Cyber Security: Effects of Penalizing Defenders in Cyber-Security Games via Experimentation and Computational Modeling.

Cyber-attacks are deliberate attempts by adversaries to illegally access online information of other individuals or organizations. There are likely to be severe monetary consequences for organizations and its workers who face cyber-attacks. However, currently, little is known on how monetary consequences of cyber-attacks may influence the decision-making of defenders and adversaries. In this research, using a cyber-security game, we evaluate the influence of monetary penalties on decisions made by people performing in the roles of human defenders and adversaries via experimentation and computational modeling. In a laboratory experiment, participants were randomly assigned to the role of "hackers" (adversaries) or "analysts" (defenders) in a laboratory experiment across three between-subject conditions: Equal payoffs (EQP), penalizing defenders for false alarms (PDF) and penalizing defenders for misses (PDM). The PDF and PDM conditions were 10-times costlier for defender participants compared to the EQP condition, which served as a baseline. Results revealed an increase (decrease) and decrease (increase) in attack (defend) actions in the PDF and PDM conditions, respectively. Also, both attack-and-defend decisions deviated from Nash equilibriums. To understand the reasons for our results, we calibrated a model based on Instance-Based Learning Theory (IBLT) theory to the attack-and-defend decisions collected in the experiment. The model's parameters revealed an excessive reliance on recency, frequency, and variability mechanisms by both defenders and adversaries. We discuss the implications of our results to different cyber-attack situations where defenders are penalized for their misses and false-alarms.

Neurocognitive mechanisms of affective conflict adaptation: An event related fMRI study.

Control of conflict can be seen in reduced effects of conflict following incompatible trials known as conflict adaptation. Such control mechanisms have been shown to depend on emotional content present in stimuli, which could be a motivational force for control adjustments. We explored the neural mechanisms of the interaction between proactive control in terms of conflict adaptation effect and emotions through an event related fMRI study involving an emotional Stroop effect (facial expression-emotional word paradigm) involving happy and angry expressions. Conflict adaptation was measured in terms of the reduction in Stroop effect as a function of previous trial congruence and previous trial emotion. Participants responded to the facial expression while ignoring the distractor word written over the face. Behavioral results showed larger Stroop effect for angry faces compared to happy faces. Conflict adaptation effect was greater for angry faces and was also influenced by previous trial emotion. Both priming and adaptation effects were observed. Stroop effect was correlated with activations in dorsal anterior cingulate. Emotion effect was correlated with activations in amygdala, fusiform face area (FFA), and insula along with the expected hemispheric asymmetry for positive and negative emotions in left vs right FFA, respectively. Conflict adaptation effect was correlated with activations in amygdala. In addition, activations in striatum supported the three-way interaction between emotion, previous and current trial congruence. Activation in dorsal anterior cingulate was correlated only with the overall Stroop effect in the current trial. Activations in amygdala and striatum were also found with facial expressions. The results indicate that emotion specific processing areas themselves such as amygdala and striatum may self-regulate and contribute toward enhanced proactive control mechanisms for task-relevant emotional stimuli. These findings further confirm the strong relationship between cognition and affect in the context of conflict monitoring and adjustments in cognitive control.

Incidental positive emotion modulates neural response to outcome valence in a monetarily rewarded gambling task.

Choices are influenced by incidental emotions. To understand the neural mechanisms underlying the potential effects of incidental emotions on outcome processing, we conducted two experiments measuring feedback-related negativity (FRN) as a function of outcome (gain and loss) and emotional context. Experiment 1 used happy, neutral, and sad faces. Experiment 2 used pleasant, neutral, and unpleasant emotional scenes. We expected that incidental emotions would influence outcome processing at the behavioral level in line with the cognitive themes associated with each emotion. At a neural level, the effect of emotion based on outcome was expected in FRN. Participants chose one of two gambles presented on either side of an emotional face (Experiment 1) or on the scene (Experiment 2), and were later shown the outcome. Behaviorally, both the experiments showed emotion specific carryover effects on outcome experience in line with the cognitive appraisal tendencies associated with specific emotions. In both experiments, mean amplitude of FRN measured related to the outcome at Fz and FCz showed a significant effect of outcome with larger amplitude for loss compared to gain. The interaction between emotion and outcome was significant at FCz in Experiment 1 and at FPz in Experiment 2. The amplitude difference between loss and gain was larger for positive emotional context compared to neutral and negative emotional contexts, indicating a dopaminergic basis moderating the emotion-outcome processing interaction.

Hippocampal activations in mesial temporal lobe epilepsy due to hippocampal sclerosis- an observational study on intramural encoding-delayed recall paradigms using task-based memory fMRI.

OBJECTIVES: To validate concurrent utility of within-scanner encoding and delayed recognition-memory paradigms to ascertain hippocampal activations during task-based memory fMRI. METHODS: Memory paradigms were designed for faces, word-pairs and abstract designs. A deep-encoding task was designed comprising of a total of 9 cycles run within a 1.5T MRI scanner. A recall session was performed after 1 h within the scanner using an event-related design. Group analysis was done with 'correct-incorrect' responses applied as parametric modulators in Statistical Parametric Mapping version 8 using boot-strap method to enable estimation of laterality indices (LI) using custom anatomical masks involving the medio-basal temporal structures. RESULTS: Twenty seven subjects with drug-resistant mesial temporal lobe epilepsy due to hippocampal sclerosis (MTLE-HS) [17 patients of left-MTLE and 10 patients of right-MTLE] and 21 right handed age-matched healthy controls (HC) were recruited. For the encoding paradigm blood oxygen level dependent (BOLD) responses in HC demonstrated right laterality for faces, left laterality for word pairs, and bilaterality for design encoding over the regions of interest. Both right and left MTLE-HS groups revealed left lateralisation for word-pair encoding, bilateral activation for face encoding, with design encoding in right MTLE-HS demonstrating a left shift. As opposed to lateralization shown in controls, group analysis of cued-recall BOLD signals acquired within scanner in left MTLE-HS demonstrated right lateralization for word-pairs with bilaterality for faces and designs. The right MTLE-HS group demonstrated bilateral activations for faces, word-pairs and designs. CONCLUSION: Recall-based fMRI paradigms indicate hippocampal plasticity in MTLE-HS, maximal for word-pair associate recall tasks.

Evolution of Cooperation with Heterogeneous Conditional Cooperators.

Conditional cooperation declines over time if heterogeneous ideal conditional agents are involved in repeated interactions. With strict assumptions of rationality and a population consisting of ideal conditional agents who strictly follow a decision rule, cooperation is not expected. However, cooperation is commonly observed in human societies. Hence, we propose a novel evolutionary agent-based model where agents rely on social information. Each agent interacts only once either as a donor or as a receiver. In our model, the population consists of either non-ideal or ideal heterogeneous conditional agents. Their donation decisions are stochastically based on the comparison between the number of donations in the group and their conditional cooperative criterion value. Non-ideal agents occasionally cooperate even if the conditional rule of the agent is not satisfied. The stochastic decision and selection rules are controlled with decision intensity and selection intensity, respectively. The simulations show that high levels of cooperation (more than 90%) are established in the population with non-ideal agents for a particular range of parameter values. The emergence of cooperation needs non-ideal agents and a heterogeneous population. The current model differs from existing models by relying on social information and not on individual agent's prior history of cooperation.

The Effect of Wealth Shocks on Loss Aversion: Behavior and Neural Correlates.

Kahneman and Tversky (1979) first demonstrated that when individuals decide whether or not to accept a gamble, potential losses receive more weight than possible gains in the decision. This phenomenon is referred to as loss aversion. We investigated how loss aversion in risky financial decisions is influenced by sudden changes to wealth, employing both behavioral and neurobiological measures. We implemented an fMRI experimental paradigm, based on that employed by Tom et al. (2007). There are two treatments, called RANDOM and CONTINGENT. In RANDOM, the baseline setting, the changes to wealth, referred to as wealth shocks in economics, are independent of the actual choices participants make. Under CONTINGENT, we induce the belief that the changes in income are a consequence of subjects' own decisions. The magnitudes and sequence of the shocks to wealth are identical between the CONTINGENT and RANDOM treatments. We investigated whether more loss aversion existed in one treatment than another. The behavioral results showed significantly greater loss aversion in CONTINGENT compared to RANDOM after a negative wealth shock. No differences were observed in the response to positive shocks. The fMRI results revealed a neural loss aversion network, comprising the bilateral striatum, amygdala and dorsal anterior cingulate cortex that was common to the CONTINGENT and RANDOM tasks. However, the ventral prefrontal cortex, primary somatosensory cortex and superior occipital cortex, showed greater activation in response to a negative change in wealth due to individual's own decisions than when the change was exogenous. These results indicate that striatum activation correlates with loss aversion independently of the source of the shock, and that the ventral prefrontal cortex (vPFC) codes the experimental manipulation of agency in one's actions influencing loss aversion.

Effects of Motivation: Rewarding Hackers for Undetected Attacks Cause Analysts to Perform Poorly.

OBJECTIVE: The aim of this study was to determine how monetary motivations influence decision making of humans performing as security analysts and hackers in a cybersecurity game. BACKGROUND: Cyberattacks are increasing at an alarming rate. As cyberattacks often cause damage to existing cyber infrastructures, it is important to understand how monetary rewards may influence decision making of hackers and analysts in the cyber world. Currently, only limited attention has been given to this area. METHOD: In an experiment, participants were randomly assigned to three between-subjects conditions ( n = 26 for each condition): equal payoff, where the magnitude of monetary rewards for hackers and defenders was the same; rewarding hacker, where the magnitude of monetary reward for hacker's successful attack was 10 times the reward for analyst's successful defense; and rewarding analyst, where the magnitude of monetary reward for analyst's successful defense was 10 times the reward for hacker's successful attack. In all conditions, half of the participants were human hackers playing against Nash analysts and half were human analysts playing against Nash hackers. RESULTS: Results revealed that monetary rewards for human hackers and analysts caused a decrease in attack and defend actions compared with the baseline. Furthermore, rewarding human hackers for undetected attacks made analysts deviate significantly from their optimal behavior. CONCLUSIONS: If hackers are rewarded for their undetected attack actions, then this causes analysts to deviate from optimal defend proportions. Thus, analysts need to be trained not become overenthusiastic in defending networks. APPLICATION: Applications of our results are to networks where the influence of monetary rewards may cause information theft and system damage.

Promises and pitfalls of relating alteration of white matter pathways causing improvement in cognitive performance.

Here, we argue systematically about the promises and pitfalls of relating Human Connectome to cognitive enhancement. We also highlight three key areas where further resolution is required before the generalization of the white-matter-related cause of cognitive enhancement across a variety of cognitive modalities is made. These key areas are: (a) inherent limitations in estimating of diffusion-weighted anisotropy index near volumes with high abundance of crossing fibers; (b) species differences in cell types and only a putative link between brain rhythms and modulation of activity in precursor cells in rodents;

Role of affect in decision making.

Emotion plays a major role in influencing our everyday cognitive and behavioral functions, including decision making. We introduce different ways in which emotions are characterized in terms of the way they influence or elicited by decision making. This chapter discusses different theories that have been proposed to explain the role of emotions in judgment and decision making. We also discuss incidental emotional influences, both long-duration influences like mood and short-duration influences by emotional context present prior to or during decision making. We present and discuss results from a study with emotional pictures presented prior to decision making and how that influences both decision processes and postdecision experience as a function of uncertainty. We conclude with a summary of the work on emotions and decision making in the context of decision-making theories and our work on incidental emotions.

Understanding decision neuroscience: a multidisciplinary perspective and neural substrates.

The neuroscience of decision making is a rapidly evolving multidisciplinary research area that employs neuroscientific techniques to explain various parameters associated with decision making behavior. In this chapter, we emphasize the role of multiple disciplines such as psychology, economics, neuroscience, and computational approaches in understanding the phenomenon of decision making. Further, we present a theoretical approach that suggests understanding the building blocks of decision making as bottom-up processes and integrate these with top-down modulatory factors. Relevant neurophysiological and neuroimaging findings that have used the building-block approach are reviewed. A unifying framework emphasizing multidisciplinary views would bring further insights into the active research area of decision making. Pointing to future directions for research, we focus on the role of computational approaches in such a unifying framework.

Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network.

Previous brain imaging studies investigating motor sequence complexity have mainly examined the effect of increasing the length of pre-learned sequences. The novel contribution of this research is that we varied the structure of complex visuo-motor sequences along two different dimensions using mxn paradigm. The complexity of sequences is increased from 12 movements (organized as a 2×6 task) to 24 movements (organized as 4×6 and 2×12 tasks). Behavioral results indicate that although the success rate attained was similar across the two complex tasks (2×12 and 4×6), a greater decrease in response times was observed for the 2×12 compared to the 4×6 condition at an intermediate learning stage. This decrease is possibly related to successful chunking across sets in the 2×12 task. In line with this, we observed a selective activation of the fronto-parietal network. Shifts of activation were observed from the ventral to dorsal prefrontal, lateral to medial premotor and inferior to superior parietal cortex from the early to intermediate learning stage concomitant with an increase in hyperset length. We suggest that these selective activations and shifts in activity during complex sequence learning are possibly related to chunking of motor sequences.

From bad to worse: striatal coding of the relative value of painful decisions.

The majority of decision-related research has focused on how the brain computes decisions over outcomes that are positive in expectation. However, much less is known about how the brain integrates information when all possible outcomes in a decision are negative. To study decision-making over negative outcomes, we used fMRI along with a task in which participants had to accept or reject 50/50 lotteries that could result in more or fewer electric shocks compared to a reference amount. We hypothesized that behaviorally, participants would treat fewer shocks from the reference amount as a gain, and more shocks from the reference amount as a loss. Furthermore, we hypothesized that this would be reflected by a greater BOLD response to the prospect of fewer shocks in regions typically associated with gain, including the ventral striatum and orbitofrontal cortex. The behavioral data suggest that participants in our study viewed all outcomes as losses, despite our attempt to induce a status quo. We find that the ventral striatum showed an increase in BOLD response to better potential gambles (i.e., fewer expected shocks). This lends evidence to the idea that the ventral striatum is not solely responsible for reward processing but that it might also signal the relative value of an expected outcome or action, regardless of whether the outcome is entirely appetitive or aversive. We also find a greater response to worse gambles in regions previously associated with aversive valuation, suggesting an opposing but simultaneous valuation signal to that conveyed by the striatum.