The Dual Mechanisms of Cognitive Control (DMCC) project: Validation of an on-line behavioral task battery

Cognitive control serves a crucial role in human higher mental functions. The Dual Mechanisms of Control (DMC) account provides a unifying theoretical framework that decomposes cognitive control into two qualitatively distinct mechanisms – proactive control and reactive control. While prior behavioral and neuroimaging work has demonstrated the validity of individual tasks in isolating these two mechanisms of control, there has not been a comprehensive, theoretically-guided task battery specifically designed to tap into proactive and reactive control across different domains of cognition. To address this critical limitation and provide useful methodological tools for future investigations, the Dual Mechanisms of Cognitive Control (DMCC) task battery was developed to probe these two control modes, as well as their intra-individual and inter-individual differences, across four prototypical domains of cognition: selective attention, context processing, multi-tasking, and working memory. We present this task battery, along with detailed descriptions of the experimental manipulations used to encourage shifts to proactive or reactive control in each of the four task domains. We rigorously evaluate the group effects of these manipulations in primary indices of proactive and reactive control, establishing the validity of the DMCC task battery in providing dissociable yet convergent measures of the two cognitive control modes.

Advancing Smart Home Awareness—A Conceptual Computational Modelling Framework for the Execution of Daily Activities of People with Alzheimer’s Disease

Utilizing context-aware tools in smart homes (SH) helps to incorporate higher quality interaction paradigms between the house and specific groups of users such as people with Alzheimer’s disease (AD). One method of delivering these interaction paradigms acceptably and efficiently is through context processing the behavior of the residents within the SH. Predicting human behavior and uncertain events is crucial in the prevention of upcoming missteps and confusion when people with AD perform their daily activities. Modelling human behavior and mental states using cognitive architectures produces computational models capable of replicating real use case scenarios. In this way, SHs can reinforce the execution of daily activities effectively once they acquire adequate awareness about the missteps, interruptions, memory problems, and unpredictable events that can arise during the daily life of a person living with cognitive deterioration. This paper presents a conceptual computational framework for the modelling of daily living activities of people with AD and their progression through different stages of AD. Simulations and initial results demonstrate that it is feasible to effectively estimate and predict common errors and behaviors in the execution of daily activities under specific assessment tests.

Quality assessment of pellets and briquettes made from glued wood waste

In accordance with sustainable economic and social development, Europe supports the use of energy from renewable sources to decrease the use of fossil fuels. Among renewable energy sources, wood, especially production wood waste from the supply chain, represents an exploitable source in line with a circular economy development. In this context, processing of residues produced by wood companies becomes an important resource. This work deals with the possible energy recovery of glued wood wastes. Two solid biofuels were produced from glued wood wastes: pellets and briquettes. They have been produced in collaboration with a local company and analyzed according to the applicable EN ISO international standards. The results were compared with the limits imposed by the standards in order to identify their quality class and their applicability to the current market. The amount of adhesive present in the wood wastes does not negatively affect the intrinsic characteristics of the material that is suitable for the production of solid biofuels. In addition, the amount of wood waste containing cross-linked polyurethane was calculated in order not to compromise the quality of solid biofuels made therefrom.

Age-Related Differences in the Online Processing of Spoken Semantic Context and the Effect of Semantic Competition: Evidence From Eye Gaze

Purpose The study examined age-related differences in the use of semantic context and in the effect of semantic competition in spoken sentence processing. We used offline (response latency) and online (eye gaze) measures, using the “visual world” eye-tracking paradigm. Method Thirty younger and 30 older adults heard sentences related to one of four images presented on a computer monitor. They were asked to touch the image corresponding to the final word of the sentence (target word). Three conditions were used: a nonpredictive sentence, a predictive sentence suggesting one of the four images on the screen (semantic context), and a predictive sentence suggesting two possible images (semantic competition). Results Online eye gaze data showed no age-related differences with nonpredictive sentences, but revealed slowed processing for older adults when context was presented. With the addition of semantic competition to context, older adults were slower to look at the target word after it had been heard. In contrast, offline latency analysis did not show age-related differences in the effects of context and competition. As expected, older adults were generally slower to touch the image than younger adults. Conclusions Traditional offline measures were not able to reveal the complex effect of aging on spoken semantic context processing. Online eye gaze measures suggest that older adults were slower than younger adults to predict an indicated object based on semantic context. Semantic competition affected online processing for older adults more than for younger adults, with no accompanying age-related differences in latency. This supports an early age-related inhibition deficit, interfering with processing, and not necessarily with response execution.

Examining the Trainability and Transferability of Working-Memory Gating Policies

Internal working memory (WM) gating control policies have been suggested to constitute a critical component of task-sets that can be learned and transferred to very similar task contexts (Bhandari and Badre (Cognition, 172, 33–43, 2018). Here, we attempt to expand these findings, examining whether such control policies can be also trained and transferred to other untrained cognitive control tasks, namely to task switching and AX-CPT. To this end, a context-processing WM task was used for training, allowing to manipulate either input (i.e., top-down selective entry of information into WM) or output (i.e., bottom-up selective retrieval of WM) gating control policies by employing either a context-first (CF) or context-last (CL) task structure, respectively. In this task, two contextual cues were each associated with two different stimuli. In CF condition, each trial began with a contextual cue, determining which of the two subsequent stimuli is target relevant. In contrast, in the CL condition the contextual cue appeared last, preceded by a target and non-target stimulus successively. Participants completed a task switching baseline assessment, followed by one practice and six training blocks with the WM context-processing training task. After completing training, task-switching and AX-CPT transfer blocks were administrated, respectively. As hypothesized, compared to CL training condition, CF training led to improved task-switching performance. However, contrary to our predictions, training type did not influence AX-CPT performance. Taken together, the current results provide further evidence that internal control policies are (1) inherent element of task-sets, also in task switching and (2) independent of S-R mappings. However, these results need to be cautiously interpreted due to baseline differences in task-switching performance between the conditions (overall slower RTs in the CF condition). Importantly though, our results open a new venue for the realm of cognitive enhancement, pointing here for the first time to the potential of control policies training in promoting wider transfer effects.

The costs (and benefits) of effortful listening on context processing: A simultaneous electrophysiology, pupillometry, and behavioral study

There is a disparity between the fields of cognitive audiology and cognitive electrophysiology as to how linguistic context is utilized when listening to perceptually challenging speech. To gain a clearer picture of how listening effort impacts context use, we conducted a pre-registered study to simultaneously examine electrophysiological, pupillometric, and behavioral responses when listening to sentences varying in contextual constraint and acoustic challenge in the same sample. Participants (N = 44) listened to sentences that were highly constraining and completed with expected or unexpected sentence-final words (“The prisoners were planning their escape/party”) or were low-constraint sentences with unexpected sentence-final words (“All day she thought about the party”). Sentences were presented either in quiet or with +3 dB SNR background noise. Pupillometry and EEG were simultaneously recorded and subsequent sentence recognition and word recall were measured. While the N400 expectancy effect was diminished by noise, suggesting impaired real-time context use, we simultaneously observed a beneficial effect of constraint on subsequent recognition memory for degraded speech. Importantly, analyses of trial-to-trial coupling between pupil dilation and N400 amplitude showed that when participants’ showed increased listening effort (i.e., greater pupil dilation), there was a subsequent recovery of the N400 effect, but at the same time, higher effort was related to poorer subsequent sentence recognition and word recall. Collectively, these findings suggest divergent effects of acoustic challenge and listening effort on context use: while noise impairs the rapid use of context to facilitate lexical semantic processing in general, this negative effect is attenuated when listeners increase effort in response to noise. However, this effort-induced reliance on context for online word processing comes at the cost of poorer subsequent memory.

Words in context: tracking context-processing during language comprehension using computational language models and MEG

The meaning of a word depends on its lexical semantics and on the context in which it is embedded. At the basis of this lays the distinction between lexical retrieval and integration, two basic operations supporting language comprehension. In this paper, we investigate how lexical retrieval and integration are implemented in the brain by comparing MEG activity to word representations generated by computational language models. We test both non-contextualized embeddings, representing words independently from their context, and contextualized embeddings, which instead integrate contextual information in their representations. Using representational similarity analysis over cortical regions and over time, we observed that brain activity in the left anterior temporal pole and inferior frontal regions shows higher similarity with contextualized word embeddings compared to non-contextualized embeddings, between 300 and 500 ms after word presentation. On the other hand, non-contextualized word embeddings show higher similarity with brain activity in the left lateral and anterior temporal lobe at earlier latencies – areas and latencies related to lexical retrieval. Our results highlight how lexical retrieval and context integration can be tracked in the brain using word embeddings obtained with computational models. These results also suggest that the distinction between lexical retrieval and integration might be framed in terms of context-independent and contextualized representations.