Symbolic Deep Networks: A Psychologically Inspired Lightweight and Efficient Approach to Deep Learning.

The last two decades have produced unprecedented successes in the fields of artificial intelligence and machine learning (ML), due almost entirely to advances in deep neural networks (DNNs). Deep hierarchical memory networks are not a novel concept in cognitive science and can be traced back more than a half century to Simon's early work on discrimination nets for simulating human expertise. The major difference between DNNs and the deep memory nets meant for explaining human cognition is that the latter are symbolic networks meant to model the dynamics of human memory and learning.

Cognitive Models in Cybersecurity: Learning From Expert Analysts and Predicting Attacker Behavior.

Cybersecurity stands to benefit greatly from models able to generate predictions of attacker and defender behavior. On the defender side, there is promising research suggesting that Symbolic Deep Learning (SDL) may be employed to automatically construct cognitive models of expert behavior based on small samples of expert decisions. Such models could then be employed to provide decision support for non-expert users in the form of explainable expert-based suggestions.

Participation shifts explain degree distributions in a human communications network.

Human interpersonal communications drive political, technological, and economic systems, placing importance on network link prediction as a fundamental problem of the sciences. These systems are often described at the network-level by degree counts -the number of communication links associated with individuals in the network-that often follow approximate Pareto distributions, a divergence from Poisson-distributed counts associated with random chance. A defining challenge is to understand the inter-personal dynamics that give rise to such heavy-tailed degree distributions at the network-level; primarily, these distributions are explained by preferential attachment, which, under certain conditions, can create power law distributions; preferential attachment's prediction of these distributions breaks down, however, in conditions with no network growth.

Cyber Teaming and Role Specialization in a Cyber Security Defense Competition.

A critical requirement for developing a cyber capable workforce is to understand how to challenge, assess, and rapidly develop human cyber skill-sets in realistic cyber operational environments. Fortunately, cyber team competitions make use of simulated operational environments with scoring criteria of task performance that objectively define overall team effectiveness, thus providing the means and context for observation and analysis of cyber teaming. Such competitions allow researchers to address the key determinants that make a cyber defense team more or less effective in responding to and mitigating cyber attacks.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors.

Enhancing Team Composition in Professional Networks: Problem Definitions and Fast Solutions.

In this paper, we study ways to enhance the composition of teams based on new requirements in a collaborative environment. We focus on recommending team members who can maintain the team's performance by minimizing changes to the team's skills and social structure. Our recommendations are based on computing team-level similarity, which includes , as well as the between the two.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness.

A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004).

Effects of Information Availability on Command-and-Control Decision Making: Performance, Trust, and Situation Awareness.

Objective: We investigated how increases in task-relevant information affect human decision-making performance, situation awareness (SA), and trust in a simulated command-and-control (C2) environment.

Background: Increased information is often associated with an improvement of SA and decision-making performance in networked organizations. However, previous research suggests that increasing information without considering the task relevance and the presentation can impair performance.

Where is ELSA? The early to late shift in aging.

Studies of cognitive and neural aging have recently provided evidence of a shift from an early- to late-onset cognitive control strategy, linked with temporally extended activity in the prefrontal cortex (PFC). It has been uncertain, however, whether this age-related shift is unique to PFC and executive control tasks or whether the functional location might vary depending on the particular cognitive processes that are altered. The present study tested whether an early-to-late shift in aging (ELSA) might emerge in the medial temporal lobes (MTL) during a protracted context memory task comprising both anticipatory cue (retrieval preparation) and retrieval probe (retrieval completion) phases.

Neural correlates of confidence during item recognition and source memory retrieval: evidence for both dual-process and strength memory theories.

Although the medial-temporal lobes (MTL), PFC, and parietal cortex are considered primary nodes in the episodic memory network, there is much debate regarding the contributions of MTL, PFC, and parietal subregions to recollection versus familiarity (dual-process theory) and the feasibility of accounts on the basis of a single memory strength process (strength theory). To investigate these issues, the current fMRI study measured activity during retrieval of memories that differed quantitatively in terms of strength (high vs. low-confidence trials) and qualitatively in terms of recollection versus familiarity (source vs.

A search-by-clusters model of visual search: fits to data from younger and older adults.

Objectives: This study aims to specify the processing operations underlying age-related differences in the speed and accuracy of visual search in a mathematical model.

Method: Eighteen older and 18 young adults searched for a predesignated target within 24-degree visual arrays containing distractors. Targets were systematically placed in regions that extended 2.

Effects of repetition on associative recognition in young and older adults: item and associative strengthening.

Young and older adults studied word pairs and later discriminated studied pairs from various types of foils including recombined word-pairs and foil pairs containing one or two previously unstudied words. We manipulated how many times a specific word pair was repeated (1 or 5) and how many different words were associated with a given word (1 or 5) to tease apart the effects of item familiarity from recollection of the association. Rather than making simple old/new judgments, subjects chose one of five responses: (a) Old-Old (original), (b) Old-Old (rearranged), (c) Old-New, (d) New-Old, (e) New-New.

Assessing the effects of age on long white matter tracts using diffusion tensor tractography.

Aging is associated with significant white matter deterioration and this deterioration is assumed to be at least partly a consequence of myelin degeneration. The present study investigated specific predictions of the myelodegeneration hypothesis using diffusion tensor tractography. This technique has several advantages over other methods of assessing white matter architecture, including the possibility of isolating individual white matter tracts and measuring effects along the whole extent of each tract.

Memory for Items and Associations: Distinct Representations and Processes in Associative Recognition.

In two experiments, participants studied word pairs and later discriminated old (intact) word pairs from foils, including recombined word pairs and pairs including one or two previously unstudied words. Rather than making old/new memory judgments, they chose one of five responses: (1) Old-Old (original), (2) Old-Old (rearranged), (3) Old-New, (4) New-Old, (5) New-New. To tease apart the effects of item familiarity from those of associative strength, we varied both how many times a specific word-pair was repeated (1 or 5) and how many different word pairs were associated with a given word (1 or 5).

Rules and more rules: the effects of multiple tasks, extensive training, and aging on task-switching performance.

Task-switching performance was assessed in young and older adults as a function of the number of task sets to be actively maintained in memory (varied from 1 to 4) over the course of extended training (5 days). Each of the four tasks required the execution of a simple computational algorithm, which was instantaneously cued by the color of the two-digit stimulus. Tasks were presented in pure (task set size 1) and mixed blocks (task set sizes 2, 3, 4), and the task sequence was unpredictable.

Acute alcohol intoxication impairs controlled search across the visual field.

Objective: The objective of the two experiments reported was to examine the effects of acute alcohol intoxication and of alcohol expectancies on controlled search across the visual field.

Method: After receiving an oral dose of 0.5 g/kg alcohol (Experiment 1), an oral dose of 0.

Modeling age-related memory deficits: a two-parameter solution.

Recent research and meta-analytic reviews suggest that 1 observed pattern of impaired and intact memory performance with advancing age is a deficit in measures of episodic but not semantic memory. The authors used computational modeling to explore a number of age-related parameters to account for this pattern. A 2-parameter solution based on lifelong experience successfully fit the pattern of results in 5 published studies of the word-frequency mirror effect and paired-associate recognition.