Difference between revisions of "ICLM Journal Club"

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=<font color="blue">'''This Week - 08 October 2021 (9:30 a.m., via Zoom)'''</font>=
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=<font color="blue">'''This Week - 15 October 2021 (9:30 a.m., via Zoom)'''</font>=
  
<u>Speaker:</u> '''Mayank Mehta and Chinmay Purandare'''
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<u>Speaker:</u> '''Michael Levin'''
  
<u>Title: </u> ''' “  Moving bar of light generates angle, distance and direction selectivity in place cells. ” '''
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<u>Title: </u> ''' “ Developmental bioelectricity as a precursor to neuroscience: how the collective intelligence of cell groups solves problems in anatomical morphospace ” '''
  
<u>Abstract:</u>  Primary visual cortical neurons selectively respond to the position and motion direction of specific stimuli retrospectively, without any locomotion or task demand. At the other end of the visual circuit is the hippocampus, where in addition to visual cues, self-motion cues and task demand are thought to be crucial to generate selectivity to allocentric space in rodents that is abstract and prospective. In primates, however, hippocampal neurons encode object-place association without any locomotion requirement. To bridge these disparities, we measured rodent hippocampal responses to a vertical bar of light in a body-fixed rat, independent of behavior and rewards. When the bar revolved around the rat at a fixed distance, more than 70% of dorsal CA1 neurons showed stable modulation of activity as a function of the bar’s angular position, while nearly 40% showed canonical angular tuning, in a body-centric coordinate frame, termed Stimulus Angle Cells or Coding (SAC). The angular position of the oriented bar could be decoded from only a few hundred neurons’ activity. Nearly a third of SAC were also tuned to the direction of revolution of the bar and most of these responses were retrospective. SAC were invariant with respect to the pattern, color, speed and predictability of movement of the bar. When the bar moved towards and away from the rat at a fixed angle, neurons encoded its distance and direction of movement, with more neurons preferring approaching motion. Thus, a majority of neurons in the hippocampus, a multisensory region several synapses away from the primary visual cortex, encode non-abstract information about stimulus-angle, distance and direction of movement, in a manner similar to the visual cortex, without any locomotion, reward or memory demand. We posit that these responses would influence the cortico-hippocampal circuit and form the basis for generating abstract and prospective representations.
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<u>Abstract:</u>  Most of the components of nervous systems - ion channels, gap junctions, and neurotransmitter pathways - existed long before brains evolved. What did tissues think about before there were brains?  In this talk, I will first introduce the emerging field of developmental bioelectricity, which has uncovered fascinating ways in which electrical networks made of non-neural cells make decisions about growth and form. Having made the first molecular tools for reading and writing the content of non-neural bioelectric circuits, we found that gradients of slowly-changing resting potentials are instructive prepatterns for gene expression and morphogenesis of the eye, brain, limb, and face. These dynamics mediate anatomical homeostasis during regulative development and regeneration, and sit as a kind of software layer between the genome and the anatomy. I will describe our efforts to crack the bioelectric code, and to understand its plasticity, modularity, and ability to store re-writable information about large scale body geometry. This work has led to the ability to permanently re-write the target morphology of planaria without genomic editing or transgenes, and to applications in limb regeneration, tumor reprogramming, and the repair of birth defects of the brain. Having introduced the tools for modulating non-neural computations, I will discuss examples of how the bioelectrically-stored information guides the behavior of the collective intelligence of somatic cell groups. In addition to the numerous biomedical applications, these data shed light on the origins of cognition, showing how the remarkable capacities of nervous systems could be an evolutionary pivot of much more ancient problem-solving in anatomical morphospace.
  
<u> Blurb: </u> A novel, simple way to activate the hippocampus and probe its function. Hippocampus is crucial for learning and memory and implicated in major disorders including Alzheimer's, epilepsy and schizophrenia. But, hippocampal responses in rodents are measured when they are navigating a spatial arena, and called place cells. While humans and nonhuman primate hippocampal function is typically measured while the subjects are seated and solving a memory task, leading to very different types of activity that is often unrelated to space. To overcome these challenges, and generate a reliable translational model of hippocampal function we need an experimental design that can be concocted in rodents and humans under identical conditions. Here we report such a novel and simple design that generates reliable responses in the rodent hippocampus.
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<u>Relevant Papers:</u> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914563/
  
<u>Relevant Papers:</u>  For background material see: http://www.physics.ucla.edu/~mayank/publications.html
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https://www.sciencedirect.com/science/article/pii/S0006291X20320064
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https://www.sciencedirect.com/science/article/pii/S0092867421002233?via%3Dihub
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https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02688/full
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667987/
  
  

Revision as of 20:14, 12 October 2021

This Week - 15 October 2021 (9:30 a.m., via Zoom)

Speaker: Michael Levin

Title: “ Developmental bioelectricity as a precursor to neuroscience: how the collective intelligence of cell groups solves problems in anatomical morphospace ”

Abstract: Most of the components of nervous systems - ion channels, gap junctions, and neurotransmitter pathways - existed long before brains evolved. What did tissues think about before there were brains? In this talk, I will first introduce the emerging field of developmental bioelectricity, which has uncovered fascinating ways in which electrical networks made of non-neural cells make decisions about growth and form. Having made the first molecular tools for reading and writing the content of non-neural bioelectric circuits, we found that gradients of slowly-changing resting potentials are instructive prepatterns for gene expression and morphogenesis of the eye, brain, limb, and face. These dynamics mediate anatomical homeostasis during regulative development and regeneration, and sit as a kind of software layer between the genome and the anatomy. I will describe our efforts to crack the bioelectric code, and to understand its plasticity, modularity, and ability to store re-writable information about large scale body geometry. This work has led to the ability to permanently re-write the target morphology of planaria without genomic editing or transgenes, and to applications in limb regeneration, tumor reprogramming, and the repair of birth defects of the brain. Having introduced the tools for modulating non-neural computations, I will discuss examples of how the bioelectrically-stored information guides the behavior of the collective intelligence of somatic cell groups. In addition to the numerous biomedical applications, these data shed light on the origins of cognition, showing how the remarkable capacities of nervous systems could be an evolutionary pivot of much more ancient problem-solving in anatomical morphospace.

Relevant Papers: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914563/

https://www.sciencedirect.com/science/article/pii/S0006291X20320064

https://www.sciencedirect.com/science/article/pii/S0092867421002233?via%3Dihub

https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02688/full

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667987/


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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