salience" (PDF). Trends in Neurosciences. 26 (8): 423–428. doi:10.1016/s0166-2236(03)00177-2. ISSN   0166-2236. PMID   12900173. S2CID   11701048.
  12. ↑ McClure, SM; Berns, GS; Montague, PR. (24 April 2003). "Temporal prediction errors in a passive learning task activate human striatum" (PDF). Neuron. 38 (2): 339–346. doi: 10.1016/s0896-6273(03)00154-5 . ISSN   0896-6273. PMID   12718866.
  13. ↑ Braver, TS; Brown, JW. (2003). "Principles of Pleasure Prediction: Specifying the Neural Dynamics of Human Reward Learning" (PDF). Neuron. 38 (2): 150–152. doi: 10.1016/S0896-6273(03)00230-7 . PMID   12718849 . Retrieved 24 April 2003.
  14. ↑ King-Casas, BB; Tomlin, D; Anen, C; Camerer, CF; Quartz, SR; Montague, PR. (1 April 2005). "Getting to Know You: Reputation and Trust in a Two-Person Economic Exchange" (PDF). Science. 308 (5718): 78–83. Bibcode:2005Sci...308...78K. doi:10.1126/science.1108062. ISSN   0036-8075. PMID   15802598. S2CID   8068031.
  15. ↑ McClure, SM; Li, J; Tomlin, D; Cypert, KS; Montague, LM; Montague, PR. (14 October 2004). "Neural correlates of behavioral preference for culturally familiar drinks" (PDF). Neuron. 44 (2): 379–387. doi: 10.1016/j.neuron.2004.09.019 . ISSN   0896-6273. PMID   15473974.
  16. ↑ Koshelev, M; Lohrenz, T; Vannucci, M; Montague, PR. (21 October 2010). "Biosensor approach to psychopathology classification" (PDF). PLOS Computational Biology. 6 (10): e1000966. Bibcode:2010PLSCB...6E0966K. doi: 10.1371/journal.pcbi.1000966 . ISSN   1553-7358. PMC   2958801 . PMID   20975934.
  17. ↑ King-Casas, B; Sharp, C; Lomax-Bream, L; Lohrenz, T; Fonagy, P; Montague, PR. (8 August 2008). "The Rupture and Repair of Cooperation in Borderline Personality Disorder" (PDF). Science. 321 (5890): 806–810. Bibcode:2008Sci...321..806K. doi:10.1126/science.1156902. ISSN   0036-8075. PMC   4105006 . PMID   18687957.
  18. ↑ Chiu, PH; Lohrenz, TM; Montague, PR. (1 April 2008). "Smokers' brains compute, but ignore, a fictive error signal in a sequential investment task" (PDF). Nature Neuroscience. 11 (4): 514–520. doi:10.1038/nn2067. ISSN   1097-6256. PMID   18311134. S2CID   205431662.
  19. ↑ Chiu, PH; Kayali, MA; Kishida, KT; Tomlin, D; Klinger, LG; Klinger, MR; Montague, PR. (7 February 2008). "Self responses along cingulate cortex reveal quantitative neural phenotype for high-functioning autism" (PDF). Neuron. 57 (3): 463–473. doi:10.1016/j.neuron.2007.12.020. ISSN   0896-6273. PMC   4512741 . PMID   18255038.
  20. ↑ Xiang, T; Ray, D; Lohrenz, T; Dayan, P; Montague, PR. (1 January 2012). "Computational phenotyping of two-person interactions reveals differential neural response to depth-of-thought" (PDF). PLOS Computational Biology. 8 (12): e1002841. Bibcode:2012PLSCB...8E2841X. doi: 10.1371/journal.pcbi.1002841 . ISSN   1553-7358. PMC   3531325 . PMID   23300423.
  21. ↑ Montague, P. Read; Dolan, Raymond J.; Friston, Karl J.; Dayan, Peter (2012). "Computational psychiatry" (PDF). Trends in Cognitive Sciences. 16 (1): 72–80. doi:10.1016/j.tics.2011.11.018. hdl:21.11116/0000-0001-A0F0-A. PMC   3556822 . PMID   22177032.
  22. ↑ Montague, PR (2017). "Computational Phenotypes Revealed by Interactive Economic Games". In Anticevic, Alan; Murray, John D. (eds.). Computational psychiatry: mathematical modeling of mental illness (PDF). Elsevier/AP, Academic Press, an imprint of Elsevier. pp. 273–292. ISBN   978-0-12-809825-7. OCLC   974698920.
  23. ↑ Kishida, Kenneth T.; Sandberg, Stefan G.; Lohrenz, Terry; Comair, Youssef G.; Sáez, Ignacio; Phillips, Paul E. M.; Montague, P. Read (4 August 2011). Zars, Troy (ed.). "Sub-Second Dopamine Detection in Human Striatum" (PDF). PLOS ONE. 6 (8): e23291. Bibcode:2011PLoSO...623291K. doi: 10.1371/journal.pone.0023291 . ISSN   1932-6203. PMC   3150430 . PMID   21829726.
  24. ↑ Kishida, Kenneth T.; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R.; Laxton, Adrian W.; Tatter, Stephen B.; White, Jason P.; Ellis, Thomas L.; Phillips, Paul E. M.; Montague, P. Read (5 January 2016). "Subsecond dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward" (PDF). Proceedings of the National Academy of Sciences. 113 (1): 200–205. Bibcode:2016PNAS..113..200K. doi: 10.1073/pnas.1513619112 . ISSN   0027-8424. PMC   4711839 . PMID   26598677.
  25. ↑ Moran, Rosalyn J; Kishida, Kenneth T; Lohrenz, Terry; Saez, Ignacio; Laxton, Adrian W; Witcher, Mark R; Tatter, Stephen B; Ellis, Thomas L; Phillips, Paul EM; Dayan, Peter; Montague, P Read (2018). "The Protective Action Encoding of Serotonin Transients in the Human Brain" (PDF). Neuropsychopharmacology. 43 (6): 1425–1435. doi:10.1038/npp.2017.304. ISSN   0893-133X. PMC   5916372 . PMID   29297512.
  26. ↑ Bang, Dan; Kishida, Kenneth T.; Lohrenz, Terry; White, Jason P.; Laxton, Adrian W.; Tatter, Stephen B.; Fleming, Stephen M.; Montague, P. Read (2020). "Sub-second Dopamine and Serotonin Signaling in Human Striatum during Perceptual Decision-Making" (PDF). Neuron. 108 (5): 999–1010.e6. doi:10.1016/j.neuron.2020.09.015. PMC   7736619 . PMID   33049201.
  27. ↑ Bang, Dan; Luo, Yi; Barbosa, Leonardo S.; Batten, Seth R.; Hadj-Amar, Beniamino; Twomey, Thomas; Melville, Natalie; White, Jason P.; Torres, Alexis; Celaya, Xavier; Ramaiah, Priya; McClure, Samuel M.; Brewer, Gene A.; Bina, Robert W.; Lohrenz, Terry (2023). "Noradrenaline tracks emotional modulation of attention in human amygdala" (PDF). Current Biology. 33 (22): 5003–5010.e6. doi:10.1016/j.cub.2023.09.074. ISSN   0960-9822. PMC   10957395 . PMID   37875110.
  28. ↑ Batten, Seth R.; Bang, Dan; Kopell, Brian H.; Davis, Arianna N.; Heflin, Matthew; Fu, Qixiu; Perl, Ofer; Ziafat, Kimia; Hashemi, Alice; Saez, Ignacio; Barbosa, Leonardo S.; Twomey, Thomas; Lohrenz, Terry; White, Jason P.; Dayan, Peter (2024). "Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange" (PDF). Nature Human Behaviour. 8 (4): 718–728. doi:10.1038/s41562-024-01831-w. ISSN   2397-3374. PMC   11045309 . PMID   38409356.
  29. ↑ Montague, Read (24 September 2012), What we're learning from 5,000 brains , retrieved 10 February 2021
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