#neurorat — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #neurorat, aggregated by home.social.
-
@adredish thanks for the input and for reading our paper!!
I definitely agree that it's better to size the figs so they fit together with their legend, on a single page, and to have the methods in the main text. In this case we did the minimal effort option and uploaded in the same format as for the journal we submitted to... and it's bad.
Still, journals have a lot more resources than individual researchers and it should be very easy and fast for them to format a manuscript properly before sending it for peer-reviews!
As for your scientific comments, thank you so much for all these! I'll answer some of them once I found some time to re-read Jackson et al. and Gupta et al., but for the rest:
place cells over days: we did not try to track individual neurons across days, so we can't say anything about that. One thing though is that between the 3 daily tracks, some of the neurons would sometimes activate in the same local position (e.g. end of a track) even though the tracks were not physically in the same place. I'd say these are the mostly BVC-driven place cells that help generalise a map 'matrix' between environments!
did the rats treat the tracks as novel? I did not run the experiment myself, but I would say, not completely, since the rats were pre-trained (in other geometries) in that room and with the same task, and from their behaviour you can see that they are doing the task quite efficiently, while if it was a completely novel experience, they would act a lot more hesitantly.
place fields stabilisation: you can see it in figure 4B (pasted below), place cells take a few laps to stabilize a lot, although their stability keeps increasing throughout. I think it mostly matches Wilson & Mc Naughton 1993 (this one, right?).
One other related and cool (I think!) finding is that local replay appears to significantly contribute to that stabilisation, in the sense that neurons that are not recruited in a local replay event on a given trial do not increase their stability as much as those who do - see 4I&J (we have a slightly better version of this figure that we'll update the preprint with soon).
More complex task: my prediction is that we'll get similar results in a more complex task, particularly since our 2019 paper did not find any effect of value changes on 'goal-related activity' (which may have been replay) when the behaviour was also properly controlled. But I'll tell you more in my next paper :)
effects of increased experience: well, the rats did experience each task for many days - only the tracks were new, but the task was the same. But you probably meant tracks. I'd say that we would probably observe the same effect (of influence of degree of quiescence, but not reward) for tracks experienced more than once; we can kind of see it in the plots of (Ambrose et al., 2016](https://www.cell.com/neuron/fulltext/S0896-6273(16)30463-9) who did not have novel tracks; the replay rates across conditions just seem to depend on duration spent at the site more than actual reward value. But it would be great to do the same analysis that we did, on their dataset, to be sure!
Let me know if you have any follow-up questions for now and thanks again for reading and engaging!
-
@adredish thanks for the input and for reading our paper!!
I definitely agree that it's better to size the figs so they fit together with their legend, on a single page, and to have the methods in the main text. In this case we did the minimal effort option and uploaded in the same format as for the journal we submitted to... and it's bad.
Still, journals have a lot more resources than individual researchers and it should be very easy and fast for them to format a manuscript properly before sending it for peer-reviews!
As for your scientific comments, thank you so much for all these! I'll answer some of them once I found some time to re-read Jackson et al. and Gupta et al., but for the rest:
place cells over days: we did not try to track individual neurons across days, so we can't say anything about that. One thing though is that between the 3 daily tracks, some of the neurons would sometimes activate in the same local position (e.g. end of a track) even though the tracks were not physically in the same place. I'd say these are the mostly BVC-driven place cells that help generalise a map 'matrix' between environments!
did the rats treat the tracks as novel? I did not run the experiment myself, but I would say, not completely, since the rats were pre-trained (in other geometries) in that room and with the same task, and from their behaviour you can see that they are doing the task quite efficiently, while if it was a completely novel experience, they would act a lot more hesitantly.
place fields stabilisation: you can see it in figure 4B (pasted below), place cells take a few laps to stabilize a lot, although their stability keeps increasing throughout. I think it mostly matches Wilson & Mc Naughton 1993 (this one, right?).
One other related and cool (I think!) finding is that local replay appears to significantly contribute to that stabilisation, in the sense that neurons that are not recruited in a local replay event on a given trial do not increase their stability as much as those who do - see 4I&J (we have a slightly better version of this figure that we'll update the preprint with soon).
More complex task: my prediction is that we'll get similar results in a more complex task, particularly since our 2019 paper did not find any effect of value changes on 'goal-related activity' (which may have been replay) when the behaviour was also properly controlled. But I'll tell you more in my next paper :)
effects of increased experience: well, the rats did experience each task for many days - only the tracks were new, but the task was the same. But you probably meant tracks. I'd say that we would probably observe the same effect (of influence of degree of quiescence, but not reward) for tracks experienced more than once; we can kind of see it in the plots of (Ambrose et al., 2016](https://www.cell.com/neuron/fulltext/S0896-6273(16)30463-9) who did not have novel tracks; the replay rates across conditions just seem to depend on duration spent at the site more than actual reward value. But it would be great to do the same analysis that we did, on their dataset, to be sure!
Let me know if you have any follow-up questions for now and thanks again for reading and engaging!
-
@adredish thanks for the input and for reading our paper!!
I definitely agree that it's better to size the figs so they fit together with their legend, on a single page, and to have the methods in the main text. In this case we did the minimal effort option and uploaded in the same format as for the journal we submitted to... and it's bad.
Still, journals have a lot more resources than individual researchers and it should be very easy and fast for them to format a manuscript properly before sending it for peer-reviews!
As for your scientific comments, thank you so much for all these! I'll answer some of them once I found some time to re-read Jackson et al. and Gupta et al., but for the rest:
place cells over days: we did not try to track individual neurons across days, so we can't say anything about that. One thing though is that between the 3 daily tracks, some of the neurons would sometimes activate in the same local position (e.g. end of a track) even though the tracks were not physically in the same place. I'd say these are the mostly BVC-driven place cells that help generalise a map 'matrix' between environments!
did the rats treat the tracks as novel? I did not run the experiment myself, but I would say, not completely, since the rats were pre-trained (in other geometries) in that room and with the same task, and from their behaviour you can see that they are doing the task quite efficiently, while if it was a completely novel experience, they would act a lot more hesitantly.
place fields stabilisation: you can see it in figure 4B (pasted below), place cells take a few laps to stabilize a lot, although their stability keeps increasing throughout. I think it mostly matches Wilson & Mc Naughton 1993 (this one, right?).
One other related and cool (I think!) finding is that local replay appears to significantly contribute to that stabilisation, in the sense that neurons that are not recruited in a local replay event on a given trial do not increase their stability as much as those who do - see 4I&J (we have a slightly better version of this figure that we'll update the preprint with soon).
More complex task: my prediction is that we'll get similar results in a more complex task, particularly since our 2019 paper did not find any effect of value changes on 'goal-related activity' (which may have been replay) when the behaviour was also properly controlled. But I'll tell you more in my next paper :)
effects of increased experience: well, the rats did experience each task for many days - only the tracks were new, but the task was the same. But you probably meant tracks. I'd say that we would probably observe the same effect (of influence of degree of quiescence, but not reward) for tracks experienced more than once; we can kind of see it in the plots of (Ambrose et al., 2016](https://www.cell.com/neuron/fulltext/S0896-6273(16)30463-9) who did not have novel tracks; the replay rates across conditions just seem to depend on duration spent at the site more than actual reward value. But it would be great to do the same analysis that we did, on their dataset, to be sure!
Let me know if you have any follow-up questions for now and thanks again for reading and engaging!
-
@adredish thanks for the input and for reading our paper!!
I definitely agree that it's better to size the figs so they fit together with their legend, on a single page, and to have the methods in the main text. In this case we did the minimal effort option and uploaded in the same format as for the journal we submitted to... and it's bad.
Still, journals have a lot more resources than individual researchers and it should be very easy and fast for them to format a manuscript properly before sending it for peer-reviews!
As for your scientific comments, thank you so much for all these! I'll answer some of them once I found some time to re-read Jackson et al. and Gupta et al., but for the rest:
place cells over days: we did not try to track individual neurons across days, so we can't say anything about that. One thing though is that between the 3 daily tracks, some of the neurons would sometimes activate in the same local position (e.g. end of a track) even though the tracks were not physically in the same place. I'd say these are the mostly BVC-driven place cells that help generalise a map 'matrix' between environments!
did the rats treat the tracks as novel? I did not run the experiment myself, but I would say, not completely, since the rats were pre-trained (in other geometries) in that room and with the same task, and from their behaviour you can see that they are doing the task quite efficiently, while if it was a completely novel experience, they would act a lot more hesitantly.
place fields stabilisation: you can see it in figure 4B (pasted below), place cells take a few laps to stabilize a lot, although their stability keeps increasing throughout. I think it mostly matches Wilson & Mc Naughton 1993 (this one, right?).
One other related and cool (I think!) finding is that local replay appears to significantly contribute to that stabilisation, in the sense that neurons that are not recruited in a local replay event on a given trial do not increase their stability as much as those who do - see 4I&J (we have a slightly better version of this figure that we'll update the preprint with soon).
More complex task: my prediction is that we'll get similar results in a more complex task, particularly since our 2019 paper did not find any effect of value changes on 'goal-related activity' (which may have been replay) when the behaviour was also properly controlled. But I'll tell you more in my next paper :)
effects of increased experience: well, the rats did experience each task for many days - only the tracks were new, but the task was the same. But you probably meant tracks. I'd say that we would probably observe the same effect (of influence of degree of quiescence, but not reward) for tracks experienced more than once; we can kind of see it in the plots of (Ambrose et al., 2016](https://www.cell.com/neuron/fulltext/S0896-6273(16)30463-9) who did not have novel tracks; the replay rates across conditions just seem to depend on duration spent at the site more than actual reward value. But it would be great to do the same analysis that we did, on their dataset, to be sure!
Let me know if you have any follow-up questions for now and thanks again for reading and engaging!
-
7 / 12
Are you ready for PART 2?...That’s not just it! We also found another strong modulator of replay (hence the article’s title): time since the experience, i.e. episode ‘recency’: the most recent episodes were replayed the most afterwards, whether during rest after running each track, or during sleep.
This finding might explain why we tend to remember better the last experience in a series! And it means that we all need to be more careful about what we do just before going to sleep (at least, if you don’t want your doom-scrolling to be consolidated) 😅
PS: this is my favourite figure of the entire manuscript 🤗 Margot really has a knack for beautiful clarity 🤩
7/12
#HippocampalReplay #NeuroRat #RecencyEffect #RecencyBias -
7 / 12
Are you ready for PART 2?...That’s not just it! We also found another strong modulator of replay (hence the article’s title): time since the experience, i.e. episode ‘recency’: the most recent episodes were replayed the most afterwards, whether during rest after running each track, or during sleep.
This finding might explain why we tend to remember better the last experience in a series! And it means that we all need to be more careful about what we do just before going to sleep (at least, if you don’t want your doom-scrolling to be consolidated) 😅
PS: this is my favourite figure of the entire manuscript 🤗 Margot really has a knack for beautiful clarity 🤩
7/12
#HippocampalReplay #NeuroRat #RecencyEffect #RecencyBias -
7 / 12
Are you ready for PART 2?...That’s not just it! We also found another strong modulator of replay (hence the article’s title): time since the experience, i.e. episode ‘recency’: the most recent episodes were replayed the most afterwards, whether during rest after running each track, or during sleep.
This finding might explain why we tend to remember better the last experience in a series! And it means that we all need to be more careful about what we do just before going to sleep (at least, if you don’t want your doom-scrolling to be consolidated) 😅
PS: this is my favourite figure of the entire manuscript 🤗 Margot really has a knack for beautiful clarity 🤩
7/12
#HippocampalReplay #NeuroRat #RecencyEffect #RecencyBias -
7 / 12
Are you ready for PART 2?...That’s not just it! We also found another strong modulator of replay (hence the article’s title): time since the experience, i.e. episode ‘recency’: the most recent episodes were replayed the most afterwards, whether during rest after running each track, or during sleep.
This finding might explain why we tend to remember better the last experience in a series! And it means that we all need to be more careful about what we do just before going to sleep (at least, if you don’t want your doom-scrolling to be consolidated) 😅
PS: this is my favourite figure of the entire manuscript 🤗 Margot really has a knack for beautiful clarity 🤩
7/12
#HippocampalReplay #NeuroRat #RecencyEffect #RecencyBias -
~ New preprint, new thread! ~
My former colleagues at UCL Margot Tirole and Dan Bendor (not on Masto) have a new #HippocampalReplay preprint out, to which I contributed a little! Check out our thread and don't hesitate to share and comment!Why do we remember some experiences more than others?
Reactivations of neurons in the #Hippocampus (“replay”), particularly during sleep, may help consolidate memories; but when many experiences occur before going to bed, the brain must sort out what is worth replaying 😴
We investigated whether reward or recency helped prioritize experiences for replay in freely-moving rats. Surprisingly, we found that reward value does not influence replay! Instead, episode recency has a major effect, with the most recent episode being replayed the most!
Check the preprint for more: Time, but not reward, shapes replay-based episodic prioritization
... or read on for a thread on the main results! ⏬#NeuroRat #SpatialMemory #MemoryConsolidation #Neuroscience #MastoThread
1/12 🧵 -
~ New preprint, new thread! ~
My former colleagues at UCL Margot Tirole and Dan Bendor (not on Masto) have a new #HippocampalReplay preprint out, to which I contributed a little! Check out our thread and don't hesitate to share and comment!Why do we remember some experiences more than others?
Reactivations of neurons in the #Hippocampus (“replay”), particularly during sleep, may help consolidate memories; but when many experiences occur before going to bed, the brain must sort out what is worth replaying 😴
We investigated whether reward or recency helped prioritize experiences for replay in freely-moving rats. Surprisingly, we found that reward value does not influence replay! Instead, episode recency has a major effect, with the most recent episode being replayed the most!
Check the preprint for more: Time, but not reward, shapes replay-based episodic prioritization
... or read on for a thread on the main results! ⏬#NeuroRat #SpatialMemory #MemoryConsolidation #Neuroscience #MastoThread
1/12 🧵 -
~ New preprint, new thread! ~
My former colleagues at UCL Margot Tirole and Dan Bendor (not on Masto) have a new #HippocampalReplay preprint out, to which I contributed a little! Check out our thread and don't hesitate to share and comment!Why do we remember some experiences more than others?
Reactivations of neurons in the #Hippocampus (“replay”), particularly during sleep, may help consolidate memories; but when many experiences occur before going to bed, the brain must sort out what is worth replaying 😴
We investigated whether reward or recency helped prioritize experiences for replay in freely-moving rats. Surprisingly, we found that reward value does not influence replay! Instead, episode recency has a major effect, with the most recent episode being replayed the most!
Check the preprint for more: Time, but not reward, shapes replay-based episodic prioritization
... or read on for a thread on the main results! ⏬#NeuroRat #SpatialMemory #MemoryConsolidation #Neuroscience #MastoThread
1/12 🧵 -
~ New preprint, new thread! ~
My former colleagues at UCL Margot Tirole and Dan Bendor (not on Masto) have a new #HippocampalReplay preprint out, to which I contributed a little! Check out our thread and don't hesitate to share and comment!Why do we remember some experiences more than others?
Reactivations of neurons in the #Hippocampus (“replay”), particularly during sleep, may help consolidate memories; but when many experiences occur before going to bed, the brain must sort out what is worth replaying 😴
We investigated whether reward or recency helped prioritize experiences for replay in freely-moving rats. Surprisingly, we found that reward value does not influence replay! Instead, episode recency has a major effect, with the most recent episode being replayed the most!
Check the preprint for more: Time, but not reward, shapes replay-based episodic prioritization
... or read on for a thread on the main results! ⏬#NeuroRat #SpatialMemory #MemoryConsolidation #Neuroscience #MastoThread
1/12 🧵 -
RE: https://fediscience.org/@rmgrieves/116692850991318267
“This is a hill I’ll die on!” - says the scientist feeding smelly paste to rats running in a home-made maze with hills and troughs just like the waves in the rat’s brain and the emotions in the scientist’s life… 🏔️ 🌊 🧠
@rmgrieves 's latest paper is out, with rats on hills, #PlaceCells recordings and modelling looking at how the brain maps real-life environments: Hippocampal place cells map terrain geometry independently of behavior
It was great fun to work with him and Jeff Taube on this, even with all the emotional rollercoasters (inherent to science-making)!
#Neuroscience #Hippocampus #3DMapping #NeuroRat #SpatialCognition
-
RE: https://fediscience.org/@rmgrieves/116692850991318267
“This is a hill I’ll die on!” - says the scientist feeding smelly paste to rats running in a home-made maze with hills and troughs just like the waves in the rat’s brain and the emotions in the scientist’s life… 🏔️ 🌊 🧠
@rmgrieves 's latest paper is out, with rats on hills, #PlaceCells recordings and modelling looking at how the brain maps real-life environments: Hippocampal place cells map terrain geometry independently of behavior
It was great fun to work with him and Jeff Taube on this, even with all the emotional rollercoasters (inherent to science-making)!
#Neuroscience #Hippocampus #3DMapping #NeuroRat #SpatialCognition
-
RE: https://fediscience.org/@rmgrieves/116692850991318267
“This is a hill I’ll die on!” - says the scientist feeding smelly paste to rats running in a home-made maze with hills and troughs just like the waves in the rat’s brain and the emotions in the scientist’s life… 🏔️ 🌊 🧠
@rmgrieves 's latest paper is out, with rats on hills, #PlaceCells recordings and modelling looking at how the brain maps real-life environments: Hippocampal place cells map terrain geometry independently of behavior
It was great fun to work with him and Jeff Taube on this, even with all the emotional rollercoasters (inherent to science-making)!
#Neuroscience #Hippocampus #3DMapping #NeuroRat #SpatialCognition
-
RE: https://fediscience.org/@rmgrieves/116692850991318267
“This is a hill I’ll die on!” - says the scientist feeding smelly paste to rats running in a home-made maze with hills and troughs just like the waves in the rat’s brain and the emotions in the scientist’s life… 🏔️ 🌊 🧠
@rmgrieves 's latest paper is out, with rats on hills, #PlaceCells recordings and modelling looking at how the brain maps real-life environments: Hippocampal place cells map terrain geometry independently of behavior
It was great fun to work with him and Jeff Taube on this, even with all the emotional rollercoasters (inherent to science-making)!
#Neuroscience #Hippocampus #3DMapping #NeuroRat #SpatialCognition
-
Sometimes you see weird things on Fedi, like this conversation between Rats (scientists)
Source:
https://neuromatch.social/@adredish/115848409406193646 -
Sometimes you see weird things on Fedi, like this conversation between Rats (scientists)
Source:
https://neuromatch.social/@adredish/115848409406193646 -
Sometimes you see weird things on Fedi, like this conversation between Rats (scientists)
Source:
https://neuromatch.social/@adredish/115848409406193646 -
Sometimes you see weird things on Fedi, like this conversation between Rats (scientists)
Source:
https://neuromatch.social/@adredish/115848409406193646 -
The world of rat models of Alzheimer's disease is proving to simultaneously be much more complex, and much smaller, than I had anticipated.
Apparently, rats are better than mice for comparing with humans, but the large majority of the research is done on mice models.
Also, apparently, much of the existing rat models are not optimal for what I would like to do (appetitive spatial tasks) for different reasons.
So I'm still looking for as much input as possible from people doing research with AD rat models who could point to one that mimics the memory deficits observed in humans 🙏🧠
(My previous post about this:
https://neuromatch.social/@elduvelle_neuro/115107318934779142) -
The world of rat models of Alzheimer's disease is proving to simultaneously be much more complex, and much smaller, than I had anticipated.
Apparently, rats are better than mice for comparing with humans, but the large majority of the research is done on mice models.
Also, apparently, much of the existing rat models are not optimal for what I would like to do (appetitive spatial tasks) for different reasons.
So I'm still looking for as much input as possible from people doing research with AD rat models who could point to one that mimics the memory deficits observed in humans 🙏🧠
(My previous post about this:
https://neuromatch.social/@elduvelle_neuro/115107318934779142) -
The world of rat models of Alzheimer's disease is proving to simultaneously be much more complex, and much smaller, than I had anticipated.
Apparently, rats are better than mice for comparing with humans, but the large majority of the research is done on mice models.
Also, apparently, much of the existing rat models are not optimal for what I would like to do (appetitive spatial tasks) for different reasons.
So I'm still looking for as much input as possible from people doing research with AD rat models who could point to one that mimics the memory deficits observed in humans 🙏🧠
(My previous post about this:
https://neuromatch.social/@elduvelle_neuro/115107318934779142) -
The world of rat models of Alzheimer's disease is proving to simultaneously be much more complex, and much smaller, than I had anticipated.
Apparently, rats are better than mice for comparing with humans, but the large majority of the research is done on mice models.
Also, apparently, much of the existing rat models are not optimal for what I would like to do (appetitive spatial tasks) for different reasons.
So I'm still looking for as much input as possible from people doing research with AD rat models who could point to one that mimics the memory deficits observed in humans 🙏🧠
(My previous post about this:
https://neuromatch.social/@elduvelle_neuro/115107318934779142) -
What are "good" models of Alzheimer's disease in rats? Ones that mimic the memory impairments seen in humans?
I know most people use mice models but are there any labs out there that have rat models? -
What are "good" models of Alzheimer's disease in rats? Ones that mimic the memory impairments seen in humans?
I know most people use mice models but are there any labs out there that have rat models? -
What are "good" models of Alzheimer's disease in rats? Ones that mimic the memory impairments seen in humans?
I know most people use mice models but are there any labs out there that have rat models? -
I contributed a little bit to this methods paper now published in #eNeuro :
Adapt-A-Maze: An Open-Source Adaptable and Automated Rodent Behavior Maze System - my contribution is mostly about the automated, pneumatic door system, as you may know, doors are my thing 😉 🚪First author Blake Porter from the #JadhavLab did a great job putting everything together in an easily-useable format and, for once, I will link to Bluesky with his nice thread on it: https://bsky.app/profile/blakep-neuro.bsky.social/post/3lms56kaj3k2x
If you ever try to implement it in your own lab, let me know!
-
I contributed a little bit to this methods paper now published in #eNeuro :
Adapt-A-Maze: An Open-Source Adaptable and Automated Rodent Behavior Maze System - my contribution is mostly about the automated, pneumatic door system, as you may know, doors are my thing 😉 🚪First author Blake Porter from the #JadhavLab did a great job putting everything together in an easily-useable format and, for once, I will link to Bluesky with his nice thread on it: https://bsky.app/profile/blakep-neuro.bsky.social/post/3lms56kaj3k2x
If you ever try to implement it in your own lab, let me know!
-
I contributed a little bit to this methods paper now published in #eNeuro :
Adapt-A-Maze: An Open-Source Adaptable and Automated Rodent Behavior Maze System - my contribution is mostly about the automated, pneumatic door system, as you may know, doors are my thing 😉 🚪First author Blake Porter from the #JadhavLab did a great job putting everything together in an easily-useable format and, for once, I will link to Bluesky with his nice thread on it: https://bsky.app/profile/blakep-neuro.bsky.social/post/3lms56kaj3k2x
If you ever try to implement it in your own lab, let me know!
-
Here's a short but related 'forum' about exactly this:
Why do primates have view cells instead of place cells?
"if primates are tested in conditions where visual information is scarce, place cell-like representations may emerge."
#MartinezTrujilloLab #Neuroscience #NeuroRat #NeuroPrimate #PlaceCells #ViewCells
-
Here's a short but related 'forum' about exactly this:
Why do primates have view cells instead of place cells?
"if primates are tested in conditions where visual information is scarce, place cell-like representations may emerge."
#MartinezTrujilloLab #Neuroscience #NeuroRat #NeuroPrimate #PlaceCells #ViewCells
-
Here's a short but related 'forum' about exactly this:
Why do primates have view cells instead of place cells?
"if primates are tested in conditions where visual information is scarce, place cell-like representations may emerge."
#MartinezTrujilloLab #Neuroscience #NeuroRat #NeuroPrimate #PlaceCells #ViewCells
-
Thinking about #PlaceCells and the #Hippocampus, do you think results in rats (/rodents) generalise well to humans, and conversely?
-
Thinking about #PlaceCells and the #Hippocampus, do you think results in rats (/rodents) generalise well to humans, and conversely?
-
Thinking about #PlaceCells and the #Hippocampus, do you think results in rats (/rodents) generalise well to humans, and conversely?
-
Thinking about #PlaceCells and the #Hippocampus, do you think results in rats (/rodents) generalise well to humans, and conversely?
-
#NeuroESC #JournalClub
Reading Mental exploration of future choices during immobility theta oscillationsIf you've read it, will you let me know what you think?
The authors look at #ThetaSequences in a working memory task in a radial arm maze. They find theta during immobility (makes sense, e.g. we saw that in our two-goals task). They also find that theta sequences might preferentially represent the next goal (also makes sense, e.g. Hippocampal theta sequences reflect current goals)!
I have only done a quick reading so far, but am confused by a few points:
- the decoding is done on all cells (pyramidals and interneurons), shouldn't it be done on pyramidal or #PlaceCells only?
- the cell counts are quite low (often less than 40 pyrs) when I would have thought at least 50 place cells would be needed for this kind of maze. I guess that shows that #Neuropixels are not the best to record from dCA1!
the decoded algorithm itself includes a ' position transition matrix' which seems like it would bias decoding towards realistic trajectories that the rat is about to do??? (but I probably missed something)
also, this study is very related to this other paper, which is not discussed or even cited (😕 ):
Assembly Responses of Hippocampal CA1 Place Cells Predict Learned Behavior in Goal-Directed Spatial Tasks on the Radial Eight-Arm Maze #CsisvariLab
Let me know what you think!
-
#NeuroESC #JournalClub
Reading Mental exploration of future choices during immobility theta oscillationsIf you've read it, will you let me know what you think?
The authors look at #ThetaSequences in a working memory task in a radial arm maze. They find theta during immobility (makes sense, e.g. we saw that in our two-goals task). They also find that theta sequences might preferentially represent the next goal (also makes sense, e.g. Hippocampal theta sequences reflect current goals)!
I have only done a quick reading so far, but am confused by a few points:
- the decoding is done on all cells (pyramidals and interneurons), shouldn't it be done on pyramidal or #PlaceCells only?
- the cell counts are quite low (often less than 40 pyrs) when I would have thought at least 50 place cells would be needed for this kind of maze. I guess that shows that #Neuropixels are not the best to record from dCA1!
the decoded algorithm itself includes a ' position transition matrix' which seems like it would bias decoding towards realistic trajectories that the rat is about to do??? (but I probably missed something)
also, this study is very related to this other paper, which is not discussed or even cited (😕 ):
Assembly Responses of Hippocampal CA1 Place Cells Predict Learned Behavior in Goal-Directed Spatial Tasks on the Radial Eight-Arm Maze #CsisvariLab
Let me know what you think!
-
#NeuroESC #JournalClub
Reading Mental exploration of future choices during immobility theta oscillationsIf you've read it, will you let me know what you think?
The authors look at #ThetaSequences in a working memory task in a radial arm maze. They find theta during immobility (makes sense, e.g. we saw that in our two-goals task). They also find that theta sequences might preferentially represent the next goal (also makes sense, e.g. Hippocampal theta sequences reflect current goals)!
I have only done a quick reading so far, but am confused by a few points:
- the decoding is done on all cells (pyramidals and interneurons), shouldn't it be done on pyramidal or #PlaceCells only?
- the cell counts are quite low (often less than 40 pyrs) when I would have thought at least 50 place cells would be needed for this kind of maze. I guess that shows that #Neuropixels are not the best to record from dCA1!
the decoded algorithm itself includes a ' position transition matrix' which seems like it would bias decoding towards realistic trajectories that the rat is about to do??? (but I probably missed something)
also, this study is very related to this other paper, which is not discussed or even cited (😕 ):
Assembly Responses of Hippocampal CA1 Place Cells Predict Learned Behavior in Goal-Directed Spatial Tasks on the Radial Eight-Arm Maze #CsisvariLab
Let me know what you think!
-
#NeuroESC #JournalClub
Reading Mental exploration of future choices during immobility theta oscillationsIf you've read it, will you let me know what you think?
The authors look at #ThetaSequences in a working memory task in a radial arm maze. They find theta during immobility (makes sense, e.g. we saw that in our two-goals task). They also find that theta sequences might preferentially represent the next goal (also makes sense, e.g. Hippocampal theta sequences reflect current goals)!
I have only done a quick reading so far, but am confused by a few points:
- the decoding is done on all cells (pyramidals and interneurons), shouldn't it be done on pyramidal or #PlaceCells only?
- the cell counts are quite low (often less than 40 pyrs) when I would have thought at least 50 place cells would be needed for this kind of maze. I guess that shows that #Neuropixels are not the best to record from dCA1!
the decoded algorithm itself includes a ' position transition matrix' which seems like it would bias decoding towards realistic trajectories that the rat is about to do??? (but I probably missed something)
also, this study is very related to this other paper, which is not discussed or even cited (😕 ):
Assembly Responses of Hippocampal CA1 Place Cells Predict Learned Behavior in Goal-Directed Spatial Tasks on the Radial Eight-Arm Maze #CsisvariLab
Let me know what you think!
-
This paper ⬆️ from Caitlin Mallory is now out in Science! Great to see a #HippocampalReplay paper there, and very well deserved!
The time course and organization of hippocampal replay
From #FosterLab, maybe soon the #MalloryLab?? -
This paper ⬆️ from Caitlin Mallory is now out in Science! Great to see a #HippocampalReplay paper there, and very well deserved!
The time course and organization of hippocampal replay
From #FosterLab, maybe soon the #MalloryLab?? -
This paper ⬆️ from Caitlin Mallory is now out in Science! Great to see a #HippocampalReplay paper there, and very well deserved!
The time course and organization of hippocampal replay
From #FosterLab, maybe soon the #MalloryLab?? -
My latest #Neuroesc #JournalClub was on this:
Rat anterior cingulate neurons responsive to rule or strategy changes are modulated by the hippocampal theta rhythm and sharp-wave ripplesI won't do a super-long summary like last time, but please share your thoughts if you've read it!
The author line-up is quite interesting, I think they were all students at the time of data collection which seems to have happened a long time ago, and now many are PIs (@BenoitGirard probably knows about the backstory...)! Probably a pandemic paper??
The scientific question (what supports rule recognition and strategy shift) is really interesting, and they record in the frontal cortex (#ACC) as well as #Hippocampus (ventral CA1!), but the rats just were not up to the task (1/5 rats actually did what they wanted). I am also not fully convinced by some of the analysis. @jessetm I'd be interested to know what you think of their strategy detection method!
Why is it that all papers looking at these themes always end up being.. quite complex??
-
My latest #Neuroesc #JournalClub was on this:
Rat anterior cingulate neurons responsive to rule or strategy changes are modulated by the hippocampal theta rhythm and sharp-wave ripplesI won't do a super-long summary like last time, but please share your thoughts if you've read it!
The author line-up is quite interesting, I think they were all students at the time of data collection which seems to have happened a long time ago, and now many are PIs (@BenoitGirard probably knows about the backstory...)! Probably a pandemic paper??
The scientific question (what supports rule recognition and strategy shift) is really interesting, and they record in the frontal cortex (#ACC) as well as #Hippocampus (ventral CA1!), but the rats just were not up to the task (1/5 rats actually did what they wanted). I am also not fully convinced by some of the analysis. @jessetm I'd be interested to know what you think of their strategy detection method!
Why is it that all papers looking at these themes always end up being.. quite complex??
-
My latest #Neuroesc #JournalClub was on this:
Rat anterior cingulate neurons responsive to rule or strategy changes are modulated by the hippocampal theta rhythm and sharp-wave ripplesI won't do a super-long summary like last time, but please share your thoughts if you've read it!
The author line-up is quite interesting, I think they were all students at the time of data collection which seems to have happened a long time ago, and now many are PIs (@BenoitGirard probably knows about the backstory...)! Probably a pandemic paper??
The scientific question (what supports rule recognition and strategy shift) is really interesting, and they record in the frontal cortex (#ACC) as well as #Hippocampus (ventral CA1!), but the rats just were not up to the task (1/5 rats actually did what they wanted). I am also not fully convinced by some of the analysis. @jessetm I'd be interested to know what you think of their strategy detection method!
Why is it that all papers looking at these themes always end up being.. quite complex??
-
My latest #Neuroesc #JournalClub was on this:
Rat anterior cingulate neurons responsive to rule or strategy changes are modulated by the hippocampal theta rhythm and sharp-wave ripplesI won't do a super-long summary like last time, but please share your thoughts if you've read it!
The author line-up is quite interesting, I think they were all students at the time of data collection which seems to have happened a long time ago, and now many are PIs (@BenoitGirard probably knows about the backstory...)! Probably a pandemic paper??
The scientific question (what supports rule recognition and strategy shift) is really interesting, and they record in the frontal cortex (#ACC) as well as #Hippocampus (ventral CA1!), but the rats just were not up to the task (1/5 rats actually did what they wanted). I am also not fully convinced by some of the analysis. @jessetm I'd be interested to know what you think of their strategy detection method!
Why is it that all papers looking at these themes always end up being.. quite complex??
-
#Tetrode recordings (in a bundle): did you know that you could record the same neuron on two different tetrodes?
or even three different tetrodes??After checking that, turns out I usually have about 5-10% of neurons that are a duplicate of another neuron, in a given 8-tetrodes recording! They are pretty easy to detect with a firing rate correlation so I can remove them from analysis.
But I bet most neuron counts in published papers are inflated of that much!Here's an example where you can see the spike plots and waveforms of 3 different, well-isolated clusters, recorded from 3 different tetrodes!
#Hexamaze #NeuroRat #Neuroscience #Ephys #Hippocampus #PlaceCells #SpikeSorting (-related)
-
#Tetrode recordings (in a bundle): did you know that you could record the same neuron on two different tetrodes?
or even three different tetrodes??After checking that, turns out I usually have about 5-10% of neurons that are a duplicate of another neuron, in a given 8-tetrodes recording! They are pretty easy to detect with a firing rate correlation so I can remove them from analysis.
But I bet most neuron counts in published papers are inflated of that much!Here's an example where you can see the spike plots and waveforms of 3 different, well-isolated clusters, recorded from 3 different tetrodes!
#Hexamaze #NeuroRat #Neuroscience #Ephys #Hippocampus #PlaceCells #SpikeSorting (-related)
-
#Tetrode recordings (in a bundle): did you know that you could record the same neuron on two different tetrodes?
or even three different tetrodes??After checking that, turns out I usually have about 5-10% of neurons that are a duplicate of another neuron, in a given 8-tetrodes recording! They are pretty easy to detect with a firing rate correlation so I can remove them from analysis.
But I bet most neuron counts in published papers are inflated of that much!Here's an example where you can see the spike plots and waveforms of 3 different, well-isolated clusters, recorded from 3 different tetrodes!
#Hexamaze #NeuroRat #Neuroscience #Ephys #Hippocampus #PlaceCells #SpikeSorting (-related)
-
#JournalClub on Closed-loop modulation of remote hippocampal representations with neurofeedback, from #FrankLab: little summary + comments.
- The goal is to see if rats can deliberately reactivate internal representations, without external cues.
- The authors design a closed-loop system that does clusterless real-time decoding of position and rewards the rats when they reactivate a specific maze arm end.
- The rats go through a gradual training process: first getting reward on the actual maze (a T-maze), then getting reward in the home box when they orient towards the target arm of the maze [head-direction task], then getting reward in the home box when they reactivate the representation of the target maze end [neurofeedback task].
- The rat's performance is not too bad given the difficulty of the task, kudos to Rat2 who seemed to really know what he was doing.
- interestingly, the reactivations do not happen during #SharpWaveRipples, and not really during theta either, just during an uncharacterised LFP state.
- Little caveat 1: as far as I can see, the head-direction of the rats is not shown in any plot and it is not possible to say if the rats might still be doing the head-direction task during the neurofeedback task. That being said, the rats clearly reactivate the target arm more in the neurofeedback than head-direction task, which is quite convincing.
Little caveat 2: the performance is always shown in terms of total rewards collected, and not reward rate. So in different sessions rats might reach the maximum reward but take twice the time. Showing reward rate would be more informative.
conclusion: this is pretty cool, but we would really need to know about the head-direction.
question for the audience: what do you think the rats "think about" during those reactivation moments??
#Neuroscience #HippocampalReplay (not really) #ThetaSequences (not really) #PlaceCells #NeuroRat #Hippocampus
-
#JournalClub on Closed-loop modulation of remote hippocampal representations with neurofeedback, from #FrankLab: little summary + comments.
- The goal is to see if rats can deliberately reactivate internal representations, without external cues.
- The authors design a closed-loop system that does clusterless real-time decoding of position and rewards the rats when they reactivate a specific maze arm end.
- The rats go through a gradual training process: first getting reward on the actual maze (a T-maze), then getting reward in the home box when they orient towards the target arm of the maze [head-direction task], then getting reward in the home box when they reactivate the representation of the target maze end [neurofeedback task].
- The rat's performance is not too bad given the difficulty of the task, kudos to Rat2 who seemed to really know what he was doing.
- interestingly, the reactivations do not happen during #SharpWaveRipples, and not really during theta either, just during an uncharacterised LFP state.
- Little caveat 1: as far as I can see, the head-direction of the rats is not shown in any plot and it is not possible to say if the rats might still be doing the head-direction task during the neurofeedback task. That being said, the rats clearly reactivate the target arm more in the neurofeedback than head-direction task, which is quite convincing.
Little caveat 2: the performance is always shown in terms of total rewards collected, and not reward rate. So in different sessions rats might reach the maximum reward but take twice the time. Showing reward rate would be more informative.
conclusion: this is pretty cool, but we would really need to know about the head-direction.
question for the audience: what do you think the rats "think about" during those reactivation moments??
#Neuroscience #HippocampalReplay (not really) #ThetaSequences (not really) #PlaceCells #NeuroRat #Hippocampus
-
#JournalClub on Closed-loop modulation of remote hippocampal representations with neurofeedback, from #FrankLab: little summary + comments.
- The goal is to see if rats can deliberately reactivate internal representations, without external cues.
- The authors design a closed-loop system that does clusterless real-time decoding of position and rewards the rats when they reactivate a specific maze arm end.
- The rats go through a gradual training process: first getting reward on the actual maze (a T-maze), then getting reward in the home box when they orient towards the target arm of the maze [head-direction task], then getting reward in the home box when they reactivate the representation of the target maze end [neurofeedback task].
- The rat's performance is not too bad given the difficulty of the task, kudos to Rat2 who seemed to really know what he was doing.
- interestingly, the reactivations do not happen during #SharpWaveRipples, and not really during theta either, just during an uncharacterised LFP state.
- Little caveat 1: as far as I can see, the head-direction of the rats is not shown in any plot and it is not possible to say if the rats might still be doing the head-direction task during the neurofeedback task. That being said, the rats clearly reactivate the target arm more in the neurofeedback than head-direction task, which is quite convincing.
Little caveat 2: the performance is always shown in terms of total rewards collected, and not reward rate. So in different sessions rats might reach the maximum reward but take twice the time. Showing reward rate would be more informative.
conclusion: this is pretty cool, but we would really need to know about the head-direction.
question for the audience: what do you think the rats "think about" during those reactivation moments??
#Neuroscience #HippocampalReplay (not really) #ThetaSequences (not really) #PlaceCells #NeuroRat #Hippocampus
-
It's always nice when you finally finish #SpikeSorting an old recording session and find many #PlaceCells (here, 101) 🥰
I also recently implemented a way to remove putative duplicate recordings (when spikes from the same neutron are detected in two different tetrodes) and there can be a surprisingly high amount, 6-10 % of cells as far as I can see, this is with bundles of 8 tetrodes.
-
It's always nice when you finally finish #SpikeSorting an old recording session and find many #PlaceCells (here, 101) 🥰
I also recently implemented a way to remove putative duplicate recordings (when spikes from the same neutron are detected in two different tetrodes) and there can be a surprisingly high amount, 6-10 % of cells as far as I can see, this is with bundles of 8 tetrodes.