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Integrative Computational and Neurocognitive Science and Technology for Intelligence Operations: Horizons of Potential Viability, Value and Opportunity

Published: Thursday, 30 June 2016 10:38
Written by James Giordano PhD, Rachel Wurzman PhD
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The authors present a case for a NEURINT (neurocognitive intelligence) approach to intelligence operations. This newly developing technology integrates tools from computational and neuro-cognitive sciences to enable automated access, acquisition and analysis of multiple sources of information to model and predict targets’ intentions and actions. The approach would utilize information from the brain sciences, together with human cognitive and machine-based processing, and cyber technologies and methods to synergize HUMINT, SIGINT and COMMINT in assessing and influencing target individuals and groups. Citing recent research in the field, the authors maintain that these techniques and technologies are ready to be further developed and engaged to optimize intelligence operations.

image credit: www.shutterstock.com/Sergey Nivens


"Past thinking and methods did not prevent world wars; future thinking must."

Albert Einstein


As international conflict dynamics shift ever more toward effecting power in the information space,  outcomes are often decided not by military capabilities on land, sea or air, but rather by the influence of ideas and emotions that motivate behaviors of state and non-state actors alike.1 Ideas about needs, values, and the nature and intentions of other groups, and resulting feelings of trust, mistrust, dread, and threat determine priorities and influence attitudes and actions. In light of this, it is becoming increasingly important for intelligence operations to understand the ways that individuals perceive and respond to various types of information. In turn, this requires knowledge about how humans communicate with one another in groups, and orient and respond to economic, social and political environments. Human perceptions and behaviors involve interacting biological, psychological and social factors. To date, detecting these interacting variables with scientific rigor has been difficult, due in part to limitations of extant technologies and techniques available for intelligence acquisition, assimilation, analysis and use. However, we believe that newly developing technology systems can be employed in and for intelligence operations, and that the use of these approaches may greatly supplement current intelligence capabilities, and in this way, afford important and perhaps necessary additions to the intelligence community (IC) toolkit.


To succeed in a global environment of increasingly complex and diversified information, the IC requires methods and instruments that can detect, assess, and respond to the evolving capabilities, actions – and intent(s) – of targets and adversaries. These dynamics require intelligence systems to be more agile and precise than those of potential targets. On a practical level, this mandates an ability to acquire and integrate massive sets of data that are highly diverse and cross domains of signal, communications, and human intelligence data. Moreover, there is a need to process these data to provide information that can yield understanding and predictions of the cognitive and behavioral conditions that define key targets’ current and future behaviors. Such information must be correctly interpreted for use in information, influence, as well as kinetic (e.g., “boots on the ground”) operations.

New techniques and technologies may enable the development of an integrated system for intelligence acquisition, assessment, and influence.2 What components might form such a system? Figure 1 represents a conception of an integrated system consisting of three overarching modules that can be conjoined in a flexible technology suite. First (on the left of the figure) is a module for the automated analysis of information content in the IC environment. This information feeds into behavior – and sentiment-predictive forecasting models that drive campaign planning tools (in the middle of the figure). These models, in turn, drive an “IO cognitive test bed” utilizing human-in-the-loop neurocognitive signal feedback to finesse the products of the campaign-planning tools, for maximal effectiveness in the human domain.3


Figure 1

Such a system could incorporate technologies to automate access, acquisition and analysis of multiple sources of information. For example, the system might combine broadcast and social media, communications, inter-individual interaction patterns, etc., summarize, and provide the information directly to analysts, and also feed data into computational agent-based modeling programs. These modeling programs would then forecast future sentiments and behaviors of individuals and groups. Outcomes of both analyst analyses and computational models can be used to drive campaign planning tools, which can be developed and implemented to optimally influence key targets’ behavior in particular operational environments.4

The construction of influence operations (IO) cognitive test beds that connect planning tools to concept of operations development would employ neuro-cognitive technologies and techniques to assess the reactions of a representative target. These predict and evaluate the physiological and psychological responses that can be expected for a given operational plan.5 The results gained from IO cognitive test beds can increase the likelihood of optimizing assessment and influence tactics and strategies by: 1) fortifying identification and analysis of target-specific variables; 2) providing information upon which to develop successful narratives and other psychological tactics, and 3) utilizing “human-in-the-loop”-based results to generate approaches that more precisely assess and affect specified target(s) in desired ways.

Many technologies essential to this system already exist, and reportedly those that are currently in “the pipeline” that require further development would not take long to mature.6 For example, mature, validated, and operationalizable systems for automated, real-time monitoring of massive international news-media, such as the Expandable Open Source – EOS – system (see: http://osvpr.georgetown.edu), and Lockheed-Martin’s Integrated Crisis Early Warning System (ICEWS), use extracted event-traces from news media to drive event-depiction and forecasting models. As well, “Big Data” tools, such as the AvesTerra system can acquire and extract information from multiple functional domains, such as biological, behavioral, economic, environmental/ecologic reports, from myriad resources to enable real-time identification and tracking. These can generate profile and output patterns for near- and intermediate-term event predictions (see: http://osvpr.georgetown.edu). Such data could be used in tandem with decision technologies to establish a modeling core to generate predictive algorithms to plot potential trajectories of targets’ behaviors, and evaluate how such trajectories and outcomes may be affected by implementing various interventions to alter variables that influence environments, resources, individual and group interactions, narratives, etc.7,8


Strategic intelligence at the individual and group levels relies critically on the roles that biological factors, social identities, cultural norms, and narratives play in the context of events.9 Furthermore, there is a neural basis for such effects, operating both upon the subject/target, and the analyst or decision-maker. This has fostered increased interest in the possible utility of systematically incorporating neuroscientific and neurocognitive techniques and technologies (neurocogS/T) to detect, analyze, and understand target information, and to provide operational planning tools to influence target behaviors in ways that are of use and value to the IC.10

There is much ongoing academic work that establishes a relationship between environmental effects with narratives and detectable neural signals that can be correlated to behavior change.11-15 Findings from recent studies support that individual and group neurophysiological data can be useful for describing and predicting the relative likelihood of targets’ cognitive and emotional state, and resulting behaviors in defined environments under particular circumstances. From this, it might be possible to identify – and implement – operational actions and messages that exert influence in ways that are specifically reflective of a particular target and/or target group. Such information provides an additional layer of context to HUMINT, SIGINT, and COMINT collection by depicting how neuro-cognitive systems and processes operate under various environmental conditions, interpersonal communications and interactions, and how neural processes contribute to certain behaviors.

Neurocognitive science may also be utilized to optimize the performance of an intelligence analyst. Information about an analyst’s neurocognitive state and processing can be fed into intelligence acquisition schemes and predictive models about their targets, so as to “fine tune” information assessment and predictions to account for the analyst’s cognitive filters and activity patterns. For example, a suitably equipped workstation would take electroencephalographic (EEG) measurements of brain-wave activity collected from the analyst (while reviewing the raw information and generating analytic products) that could be integrated with state-of-the-art computational systems to assess patterns of neuro-cognitive engagement in various information processing regimes. This could be coupled to neurofeedback systems to fortify neuro-cognitive mechanisms and optimize analyst performance. Laboratory experiments of this sort have been conducted have been conducted in the past.16, 17

Thus we define a new kind of intelligence collection modality based on this assimilated approach, which we call “NEURINT” (i.e., neuro-cognitive or neural intelligence).18 NEURINT could enhance intelligence analysis in several ways. First, it employs information from the brain sciences (in tandem with other forms of human terrain information) to establish patterns of human neuro-cognitive and behavioral processes. Second, it enables pairing of human cognitive and machine-based computational processing to increase analyst capabilities in information detection, discrimination and assessment. Third, it could be linked to cyber-based approaches to assess and influence effects of various forms of messaging used by target individuals and groups (e.g., social media).19 The resulting analysis could optimize tactical and/or strategic engagement of target individuals’ or groups’ psychological states to achieve best advantage in effecting changes in their cognitions, emotions and behaviors.20


Human beings are often portrayed as “rational actors” and indeed, rational actor models can be useful for predicting the behavior of individuals or groups.21 However, findings from neuroscientific studies increasingly reveal human behavior, cognition, and decision-making as a combination of both rational and irrational, more emotively driven processes, driven by social cognition and social dynamics.22,23 Given that neuro-cognitive sciences have only recently advanced these insights, the neuro-cognitive bases and effects of social identities, cultural norms, and narratives have heretofore been somewhat under-valued,24 and under-employed when considering contexts for strategic intelligence.

The commander of US Central Command (CENTCOM) has said that success in an age in which the human domain trumps the land, sea, air, and space domains requires that strategic intelligence incorporate a neuro-cognitive understanding of the dynamics that mark this seemingly-perpetual conflict.25 The outcomes of intelligence and influence operations are dynamic, and can be expected to change as a consequence of biological, psychological and social factors. NEURINT approaches can synergize HUMINT, SIGINT and COMMINT, and, we posit, in this way, make neuro-cognitive advances especially valuable for strategic intelligence in the human domain.


While NEURINT can, and arguably should be employed to enhance certain IC operations, it is important not to misinterpret and/or misuse these techniques.26,27 Indeed, human thought and activity involves biological, and social factors and effects, and all must be taken into account when gathering and interpreting intelligence. As stated in a recent Joint Staff Strategic Multilayer Assessment (SMA) group report:

Neuro-cognitive technology can reduce the volume and complexity of information…by sorting complicated information in order to augment human analysts’ formulating a cohesive picture from which to draw necessary inferences about the capabilities and intentions of (friendly, neutral or hostile) intelligence targets. Neurotechnologies can facilitate and enhance collection and interpretation capabilities and… might decrease the fallibility of “human weak links” in the intelligence chain.28

In sum, there is great potential and opportunity to utilize currently available neurocognitive science and technology in IC operations. In light of growing threats to national security, and the rapidly shifting international capabilities in science, technology and intelligence,29-31 we believe that investment in neurocognitive technologies could produce particularly high returns. These approaches are ready to move from the laboratory to be evaluated for viability and value in practical applications and for use in real-world intelligence operations. By so doing, they can be further developed and articulated so as to keep pace with the tasks and challenges of the future IC mission to mitigate or prevent the escalation of international conflict and threats to national security.


The authors are grateful to ongoing collaboration with Drs. William Casebeer, Hriar Cabayan, Diane DiEuliis, Jason Spitaletta and Nicholas Wright, as part of the Strategic Multilayer Assessment Group of the Joint Staff of the Pentagon, studying the potential roles of neuro-cognitive science and technology in national intelligence, security and defense.


The perspectives and opinions presented in this essay are the authors’ and do not necessarily reflect those of the Department of Defense, Joint Staff of the Pentagon, or the Defense Advanced Research Projects Agency (DARPA).


1. Daniel Cunningham, Sean Everton, and Philip Murphy, Understanding Dark Networks: A Strategic Framework for the Use of Social Network Analysis (Lanham, MD: Rowman and Littlefield, 2016).

2. William D Casebeer, “Countering Adversary Ideological Influence in Conflict Zones – Technology Implictions,” in: White Paper on Social and Cognitive Neuroscience Underpinnings of ISIL Behavior and Implications for Strategic Communication, Messaging, and Influence. Department of Defense; Strategic Multilayer Assessment Group- Joint Staff/J-3 Report (2015).

3. Ibid.

4. Ibid.

5. Ibid.

6. Ibid.

7. P. Justin Rossi, Philipp Novotny, Peyton Paulick, et al., “Decision Technologies in Medical Research and Practice: Practical Considerations, Ethical Implications and Need for Dialectical Evaluation,” Ethics Biol Engineer Med 4 no 2 (2013): 91-102.

8. James Giordano, ed., “Leveraging Neuroscientific and Neurotechnological Developments with Focus on Influence and Deterrence in a Networked World,” Department of Defense; Strategic Multilayer Assessment Group- Joint Staff/J-3 Report (May 2014).

9. A Biopsychosocial Science Approach for Understanding the Emergence of and Mitigating Violence and Terrorism. (2016). Department of Defense; Strategic Multilayer Assessment Group- Joint Staff/J-3/Pentagon Report.

10. Ibid, ref. 2.

11. See: http://neuralengr.com; and/or http://bme.ccny.cuny.edu/faculty/lparra.

12. See: http://dornsife.usc.edu/bci.

13. See: http://saxelab.mit.edu.

14. See: http://camplab.psych.yale.edu.

15. Ibid, ref. 8.

16. Kelly Hale, Sven Fuchs, Par Axelsson, Chris Berka, and Andrew Cowell, “Using Physiological Measures to Discriminate Signal Detection Outcome During Imagery Analysis,” Human Factors and Ergonomics Society Proceedings 52 no 3 (2008): 182-186.

17. Kay Stanney, Kelly Hale, Sven Fuchs, Angela Carpenter, Chris Berka, “Neural Systems in Intelligence and Training Applications,” in: Neurotechnology in National Security and Defense: Practical Considerations, Neuroethical Concerns, ed. James Giordano (Boca Raton, CRC Press, 2014), 23-32.

18. Rachel Wurzman and James Giordano, “NEURINT and Neuroweapons: Neurotechnololgies in National Intelligence and Defense,” in: Neurotechnology in National Security and Defense: Practical Considerations, Neuroethical Concerns, ed. James Giordano (Boca Raton: CRC Press, 2014), 79-114.

19. Ibid, ref. 8.

20. Ibid, ref. 9.

21. Valerie Hudson, Foreign Policy Analysis: Classic and Contemporary Theory (Lanham MD: Rowman and Littlefield, 2007).

22. Milton Lodge and Charles Taber, “The Automaticity of Affect for Political Leaders, Groups, and Issues: An Experimental Test of the Hot Cognition Hypothesis,” Political Psychology 26 no 3 (2005): 455–482.

23. Ellen Peters, Daniel Västfjäll, Tommy Gärling, Paul Slovic, “Affect and Decision Making: A ‘Hot’ Topic,” Journal of Behavioral Decision Making 19 no 2 (2006): 79–85.

24. National Research Council of the National Academy of Sciences (NAS). Committee on Military and Intelligence Methodology for Emergent Neurophysiological and Cognitive/Neural Research in the Next Two Decades. Emerging Cognitive Neuroscience and Related Technologies (Washington, DC: National Academies Press, 2008).

25. Joseph Votel. (2016). “Foreword,” in: A Biopsychosocial Science Approach for Understanding the Emergence of and Mitigating Violence and Terrorism, Department of Defense; Strategic Multilayer Assessment Group- Joint Staff/J-3/Pentagon Report, p.1.

26. James Giordano, “Neurotechnology as Demiurgical Force: Avoiding Icarus’ Folly,” in: Neurotechnology: Premises, Potential and Problems, ed. James Giordano (Boca Raton: CRC Press, 2012), 1-14.

27. Wiliam Casebeer, “A Neuroscience and National Security Normative Framework for the Twenty-First Century,” in: Neurotechnology in National Security and Defense: Practical Considerations, Neuroethical Concerns, ed. James Giordano (Boca Raton, CRC Press, 2014), 279-284.

28. Ibid. ref. 2.

29. Strategic Latency and Warning: Private Sector Perspectives on Current Intelligence Challenges in Science and Technology, Report of the Expert Advisory Panel Workshop (Livermore, CA: Lawrence Livermore National Laboratory, 2016).

30. Andrew Phillip Hunter and Ryan Crotty, Keeping the Technological Edge (Lanham MD: Rowman and Littlefield: 2016).

31. Chris Forsythe and James Giordano, On the Need for Neurotechnology in the National Intelligence and Defense Agenda: Scope and Trajectory. Synesis: A Journal of Science, Technology, Ethics and Policy 2 no 1, (2011): 5-8, http://www.synesisjournal.com/vol2_no2_t1/Forsythe_Giordano_2011_2_1.pdf.