Abstract
How humans make decisions is one of the primary domains of inquiry in psychology. Our ability to make decisions leads to direct consequences in our lives and defines one aspect of autonomous function. Among clinicians and researchers, the pursuit of effective cognitive enhancements and treatments that could directly or indirectly influence our decision processes has become widespread, since many of the neural circuits that we stimulate are involved in autonomous decision-making. Given rapid scientific developments, it is prudent to consider how neuromodulation could affect a person’s ability to make choices and manage trade-offs between decision outcomes. In light of this dilemma, we offer a framework based in decision neuroscience that separates brain networks into decision-making core, volitional action, and moderating systems. This framework bridges bioethics and cognitive neuroscience to provide heuristics for the neural basis of autonomous decision-making. In doing so, we provide a general call to predict and weight risks and benefits of different degrees and kinds with regard to decision-making as increasingly precise neuromodulation techniques emerge.
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Notes
Providing consent can also be a more or less rational decision. Decision-making tasks also allow us to consider various notions of “rationality” by comparing theoretically optimal strategies to real-world behavior. As some researchers have noted, in real life, forced-choice tasks are unlike many natural decisions because we can opt not to participate, either at entry during informed consent or during any portion of the task (Dhar & Simonson, 2003). For our current purposes, forced-choice tasks are simple tasks that elicit some aspects of decision-making after a subject has agreed to participate. In other words, the participant has already completed one superordinate choice in which she has opted to participate in the experimental task, rather than not.
The classic distinction of cognitive versus motor systems is a heuristic that has been challenged from several cognitive-behavioral perspectives, which suggest that no clear distinction between the two is obvious (Rosenbaum, 2005). Here, the distinction is useful because we should study the representations and processes involving decision-making and motor systems to clarify their roles in decision-making.
Incidentally, this treatment is administered to the left dlPFC, which is part of the autonomous decision core.
References
An, J., Lee, S., & Jin, S. (2019). Fully closed-loop neuromodulation approach in real-time. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation, 12, 567.
Aravanis, A. M., et al. (2007). An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology. Journal of Neural Engineering, 4, S143.
Arpaly, N. Which autonomy? Freedom and determinism 173 (2004).
Ashley, E. A. (2015). The precision medicine initiative: a new national effort. Jama, 313, 2119–2120.
Aston-Jones, G., & Cohen, J. D. (2005). An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annual Review of Neuroscience, 28, 403–450.
Barack, P. (2016). Precision medicine and the changing landscape of research ethics. In Oncology nursing forum, 43, 149.
Bassett, D. S., & Sporns, O. (2017). Network neuroscience. Nature Neuroscience, 20, 353.
Bassett, D. S., Zurn, P., & Gold, J. I. (2018). On the nature and use of models in network neuroscience. Nature Reviews Neuroscience, 19, 566.
Belzung, C., Turiault, M., & Griebel, G. (2014). Optogenetics to study the circuits of fear-and depression-like behaviors: a critical analysis. Pharmacology Biochemistry and Behavior, 122, 144–157.
Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J. D. (2006). The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychological Review, 113, 700.
Bogacz, R., Wagenmakers, E.-J., Forstmann, B. U., & Nieuwenhuis, S. (2010). The neural basis of the speed–accuracy tradeoff. Trends in Neurosciences, 33, 10–16.
Boggio, P. S., et al. (2010). Modulation of decision-making in a gambling task in older adults with transcranial direct current stimulation. European Journal of Neuroscience, 31, 593–597.
Borchers, S., Himmelbach, M., Logothetis, N., & Karnath, H.-O. (2012). Direct electrical stimulation of human cortex-the gold standard for mapping brain functions? Nature Reviews Neuroscience, 13, 63.
Brandt, J., et al. (2015). Betting on dbs: effects of subthalamic nucleus deep brain stimulation on risk taking and decision making in patients with Parkinson’s disease. Neuropsychology, 29, 622.
Braver, T. S. (2012). The variable nature of cognitive control: a dual mechanisms framework. Trends in Cognitive Sciences, 16, 106–113.
Brem, A.-K., Fried, P. J., Horvath, J. C., Robertson, E. M., & Pascual-Leone, A. (2014). Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition? Neuroimage, 85, 1058–1068.
Buchanan, A. E. (2011). Beyond humanity?: The ethics of biomedical enhancement. Oxford: Oxford University Press.
Chan, S. & Harris, J. Cognitive regeneration or enhancement: the ethical issues (2006).
Churchland, A. K., Kiani, R., & Shadlen, M. N. (2008). Decision-making with multiple alternatives. Nature Neuroscience, 11, 693.
Cohen, J. D., Aston-Jones, G. & Gilzenrat, M. S. A systems-level perspective on attention and cognitive control: guided activation, adaptive gating, conflict monitoring, and exploitation versus exploration. (2004).
Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B., & Uchida, N. (2012). Neuron-type specific signals for reward and punishment in the ventral tegmental area. Nature, 482, 85.
Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014). Intrinsic and task-evoked network architectures of the human brain. Neuron, 83, 238–251.
Connolly, K. R., Helmer, A., Cristancho, M. A., Cristancho, P., & O’Reardon, J. P. (2012). Effectiveness of transcranial magnetic stimulation in clinical practice post-fda approval in the United States: results observed with the first 100 consecutive cases of depression at an academic medical center. The Journal of Clinical Psychiatry, 73, e567–e573.
Coutlee, C. G., & Huettel, S. A. (2012). The functional neuroanatomy of decision making: prefrontal control of thought and action. Brain Research, 1428, 3–12.
Deci, E. L., Koestner, R. & Ryan, R. M. A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. (1999).
Deisseroth, K. (2011). Optogenetics. Nature Methods, 8, 26–29.
Desmurget, M., et al. (2009). Movement intention after parietal cortex stimulation in humans. Science, 324, 811–813.
Dhar, R., & Simonson, I. (2003). The effect of forced choice on choice. Journal of Marketing Research, 40, 146–160.
Dobson, K. S., & Dozois, D. J. (2019). Handbook of cognitive-behavioral therapies. New York: Guilford Publications.
Ezzyat, Y., et al. (2018). Closed-loop stimulation of temporal cortex rescues functional networks and improves memory. Nature Communications, 9, 1–8.
Farah, M. J. (2015). The unknowns of cognitive enhancement. Science, 350, 379–380.
Fecteau, S., et al. (2007). Activation of prefrontal cortex by transcranial direct current stimulation reduces appetite for risk during ambiguous decision making. Journal of Neuroscience, 27, 6212–6218.
FeldmanHall, O., et al. (2012). What we say and what we do: the relationship between real and hypothetical moral choices. Cognition, 123, 434–441.
Felsen, G., & Reiner, P. B. (2011). How the neuroscience of decision making informs our conception of autonomy. AJOB Neuroscience, 2, 3–14.
Fiore, R. N., & Goodman, K. W. (2016). Precision medicine ethics: selected issues and developments in next-generation sequencing, clinical oncology, and ethics. Current Opinion in Oncology, 28, 83–87.
Fisher, A. J., & Boswell, J. F. (2016). Enhancing the personalization of psychotherapy with dynamic assessment and modeling. Assessment, 23, 496–506.
Frank, M. J., Samanta, J., Moustafa, A. A., & Sherman, S. J. (2007). Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism. Science, 318, 1309–1312.
Fregni, F., & Pascual-Leone, A. (2007). Technology insight: noninvasive brain stimulation in neurology-perspectives on the therapeutic potential of rtms and tdcs. Nature Reviews Neurology, 3, 383.
Friedman, A., et al. (2015). A corticostriatal path targeting striosomes controls decision-making under conflict. Cell, 161, 1320–1333.
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016). The road to precision psychiatry: translating genetics into disease mechanisms. Nature Neuroscience, 19, 1397.
Glannon, W. (2014). Neuromodulation, agency and autonomy. Brain Topography, 27, 46–54.
Glimcher, P. W. & Fehr, E. Neuroeconomics: decision making and the brain (Academic Press, 2013).
Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Review Of Neuroscience, 30, 535.
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74, 1464.
Hanslmayr, S., Axmacher, N., & Inman, C. S. (2019). Modulating human memory via entrainment of brain oscillations. Trends in Neurosciences, 42, 485.
Hirstein, W., Sifferd, K. & Fagan, T. Responsible brains: neuroscience and human culpability (2018).
Javadi, A.-H., Beyko, A., Walsh, V., & Kanai, R. (2015). Transcranial direct current stimulation of the motor cortex biases action choice in a perceptual decision task. Journal of Cognitive Neuroscience, 27, 2174.
Kiani, R., & Shadlen, M. N. (2009). Representation of confidence associated with a decision by neurons in the parietal cortex. Science, 324, 759–764.
Kiani, R., Corthell, L., & Shadlen, M. N. (2014). Choice certainty is informed by both evidence and decision time. Neuron, 84, 1329–1342.
Kim, K., Ekstrom, A. D., & Tandon, N. (2016). A network approach for modulating memory processes via direct and indirect brain stimulation: toward a causal approach for the neural basis of memory. Neurobiology of Learning and Memory, 134, 162–177.
Kim, C. K., Adhikari, A., & Deisseroth, K. (2017). Integration of optogenetics with complementary methodologies in systems neuroscience. Nature Reviews Neuroscience, 18, 222.
Knoch, D., Pascual-Leone, A., Meyer, K., Treyer, V., & Fehr, E. (2006). Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science, 314, 829–832.
Koivisto, M., Harjuniemi, I., Railo, H., Salminen-Vaparanta, N., & Revonsuo, A. (2017). Transcranial magnetic stimulation of early visual cortex suppresses conscious representations in a dichotomous manner without gradually decreasing their precision. NeuroImage, 158, 308–318.
Krause, M. R., Vieira, P. G., Csorba, B. A., Pilly, P. K., & Pack, C. C. (2019). Transcranial alternating current stimulation entrains single-neuron activity in the primate brain. Proceedings of the National Academy of Sciences, 116, 5747–5755.
Kuersten, A., & Hamilton, R. H. (2014). The brain, cognitive enhancement devices, and european regulation. Journal of Law and the Biosciences, 1, 340–347.
Lüders, H., et al. (1985). The second sensory area in humans: evoked potential and electrical stimulation studies. Annals of Neurology, 17, 177–184.
Mahayana, I. T., Tcheang, L., Chen, C.-Y., Juan, C.-H., & Muggleton, N. G. (2014). The precuneus and visuospatial attention in near and far space: a transcranial magnetic stimulation study. Brain Stimulation, 7, 673–679.
Maner, J. K., et al. (2005). Functional projection: How fundamental social motives can bias interpersonal perception. Journal of Personality and Social Psychology, 88, 63.
McClure, S. M., Gilzenrat, M. S. & Cohen, J. D. An exploration-exploitation model based on norepinepherine and dopamine activity. In Advances in neural information processing systems, 867–874 (2006).
Medaglia, J. D., Lynall, M.-E., & Bassett, D. S. (2015). Cognitive network neuroscience. Journal of Cognitive Neuroscience, 27, 1471.
Medaglia, J. D., Zurn, P., Sinnott-Armstrong, W., & Bassett, D. S. (2017). Mind control as a guide for the mind. Nature Human Behaviour, 1, s41562–s41017.
Medaglia, J. D., Yaden, D. B., Helion, C., & Haslam, M. (2019). Moral attitudes and willingness to enhance and repair cognition with brain stimulation. Brain Stimulation, 12, 44–53.
Mischel, W., Shoda, Y., & Rodriguez, M. L. (1989). Delay of gratification in children. Science, 244, 933–938.
Muldoon, S. F., et al. (2016). Stimulation-based control of dynamic brain networks. PLoS Computational Biology, 12, e1005076.
Neubert, F.-X., Mars, R. B., Sallet, J., & Rushworth, M. F. (2015). Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex. Proceedings of the National Academy of Sciences, 112, 201410767.
NIH. The belmont report. Belmont Rep. Ethical Princ. Guidel. Prot. Hum. Subj. Res 4–6 (1979).
O’Connor, C., & Joffe, H. (2015). How the public engages with brain optimization: the media-mind relationship. Science, Technology, & Human Values, 40, 712–743.
Ouellet, J., et al. (2015). Enhancing decision-making and cognitive impulse control with transcranial direct current stimulation (tdcs) applied over the orbitofrontal cortex (ofc): a randomized and sham-controlled exploratory study. Journal of Psychiatric Research, 69, 27–34.
Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.
Platt, M. L., & Glimcher, P. W. (1999). Neural correlates of decision variables in parietal cortex. Nature, 400, 233–238.
Polania, R., Nitsche, M. A., & Ruff, C. C. (2018). Studying and modifying brain function with non-invasive brain stimulation. Nature Neuroscience, 21, 174.
Quentin, R., & Cohen, L. G. (2019). Reversing working memory decline in the elderly. Nature Neuroscience, 22, 686.
Rao, R. P., et al. (2014). A direct brain-to-brain interface in humans. PLoS One, 9, –e111332.
Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85, 59.
Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: theory and data for two-choice decision tasks. Neural Computation, 20, 873–922.
Reinhart, R. M., & Nguyen, J. A. (2019). Working memory revived in older adults by synchronizing rhythmic brain circuits. Nature Neuroscience, 22, 820–827.
Rosenbaum, D. A. (2005). The cinderella of psychology: the neglect of motor control in the science of mental life and behavior. American Psychologist, 60, 308.
Rosenbloom, M. H., Schmahmann, J. D., & Price, B. H. (2012). The functional neuroanatomy of decision-making. The Journal of Neuropsychiatry and Clinical Neurosciences, 24, 266–277.
Ross, L. D., Amabile, T. M., & Steinmetz, J. L. (1977). Social roles, social control, and biases in social-perception processes. Journal of Personality and Social Psychology, 35, 485.
Sadock, B. J., & Sadock, V. A. (2011). Kaplan and Sadock’s synopsis of psychiatry: behavioral sciences/clinical psychiatry. Philadelphia: Lippincott Williams & Wilkins.
Samanez-Larkin, G. R., & Knutson, B. (2015). Decision making in the ageing brain: changes in affective and motivational circuits. Nature Reviews Neuroscience, 16, 278.
Sandberg, A., et al. (2019). Hacking the brain: dimensions of cognitive enhancement. ACS Chemical Neuroscience.
Santarnecchi, E., et al. (2015). Enhancing cognition using transcranial electrical stimulation. Current Opinion in Behavioral Sciences, 4, 171–178.
Savulescu, J., Ter Meulen, R., & Kahane, G. (2011). Enhancing human capacities. Hoboken: Wiley.
Scharnowski, F., & Weiskopf, N. (2015). Cognitive enhancement through real-time fmri neurofeedback. Current Opinion in Behavioral Sciences, 4, 122–127.
Schiff, S. J. Neural control engineering: the emerging intersection between control theory and neuroscience (MIT Press, 2012).
Schmidt, R. A., Lee, T. D., et al. (2005). Motor control and learning: a behavioral emphasis (Vol. 4). Champaign: Human kinetics Champaign.
Scott, S. H. (2004). Optimal feedback control and the neural basis of volitional motor control. Nature Reviews Neuroscience, 5, 532.
Scott, L. S., & Monesson, A. (2009). The origin of biases in face perception. Psychological Science, 20, 676–680.
Shadlen, M. N., & Newsome, W. T. (2001). Neural basis of a perceptual decision in the parietal cortex (area lip) of the rhesus monkey. Journal of Neurophysiology, 86, 1916–1936.
Shepherd, G. M. (2013). Corticostriatal connectivity and its role in disease. Nature Reviews Neuroscience, 14, 278–291.
Siebner, H. (2016). Tms-fmri to uncover cognition and behavior in healthy individuals. Clinical Neurophysiology, 127, e45.
Simon, H. A. (1959). Theories of decision-making in economics and behavioral science. The American Economic Review, 49, 253–283.
Smeding, H., et al. (2007). Pathological gambling after bilateral subthalamic nucleus stimulation in Parkinson disease. Journal of Neurology, Neurosurgery & Psychiatry, 78, 517–519.
Smith, E. R., & DeCoster, J. (2000). Dual-process models in social and cognitive psychology: conceptual integration and links to underlying memory systems. Personality and Social Psychology Review, 4, 108–131.
Smith, D. V., & Huettel, S. A. (2010). Decision neuroscience: neuroeconomics. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 854–871.
Snowball, A., et al. (2013). Long-term enhancement of brain function and cognition using cognitive training and brain stimulation. Current Biology, 23, 987–992.
Söllner, A., Bröder, A., & Hilbig, B. E. (2013). Deliberation versus automaticity in decision making: Which presentation format features facilitate automatic decision making? Judgment and Decision making, 8, 278.
Stam, C. J. (2006). Nonlinear brain dynamics. Hauppauge: Nova Publishers.
Stewart, L., Ellison, A., Walsh, V., & Cowey, A. (2001). The role of transcranial magnetic stimulation (tms) in studies of vision, attention and cognition. Acta Psychologica, 107, 275–291.
Summerfield, C., & De Lange, F. P. (2014). Expectation in perceptual decision making: neural and computational mechanisms. Nature Reviews. Neuroscience, 15, 745.
Swann, N. C., et al. (2018). Adaptive deep brain stimulation for Parkinson’s disease using motor cortex sensing. Journal of Neural Engineering, 15, 046006.
Szczepanski, S. M., & Knight, R. T. (2014). Insights into human behavior from lesions to the prefrontal cortex. Neuron, 83, 1002–1018.
Tang, E., & Bassett, D. S. (2018). Colloquium: control of dynamics in brain networks. Reviews of Modern Physics, 90, 031003.
Thompson-Schill, S. L., Ramscar, M., & Chrysikou, E. G. (2009). Cognition without control: when a little frontal lobe goes a long way. Current Directions in Psychological Science, 18, 259–263.
Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315, 515–518.
Tremblay, S., Sharika, K., & Platt, M. L. (2017). Social decision-making and the brain: a comparative perspective. Trends in Cognitive Sciences, 21, 265–276.
Turner, B. M., Van Maanen, L., & Forstmann, B. U. (2015). Informing cognitive abstractions through neuroimaging: the neural drift diffusion model. Psychological Review, 122, 312.
Valero-Cabré, A., Amengual, J., Stengel, C., Pascual-Leone, A., & Coubard, O. A. (2017). Transcranial magnetic stimulation in basic and clinical neuroscience: a comprehensive review of fundamental principles and novel insights. Neuroscience & Biobehavioral Reviews, 83, 381.
van’t Wout, M., Kahn, R. S., Sanfey, A. G., & Aleman, A. (2005). Repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex affects strategic decision-making. Neuroreport, 16, 1849–1852.
Veatch, R. M. A theory of medical ethics. (1981).
Vossel, S., Geng, J. J., & Fink, G. R. (2014). Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. The Neuroscientist, 20, 150–159.
Vuilleumier, P., & Huang, Y.-M. (2009). Emotional attention: uncovering the mechanisms of affective biases in perception. Current Directions in Psychological Science, 18, 148–152.
Warden, M. R., et al. (2012). A prefrontal cortex–brainstem neuronal projection that controls response to behavioural challenge. Nature, 492, 428.
Wexler, A. (2017). Understanding the practices of the do-it-yourself brain stimulation community: implications for regulatory proposals and ethical discussions. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation, 10, e2.
Wexler, A., & Reiner, P. B. (2019). Oversight of direct-to-consumer neurotechnologies. Science, 363, 234–235.
Widge, A., et al. (2019). Deep brain stimulation of the internal capsule enhances human cognitive control and prefrontal cortex function. Nature Communications, 10, 1536.
William, B. M. (1979). Matching, undermatching, and overmatching in studies of choice. Journal of the Experimental Analysis of Behavior, 32, 269–281.
Yoo, S.-S., Kim, H., Filandrianos, E., Taghados, S. J., & Park, S. (2013). Non-invasive brain-to-brain interface (bbi): establishing functional links between two brains. PLoS One, 8, e60410.
Yuste, R., et al. (2017). Four ethical priorities for neurotechnologies and ai. Nature News, 551, 159.
Zhou, T., et al. (2017). History of winning remodels thalamo-pfc circuit to reinforce social dominance. Science, 357, 162–168.
Zrenner, C., Tünnerhoff, J., Zipser, C., Müller-Dahlhaus, F., & Ziemann, U. (2016). Brain-state dependent non-invasive brain-stimulation with real-time closed-loop simultaneous eeg/tms. Clinical Neurophysiology, 127, e41.
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Medaglia, J.D., Kuersten, A. & Hamilton, R.H. Protecting Decision-Making in the Era of Neuromodulation. J Cogn Enhanc 4, 469–481 (2020). https://doi.org/10.1007/s41465-020-00171-7
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DOI: https://doi.org/10.1007/s41465-020-00171-7