CogPonder: Towards a Computational Framework of General Cognitive Control

Poster (2023, August)

Current computational models of cognitive control exhibit notable limitations. In machine learning, artificial agents are now capable of performing complex tasks but often ignore critical constraints such ... [more ▼]

Current computational models of cognitive control exhibit notable limitations. In machine learning, artificial agents are now capable of performing complex tasks but often ignore critical constraints such as resource limitations and how long it takes for the agent to make decisions and act. Conversely, cognitive control models in psychology are limited in their ability to tackle complex tasks (e.g., play video games) or generalize across a battery of simple cognitive tests. Here we introduce CogPonder, a flexible, differentiable, cognitive control framework that is inspired by the Test-Operate-Test-Exit (TOTE) architecture in psychology and the PonderNet framework in machine learning. CogPonder functionally decouples the act of control from the controlled processes by introducing a controller that acts as a wrapper around any end-to-end deep learning model and decides when to terminate processing and output a response, thus producing both a response and response time. Our experiments show that CogPonder effectively learns from data to generate behavior that closely resembles human responses and response times in two classic cognitive tasks. This work demonstrates the value of this new computational framework and offers promising new research prospects for both psychological and computer sciences. [less ▲]

Towards a Computational Model of General Cognitive Control Using Artificial Intelligence, Experimental Psychology and Cognitive Neuroscience

Doctoral thesis (2023)

Cognitive control is essential to human cognitive functioning as it allows us to adapt and respond to a wide range of situations and environments. The possibility to enhance cognitive control in a way ... [more ▼]

Cognitive control is essential to human cognitive functioning as it allows us to adapt and respond to a wide range of situations and environments. The possibility to enhance cognitive control in a way that transfers to real life situations could greatly benefit individuals and society. However, the lack of a formal, quantitative definition of cognitive control has limited progress in developing effective cognitive control training programs. To address this issue, the first part of the thesis focuses on gaining clarity on what cognitive control is and how to measure it. This is accomplished through a large-scale text analysis that integrates cognitive control tasks and related constructs into a cohesive knowledge graph. This knowledge graph provides a more quantitative definition of cognitive control based on previous research, which can be used to guide future research. The second part of the thesis aims at furthering a computational understanding of cognitive control, in particular to study what features of the task (i.e., the environment) and what features of the cognitive system (i.e., the agent) determine cognitive control, its functioning, and generalization. The thesis first presents CogEnv, a virtual cognitive assessment environment where artificial agents (e.g., reinforcement learning agents) can be directly compared to humans in a variety of cognitive tests. It then presents CogPonder, a novel computational method for general cognitive control that is relevant for research on both humans and artificial agents. The proposed framework is a flexible, differentiable end-to-end deep learning model that separates the act of control from the controlled act, and can be trained to perform the same cognitive tests that are used in cognitive psychology to assess humans. Together, the proposed cognitive environment and agent architecture offer unique new opportunities to enable and accelerate the study of human and artificial agents in an interoperable framework. Research on training cognition with complex tasks, such as video games, may benefit from and contribute to the broad view of cognitive control. The final part of the thesis presents a profile of cognitive control and its generalization based on cognitive training studies, in particular how it may be improved by using action video game training. More specifically, we contrasted the brain connectivity profiles of people that are either habitual action video game players or do not play video games at all. We focused in particular on brain networks that have been associated with cognitive control. Our results show that cognitive control emerges from a distributed set of brain networks rather than individual specialized brain networks, supporting the view that action video gaming may have a broad, general impact of cognitive control. These results also have practical value for cognitive scientists studying cognitive control, as they imply that action video game training may offer new ways to test cognitive control theories in a causal way. Taken together, the current work explores a variety of approaches from within cognitive science disciplines to contribute in novel ways to the fascinating and long tradition of research on cognitive control. In the age of ubiquitous computing and large datasets, bridging the gap between behavior, brain, and computation has the potential to fundamentally transform our understanding of the human mind and inspire the development of intelligent artificial agents. [less ▲]

Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: The Example of Cognitive Control

E-print/Working paper (2022)

Traditionally, theory and practice of Cognitive Control are linked via literature reviews by human domain experts. This approach, however, is inadequate to track the ever-growing literature. It may also ... [more ▼]

Traditionally, theory and practice of Cognitive Control are linked via literature reviews by human domain experts. This approach, however, is inadequate to track the ever-growing literature. It may also be biased, and yield redundancies and confusion. Here we present an alternative approach. We performed automated text analyses on a large body of scientific texts to create a joint representation of tasks and constructs. More specifically, 385,705 scientific abstracts were first mapped into an embedding space using a transformers-based language model. Document embeddings were then used to identify a task-construct graph embedding that grounds constructs on tasks and supports nuanced meaning of the constructs by taking advantage of constrained random walks in the graph. This joint task-construct graph embedding, can be queried to generate task batteries targeting specific constructs, may reveal knowledge gaps in the literature, and inspire new tasks and novel hypotheses. [less ▲]

Training Cognition with Video Games

in Cohen Kadosh, Kathrin (Ed.) The Oxford Handbook of Developmental Cognitive Neuroscience (2021)

This chapter reviews the behavioral and neuroimaging scientific literature on the cognitive consequences of playing various genres of video games. The available research highlights that not all video ... [more ▼]

This chapter reviews the behavioral and neuroimaging scientific literature on the cognitive consequences of playing various genres of video games. The available research highlights that not all video games have similar cognitive impact; action video games as defined by first- and third-person shooter games have been associated with greater cognitive enhancement, especially when it comes to top-down attention, than puzzle or life-simulation games. This state of affairs suggests specific game mechanics need to be embodied in a video game for it to enhance cognition. These hypothesized game mechanics are reviewed; yet, the authors note that the advent of more complex, hybrid, video games poses new research challenges and call for a more systematic assessment of how specific video game mechanics relate to cognitive enhancement. [less ▲]

A Formal Framework for Structured N-Back Stimuli Sequences

Scientific Conference (2019, September 15)

Ontology-based modeling of DDoS attacks for attack plan detection

in 6th International Symposium on Telecommunications (IST) (2012)

This paper proposes an effective approach to model DDoS attacks, and its application to recognize attack plans prior to the actual incident. The goals of this study are, firstly model DDoS attacks, their ... [more ▼]

This paper proposes an effective approach to model DDoS attacks, and its application to recognize attack plans prior to the actual incident. The goals of this study are, firstly model DDoS attacks, their prerequisites and consequences using semantic representation in order to provide description logic of DDoS attacks; and secondly, propose an ontology-based solution which detects potential DDoS attacks using inference over observing knowledge provided by sensory inputs. Unlike other ontologies in network attack domains, proposed ontology is generated automatically using well-known taxonomies like CAPEC, CWE, and CVE datasets. Proposed method not only introduces semantic to exchange knowledge between machines, but also provides a framework by which machine can detect intrusions. [less ▲]

Serial Ports in Interfacing Circuits

Book published by Nahr-e Danesh Press (2009)

A Fault Injection Attitude based on Background Debug Mode in Embedded Systems

in Arabnia, Hamid R.; Solo, Ashu M. G. (Eds.) Proceedings of the 2009 International Conference on Computer Design (CDES2009) (2009)

The embedded systems usage in different applications are prevalent in recent years. These systems include a wide range of equipments from cell phones to medical instruments, which consist of hardware and ... [more ▼]

The embedded systems usage in different applications are prevalent in recent years. These systems include a wide range of equipments from cell phones to medical instruments, which consist of hardware and software. In many examples of embedded systems, fault occurrence can lead to serious dangers in system behavior (for example in satellites). Therefore, we try to increase the fault tolerance feature in these systems. Therefore, we need some mechanisms that increase the robustness and reliability of such systems. These objects cause the on-line test to be a great concern. It is not important that these mechanisms work in which level (Hardware level, Software level or Firmware). The major concern is that how well these systems can provide debugging, test and verification features for the user regardless of their implementation levels. Background Debug Module is a real time tool for these features. In this paper we apply an innovative way to use the BDM tool for fault injection in an embedded system. [less ▲]