Difference between revisions of "ICLM Journal Club"

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=<font color="blue">'''This Week - 19 March 2021 (9:30 a.m., via Zoom)'''</font>=
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=<font color="blue">'''This Week - 02 April 2021 (9:30 a.m., via Zoom)'''</font>=
  
<u>Speaker:</u> '''Panayiota Poirazi'''
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<u>Speaker:</u> '''Mohamady El-Gaby'''
  
<u>Title:</u> “ How dendrites help solve biological and machine learning problems
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<u>Title:</u> “ An emergent neural coactivity code for dynamic memory
  
<u>Abstract:</u>  Dendrites are thin processes that extend from the cell body of neurons, the main computing units of the brain. The role of dendrites in complex brain functions has been investigated for several decades, yet their direct involvement in key behaviors such as for example sensory perception has only recently been established. In my presentation I will discuss how computational modelling has helped us illuminate dendritic function [1]. I will present the main findings of a number of projects in lab dealing with dendritic nonlinearities in excitatory and inhibitory and their consequences on neuronal tuning [2] and memory formation [3], the role of dendrites in solving nonlinear problems in human neurons [4] and recent efforts to advance machine learning algorithms by adopting dendritic features.  
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<u>Abstract:</u>  Neural correlates of external variables provide potential internal codes that guide an animal’s behavior. Notably, first-order features of neural activity, such as single-neuron firing rates, have been implicated in encoding information. However, the extent to which higher-order features, such as multineuron coactivity, play primary roles in encoding information or secondary roles in supporting single-neuron codes remains unclear. Here, we show that millisecond-timescale coactivity among hippocampal CA1 neurons discriminates distinct, short-lived behavioral contingencies. This contingency discrimination was unrelated to the tuning of individual neurons, but was instead an emergent property of their coactivity. Contingency-discriminating patterns were reactivated offline after learning, and their reinstatement predicted trial-by-trial memory performance. Moreover, optogenetic suppression of inputs from the upstream CA3 region during learning impaired coactivity-based contingency information in the CA1 and subsequent dynamic memory retrieval. These findings identify millisecond-timescale coactivity as a primary feature of neural firing that encodes behaviorally relevant variables and supports memory retrieval.
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<u>Relevant Paper(s):</u>  https://www.nature.com/articles/s41593-021-00820-w#Sec9
  
<u>Relevant Paper(s):</u>    https://www.nature.com/articles/s41583-020-0301-7
 
https://www.nature.com/articles/s41467-019-11537-7
 
https://doi.org/10.1038/s41467-019-13029-0
 
https://science.sciencemag.org/content/367/6473/83
 
 
   
 
   
 
='''About Us'''=
 
='''About Us'''=

Revision as of 15:01, 30 March 2021

This Week - 02 April 2021 (9:30 a.m., via Zoom)

Speaker: Mohamady El-Gaby

Title: “ An emergent neural coactivity code for dynamic memory ”

Abstract: Neural correlates of external variables provide potential internal codes that guide an animal’s behavior. Notably, first-order features of neural activity, such as single-neuron firing rates, have been implicated in encoding information. However, the extent to which higher-order features, such as multineuron coactivity, play primary roles in encoding information or secondary roles in supporting single-neuron codes remains unclear. Here, we show that millisecond-timescale coactivity among hippocampal CA1 neurons discriminates distinct, short-lived behavioral contingencies. This contingency discrimination was unrelated to the tuning of individual neurons, but was instead an emergent property of their coactivity. Contingency-discriminating patterns were reactivated offline after learning, and their reinstatement predicted trial-by-trial memory performance. Moreover, optogenetic suppression of inputs from the upstream CA3 region during learning impaired coactivity-based contingency information in the CA1 and subsequent dynamic memory retrieval. These findings identify millisecond-timescale coactivity as a primary feature of neural firing that encodes behaviorally relevant variables and supports memory retrieval.

Relevant Paper(s): https://www.nature.com/articles/s41593-021-00820-w#Sec9


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)

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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