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K a r i m B e n c h e n a n e Importance of rhythms for cell assemblies synchronization Master BIP - Dec 1th 2015 << Importance of rhythms in cell assemblies synchronization 1) Cell assemblies 2) Rhythms 3) Rhythms and cell

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K a r i m B e n c h e n a n e Importance of rhythms for cell assemblies synchronization

Master BIP - Dec 1th 2015

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1) Cell assemblies 2) Rhythms 3) Rhythms and cell assemblies

Importance of rhythms in cell assemblies synchronization

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Extracellular electrophysiological recordings

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PPSE PPSI PPSE PPSE PPSE PPSI PPSI

Local Field Potential = Sum of all PPSE and PPSI

Action potential (spike) Action potential (spike) Action potential (spike) Action potential (spike)

LFP = Input Spike = Output

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Excitatory** input*

?*

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Excitatory** input*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Excitatory** input*

?* ?*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Excitatory** input*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Inhibitory* input*

?* ?* ?*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Inhibitory* input*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Excitatory** input*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Inhibitory* input*

?* ?* ?*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Inhibitory* input*

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LFP$electrode$ superficial+ LFP$electrode$ deep+ Excitatory** input*

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Reference' Cortex'pariétal'

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Reference' Cortex'pariétal'

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Reference' Cortex'pariétal'

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Reference' Cortex'pariétal'

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Extracellular electrophysiological recordings

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Extracellular electrophysiological recordings

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Extracellular electrophysiological recordings

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Note that in a particular condition 90% of the neurons are silent Extracellular electrophysiological recordings

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Extracellular electrophysiological recordings

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Extracellular recordings in human (epileptic patients)

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Quian Quiroga et al., Nature 2005

Neural bases of semantic memory

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Neural bases of semantic memory

Quian Quiroga et al., Nature 2005

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Neural bases of semantic memory

Quian Quiroga et al., Nature 2005

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Response in IT : ~130 ms (primate) Response in MTL: ~250-300 ms Recognition in human : ~150ms

The cell responding to pictures of Darth Vador might not be involved in recognizing him Crucial for the storage of new long-term memories and related to the fact that the patient viewed his pictures in the clinic.

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1/ Presentation of several movies with different actors 2/ Recollection task: which movies have you seen? Gelbard-Sagiv, et al., Science, 2008

Neural bases of semantic memory

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Place cell

Jung, Wiener et McNaughton,1994

The position of the animal can be predicted by the neuronal activity in the hippocampus

Internal representation of space in the hippocampus

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The position of the animal can be predicted by the neuronal activity in the hippocampus

Place cell

Internal representation of space in the hippocampus

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  • Place cells properties:

– Discharge a pyramidal neurons related to the position of the animal – Place Field is formed after few minutes and is stable for months – Rotation of external cues induce the rotation of place fields – A particular place cells have different place fields in different contexts

Internal representation of space in the hippocampus

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  • Place cells properties:

– Discharge a pyramidal neurons related to the position of the animal – Place Field is formed after few minutes and is stable for months – Rotation of external cues induce the rotation of place fields – A given place cell can have different place fields in different contexts

Internal representation of space in the hippocampus

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Internal representation of space in the hippocampus

Contexte A Contexte B

time time

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Neural bases of semantic memory

Quian Quiroga et al., Nat rev Neurosci

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Quian Quiroga et al., Trends Cog Sci & Nat rev Neurosci

Sparse coding with cell assemblies or grandmother’s cell ?

(1) Probability to find the item selective for the recorded neuron is

  • ne over 1 million

(2) Images already known by the subjects were used (3) Two million neurons represent a given percept over few hundred millions neurons in MTL (bayesian estimation) (4) One neuron could fire for different items.

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Cell assemblies

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Donald Hebb, The Organization of Behavior, 1949

"The general idea is an old one, that any two cells or systems of cells that are repeatedly active at the same time will tend to become 'associated', so that activity in one facilitates activity in the other." (p. 70) "When one cell repeatedly assists in firing another, the axon of the first cell develops synaptic knobs (or enlarges them if they already exist) in contact with the soma of the second cell." (p. 63)

Assemblée cellulaire

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"If the inputs to a system cause the same pattern of activity to occur repeatedly, the set

  • f active elements constituting that pattern will become increasingly strongly
  • interassociated. That is, each element will tend to turn on every other element and (with

negative weights) to turn off the elements that do not form part of the pattern. To put it another way, the pattern as a whole will become 'auto-associated'. We may call a learned (auto-associated) pattern an engram." (p. 44) Donald Hebb, The Organization of Behavior, 1949

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(d’après Bi & Poo 1998)

Spike 'ming dependent plas'city Cell assemblies: synchroniza'on within 'me period compa'ble with STDP

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synchronization

Synchroniza'on & cell assemblies

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synchronization

Synchroniza'on & cell assemblies

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global noise local noise claping period Average noise intensity correlation

Neda et al Nature 2000

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Cell assemblies, rhythms and the binding problem

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Cell assemblies synchronization and the binding problem

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Cell assemblies synchronization and the binding problem

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Cell assemblies synchronization and the binding problem

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"This situation was instantaneously and radically changed by a historical event, the symposium on visual perception at the Society for Neuroscience meeting in Washington, DC, in the fall of 1993. I have never seen so many neuroscientists attending any lecture on any topic of neuroscience than at that milestone

  • event. ... After a long vacuum in systems research, a radicaly different and

comprehensive theory was on the horizon.The protagonist of the symposium was Wolf Singer from the Max-Planck Institute in Frankfurt- am-Main, Germany." György Buzsáki, Rhythms of the brain

Wolf Singer

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Cell assemblies synchronization and the binding problem

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Cell 1 Cell 2 Synchronisation ???

Cell assemblies synchronization and the binding problem

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if you’re interested, read this…

« It needs still to be clarified, however, if the temporal code could solve the riddles of perceptual grouping. As things are at present, the binding problem reflects at least three correlated subquestions: (1) the segmentation of a complex visual scene, or figure- ground segregation; (2) the integration of a single perceptual object as from its components, and (3) the recognition of an object in spite of its variation in position, size, perspective, etc. » « An important aspect of this hypothesis, is that for the first time in the history of neuroscience, it has accounted for perceptual processes without invoking the idea of a superior area or center, where all processed information would converge. Accordingly, the fallacy of the homunculus (a torment for philosophers à la Daniel Dennett [51]) would be exorcised forever. » « For reasons largely unresolved until now, it appeared difficult to replicate in some laboratories the seminal results reported by Wolf Singer and his colleagues at the Max-Planck-Institute for Brain Research in Frankfurt, and by Reinhard Eckhorn and his group at the Philipps- University in

  • Marburg. Some critical observations, moved by Martin Tovée and Edmund Rolls [16, 17] and by

Geoffrey Ghose and Ralph Freeman [18] in 1992, deserve particular attention in this context: either oscillations were not found in the visual cortex, or if they were, they appeared to be rhythmic responses not correlated to the stimulus. »

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Delta waves - Delta rhythm(s)

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Deep Sup

Pfc

Deep Sup

Par Cx

Deep Sup

Aud Cx Aud Th Hpc

Delta waves - Delta rhythm(s)

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Deep Sup

Pfc

Deep Sup

Par Cx

Deep Sup

Aud Cx Aud Th Hpc

* * * * * * * * * *

Delta waves - Delta rhythm(s)

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Theta oscillations

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INTERNEURONS PYRAMIDAL CELLS

Theta oscillations

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Theta

π 2π π 2π

π 2π

Modulation of hippocampal neurons by theta

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Pyramidal neurons





Interneurones


25-30 classes of interneurons

Cellular types within the hippocampus

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Modulation of hippocampal neurons by theta

Somogyi and Klauberger, Science, 2008

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Theta oscillations

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Rhythm generator

Vertes et al 2004

medial septum inactivation

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EC3 CA1 CA3 EC5 DG EC2 Current generator

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Current generator

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Coupling theta - Gamma

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Cross-frequency coupling

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INTERNEURONS PYRAMIDAL CELLS

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INTERNEURONS PYRAMIDAL CELLS

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INTERNEURONS PYRAMIDAL CELLS

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INTERNEURONS PYRAMIDAL CELLS

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INTERNEURONS PYRAMIDAL CELLS

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Geisler PNAS 2008

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Köning et al. TINS 1996

Rate coding “Integrator” Temporal coding “Coincidence detector” Importance of Rhythms: Temporal versus rate coding

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threshold AP 5me

Importance of Rhythms: Temporal versus rate coding

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threshold AP 5me

Importance of Rhythms: Temporal versus rate coding

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threshold AP 5me

Importance of Rhythms: Temporal versus rate coding

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threshold AP 5me

rythmical inhibi4on

Gilles Laurent (olfactory system in locust)

Importance of Rhythms: Temporal versus rate coding

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Inhibition could act by a non intuitive way …

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Schreiber J Neurophy 2004

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Schreiber J Neurophy 2004

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93

What are the experimental evidences of the importance of rhythms

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94

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Phase

0° 360° 180°

Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

Phase

0° 360° 180°

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Modulation of hippocampal neurons by theta: Phase precession

Phase

0° 360° 180°

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Modulation of hippocampal neurons by theta: Phase precession

Phase

0° 360° 180°

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Modulation of hippocampal neurons by theta: Phase precession

Phase

0° 360° 180°

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Phase precession

O'Keefe et Recce 1993 Modulation of hippocampal neurons by theta: Phase precession

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The phase of spikes improves their spatial information content

Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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Modulation of hippocampal neurons by theta: Phase precession

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In a theta cycle: where I was, where I am, where I am going. Temporal compression of sequence in time delays compatible with STDP

Modulation of hippocampal neurons by theta: Phase precession

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(d’après Bi & Poo 1998)

Spike 'ming dependent plas'city Cell assemblies: synchroniza'on within 'me period compa'ble with STDP

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In a theta cycle: where I was, where I am, where I am going. Temporal compression of sequence in time delays compatible with STDP

Modulation of hippocampal neurons by theta: Phase precession

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Robbe & Buzsaki J Neurosci 2009

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CA1 CA3 EC5 DG EC2

Grid cells / Place cells Theta rhythm

Holly grail of electrophysiologists in freely moving rodents

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CA1 CA3

Place cells not affected by CA3 removal > Place signal comes from Entorhinal cortex (Grid cells) Grid cells > Place cells Theta rhythm

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Koenig et al. Science 2011

Theta inactivation by lidocaine in the septum

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Team Memory, Oscillations and Brain States

Laboratoire de Neurobiologie, UMR 7637 CNRS ESPCI Paris Tech (directeur Thomas Preat) Karim Benchenane CR1 CNRS Gaetan De Lavilléon PhD student Marie Lacroix PhD student Noelia Do Carmo Blanco Master 2 Matthieu Koroma Master 1