Difference between revisions of "ICLM Journal Club"

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(This Week - 11 February 2022 (9:30 a.m., via Zoom))
(This Week - 11 February 2022 (9:30 a.m., via Zoom))
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=<font color="blue">'''This Week - 11 February 2022 (9:30 a.m., via Zoom)'''</font>=
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=<font color="blue">'''This Week - 18 February 2022 (9:30 a.m., via Zoom)'''</font>=
  
<u>Speaker:</u> '''Lukas Oesch '''
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<u>Speaker:</u> '''Saray Soldado Magraner '''
  
<u>Title: </u> ''' “ Mouse prefrontal cortex represents learned rules for categorization ” '''
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<u>Title: </u> ''' “ What is the dynamic regime of the cerebral cortex” '''
  
<u>Summary:</u> How animals learn to classify a set of stimuli into discrete categories that can guide the selection of adequate behavioral responses remains poorly understood. One of the major challenges in identifying the neural representation of such categories is that they might partially overlap with other representations, such as stimulus identity or chosen actions. In their study Reinert and colleagues recorded neural activity in the mouse prefrontal cortex while animals were learning a visual Go/NoGo task. They demonstrate the presence of category selective neurons by changing either the categorization rule on a constant set of stimuli or the way animals reported their choice. They further show that category selectivity for Go-associated stimuli arises earlier in learning than NoGo-category selectivity.  
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<u>Blurb: </u> In which regime does the cerebral cortex operate? This is a fundamental question for understanding cortical function. Decades of theoretical and experimental studies have converged into a model where strong recurrent excitation--unstable by itself--is balanced by recurrent inhibition. Circuits operating in this regime are known as Inhibition Stabilized Networks (ISN). However, it has been unclear whether the cortex operates as an ISN 'by default' or just under certain circumstances (for example, under strong sensory input). In this talk, I will introduce what ISN are and how we can prove them experimentally. I will then present the most compelling experimental study to date supporting that ISN may be the default dynamic regime of the cortex.
  
<u>Relevant papers:</u>  https://www.nature.com/articles/s41586-021-03452-z
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<u>Summary:</u> Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.
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<u>Relevant papers:</u>  https://elifesciences.org/articles/54875
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https://www.nature.com/articles/s41583-020-00390-z
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https://www.sciencedirect.com/science/article/pii/S0896627321005754
  
 
='''About Us'''=
 
='''About Us'''=

Revision as of 01:44, 16 February 2022

This Week - 18 February 2022 (9:30 a.m., via Zoom)

Speaker: Saray Soldado Magraner

Title: “ What is the dynamic regime of the cerebral cortex? ”

Blurb: In which regime does the cerebral cortex operate? This is a fundamental question for understanding cortical function. Decades of theoretical and experimental studies have converged into a model where strong recurrent excitation--unstable by itself--is balanced by recurrent inhibition. Circuits operating in this regime are known as Inhibition Stabilized Networks (ISN). However, it has been unclear whether the cortex operates as an ISN 'by default' or just under certain circumstances (for example, under strong sensory input). In this talk, I will introduce what ISN are and how we can prove them experimentally. I will then present the most compelling experimental study to date supporting that ISN may be the default dynamic regime of the cortex.

Summary: Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.

Relevant papers: https://elifesciences.org/articles/54875 https://www.nature.com/articles/s41583-020-00390-z https://www.sciencedirect.com/science/article/pii/S0896627321005754

About Us

Introduction

The Integrative Center for Learning and Memory (ICLM) is a multidisciplinary center of UCLA labs devoted to understanding the neural basis of learning and memory and its disorders. This will require a unified approach across different levels of analysis, including;

1. Elucidating the molecular cellular and systems mechanisms that allow neurons and synapses to undergo the long-term changes that ultimately correspond to 'neural memories'.

2. Understanding how functional dynamics and computations emerge from complex circuits of neurons, and how plasticity governs these processes.

3. Describing the neural systems in which different forms of learning and memory take place, and how these systems interact to ultimately generate behavior and cognition.

History of ICLM

The Integrative Center for Learning and Memory formally LMP started in its current form in 1998, and has served as a platform for many interactions and collaborations within UCLA. A key event organized by the group is the weekly ICLM Journal Club. For more than 10 years, graduate students, postdocs, principal investigators, and invited speakers have presented on topics ranging from the molecular mechanisms of synaptic plasticity, through computational models of learning, to behavior and cognition. Dean Buonomano oversees the ICLM journal club with help of student/post doctoral organizers. For other events organized by ICLM go to http://www.iclm.ucla.edu/Events.html.

Current Organizers:

Megha Sehgal (Silva Lab) & Giselle Fernandes (Silva Lab). Please email us at iclm.journalclub@gmail.com if you would like to get regular updates regarding our journal club and weekly reminders.

Current Faculty Advisor:

Dean Buonomano


Past Organizers:

i) Anna Matynia(Aug 2004 - Jun 2008) (Silva Lab)

ii) Robert Brown (Aug 2008 - Jun 2009) (Balleine Lab)

iii) Balaji Jayaprakash (Aug 2008 - Nov 2011) (Silva Lab)

iv) Justin Shobe & Thomas Rogerson (Dec 2011 - June 2013) (Silva Lab)

v) Walt Babiec (O'Dell Lab) (2013-2014)

vi) Walt Babiec (O'Dell Lab) & Helen Motanis (Buonomano Lab) (2014-2017)

vii) Helen Motanis (Buonomano Lab) & Shonali Dhingra (Mehta Lab) (2017-2018)

viii) Shonali Dhingra (Mehta Lab) (2018-2020)

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