The “Squidworm” Is Believed To Be A Transitional Organism From Benthic Worms To Free-swimming Pelagic

Entelodonts: terrifying.

Shown here compared to a modern pig skull on the left. (Entelodonts were actually more closely related to whales and hippos than pigs.)

Fiann on Instagram: “Here is a shot along the vertebral column of my smallest ichthyosaur called Bella. At the end you’ll see how her vertebrae compare to the biggest vert I’ve found from the same location. This huge bone is from an animal that would have been over 8 metres long, which is a bit bigger than poor little Bella! These fossils are both around 198 million years old. Bella was prepared by the ever talented @alexander_james_moore.

Morphing necker cubes

Spectacular fossil collection starting off with whales and other ocean-dwelling organisms at the Gallery of paleontology and comparative anatomy, France

(Image caption: An electron micrograph image shows a parallel fiber-Purkinje cell. The presynaptic cell, a parallel fiber, is colored red while the postsynaptic cell, a Purkinje cell, is colored green. Credit: OIST Computational Neuroscience Unit)

Scientists Illuminate Mechanism at Play in Learning

The process we call learning is in fact a well-orchestrated symphony of thousands of molecular reactions, but the exact interplay between these reactions remains largely unknown. Now, researchers at the Okinawa Institute of Science and Technology Graduate University (OIST) have modelled the molecular basis of learning in the cerebellum, a part of the brain that receives sensory input and coordinates voluntary movements.

“As far as we know, this is the most complex model of such a system that exists,” said Erik De Schutter, head of OIST’s Computational Neuroscience Unit and senior author on the recent paper, published in Cell Reports. Previous models focused on the signals that arrive at the receiving end of a neuron, he said, “whereas now we’re looking at the ongoing communication between the two ends.”

Learning is thought to be a balance between two processes that act as a kind of molecular dial: long-term potentiation (LTP), in which the connection between two neurons is strengthened, and long-term depression (LTD), in which the connection between two neurons is weakened. Both these processes take place at the synapse—the junction between two neurons. Andrew Gallimore, first author on the paper and a postdoctoral researcher at OIST, modeled how they work in two types of cells: parallel fibers and Purkinje cells, which play a key role in motor learning.

(Image caption: Learning is thought to be a balance between two processes that act as a kind of molecular dial: long-term potentiation (LTP), in which the connection between two neurons is strengthened, and long-term depression (LTD), in which the connection between two neurons is weakened. Such a large, comprehensive model allows scientists to examine how complex signaling systems work together. Credit: OIST Computational Neuroscience Unit)

Using a computer program to create a model of this complex system, Gallimore combined several hundred equations taken from experiments in which such neurons were activated. The model was put to the test when colleagues in Korea took recordings from neurons in the cerebellum of mice. The OIST researchers then incorporated these recordings into the model.

Their findings show that the molecular networks on both sides of a synapse are important for controlling learning: communication must occur in both directions across the synapse to control whether LTD or LTP is generated during neural activity.

The model also showed that the molecular dial balancing LTP and LTD has an automatic off-switch that, when triggered, allows the system to return to its resting state. Although previous research hinted at the presence of this off-switch, this is the first time that the mechanism behind it—a complex network of proteins and receptors—has been demonstrated. Such a large, comprehensive model allows scientists to examine how complex signaling systems work together, something that is often absent in experimental literature, De Schutter said.

The researchers’ work allows scientists to more accurately predict the behavior of the chaotic, complex system of molecules that controls learning. It also hints at what might be happening at the molecular level when these switches break—which might occur when the brain is injured or during neurodegenerative diseases that affect learning.

“The whole function of a brain is based on the strengths of these synaptic connections,” said Gallimore. “The better we understand these processes, the greater potential there is to intervene to mitigate severe problems.”

Some cool engineering please !!!

F1 engine playing Happy Birthday

When I was researching about F1 sometime ago, I stumbled upon this amazing video of the lotus team playing happy birthday on a F1 freaking engine!

The way this works is that the sheet music is taken and broken down into frequency and the milliseconds that it lasts for.

And the engine is turned on and off rapidly with different frequency tones to produce the tone i.e

OFF  - f1 Hz - f1 Hz - OFF - f2 Hz - f2 Hz - f2 Hz- OFF …. (entire song)

The dynamic response of the F1 engine to changes in the throttle is what blew my mind. F1 cars are able to pull this off due to the extremely lightweight flywheel/general rotating assembly. 

Imperial march on Floppy drive

Now you can do the same thing with motors as well. The motors can be revved up or down based on the frequency of the input.

Here’s the imperial march played on the floppy drive and Super Mario on the stepper motor:

What you are hearing is the tones made by the motor. 

Notice the slider moving faster for higher frequency

If you are into Arduino and DIY projects you can play around with the ToneMelody package and piezo-buzzer to get a similar response.

Thanks for asking. Have a great day!

some recent stuff from my sketchbook!