The creation and updating of reference frames in the brain's neocortex is a complex process that is only partially understood. The latest research validates that the brain forms “mental models” from tangible and intangible objects, places, and concepts. Our brain is equally adapted to forming a model of what a tangible thing such as a toothbrush should look and feel like, as it is a purely conceptual concept such as socialism. We see the lack of complementarity when we couple this deep understanding of how the brain learns and informs itself with the current data-embodied UI design. Why “data-driven decision-making” is such an elusive goal with the current tools and techniques suddenly becomes apparent.

The question at hand is can understanding of how the brain functions be applied to reimagine UI/UX design, increase the degree of brain/UI complementarity, and attain defined desirable outcomes such as improved understanding, enhanced intuition, or a reduction in decision errors? To, in effect, redefine the UI sensory experience by moving through data. I propose the answer is a resounding “Yes” through what I will call Multi-dimensional Object Space. I propose the answer is a resounding “Yes” through what I will call Multi-dimensional Object Space.

Multi-Dimensional Object Space (MOS) – Designing Complementarity

An issue with current business intelligence software and the standard dashboard construct is that they often fail to create a unified and robust global perception and organization of objects necessary for action-oriented decision-making. As previously stated, dashboards are purely artificial constructions and a purist form of abstractism to the brain from an evolved perspective of learning and decision-making. To elevate the brain's use of data in organizational decision-making, we must reconceptualize the UX/UI into one of extreme complementarity between tech and the brain. It is not the precept of this author that tech disappears as advocated by some, but rather, it evolves. We can use Cognitive Neuroscience as one of the foundations for what will be termed multi-dimensional object space in the UI.

It is theorized that a multi-dimensional object space of visually unique, semantically prototypical features such as physical attributes, functions, product characteristics, etc., nested in space-time will complement the primary method of reference frame formulation in the brain. The more accurate the perception and organization of objects, the more predictive it is of cognitive impact. The intent is to manipulate UI dimensions and features while leveraging organizational principles of perception to enable multi-modal cognition through dynamic user interaction with data/information to mimic movement through an ecosystem. At the design level, higher-level semantic and object relations may become ‘fine grain. Relationships such as antonymy, synonymy, and hyponymy of both words and objects on usability and memorability in the MOS become essential to test.

The UI's most definitive decision-making aspect is the conceptual visualization of data and information interrogation, augmented with a multi-layered architecture of interactable visual analytics, metrics, and measures. Images have intrinsic memorability, and research shows that the number of semantic dimensions directly correlates with cognitive functioning.Thus, creating a data-dense, multi-dimensional object space of unique 3D and 2D visual analytics, space/time, geolocation, metrics and measures, and contextual text with dynamic exploration functionality may hold the key to a next-generation UI sensory experience that enables more robust mental model formulation and correction and possibly reduces cognitive load. Cutting-edge research shows that semantic properties impact the brain more than visual properties. However, there is still debate on the roles of low-level visual features such as color.

In conceptualizing this modern UX/UI design treatment, we have many examples of possible structures and visualizations from conceptual artists. These range from modifications of current visual analytics paired with geolocation to artificial constructions such as types of cyber security hardware and patching schedules by location concerning threat or security framework. If this theoretical construction is to become a reality, practical use cases and applications are required and are in no short supply. Fundamentally, almost any use case today will apply as MOS will allow the user to approach the analysis process uniquely differently.