Flexible communication between cell assemblies and ‘reader’ neurons

Cell assemblies are considered fundamental units of brain activity, underlying diverse functions ranging from perception to memory and decision-making. Cell assemblies have historically been theorized as internal representations of specific stimuli or actions. Alternatively, cell assemblies can be defined without reference to an external world, by their endogenous ability to effectively elicit specific responses in downstream (‘reader’) neurons. However, this compelling framework currently lacks experimental support. Here, we provide evidence for assembly– reader communication. Reader activation was genuinely collective, functionally selective, yet flexible, implementing both pattern separation and completion. These processes occurred at the time scale of membrane integration, synaptic plasticity and gamma oscillations. Finally, assembly–reader couplings were selectively modified upon associative learning, indicating that they were plastic and could become bound to behaviorally relevant variables. These results support cell assemblies as an endogenous mechanism for brain function.

[1]  Ralitsa Todorova,et al.  Discriminating Sleep From Freezing With Cortical Spindle Oscillations , 2022, Frontiers in Neural Circuits.

[2]  M. Zugaro,et al.  Distributed cell assemblies spanning prefrontal cortex and striatum , 2021, Current Biology.

[3]  K. Mizuseki,et al.  De novo inter-regional coactivations of preconfigured local ensembles support memory , 2021, Nature Communications.

[4]  Katalin M. Gothard,et al.  Multidimensional processing in the amygdala , 2020, Nature Reviews Neuroscience.

[5]  Michaël Zugaro,et al.  Isolated cortical computations during delta waves support memory consolidation , 2019, Science.

[6]  Mohamady El-Gaby,et al.  An Emergent Neural Coactivity Code for Dynamic Memory , 2019, Nature Neuroscience.

[7]  G. Buzsáki The Brain from Inside Out , 2019 .

[8]  G. Buzsáki,et al.  Cocaine Place Conditioning Strengthens Location-Specific Hippocampal Coupling to the Nucleus Accumbens , 2018, Neuron.

[9]  György Buzsáki,et al.  Reactivations of emotional memory in the hippocampus–amygdala system during sleep , 2017, Nature Neuroscience.

[10]  H. Eichenbaum Barlow versus Hebb: When is it time to abandon the notion of feature detectors and adopt the cell assembly as the unit of cognition? , 2017, Neuroscience Letters.

[11]  Elad Eban,et al.  A cortical–hippocampal–cortical loop of information processing during memory consolidation , 2016, Nature Neuroscience.

[12]  Kenneth D. Harris,et al.  Fast and accurate spike sorting of high-channel count probes with KiloSort , 2016, NIPS.

[13]  Matthieu O. Pasquet,et al.  Wireless inertial measurement of head kinematics in freely-moving rats , 2016, Scientific Reports.

[14]  Nikolaos Karalis,et al.  Prefrontal neuronal assemblies temporally control fear behaviour , 2016, Nature.

[15]  G. Petrovich,et al.  Organization of connections between the amygdala, medial prefrontal cortex, and lateral hypothalamus: a single and double retrograde tracing study in rats , 2016, Brain Structure and Function.

[16]  György Buzsáki,et al.  What does gamma coherence tell us about inter-regional neural communication? , 2015, Nature Neuroscience.

[17]  G. Palm,et al.  Cell assemblies in the cerebral cortex , 2014, Biological Cybernetics.

[18]  Vítor Lopes-dos-Santos,et al.  Detecting cell assemblies in large neuronal populations , 2013, Journal of Neuroscience Methods.

[19]  K. Harris Cell Assemblies of the Superficial Cortex , 2012, Neuron.

[20]  György Buzsáki,et al.  Neural Syntax: Cell Assemblies, Synapsembles, and Readers , 2010, Neuron.

[21]  M. Häusser,et al.  Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons , 2010, Science.

[22]  Mehdi Khamassi,et al.  Coherent Theta Oscillations and Reorganization of Spike Timing in the Hippocampal- Prefrontal Network upon Learning , 2010, Neuron.

[23]  Daniela Popa,et al.  Coherent amygdalocortical theta promotes fear memory consolidation during paradoxical sleep , 2010, Proceedings of the National Academy of Sciences.

[24]  M. Khamassi,et al.  Replay of rule-learning related neural patterns in the prefrontal cortex during sleep , 2009, Nature Neuroscience.

[25]  A. Lüthi,et al.  Switching on and off fear by distinct neuronal circuits , 2008, Nature.

[26]  G. Buzsáki,et al.  Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex , 2008, Nature Neuroscience.

[27]  Lynn Hazan,et al.  Klusters, NeuroScope, NDManager: A free software suite for neurophysiological data processing and visualization , 2006, Journal of Neuroscience Methods.

[28]  D. Paré,et al.  Prefrontal Control of the Amygdala , 2005, The Journal of Neuroscience.

[29]  K. Harris Neural signatures of cell assembly organization , 2005, Nature Reviews Neuroscience.

[30]  Yuji Ikegaya,et al.  Synfire Chains and Cortical Songs: Temporal Modules of Cortical Activity , 2004, Science.

[31]  J. Csicsvari,et al.  Organization of cell assemblies in the hippocampus , 2003, Nature.

[32]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[33]  R. Zemel,et al.  Information processing with population codes , 2000, Nature Reviews Neuroscience.

[34]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[35]  Joseph E LeDoux,et al.  Functional inactivation of the lateral and basal nuclei of the amygdala by muscimol infusion prevents fear conditioning to an explicit conditioned stimulus and to contextual stimuli. , 1997, Behavioral neuroscience.

[36]  C. Koch,et al.  A brief history of time (constants). , 1996, Cerebral cortex.

[37]  Joseph E LeDoux,et al.  Differential contribution of dorsal and ventral medial prefrontal cortex to the acquisition and extinction of conditioned fear in rats. , 1995, Behavioral neuroscience.

[38]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[39]  H. Maturana,et al.  The Tree of Knowledge: The Biological Roots of Human Understanding , 2007 .

[40]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.

[41]  A. P. Georgopoulos,et al.  Neuronal population coding of movement direction. , 1986, Science.

[42]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[43]  V. Marčenko,et al.  DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES , 1967 .

[44]  W. Hager,et al.  and s , 2019, Shallow Water Hydraulics.

[45]  G. Quirk,et al.  Dissociable Roles of Prelimbic and Infralimbic Cortices, Ventral Hippocampus, and Basolateral Amygdala in the Expression and Extinction of Conditioned Fear , 2011, Neuropsychopharmacology.

[46]  James L. McClelland,et al.  Considerations arising from a complementary learning systems perspective on hippocampus and neocortex , 1996, Hippocampus.

[47]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[48]  A. Lansner,et al.  Modelling Hebbian cell assemblies comprised of cortical neurons , 1992 .

[49]  G. Paxinos,et al.  The Rat Brain in Stereotaxic Coordinates , 1983 .

[50]  Professor Moshe Abeles,et al.  Local Cortical Circuits , 1982, Studies of Brain Function.

[51]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[52]  H B Barlow,et al.  Single units and sensation: a neuron doctrine for perceptual psychology? , 1972, Perception.