Science
Communication
I am interested in open science and passionate about making science & technology accessible to as many people as possible. I use photography as a medium to engage people in scientific themes.
Embedded Files
Book Review: Mama’s Last Hug: Animal Emotions and What They Tell us about Ourselves by Frans de Waal published in Natural Selections Magazine: http://selections.rockefeller.edu/review-mamas-last-hug-animal-emotions-and-what-they-tell-us-about-ourselves/?fbclid=IwAR0OH0AWvMuQddHS6mLhvTEYoh8vr9iq--RLf2ZFLPaaQz2QxwhYzykKdL0.
Public talk about Faces & Facial Expressions at The Science is Everywhere Festival with Biobus & RockEDU as part of the Brain Awareness week 2021 ( in Spanish / en Español) https://www.youtube.com/watch?v=hOpIPzwVJfY
WHAT MAKES YOU MOVE? for the Incubator Blog at RockEDU SCIENCE OUTREACH:
LOS ROSTROS DE CHUCK CLOSE: CALLE 86 Y SEGUNDA AVENIDA
Chuck Close, el renombrado artista estadounidense, tenía un enfoque único para crear retratos. Este enfoque estaba profundamente influenciado por su prosopagnosia o ceguera de rostros. Este trastorno neurológico, hacía muy difícil que Close reconociera o distinguiera distintos rostros. Sin embargo, la prosopagnosia de Close, no fue un obstáculo para su desempeño artístico, sino por el contrario fungió como una fuerza motora que impulsó su trabajo artístico.
Los retratos de Close, que se exponen actualmente en la estación de la calle 86 en la línea Q del metro de Nueva York, muestran su estilo único de convertir fotografías en pinturas al dividirlas en pequeños mosaicos individuales. Estos mosaicos, similares a los píxeles de una imagen digital amplificada, se juntan para formar rostros increíblemente realistas, que nuestro cerebro percibe y reconoce con facilidad. Pero, ¿cómo es que nuestro cerebro es capaz de percibir estos rostros formados por pequeños mosaicos?
La percepción y el reconocimiento de rostros son procesos fundamentales que facilitan las interacciones sociales. Cuando percibimos un rostro, obtenemos información acerca de la identidad de la persona, su estado de ánimo, y su atención en cuestión de segundos. Por ejemplo, cuando miramos el retrato de Sienna, realizado por Close, en segundos percibimos: una mujer, afroamericana, joven, con actitud pensativa.
Nuestro cerebro está equipado con mecanismos especializados en procesar y reconocer rostros. Uno de los descubrimientos científicos más importantes en este campo, fue el descubrimiento de lo que se conoce en inglés como “face patches”: regiones en la corteza cerebral -con varios milímetros de diámetro, especializadas en el procesamiento de rostros. Estos “face patches” o “áreas de procesamiento facial” contienen neuronas responsivas a caras, es decir, neuronas que aumentan su actividad -el número de potenciales de acción por unidad de tiempo, cuando observamos un rostro. Estas áreas de procesamiento facial se encuentran a lo largo de la corteza temporal1 y prefrontal2 (PFC) en el cerebro de los primates.
El descubrimiento de las neuronas especializadas en la percepción de caras se remonta a 1972, cuando Charles Gross, encontró que ciertas neuronas en la corteza inferotemporal de monos responden selectivamente a caras. Los experimentos demostraron un aumento en la tasa de disparo de las neuronas, cuando el mono miraba los rostros de otros monos o rostros humanos3,4.
Estudios posteriores han demostrado que las neuronas en estas “áreas de procesamiento facial”, prefieren “caras” sobre otros estímulos como objetos, lugares o partes del cuerpo 4,5. La información de un rostro es transformada de un estado inicial, donde las neuronas responden a representaciones específicas como la geometría de los atributos faciales y su orientación, hacia un estado final donde las neuronas responden a representaciones más abstractas u holísticas como lo es la representación de la identidad 6,7 . Por ejemplo, en los estados de procesamiento inicial nuestras neuronas responden a detalles como qué tan cerca está un ojo del otro, o si el retrato de Sienna nos mira de frente o de perfil. Mientras que en estados de procesamiento más tardío, nuestras neuronas responden a la identidad de Sienna no importa si su rostro nos mira de frente o de perfil, o si sonríe o está enojada.
En 1997, Nancy Kanwisher, utilizando la técnica de imagenología por resonancia magnética funcional (fMRI) en humanos, descubrió que el cerebro humano contiene módulos. La técnica de fMRI mide de manera indirecta la actividad de las neuronas, midiendo el flujo sanguíneo en el cerebro. Kanwisher descubrió que el cerebro humano posee varios módulos, cada uno de los cuales procesa información sobre rostros, cuerpos y lugares. Las siguientes áreas: 1) área fusiforme (FFA), 2) área occipital (OFA) y 3) área posterior (pSTS), forman parte del módulo encargado de procesar rostros en humanos8.
Autoretrato (2017) Hand-glazed ceramic
Sienna (2017) Stained Glass micro-mosaic
Ojo detalle en Sienna (2017)
Ojo detalle en Autoretrato: Yellow Raincoat (2017). Stained Glass micro-mosaic
Lou (2017) Hand-glazed porcelain and stoneware tile
Cecily (2017) Tumbled Glass Smalti
Es importante destacar que la percepción de caras no solo implica la percepción, sino el reconocimiento de estos rostros e interpretación de expresiones faciales. Estos procesos son esenciales para la comunicación social y la percepción de estados internos. Las áreas de procesamiento facial en el lóbulo frontal9, contienen neuronas que se activan en función de la expresión facial. Otras ”áreas de procesamiento facial” se activan cuando observamos rostros familiares, por ejemplo cuando miramos el rostro de un ser querido o a Lou Reed 10.
Todas estas “áreas de procesamiento facial” forman parte de una gran red neuronal, cuyas funciones son percibir, discriminar rostros o expresiones faciales, así como interactuar con otras regiones encargadas de guardar en la memoria estos rostros. Cuando alguno de los componentes de esta red se daña, por un accidente cerebrovascular o por déficits genéticos, estas funciones se ven severamente afectadas.
Chuck Close, creador de los rostros que ilustran esta publicación, sufria de prosopagnosia o ceguera facial. La prosopagnosia es una condición que dificulta el reconocimiento de rostros 11. El término proviene del griego prosopon (cara) y gnosis (conocimiento). Las personas con prosopagnosia tienen dificultad para determinar si un rostro es familiar, y no pueden identificar a otros por su rostro. También, les es difícil discriminar entre distintos rostros. La prosopagnosia se limita a rostros y es independiente del procesamiento de otros estímulos visuales e.g. objetos y letras. Las personas con prosopagnosia se valen de otro tipo de información sensorial e.g. la voz, el olor, entre otros para preservar la identidad de otras personas.
En el caso de Chuck Close, su condición de ceguera facial le permitió tener un enfoque único, el cual influyó crucialmente su trabajo artístico. Close hizo retratos como una forma de grabar las imágenes de sus seres queridos en la memoria, ya que debido a la prosopagnosia que sufría le era imposible reconocer rostros. Para Close, si alguien movía el rostro medio centímetro, la percepción de ese rostro se tornaba en la de un rostro completamente nuevo. Por esta razón a menudo cuando salía a la calle no reconocía a las personas con las cuales tuvo largas conversaciones la noche anterior.
La prosopagnosia de Close, lejos de ser un obstáculo, se convirtió en una fuente de inspiración y una fuerza impulsora en su arte. Su enfoque único y su habilidad para transformar una fotografía en una pintura a través de marcas individuales, es un testimonio de su inquebrantable búsqueda de innovación. A pesar de su ceguera facial, Close encontró una manera de ver y recordar rostros a través de su arte, demostrando que incluso los desafíos más grandes pueden convertirse en oportunidades para la creatividad y la innovación.
Referencias:
Este artículo de divulgación científica fue creado en colaboración con Platogram y está basado en los siguientes contenidos de audio-video y referencias bibliográficas:
a) “Detrás de Nuestra Sonrisa” | Yuriria Vázquez, Semana Internacional del Cerebro, Morelia Michoacan, 2024.
Platogram link: https://web.platogram.ai/summary?coll=public&id=hOpIPzwVJfY
b) In the Studio: Chuck Close | White Cube
Platogram link: https://web.platogram.ai/summary?coll=public&id=m3y7fMA23co
1.- Perret DI, Smith PAJ, Potter DD, Mistlin AJ, Head AS (1984) Neurons responsive to faces in the temporal cortex: studies of functional organization, sensitivity to identity and relation to perception. Hum. Neurobiol. 3: 197-208.
2.- O’Scalaidhe SP, Wilson FAW, Goldman-Rakic PS (1997) Areal segregation of face-processing neurons in prefrontal cortex. Science 278:1135-38.
3.- Gross CG, Rocha-Miranda CE, Bender DB (1972) Visual properties of neurons in inferotemporal cortex of the Macaque. JNeurophysiol. 35(1):96-111.
4.- Tsao DY*, Freiwald WA*, Tootell RB, Livingstone MS (2006) A cortical region consisting entirely of face-selective cells. Science 311:670-674. *These authors contributed equally to this work.
5.- Hesse JK & Tsao DY (2020) The macaque face patch system: a turtle’s underbelly for the brain. Nature Review Neuroscience, 21: 695-716.
6.- Freiwald W, Duchaine B & Yovel G (2016) Face Processing Systems: From Neurons to Real World Social Perception, Annu Rev Neurosci, 39: 325-346.
7.- Taubert J, Wardle SG, Ungerleider LG (2020) What does a “face cell” want? Progress in Neurobiology. 195:101880.
8.- Kanwisher N, McDermott J, Chun M. (1997) The fusiform face area: A module in human extrastriate cortex specialized for face perception. J Neurosci. 17:4302–4311.
9.- Tsao DY, Schweers N, Moeller S, Freiwald WA (2008b) Patches of face-selective cortex in the macaque frontal lobe. Nat Neurosci. 11:877-79.
10.- Landi SM, Viswanathan P., Serene S, Freiwald WA. (2021) A fast link between face perception and memory in the temporal pole. Science 373(6554):581-585.
11.- Lahiri D., Prosopagnosia, (2020) Cortex 132, 479.
DOUBLE HELIX IN THE SKY
Double helix, is a term used to describe the physical structure of DNA. The deoxyribonucleic acid or DNA is a molecule that stores our genetic instructions, i.e. the information that programs all of our cell’s activities. It is a letter code providing the instructions for everything you are. And it does the same for every other living thing. If you are a human, every one of your somatic cells has 46 chromosomes each containing one big DNA molecule. These chromosomes are packed together tightly with proteins in the nucleus of the cell.
A DNA molecule is made up of two linked strands that wind around each other to resemble a twisted ladder in a helix-like shape. Each strand has a backbone made of alternating sugar (deoxyribose) and phosphate groups. Attached to each sugar is one of four bases: adenine (A), cytosine (C), guanine (G) or thymine (T). The two strands are connected by chemical bonds between the bases: adenine bonds with thymine, and cytosine bonds with guanine.
The DNA's double-helical structure was discovered in 1950s. Knowledge about the structure, involving two complementary strands of DNA, each providing the template for making the other strand, provided a key insight about how DNA serves as the information molecule of all living systems. The double-helix model of DNA structure was published in the journal Nature by James Watson and Francis Crick in 1953, and it was based on the work of Rosalind Franklin, and her student Raymond Gosling, who took the X-ray diffraction imagine of DNA labeled Photo 51, and Maurice Wilkins, Alexander Stokes and Herbert Wilson, and base pairing chemical and biochemical information by Erwin Chargaff. The prior model was a triple-stranded DNA. Watson, Crick and Wilkins received the Nobel Prize in Physiology or Medicine for their contributions to the discovery.
Sources: NIH National Human Genome Research Institute; Molecular Biology of the Cell, Bruce Alberts, et.al.; “DNA structure and replication @ Crash Course Biology #110.
ABOUT AUTISM SPECTRUM DISORDER (ASD)
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder, present in childhood, involving distinct human deficits or difficulties around social communication and repetitive behaviors. Not every autistic human shares the same difficulties. However, some of the overlapping difficulties involve:
a) Social emotional reciprocity i.e. how you share your social world.
b) Repetitive behaviors of interest and routines, as well as repetitive motor behaviors.
c) An infrequent or inappropriate use of gestures.
d) Challenges in social interactions and relationships.
Other difficulties involve high sensitivity to sounds, light, touch, smell or taste. As well as a lack of sensory reactions to pain, temperature or sounds. Although, all of these features are diagnostic, individuals under the ASD umbrella often represent a wide range of severity and often co-occurring signs and symptoms that can include anxiety, depression, sleep disturbance, epilepsy, or savant skills e.g. obsessive preoccupation with, and memorization of music, maps, historical facts, etc.
Until 2019, according to the statistics, ~ 2.7-3.6% of the American population has been found with an autism diagnosis. Unfortunately, the estimate has been rising over time. Although, ASD ranks at the top of the neuropsychiatric disorders with regard to its relative genetic contribution and variety of clinical manifestations, we still don’t have clear diagnostic biomarkers for it. One of the first successful efforts at isolating true ASD risk genes involved the identification of mutations in Nlg3 and Nlg4 genes. These genes belong to a phylogenetically conserved family of adhesion proteins located in the post-synapsis. Impaired function of Nlg3 and Nlg4 genes is associated with ASD in humans, and impaired social behavior in mice. Nowadays, there is enough evidence to support the association of about a dozen copy number variant (CNV)* loci and more than 100 genes involved in ASD, with this list growing.
The fact that ASD involves very different human features, poses a challenge for the interpretation of results coming from evolutionarily distinct experimental models e.g. mice. For this reason, in addition to the progress in gene discovery, there have been huge efforts to encourage what is known as the “convergence neuroscience research approach”, which involve the intersection among molecular-level, cellular level and circuit level functions across multiple ASD risk genes. This approach has revealed among others that:
1) Developing excitatory neurons in the human cortex differ substantially between ASD and control subjects. In ASD subjects the excitatory neurons in the developing frontal & parietal cortices contain high expression of ASD genes during early mid-gestation.
2) ASD genetic risk may cause disruptions in the neurogenesis of the cortex by disrupting the connectivity of the network within the cortical layers.
3) ASD risk genes are differentially enriched in distinct cell types of the human brain. For example, post-mortem ASD human cortex reveals an increase in the representation of excitatory neurons and microglia in comparison to control brains.
In the last few years, there has been a global phenomenon of increasing autism prevalence. It is not clear what is changing in the developing brains to make autism more common. Early diagnosis contributes to improving the cognitive skills of the ASD population. Thus, there has been tremendous efforts to generate biomarkers that allow for a quick and accurate diagnosis. Some of these efforts involves deep learning algorithms trained to detect particularities at the level of behavior e.g. eye movements & facial gestures, brain imaging & circuits, as well as genetic profiles. Other strategies involve novel gene therapies like gene replacement, editing, and antisense sense oligonucleotide strategies.
Early diagnosis in combination with cognitive and behavioral therapies are fundamental for improving the cognitive skills and life quality of the ASD population. More work needs to be done in order to guarantee access to early diagnosis regardless of race, gender or social status. It turns out to be fundamental to reflect about how the ASD population perceive the world, what their needs are and how we can adapt our environment and social construction for them.
*Copy number variation (CNV) is a phenomenon in which sections of the genome are repeated and the number of repeats in the genome varies between individuals.
Sources:
1) Willsey H.R. et.al (2022), Genomics convergent neuroscience and progress in understanding autism spectrum disorder, Nature Reviews Neuroscience, 323-341.
2) Autism by the numbers (2021), Spectrum’s Guide to Prevalence Estimates, Spectrum, Simons Foundation.
4) Embracing Autism, A little help for Our Friends Podcast
5) https://www.spectrumnews.org/
6) Corthals, et. al., (2017) Neuroligins Nlg2 and Nlg4 affect social behavior in Drosophila Melanogaster, Frontiers in Psychiatry, 1-13.
OCÉANO PLÁSTICO / PLASTIC OCEAN
"El Plástico – es una increíble invención y una tortura para nuestro planeta. Cerca de 300 millones de toneladas de plástico son producidas cada año. La mayoría de este plástico nunca será reciclado y permanecerá en nuestra tierra y en nuestros océanos para siempre. Nuestra historia muestra el daño que el plástico ocasiona a todos los seres vivos cuya comida depende del océano - de los pájaros... para nosotros. "
"Plastic - both a wonderful invention and a scourge on our planet. Over 300 million tons will be produced this year. Most is never recycled and remains on our land and in our seas forever. Our story shows the damage to all creatures who depend on the ocean for their food – from birds… to us."
Océano plástico es un video producido por la Organización de las Naciones Unidas (ONU), originalmante en el idioma inglés. El video ha sido doblado al español utilizando Free-Speech AI -un asistente de doblaje que utiliza inteligencia artificial. https://freespeechnow.ai/
Plastic Ocean is a video originally produced by the United Nations: https://www.youtube.com/watch?v=ju_2NuK5O-E. The video was translated from english to spanish using the Free-Speech AI powered assistant. https://freespeechnow.ai/
AUTUMN LEAVES
Fall is probably my favorite season. The autumn light is particularly beautiful and the display of leaves switching from green to yellow, orange, red, or eventually brown makes me think of the beauty of the seasons and changes.
The change in the color of the leaves and their falling is mainly dictated by the calendar. As the nights grow longer and cooler, a series of biochemical processes in the leaf start to paint the hues of fall. When the trees sense from the environment the cold and shortness of the days, they signal a cascade of biochemical events to start their downbeat for the winter. These signals start to degrade the chlorophyll , the green pigment , that allows the trees to absorb energy from light, and also makes them green. Once the chlorophyll starts to degrade, other pigments that have always been in the leaf start to display, and that is how you get yellows, oranges and sometimes browns. Thus, autumn colors are given by other non- chlorophyll pigments. The pigments responsible for the autumn palette are:
carotenoids: producing yellow, orange and brown leaves. These pigments give color to the leaves of birches, poplar and elms, as well as to foods like bananas and carrots.
anthocyanins: producing red, purples and blended combinations of these. Unlike the carotenoids, the anthocyanins aren’t present throughout the growing season, they are produced once the cold temperatures start. Their formation depends on the breakdown of sugars in the presence of light as the phosphate levels in the leaf start to decrease. These new anthocyanin pigments make leaves turn red or purple. The more sugar the brighter the color. Red & sugar maple trees and foods such as beets and radishes get their colors from this pigment
But, why would the trees spend energy producing reds for leaves that will fall into the ground? Some scientists think these pigments act as a sunscreen or a deterrent for insects, protecting the leaves as the tree is trying to save as much of the material as possible . In some way the red helps the leaves to hang a bit longer from the tree. Thus, it is a tradeoff, the tree is using some energy to get the other energy that is present in the leaf back to the tree. However, this is not a conclusive explanation behind the red pigmentation.
After the leaves change color they are ready to separate from the tree and a little bit of wind or rain will make them fall to the ground. So before all leaves fall into the ground and the winter arrives, go out for a hike and smile at the autumn and its colors.
Sources:
1) https://www.compoundchem.com/2014/09/11/autumnleaves/
2) https://www.fs.usda.gov/visit/fall-colors/science-of-fall-colors
Page updated
Google Sites
Report abuse