Here is the novel I was referring to en.wikipedia.org/wiki/Understand_(story)

This is insane! This is genuinely so cool.

Thanks! Awesome format and research!

Algum brasileiro poderia nos dizer o que eles falaram no vídeo?? Tenho 44 anos e tenho Glioblastomas a 4 anos

Thank you so much for your material! It’s excellent! I have already entered the password and the account you kindly shared with us. However, when I open the program on my MacBook Air M2, it automatically closes with the following error: Problem Report for TrackVis: TrackVis quit unexpectedly. Notes: PC register does not match casting Frame (0x0 vs 0x10F120F04). Could you please provide some guidance on how to resolve this issue? Best regards

What happens to the children when they grow up. What is you are undiagnosed? How do you get help?

Nice presentation

This is not loud enough.

So: 1Neanderthal pre natal :23 AMH pre natal ratio. What's the ratio on the other two categories?

@Clinical Neuroanatomy Seminars Do you know if the newer, non-invasive procedure known as Temporal interference (TI) can be used for OCD also?, Thanks

I'm one of the patients

Hi, hello . Do you have the actual video of doing klingler dissection?

Did you say 9:30 on a Monday, who does that? Are you out to injure people.

I like to ask Chris whether published articles can be open to public comments just like KZbin video. This level of openness can reduce publishing bias and publishing corruption, which may be the root of problems. I assume authors who opt to open their publications to public comments could receive very harsh criticisms, but that should be good for science

A strong sense of responsibility for good science. A truly worthy exploration with great prospects.

The authors got back to us about the discussion and added these points. Very cool that Herve saw the inspiration was the Bethlehem et al. Brain Charts study. We didn’t explicitly say this, but this study was an inspiration for this work. Combining cohorts: this is the biggest limitation of the study. We cannot use existing harmonization methods here because there is no age-overlap in the cohorts. I truly believe this created some false peaks/bumps/discontinuities in our lifespan data (which is why we downplay the ‘peak’ analysis, and try to analyze each cohort separately for most questions we ask) Biases and challenges with DTI: you are right - something like FA doesn’t truly tell us what is happening across the lifespan and is particularly challenging due to partial volume. We’ve had some interesting discussions on FA of the CST - some studies show an increase with age, some show a decrease. Ours showed a slight increase (but it was not statistically significant, and was only positive ~65% of the time in bootstrap experiments). Along/across bundles… this would be a fascinating question to ask about relationships between bundles (instead of between features). We did do along-tract analysis (for example, along the arcuate fasciculus) but didn’t include it because the paper was getting quite long. Scales across datasets: for visualization we have to choose different scales for each cohort - Herve was right, because the Baby cohort has such large changes, all other datasets had no contrast in the matrices. Normalizing by brain size: results are shown without covarying for sex or brain size…although we also did analysis with covarying for both (and have the effect sizes and slopes still saved somewhere!). Figure error: Figure 3 has a very small mislabel on the colour. Our scales are all positive-to-negative, but our Matlab printing mislabeled a couple of the colours. We immediately let the editors know but these changes haven’t been reflected yet. It does not change anything else about the figure or interpretation. Herve had an excellent point about comparing development to aging - indeed, we only compared slopes in the paper. We did try a few ways to ask about relationships between these stages of the lifespan, but settled on this approach because it seemed to be the most common in the literature.

Great presentation:) one little addition to a question in the video: the neurodesktop container is 1.5gb in size and we download all neuroimaging software either on demand from a distributed file system (cvmfs) or we download a singularity/apptainer container depending on what’s available for use.

It is pretty surprising to see superior temporal gyrus implicated in processing of visual distractors. Thanks for the talk!

If this video were a flavor, it'd be my favorite ice cream!

Can you guys please do more sessions of just like the same from research paper

I am a non academic but interested in your talk...In particular is Gregory's focus on single hemispere due to practical difficulties studying both sides concurrently? as I would have thought even the presence of functional lateralisation and the coordination/dual processing and end processing decision mechanisms would be mind blowing in complexity but would warrant further research.??Amazed how much you all do know with apparent certainty Thanks AH

Fantastic session. Thank you for sharing it!

THANK YOU DR. RATIU FOR THIS GREAT ADITION TO MODERN MEDICINE AND RADIOLOGY🙏🙏

1:02:22 1:07:38

Equipotentiality in learning theory is when every stimulus, response and reinforcement are potentially subject to association - equally associable- thus learning. This is one of the principles of behaviorism, environmentalism-- while, the neural level reflects STP/LTP regardless of sensory motor modality! Kiumars Lalezarzadeh, PhD

what are S and O information?

thanks, good vedio！

Thank you for your comment and for clarifying the point regarding the benchmarking in our discussion. We appreciate your input and the detailed explanation!

Thanks for journal clubbing our paper! I do want to point one one inaccuracy in your debate -- it was raised that we should have benchmarked 3D UMAP, but we benchmark in equivalent dimensions, as we state in the paper clearly. CEBRA 3D is ON a hypersphere, this is fully equivalent to a 2D Euclidean space topologically. AS in our 3D space we can't "fill the globe," we can only be on the surface. And, as you see in Figure 1, we actually used a 2D CEBRA embedding, not 3D, where we outperform UMAP. -Mackenzie Mathis

The idea that structure can predict function is so old, is not surprising, is innate in electromagnetic,complex information systems. Alex Fornito and his team are doing great job for a decade ✌🏼😁

🎉😮🎉

Thank you for the presentation. Was there any reference to the thickness of the thalamus and its influence on threshold for levels of consciousness- oscillations - variability? How about coupling? Which, coupling or variability could be directly involved in consciousness or semantics? How about RAS and consciousness in this? Kiumars Lalezarzadeh, Ph.D.

It would be cool to integrate vision with latent diffusion and words with gpt into a single reconstruction, maybe adding sound, emotions, tactile proprioceptive sensations, premotor activity etc.

nice tutorial, clear and easy to follow.

whats the piano song the guy plays in the trailer video???

Thank you for an interesting presentation. I recalled the lab from the past. If understood accurately, representation of "meaning" in the brain is spread out- there is a redundancy in decoding in different regions given a stimulus. One would want to know if the activation is simultaneous, or there might be a temporal order and spread of activation. In addition the underlying neurochemistry might differ in the gray matter in response to different word stimuli - 'meaning'. If the neurochemistry differs in response to different stimuli, the amino acid expressions would differ too. In that case the 'meaning' may not be all over the brain in the same way. Or alternatively, the there might be common code in the brain for all word stimuli regardless of meaning. That is, the brain encoded all words equally (i.e., as in Aristotle's tabula rasa) to begin with and then associated affective meaning to words depending on pleasant and unpleasant events, or alternatively as in Plato, there was a preexisting codes in the brain for separate meanings. I wonder if one could derive at the fundamental question given fMRI, PET or any other imaging whether or not, as such did word-stimulus-meaning preexist or condition-evolve with other affective stimuli. Kiumars Lalezarzadeh, Ph.D.

Grande Dori

Dori shume djal perfekt

❤

Excellent 😊Erick

this is good, thanks for sharing such a thing

Thank you! 👍

Great Video! Thanks!

thank you for posting this! It made me understand this condition better and you gave a good idea the studies I should take a look at!

Your are a hero god bless you

Thanks for highlighting our work! Just two comments that might be useful: First, we did test whether one could apply tractography algorithms on top of the tensor field you get from Nissl-ST. We found that it is indeed possible, and as an example we tracked both the corpus callosum and a novel U-fiber around the occipitotemporal sulcus. You can see it in Supplementary Figure 16 in the paper: www.science.org/doi/10.1126/science.abj7960 Second, the RGB map of the diffusion MRI data in Figure 2 does look a little different than what is common in the field. This map is based on HCP data (with 1.25 isotropic resolution). We color-coded it using the in-plane orientation (as opposed to the regular RGB color map used in 3D diffusion imaging). To obtain the in-plane orientation we used CSD and projected the dominant in-plane lobe onto the plane (we show this process in Sup. Fig. 2). Then, we just smoothed the image a bit for visualization purposes. The unsmoothed image appears in Sup. Fig. 3.

so interesting! its got to be less noise than traditional scanner to.

dear thomas! thx a lot for this highly interesting talk which i just watched for 30mins. if you combined your tools with a tilt bed you could turn it into an invaluable diagnostic tool, as slipperiness is something that’s always being monitored unconsciously in sleep, and if not so most likely pointing to some peripheral and/or central neuropathology. there’s quite a recent paper on how to translate that research into the MRI without actually having to tilt a table -> wrt. dynamic functional connectivity etc. 10.1109/TOH.2021.3139890 best regards atto

Code availability "The custom software codes used for the EMI removal demonstrated in Fig. 3 can be also downloaded from the public repository (github.com/bispmri/Ultra-low-field-MRI-Scanner). "

Really good interview. Thanks for putting so much effort with the timeline, titles etc that make the interview a great resource.