Neuro Architectural Design

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Neuro Architectural Design

Fahd Abd ElAziz Hemeida Hamad Hassan Mostafa Department Of Architectural Engineering and Environmental Design, Faculty of Engineering & Technology, Arab Academy for Science and Technology and Maritime Transport, Alexandria, Egypt [email protected] [email protected]

Neuro Architectural Design The relationship between the human mind and creativity in design is always confusing where it is interspersed with a lot of consequences that might hinder the design process. Since the beginning of creation, the design is constantly evolving. However, architectural science has lately witnessed tremendous boom in the use of computers to express complex geometric shapes that were difficult to move from the mind to the drawings. The design process relies in all stages of the transfer on signals from the right lobes of the brain to the nerves and then to the hand to carry whatever information that is reached by the mind to graphics. With the development of science, design three-dimensional programs have begun to rely on coordinates instead of the two-dimensional drawing and turn it into perspective. Therefore, it is possible to imagine that there could be a direct connection between the waves of the human mind and programs in order to design the coordinates of the cell is to be the future design codes. Keywords: Neuroscience; Brain decoding; 3D Brain visualization; Architectural Design process; Brain computer interface.

Introduction: Design is a complex process with a beginning of known inputs, liabilities and unlimited results. Three consecutive and overlapping phases are the key to find out the translation sequence of the ideas during the design process; (1) the initial cognition of the design problems where the mind in case of dispersion, interfering information and when it issuance gamma waves; (2) a stage of dealing with the design inputs and the deep thinking about solutions, alternatives. The mind is in a state of concentration and excitability mental severe where the mind in the event of issuance of beta waves; (3) the case of alpha waves which is characterized by extraction the unlimited results, permeates the second phase and the third a state of brainstorming where it shows most cases of mental inspiration.

Figure 1. How the brain work Traditional Design Process: According to the development of these applications, the Traditional Design Process (TDP) has changed. It depends on the limits of the time, location and the users. It exceeds these limits to give man new forms in the virtual educational spaces. It affects the design process of the present real spaces since it adds a new dimension which is not expected. By mixing reality and imagination, it gives man possibilities to reform reality according to new fields of unlimited technology.  Development of the architecture design process occurs according to the development of the tools and the architecture application.  As the result of the development of computer technology, a new dimension of the architectural design and presentation is achieved. With the development of the educational process, it is logical to create an impact on the design process of the educational spaces, generating a new functional space resulting from these developments (Hassan, Hamad, 2012).

Figure 2. The process of Traditional Design Studio (Hassan, Hamad, 2012)

EEG Background and The Brain Activity:

Figure 3. Artistic illustration of a single neuron and its synapses (Kropotov, 2009) The brain has always fascinated humans, and particularly a German scientist named Hans Berger, who has discovered electroencephalography (EEG) about 80 years ago. After this, new methods for exploring it have been found and which can be categorized into two main groups; invasive and non-invasive. An invasive approach requires physical implants of electrodes in humans or animals, making it possible to measure single neurons or very local field potentials. A non-invasive approach makes use of, for instance, magnetic resonance imaging (MRI) and EEG technology to make measurements. Both gives different perspectives and enables us to look inside the brain and to observe what happens (Kropotov, 2009). In EEG, brain-related electrical potentials are recorded from the scalp. Pairs of conductive electrodes(see figure 7) made of silver, for example, are

used to read this electricity (Larsen, Erik Andreas, 2011). Figure 4. The 1020 System - Standardized placement of electrodes on scalp for EEG measurements (Immara, N.D.)

Identifying Different Brain Activity Patterns: Returning to Berger, he has found that different electrical frequencies could be linked to actions and different stages of consciousness. This is done by observing subjects performing different tasks, like solving mathematical problems, while recording their EEG. Figure 5 shows the most frequency used bands, and their relations, of the human brain wave activity. Figure 5. Gamma wave

Figure 6. Beta wave

Figure 7. Alpha wave

Figure 8. Theta wave

Figure 9. Gamma wave

Gamma waves are in the frequency range of 31Hz and up. It is thought that it reflects the mechanism of consciousness. Beta and gamma waves together have been associated with attention, perception, and cognition (Rangaswamy et al., 2002). Beta waves are in the frequency range of 12 and 30 Hz, but are often divided into β1 and β2 to get a more specific range. The waves are small and fast, associated with focused concentration and best defined in central and frontal areas. When resisting or suppressing movement, or solving a math task, there is an increase of beta activity (Y. Zhang, Chen, Bressler, & Ding, 2009). Alpha waves, ranging from 7.5 to 12 Hz, are slower and associated with relaxation and disengagement. Thinking of something peaceful with eyes closed should give an increase of alpha activity. Most profound in the back of the head (o1 and o2, figure 4) and in the frontal lobe (Lukas, Mendelson, & Benedikt, 1995). Theta waves, ranging from 3.5 to 7.5 Hz, are linked to inefficiency, daydreaming, and the very lowest waves of theta represent the fine line between being awake or in a sleep state. Theta arises from emotional stress, especially frustration or disappointment (L. Zhang, He, Miao, & Yang, 2005). It has also been associated with access to unconscious material, creative inspiration and deep meditation. High levels of theta are considered abnormal in adults, and are, for instance, much related to AD/HD (Heinrich, Gevensleven, & Strehl, 2007). Delta waves, ranging from 0.5 to 3.5 Hz, are the slowest waves and they occur when sleeping (Hammond, 2006). If these waves occur in the wake state, it thought to indicate physical defects in the brain. Movement can make artificial delta waves, but with an instant analysis (just observing raw EEG records), this can be verified or unconfirmed.

Table 1. The Human Brain Wave Activity (Larsen, Erik Andreas, 2011) Figure 5. The 5 main frequency bands and their relation to each other (Larsen, Erik Andreas, 2011) MU is associated with motor activities, and is also found in the alpha wave frequency range, but where the maximum amplitude is recorded over motor cortex. Thus, it is basically triggered when there is an actual movement or there is an intent to move (Bernier, Dawson, Webb, & Murias, 2007). All these wave-groups occur in different parts of the brain in varying degree. The Involved Brain Areas with Architecture: Perceiving buildings is a complex process. It involves sensations such as seeing but also perception. Experience with other prior buildings is also of importance. How do we store and recall our sensory experiences when it comes to architecture, namely, buildings. Evaluation, decision making, emotions and affect, as well as interaction, movement all play a part in the neuroscience of architecture. Research on neuroscience and brain location is scarce. In 1999, Nancy Kanwisher and her associates published an article in Neuron (Epstein et al., 1999) that established grounds for linking the brain to experiences with architecture. She called the place in the brain where this link is made to the parahippocampal place area (PPA). The PPA is defined as the set of all contiguous voxels within the parahippocampal region that respond significantly more during viewing of scenes than during viewing of faces or objects. They found that PPA activity (1) is not affected by the subjects' familiarity with the place depicted, (2) does not increase when subjects experience a sense of motion through the scene, and (3) is greater when viewing novel versus repeated scenes. The authors had earlier reported that the PPA was significantly more active when subjects viewed complex scenes such as rooms with furniture, landscapes, and city streets than when they viewed photographs of objects, faces, house (elevations), or other kinds of visual stimuli. By place recognition, the authors mean the matching of current perceptual information to the memories of places that had been encountered in the past and stored in one's cognitive map. They do not use the term disposition, but it seems likely that what is stored in the PPA are the dispositions of past experiences of these buildings (John P. Eberhard, 2009).

Neuro Architecture:

Figure 6. Neuro Architecture

Design Process

In the twenty-first century, after the boom of technology evolution especially in computer neuroscience, it is impossible that the methods of architectural design remain the same as before but it must keep pace with this tremendous development.

Figure 7. Neuro Architecture Insulation In order to reach the summit of creativity in the use of the new settings, there should be a vision for the new order of modern design process. This perception will be based on a combination between augmented reality, neuroscience and architecture through the use of virtual reality glasses and mind-waves headset to integrate the designer inside the virtual space in order to be part of this reality and then the design process begins by the transmitted waves from the mind of the architect in order to be realized directly inside the 3D environment.

Neuro Architecture Design Principles: First step will be the awareness of architect concerning the design problems which will affect the design process. The second phase will be the connection of devices to architect's mind in order to be interactive with the cyber space and controlled by brain cells and then the design process starts with site plan, buildings, roads and landscaping, etc. Finally, the design process will synchronize with the thinking of the architect's mind inside the 3D environment. Conclusion: Future architectural design codes will be the preliminary results of this merge between the different specialties to get the top of innovation and development in the field of architecture. This evolution will have some impacts; these include:  Redefining the architecture design process from traditional way of 2D sketching, drafting then 3D simulation to another vision of fully interactive with the 3D

virtual environment with the possibility of real time modifications. Figure 8. Development of architecture design tools  The chance which can be given to users and clients to interaction the cyberspace with the architects using the new architectural tools to express the hidden ideas.  Reshaping of architecture design studio will be a must to adopt with the new vision of neuro architecture. References: Bernier, R., Dawson, G., Webb, S., & Murias, M. (2007, August). EEG mu rhythm and imitation impairments in individuals with autism spectrum disorder.Brain and cognition, 64(3), 228–37. Epstein, R., Harris, A., Stanley, D., and Kanwisher, N. (1999). Neuron 23, 115–125. Hammond, D. C. (2006). What is Neurofeedback? Journal of Neurotherapy, 10:4, 11. Hassan, Hamad, 2012. The Impact of Information and Communication technology ICT on architectural form of higher educational spaces. Master thesis.

Heinrich, H., Gevensleven, H., & Strehl, U. (2007). Annotation: Neurofeedback - train your brain to train behaviour. Journal of Child Psychology and Psychiatry, 48:1, 3–16. Immrama. (n.d.). Available from http://www.immrama.org/eeg/electrode.html John P. Eberhard, 2009. Applying Neuroscience to Architecture. Neuron, Volume 62(6):753-756. Kropotov, J. D. (2009). Quantitative EEG, Event-Related Potentials And Neurotherapy. 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA: Elsevier Inc. Larsen, Erik Andreas, 2011. Classification of EEG Signals in a Brain-Computer Interface System. Thesis, Master of Science in Computer Science. Lukas, S. E., Mendelson, J. H., & Benedikt, R. (1995, February). Electroencephalographic correlates of marihuana-induced euphoria. Drug and alcohol dependence, 37(2), 131–40. Available from http://www.ncbi.nlm.nih.gov/pubmed/7758402 Rangaswamy, M., Porjesz, B., Chorlian, D. B., Wang, K., Jones, K. a., Bauer, L. O., et al. (2002, October). Beta power in the EEG of alcoholics. Biological psychiatry, 52(8), 831–42. Available from http://www.ncbi.nlm.nih.gov/pubmed/12372655 Zhang, Y., Chen, Y., Bressler, S. L., & Ding, M. (2009). Response preparation and inhibition: The role of the cortical sensorimotor beta rhythm. Neuroscience, 156:1, 238–246. Zhang, L., He, W., Miao, X., & Yang, J. (2005, January). Dynamic EEG Analysis via the Variability of Band Relative Intensity Ratio: A Time-Frequency Method. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 3(1), 2664–7. Available from http://www.ncbi.nlm.nih.gov/pubmed/17282787

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