Comparing the cognitive Flexibility and Response Inhibition Abilities in Individuals with Mild Cognitive Impairment and Older Healthy Individuals

Cognitive flexibility refers to the ability to switch rapidly between different responses sets. It is further sub divided into set shifting and cognitive shifting. While set shifting is considered to be automatic, cognitive shifting is considered to be conscious and strategic. Cognitive shifting can be assessed through a variety of linguistic and non-linguistic tasks. The non-linguistic tasks include stroop task, non-zero task etc. The alternating fluency task is a linguistic task, built in the same lines of generative naming. The only difference is that the participant has to rapidly alternate between two lexical categories in other words has to name a lexical item from first lexical category and then name a lexical item from the other lexical category. Response inhibition is the other executive function required for performing the alternating fluency task, as it would require the participants to inhibit the response belonging to the other lexical category. The current study was taken up with the aim of comparing cognitive shifting abilities in individuals with MCI and older individuals by employing alternating fluency task. Four lexical category combinations (animals-vehicles; birds-common objects; fruits-vegetables, colours and body parts) were considered and the task of participant was to name a lexical category from each combination (at once) within a period of 2 minutes. Each correct response was given a score of 1 when the participant could produce responses from both lexical categories given. 0 was given for partial and incorrect responses. Older participants performed better compared to participants with MCI. Individuals with MCI performed poorly as the cognitive flexibility and response inhibition are found to be compromised in these individuals

Reimagining the role of the expert

User Interface (UI) design has been a core topic of HCI research for several decades. Equipped with design skills and knowledge, the expert interface designer meticulously analyses a design brief, conceptualises design ideas, and constructs viable solutions. The intended outcome of this tedious process is a usable and aesthetically-pleasing UI. Classical approaches in HCI have relied upon providing designers with guidelines, heuristics, and best practices for realising good designs. In recent years, computational approaches have turned towards formalising and automating parts of the design process. In this provocation, I claim that the future expert will hand over the task of creating design solutions entirely to the machine, and instead take on the role of an interface curator who inspects a set of feasible designs and picks out the best possible solutions for a given problem. I discuss the current state of computational interface design, and suggest a path forward towards realising this vision.Peer reviewe