The Art of Seeing and Painting

The human urge to represent the three-dimensional world using two-dimensional pictorial representations dates back at least to Paleolithic times. Artists from ancient to modern times have struggled to understand how a few contours or color patches on a flat surface can induce mental representations of a three-dimensional scene. This article summarizes some of the recent breakthroughs in scientifically understanding how the brain sees that shed light on these struggles. These breakthroughs illustrate how various artists have intuitively understand paradoxical properties about how the brain sees, and have used that understanding to create great art. These paradoxical properties arise from how the brain forms the units of conscious visual perception; namely, representations of three-dimensional boundaries and surfaces. Boundaries and surfaces are computed in parallel cortical processing streams that obey computationally complementary properties. These streams interact at multiple levels to overcome their complementary weaknesses and to transform their complementary properties into consistent percepts. The article describes how properties of complementary consistency have guided the creation of many great works of art.

Museum of foreign literature, science and art.

Edited at first by Robert Walsh, Jr. and then by Eliakim and Squier Littell, the monthly Museum of Foreign Literature, Science, and Art was the leading American eclectic for twenty years. Much of its contents were selected from British magazines; included were reviews, poetry, literary and scientific news, biographical sketches of British authors, lists of new British publications, and articles on literature. The engraved portraits in each number were a popular feature. After 1830, plates were published regularly, and the magazine began to devote a large proportion of its space to serial fiction by Dickens, Reade, Bulwer, Thackeray and other popular English novelists.

Saturday review of politics, literature, science and art.

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Integrated science and art education for creative climate change communication

An interdisciplinary field trip to a remote marine lab joined graduate students from fine arts and natural resource science departments to think creatively about the topic of climate change and science communication. We followed a learning cycle framework to allow the students to explore marine ecosystems and participate in scientific lectures, group discussions, and an artist-led project making abstract collages representing climate change processes. Students subsequently worked in small groups to develop environmental communication material for public visitors. We assessed the learning activity and the communication product using pre- and post-field trip participant surveys, focus group discussions, and critiques by art and communication experts of the products. Significant changes in knowledge about climate change occurred in program participants. Incorporating artists and the arts into this activity helped engage multiple senses and emphasized social interaction, as well as providing support to participants to think creatively. The production of art helped to encourage peer learning and normalize the different views among participants in communicating about climate change impacts. Students created effective communication products based on external reviews. Disciplinary differences in cultures, language, and standards challenged participating faculty, yet unanticipated outcomes such as potentially transformative learning and improved teacher evaluations resulted.

Neuroscience and Hindu Aesthetics: A Critical Analysis of V.S. Ramachandran’s “Science of Art”

Neuroaesthetics is the study of the brain’s response to artistic stimuli. The neuroscientist V.S. Ramachandran contends that art is primarily “caricature” or “exaggeration.” Exaggerated forms hyperactivate neurons in viewers’ brains, which in turn produce specific, “universal” responses. Ramachandran identifies a precursor for his theory in the concept of rasa (literally “juice”) from classical Hindu aesthetics, which he associates with “exaggeration.” The canonical Sanskrit texts of Bharata Muni’s Natya Shastra and Abhinavagupta’s Abhinavabharati, however, do not support Ramachandran’s conclusions. They present audiences as dynamic co-creators, not passive recipients. I believe we could more accurately model the neurology of Hindu aesthetic experiences if we took indigenous rasa theory more seriously as qualitative data that could inform future research.

Complimentary collaborations: Teachers and researchers co-developing best practices in art education

Australia is currently experiencing a huge cultural shift as it moves from a State-based curriculum, to a national education system. The Australian State-based bodies that currently manage teacher registration, teacher education course accreditation, curriculum frameworks and syllabi are often complex organisations that hold conflicting ideologies about education and teaching. The development of a centralised system, complete with a single accreditation body and a national curriculum can be seen as a reaction to this complexity. At the time of writing, the Australian Curriculum is being rolled out in staggered phases across the states and territories of Australia. Phase one has been implemented, introducing English, Mathematics, History and Science. Subsequent phases (Humanities and Social Sciences, the Arts, Technologies, Health and Physical Education, Languages, and year 9-10 work studies) are intended to follow. Forcing an educational shift of this magnitude is no simple task; not least because the States and Territories have and continue to demonstrate varying levels of resistance to winding down their own curricula in favour of new content with its unfamiliar expectations and organisations. The full implementation process is currently far from over, and far from being fully resolved. The Federal Government has initiated a number of strategies to progress the implementation, such as the development of the Australian Institute for Teaching and School Leadership (AITSL) to aid professional educators to implement the new curriculum. AITSL worked with professional and peak specialist bodies to develop Illustrations of Practice (hereafter IoP) for teachers to access and utilise. This paper tells of the building of one IoP, where a graduate teacher and a university lecturer collaborated to construct ideas and strategies to deliver visual arts lessons to early childhood students in a low Socio- Economic Status [SES] regional setting and discusses the experience in terms of its potential for professional learning in art education.

ART-EMAP: A Neural Network Architecture for Object Recognition by Evidence Accumulation

A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object recognition from a series of ambiguous 2-D views. The architecture, called ART-EMAP, achieves a synthesis of adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). ART-EMAP extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage 1 introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory (MTM). Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Each ART-EMAP stage is illustrated with a benchmark simulation example, using both noisy and noise-free data. A concluding set of simulations demonstrate ART-EMAP performance on a difficult 3-D object recognition problem.

Fuzzy ART

Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks by exploiting the formal similarity between the computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic: intersection (∩) with the fuzzy intersection (∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric: theory in which the fuzzy inter:>ec:tion and the fuzzy union (∨), or component-wise maximum, play complementary roles. Complement coding preserves individual feature amplitudes while normalizing the input vector, and prevents a potential category proliferation problem. Adaptive weights :otart equal to one and can only decrease in time. A geometric interpretation of fuzzy AHT represents each category as a box that increases in size as weights decrease. A matching criterion controls search, determining how close an input and a learned representation must be for a category to accept the input as a new exemplar. A vigilance parameter (p) sets the matching criterion and determines how finely or coarsely an ART system will partition inputs. High vigilance creates fine categories, represented by small boxes. Learning stops when boxes cover the input space. With fast learning, fixed vigilance, and an arbitrary input set, learning stabilizes after just one presentation of each input. A fast-commit slow-recode option allows rapid learning of rare events yet buffers memories against recoding by noisy inputs. Fuzzy ARTMAP unites two fuzzy ART networks to solve supervised learning and prediction problems. A Minimax Learning Rule controls ARTMAP category structure, conjointly minimizing predictive error and maximizing code compression. Low vigilance maximizes compression but may therefore cause very different inputs to make the same prediction. When this coarse grouping strategy causes a predictive error, an internal match tracking control process increases vigilance just enough to correct the error. ARTMAP automatically constructs a minimal number of recognition categories, or "hidden units," to meet accuracy criteria. An ARTMAP voting strategy improves prediction by training the system several times using different orderings of the input set. Voting assigns confidence estimates to competing predictions given small, noisy, or incomplete training sets. ARPA benchmark simulations illustrate fuzzy ARTMAP dynamics. The chapter also compares fuzzy ARTMAP to Salzberg's Nested Generalized Exemplar (NGE) and to Simpson's Fuzzy Min-Max Classifier (FMMC); and concludes with a summary of ART and ARTMAP applications.

Fuzzy ART Choice Functions

Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP networks synthesize fuzzy logic and ART by exploiting the formal similarity between tile computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic intersection (∩) with the fuzzy intersection(∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric theory in which the fuzzy intersection and the fuzzy union (∨), or component-wise maximum, play complementary roles. A geometric interpretation of fuzzy ART represents each category as a box that increases in size as weights decrease. This paper analyzes fuzzy ART models that employ various choice functions for category selection. One such function minimizes total weight change during learning. Benchmark simulations compare peformance of fuzzy ARTMAP systems that use different choice functions.

Normal and Amnesis Learning, Recognition, and Memory by a Neural Model of Cortico-Hippocampal Interactions

The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such model class (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how inferotemporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia may be caused by lesions in the hippocampal formation. The model also suggests how hippocampal and inferotemporal processing may be linked during recognition learning.

Discourse and soul: Jung, literature, science and tragedy as mythical writing

This paper will propose that literature and science, far from being discrete spheres of cultural activity, are, in fact, the cultural expressions of interlocking myths. They therefore overlap and even take each other’s places, as examination of the ‘science��� of C.G. Jung and the ‘art’ of a writer such as John Cowper Powys, will show. ‘Dis-course’, I argue, is the material aspect of the mythical structuring of psychic experience. In the work of Jung and Powys, discourse is the articulation of the soul in the world that spans personal, social, natural and cosmic space. [From the Author]

Analectic magazine and naval chronicle [microform.]

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Lettres sur le préjudice qu'occasionneroient aux arts et à la science, le déplacement des monumens de l'art de l'Italie, Le démembrement de ses ecoles, et la spoliation de ses collections, galeries, musées, &c.

Mode of access: Internet.

Mardelle Shepley: Art+Science

Mardelle Shepley, associate director of the Cornell Institute for Healthy Futures and professor of design and environmental analysis, presents at the Cornell Family Fellows event, "Where Art, Science, and Technology Intersect – Fostering Innovation at Cornell," on April 30, 2016. When campus leaders link art, science, and technology through interdisciplinary collaboration and experimentation, extraordinary advancements emerge.