Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia—the existence of a direct and an indirect pathway that compete against each other. This characteristic has important consequences in decision-making tasks, which are brought to light by Parkinson's disease as (...) well as genetic differences in dopamine receptors. This paper shows that a standard model of action selection in a cognitive architecture cannot replicate any of these findings, details an alternative solution that reconciles action selection in the architecture with the physiology of the basal ganglia, and extends the domain of application of cognitive architectures. The implication of this solution for other architectures and existing models are discussed. (shrink)

Going from cognitive theory to neural data to ACT‐R models, the authors relate brain activity in a lexical ambiguity priming task to brain processes that resolve ambiguity in word meanings. These detailed data were tested and found compatible to the results of an ACT‐R computational model of reinforcement learning (RL). The model confirms and extends the behavioral findings to provide a RL account of individual differences in lexical ambiguity resolution.

Recent years have seen a gradual convergence of seemingly distant research fields over a single goal: understanding and replicating biological intelligence in artifacts. This work presents a general overview on the origin, the state-of-the-art, scientific challenges and the future of Biologically Inspired Cognitive Architecture (BICA) research. Our perspective decomposes the field into the four principal semantic components associated with the BICA challenge that together call for an integration of efforts of researchers across disciplines. Areas and directions of study where new (...) integrated efforts will be primarily needed are summarized. (shrink)

Cognitive architectures (i.e., theorized blueprints on the structure of the mind) can be used to make predictions about the effect of multiregion brain activity on the systems level. Recent work has connected one high-level cognitive architecture, known as the “Common Model of Cognition,” to task-based functional MRI data with great success. That approach, however, was limited in that it was intrinsically top-down, and could thus only be compared with alternate architectures that the experimenter could contrive. In this paper, we propose (...) a bottom-up method to infer a cognitive architecture directly from brain imaging data itself, overcoming this limitation. Specifically, Granger causality modeling was applied to the same task-based fMRI data to infer a network of causal connections between brain regions based on their functional connectivity. The resulting network shares many connections with those proposed by the Common Model of Cognition but also suggests important additions likely related to the role of episodic memory. This combined top-down and bottom-up modeling approach can be used to help formalize the computational instantiation of cognitive architectures and further refine a comprehensive theory of cognition. (shrink)

The Role of Dorsal Premotor Cortex in Resolving Abstract Motor Rules provides alternative hypotheses about the cognitive functions affected by the application of repetitive transcranial magnetic stimulation. Their model simulated the effect of stimulation of the left dorsal premotor cortex right as participants provide a Models were used to demonstrate that the increased variability in observed response times can result from interference in replanning during the process of responding to the uninstructed stimulus.

Transcranial magnetic stimulation (TMS) of the visual cortex can induce phosphenes as can non-diagnostic ultrasound, the latter while participants have closed their eyes during Stimulation. Here we sought to study potential alteration of a visual target (a white crosshair) due to application of diagnostic ultrasound to the visual cortex. We applied a randomized series of actual or sham diagnostic ultrasound to the visual cortex of healthy participants while they stared at a visual target, with the ultrasound device placed where TMS (...) elicited phosphenes. These participants observed percepts 7 out of 10 times, consisting of extra or extensions of lines relative to the original crosshair, and additional colors. Observation of a percept occurred an average of 53.7 +/- 2.6% of the time over the course of the experiment for these participants. In contrast, 7 out of 10 participants exposed to sham-only diagnostic ultrasound observed comparable percepts an average of 36.3 +/ 1.9% of the time, a statistically significant difference (p < 0.00001). Moreover, on average, participants exposed to a combination of sham and actual ultrasound reported a net increase of 47.9 percentage points in the likelihood that they would report a visual effect by the end of the experiment. Our experiment demonstrated that a random combination of sham-only and actual diagnostic ultrasound applied to the visual cortex of participants increased the likelihood that they would observe visual effects, but not the type of effects, with that likelihood increasing over the course of the experiment. From this we conclude that repeated exposures by diagnostic ultrasound made the visual cortex more responsive to stimulation of their visual cortex by the visual target. These observations, consistent with other’s observation of effects of diagnostic ultrasound stimulation of human motor cortex and amygdala, as well as the FDA approved nature of diagnostic ultrasound, may lead to increased study of diagnostic ultrasound applied to human brain. (shrink)

This paper presents a neurocomputational model using the ACT‐R cognitive architecture that simulates intrusive memory retrieval following a potentially traumatic event and predicts hippocampal volume changes observed in Post‐Traumatic Stress Disorder.

The ability to reason and problem‐solve in novel situations, as measured by the Raven's Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task performance and real‐world outcomes. Here we provide evidence that RAPM performance depends on the ability to reallocate attention in response to self‐generated feedback about progress. We propose that such an ability is underpinned by the basal ganglia nuclei, which are critically tied to both reward processing and cognitive control. This hypothesis was implemented in a neurocomputational (...) model of the RAPM task, which was used to derive novel predictions at the behavioral and neural levels. These predictions were then verified in one neuroimaging and two behavioral experiments. Furthermore, an effective connectivity analysis of the neuroimaging data confirmed a role for the basal ganglia in modulating attention. Taken together, these results suggest that individual differences in a neural circuit related to reward processing underpin human fluid reasoning abilities. (shrink)