Art and Psychology Blog

Delicate Tension, Wassily Kandinsky, Thyssen-Bornemisza Museum, Wikimedia Commons, Date Accessed: November 1, 2021.

“Each color lives by its mysterious life.” – Wassily Kandinsky

Wassily Kandinsky’s Delicate Tension is a great example of the ability of color and shape to tell their own story. Kandinsky felt that circles and triangles were the two most primary and conflicting shapes, which creates a sense of tension in this watercolor painting. Larger shapes are subdivided by intersecting lines which create a latticework of color. Primary colors dominate these subdivisions giving each compartment a life of its own. These compartments lend a sense of harmony to what would otherwise be a conflicting and dissonant image. Each independent color is surrounded by barriers that keep it from blending into something our mind would struggle to disentangle. Every color unimpeded by the lack of agreement surrounding it. Sometimes our mind can function like the colors in Kandinsky’s painting, separating thoughts and ideas into boxes which don’t agree with the prevailing narrative. Those thoughts may even have lives of their own with rationales that don’t fit with our sense of self. These micro conflicts can occasionally create a sense of tension within. Yet when we take a step back, everything seems perfectly ordered and those compartmentalized thoughts appear structured by intention. Perhaps that is how Kandinsky felt while composing this work. There is a balance between harmony and dissonance, and that balance rests on a series of thin lines. Conflicting narratives of self can be subdivided to expose commonalities and discordances. All the while, differences can be comfortably resolved through the process of compartmentalization.

Purkinje Cells and Granule Cells From Pigeon Cerebellum, Santiago Ramon y Cajal, Instituto Santiago Ramon y Cajal, Wikimedia Commons, Date Accessed: May 7, 2020.

“Nature is a harmonious mechanism where all parts, including those appearing to play a secondary role, cooperate in the functional whole.” – Santiago Ramón y Cajal

· Out on my back patio I am gazing at the silhouette of black trees set against a blue grey Colorado sky. Like so many of the famed neuroscientist Santiago Ramón y Cajal’s neuron drawings, the branches intertwine to form a dense network of life. Each individual branch contributes to the overall brilliance of the display. The illustrations of neuron forests that Cajal is so famous for exhibit the same dense connectivity, with individual neurons weaving to and fro in a montage of organized chaos. Much like the leaves on the tree forming a net to receive sunlight, the dendrites on Cajal’s Purkinje cells reach out to receive impulses from other neurons. In Cajal’s time, little was known about how the organization of these independent cells contributed to the functioning of the human brain. Now over 100 years after the start of these pivotal drawings more is known at both the cellular and cognitive level. Perhaps Cajal even had an intuition that the glial cells so often depicted in his cellular renderings were much more than meets the eye. His observations on the importance of all the secondary contributions in nature were far ahead of his time. Today, how many times can we write a great algorithm, only to have the program fail because of a flaw in its dependencies. Doctors around the world have always grappled with prescribing the “right” medication for a patient, due to the complexity of secondary drug interactions. Even the most beautiful oil portrait can look unappealing if presented in a gallery with the wrong lighting conditions. With modern technology moving at such a quick pace, it’s important to take a moment to appreciate all of the smaller parts which make up the cohesive whole. When we start looking at the individual parameters and components, even those of trivial importance, we may be able to better see the forest through the trees.  

Portrait of Daniel-Henry Kahnweiler, Pablo Picasso, Art Institute of Chicago, Wikipedia, Date Accessed: May 6, 2020.

“But they are useless. They can only give you answers.” – Pablo Picasso 

· If Picasso were alive today, he would no doubt be taken aback by the exponential advances in computing that have been made in the past few decades. A far cry from the giant mechanical brains and mere calculating machines of the 1960’s, today’s computers look like yesterday’s science fiction. Glancing at Picasso’s 1910 masterpiece “Portrait of Daniel-Henry Kahnweiler”, you have to wonder what modern day computers would make of such abstract works of art. Deep learning visual processing systems have become experts at tagging our friends in photos, but could they derive meaning from such a composite image of loose shapes and forms? Plenty of AI software packages can create art. Recognizing what unique pieces make an abstracted version of Daniel-Henry Kahnweiler is a little more tricky. To accomplish this feat a deep learning system would need to perform feature extraction on the image and somehow make a connection to not only Picasso’s particular style, but mimic his emotive state at the time. This seems like a tall order for the current state of machine learning. Nonetheless, advances in machine learning are happening all the time in areas as diverse as art and psychology. For instance, the field of artificial empathy is blooming with robots and virtual agents that can both detect and respond to a wide range of human emotions. Is it too far fetched to see this technology harnessed to mimic specific emotive states, including those associated with artistic expression? Could these abilities then be used to more fully “understand” Picasso’s mental state while he was painting this iconic portrait in 1910? If all of this was somehow quantifiable, the benefits to society at large would be immense. Psychology would have a new window into the creative mind and art could be appreciated from new and exciting perspectives. Once the layers of abstraction are peeled away, understanding the creative mind may become more logic driven. Perhaps then we could better understand the black box containing this logic.