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NeuraMod

Architectural Modelling with Neural Potentials.

Lay Summary

The project aims at assessing a new modelling approach, in the early design phases, involving human and artificial intelligence to generate meaningful architectonic articulations from visuosemantic tokens and neural responses. Its goal is to contribute to the next generation of grammar-less methods which should allow for greater variance in design explorations.

By researching brain-computer interfaces for generative architectural modelling, this project will elaborate progressively on a technical infrastructure, allowing for the production and evaluation of visuospatial and physical experiments.

As a Use-Inspired Basic Research project, it aims at establishing significant basic theoretical and technical knowledge which, by its modalities, might also address consequently a much larger audience than expert practitioners. Its scope of development should allow for a wide array of use cases and create an ideal ground for near-future implementations through further technology transfer mechanisms.

The project’s schedule is organised in two main phases in a progressive and iterative fashion. While the first phase consists of integrating pluridisciplinary technical and theoretical knowledge from the scientific fields involved in Computer-Aided Architectural Design and Cognitive Science, the second phase focuses on implementing learned methods for the modelling of architectural prototypes at a small scale.

Description

A great part of Brain-Computer Interfaces research has so far, been focusing on interactions using exogenous responses under selective attention with synchronous and reactive methods for clear relation with controlled stimuli and the widespread applicability of the methods. Over the two past decades, Event-Related Potentials have become more and more investigated for a broader community of researchers due to the relatively little amount of training necessary for a system to perform and their detection across diverse modalities of acquisition to correlate with the sensory discrimination of dedicated stimuli.

The proposed study aims to observe the detection of Event-Related Potentials components and correlated neural phenomena under the visual presentation of complex stimuli and devise processing methods that would generalize their classification and cardinality for applications in Computer-Aided Architectural Design, where visual complexity becomes an intrinsic feature of the tasks. Its objective is exploratory and twofold: evaluating data processing and stimulus presentation methods, as well as the evolution of similar responses in repeated measures intra- and inter-subjects in non-clinical states.

Funding & Institutions

The Neuramod project is fully funded by the Swiss National Science Foundation SNSF Project Funding Div. 1-2 for Humanities, Social sciences, Mathematics, Natural and Engineering sciences. It is hosted at the Institute of Technology for Architecture (ITA), Chair of Digital Architectonics (CAAD) of ETH Zürich. Its two main individual partners are Dr. Ricardo Chavarriaga from the Center for Artificial Intelligence (CAI) of ZHAW Zürich, and Dr. Marco Congedo from the Vision and Brain Signal Processing Group (GIPSA) of CNRS Grenoble. Further secondary partnerships might be sought along the project for complementing advisory, scientific or industrial expertises.

Aim

A use-inspired Basic Research Project for a novel architectural modelling technology.

Hypotheses

The general hypotheses, regarding decisions under uncertainty, is that covert responses found in physiological data may allow for a greater variance than behavioral ones. But a systemization of the process is necessary for evaluation. Logical discrimination is generally framed by 4 distinct classification outcomes labeling an instance whether or not to be positively mapped to a label. While it is widely used in BCI classification methods, in correlation with labeled stimuli under attention, it becomes insufficient or even inappropriate when lacking labels and elicitations come from complex and ambiguous inputs. Classes may become unbalanced, and labels absent from the design of the task.

There should be, however, a minimal amount of found classes involved in particular sensory discrimination under a logical framework, once provided with a standardized presentation of these stimuli. Their cardinality should remain independent from the informational complexity of the stimulus but should be factored by cognitive parameters linked to attention such as stimulus probability, mental workload, and the user’s literacy in practicing with a BCI. Moreover, the separation of these classes under uncertainty should allow for a generalization inter-session and inter-subject given the development of adequate adaptive learning methods on a prolonged usage basis.

Relevance

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Impact

Timeline

Every milestone event of the project put as a timeline along its duration.

Mar. 2020

Project Funded by SNSF!

The Swiss National Science Foundation (SNSF) has officially granted full funding to the Neuramod project for a period of 48 months. Under both Divisions 1-2 (Humanities & Social Sciences / Mathematics, Natural & Engineering Sciences), the project has been selected among 245 related applications to start in 2021

Feb. 2021

Neuramod has begun

Hosted at the Chair of Digital Architectonics (Prof. Dr. Hovestadt, fka. CAAD) within the Institute of Technology for Architecture (ITA) and the Department of Architecture (D-ARCH) of ETH Zürich, the project will focus on the prototyping and development of new modeling technologies with neural potentials. It will run until 2024

Oct. 2021

Phase 1 launched

After careful design and preparations, the first phase of our BCI experiments has been reviewed by the Ethics Committee and granted green light. An initial sample of the population involved in the activity sector of the built environment will participate in data acquisition sessions, with the support of the Neurolab and the COG Chair of D-GESS ETH.