Epistimones

Jose Jimenez is a Senior Lecturer in Synthetic Biology at Imperial College London, whose research occurs at the interface of synthetic biology and evolution. His lab is interested in how evolution shapes the properties of proteins exhibiting quantum mechanisms, cell economics, and the dynamics of complex microbial communities. The applications of this research range from the development of novel methods to fight antibiotic resistance, to the use of engineered microorganisms for the upcycling of plastic waste.

TIMESTAMPS

(00:48) – What is quantum biology? 

(07:28) – Investigating the evolution of quantum systems in biology 

(11:28) – Quantum biology and synthetic biology 

(14:56) – What can quantum biology explain? 

(20:00) – What is cell economics? 

(27:10) – Feedback control to reduce the cost of protein synthesis 

(32:45) – Cell economics and fundamental biology 

(36:50) – Bacterial bet-hedging 

(39:07) – Microbial communities in synthetic biology 

(46:48) – Potential of manipulating microbial social interactions 

(51:28) – Jose's research interests 

(56:19) – The landscape of synthetic biology - academia vs industry 

(1:03:31) – Advice for young scientists

Ian Maze is a Howard Hughes Medical Institute Investigator and Professor of Neuroscience and Pharmacological Sciences at the Icahn School of Medicine at Mount Sinai. His research involves studying the chromatin-based mechanisms of adult cognitive and psychiatric disorders like addiction and major depression, in particular how monoamines like serotonin and dopamine can act as epigenetic regulators to influence gene expression, and the implications in disease and treatment.

TIMESTAMPS

(00:42) – Epigenetics

(15:20) – Serotonin and depression

(18:42) – Serotonylation

(36:20) – Depression and epigenetics

(40:12) – Dopaminylation

(42:20) – Studying epigenetics of psychiatric disorders

(48:48) – Future of depression diagnosis and treatment

(51:40) – Ian’s academic journey

(57:00) – Advice for young scientists

Jenny Saffran is a Professor of Psychology at the University of Wisconsin-Madison, studying how infants use statistical learning – the detection of pattern and regularities in the environment, to learn about the structure of language. Language learning is a highly complex problem and is not a trivial task for an infant, but behavioral experiments from Jenny’s labs have led to many insights into how infants solve this task.

TIMESTAMPS

(00:38) – What is language

(08:33) – Structure of human languages

(19:58) – Language and intelligence

(23:57) – Is language innate

(40:44) – How babies learn language

(57:10) – Learning different languages

(1:07:12) – Psychologists, linguists, and neuroscientists

(1:10:21) – Studying language in babies

(1:15:33) – Jenny’s academic journey

(1:23:30) – Natural language processing

(1:31:44) – Advice for young scientists

NOTES

Seeing faces is necessary for face-patch formation (Arcaro et al., 2017)

Irene Tracey is a neuroscientist at the University of Oxford, using neuroimaging tools to study the neurobiological mechanisms of pain perception in acute and chronic pain, as well how states of consciousness are altered with anaesthetics. Until recently, she held the Nuffield Chair of Anaesthetic Sciences, and was Head of the Nuffield Department of Clinical Neurosciences and Director of the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain. She is currently the Warden of Merton College in Oxford and has recently been appointed CBE for her services to medical research.

TIMESTAMPS

(00:48) – Why we feel pain

(06:09) – Mechanisms of pain perception

(17:54) – Modulating pain perception

(22:37) – Pain tolerance

(26:07) – Chronic pain

(32:39) – Studying pain experimentally

(46:14) – Empathy

(48:57) – Advice for young scientists

Kent Berridge is a Distinguished Professor of Psychology and Neuroscience at the University of Michigan, studying the neurobiology and brain systems underlying psychological processes like motivation, pleasure, craving, and addiction. His research has shown a dissociation between reward liking and reward wanting, and has led him to propose the Incentive Salience Hypothesis of dopamine, which states that dopamine mediates wanting and craving but not liking and pleasure. Contrary to popular belief, dopamine is not a pleasure molecule, and its psychological function remains highly controversial.

TIMESTAMPS

(00:51) – Dopamine

(02:59) – Is dopamine a pleasure molecule?

(09:11) – Liking vs wanting

(15:03) – Incentive Salience Theory

(18:22) – Dopamine and learning

(33:59) – Neurobiology and evolution of pleasure

(41:14) – Why people have different preferences

(45:09) – Experimental techniques and challenges

(51:05) – Pleasure in life

(54:26) – Advice for young scientists

Juan Caicedo is a Schmidt Fellow and computer scientist at the Broad Institute of MIT and Harvard, working at the intersection of biology and machine learning. His research involves the use of deep learning and machine learning approaches to analyze microscopy images and genetic data for decoding cellular phenotypes and their interactions in order to gain deeper insights into basic cell biology, how disease affects cells, and to test different types of treatments in a high-throughput manner.

TIMESTAMPS

(00:45) – Image-based profiling

(26:15) – Algorithms for cell image segmentation

(59:10) – Characterizing cell phenotypes

(1:06:48) – Imaging interactions between cells

(1:11:19) – Cancer

(1:16:26) – Future of personalized medicine

(1:20:27) – Advice for young scientists

Randy Gallistel is an Emeritus Professor of Psychology at Rutgers University, studying the cellular substrate of learning and memory. He is one of the biggest critics of the mainstream hypothesis that synaptic plasticity is the neurobiological basis of memory, and has argued for the cell-intrinsic hypothesis of memory storage – the idea that memory is stored in intracellular molecules.

TIMESTAMPS

(00:36) – Memory and computation

(24:42) – Critique of the synaptic plasticity hypothesis of memory

(41:48) – Number coding  

(55:48) – Computational theory of mind vs Connectionism

(01:08:54) – The synaptic plasticity debate

(1:26:15) – Cell-intrinsic hypothesis of memory storage

(2:16:30) – Resistance against the cell-intrinsic hypothesis

(2:31:57) – Neural networks

(2:40:56) – Favourite part of science

(2:46:12) – Meaning of life

(2:47:18) – Advice for young scientists 

NOTES

Hessameddin Akhlaghpour's paper showing RNA can be a computation system: An RNA-based theory of natural universal computation

Kate Jeffery is a Professor of Behavioural Neuroscience at University College London, researching how the brain assembles sensory information into an internal representation of space for navigation. Her current research focuses on how the brain represents complex space like three dimensional space, as well as the internal sense of direction. She founded and is currently the director of the Institute of Behavioural Neuroscience in the Division of Psychology and Language Sciences at UCL, and is also a Fellow of the Royal Society of Biology and the Royal Institute of Navigation.

TIMESTAMPS

(00:48) – Entropy and life

(05:58) – Evolutionary transitions

(19:36) – Evolution of spatial navigation

(22:37) – Discovering the neural representations of space

(35:54) – Spatial maps

(1:05:25) – Mapping 3D space

(1:30:35) – Mapping arbitrary dimensions

(1:36:18) – Kate’s journey into neuroscience

(1:48:10) – Existential risks

(1:58:55) – Meaning of life

(2:04:18) – Extraterrestrial life

(2:07:45) – Advice for young scientists

Thomas Gorochowski is a synthetic biologist and Royal Society University Research Fellow based in the School of Biological Sciences at the University of Bristol. His lab applies tools from synthetic biology for the rational engineering of biological systems, to both provide insights into how biology controls the complex processes sustaining life, and to tackle problems spanning the sustainable production of materials to novel therapeutics.

TIMESTAMPS

(00:41) – Bioprogramming and genetic circuits 

(10:52) – Simplicity vs complexity in genetic circuit design 

(13:59) – Applications of control theory 

(19:15) – Evolution and genetic circuits 

(23:29) – Breaking down the complexity of evolution 

(30:00) – Paradigm shifts in bioprogramming 

(31:30) – Improving robustness by controlling evolution 

(36:50) – Crosstalk between computer science and biology 

(40:00) – Thomas' career path 

(47:00) – Advice for aspiring synthetic biologists

Vandana Ravindran is a computational biologist at the Oslo Center for Biostatistics and Epidemiology. Her research involves applying mathematical modelling, specifically complex network analysis, to understand viral interactions in relation to cancer.

TIMESTAMPS

(00:29) – Basis of complex network analysis to understand biology 

(06:02) – Understanding viral infection 

(09:37) – Machine learning methods vs experimental data 

(23:05) – Modelling cancer signalling pathways 

(33:15) – Bridging the gap between computational and experimental work 

(37:12) – How to get into the field

(39:15) – Advice for young scientists