Drifting assemblies for persistent memory: Neuron transitions and unsupervised compensation

2021 ◽  
Vol 118 (46) ◽  
pp. e2023832118
Author(s):  
Yaroslav Felipe Kalle Kossio ◽  
Sven Goedeke ◽  
Christian Klos ◽  
Raoul-Martin Memmesheimer
Keyword(s):  
Temporal Evolution ◽  
Memory Systems ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Associative Memories ◽  
Neural Representations ◽  
Persistent Memory ◽  
Memory Representations ◽  
Autonomous Network ◽  
Activity Dependent

Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless, behaviors and memories often persist over long times. In a standard model, associative memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. Here we propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of synapses and neural representations. The assemblies drift freely as noisy autonomous network activity and spontaneous synaptic turnover induce neuron exchange. The gradual exchange allows activity-dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs, and assemblies consistent. This leads to persistent memory. Our findings explain recent experimental results on temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.

scholarly journals Drifting Assemblies for Persistent Memory

2020 ◽  
Author(s):  
Yaroslav Felipe Kalle Kossio ◽  
Sven Goedeke ◽  
Christian Klos ◽  
Raoul-Martin Memmesheimer
Keyword(s):  
Temporal Evolution ◽  
Fear Memory ◽  
Memory Systems ◽  
Homeostatic Plasticity ◽  
Memory Model ◽  
Neural Representations ◽  
Random Activity ◽  
Persistent Memory ◽  
Memory Representations ◽  
Activity Dependent

Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless behaviors and memories often persist over long times. In a standard model, memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. Here we propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of connections and neural representations. The assemblies drift freely as spontaneous synaptic turnover or random activity induce neuron exchange. The gradual exchange allows activity dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs and assemblies consistent. This leads to persistent memory. Our findings explain recent experimental results on the temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.

scholarly journals GluA4 subunit of AMPA receptors mediates the early synaptic response to altered network activity in the developing hippocampus

2016 ◽  
Vol 115 (6) ◽  
pp. 2989-2996 ◽  
Author(s):  
J. Huupponen ◽  
T. Atanasova ◽  
T. Taira ◽  
S. E. Lauri
Keyword(s):  
Ampa Receptors ◽  
Pyramidal Neurons ◽  
Activity Patterns ◽  
Critical Role ◽  
Long Term Potentiation ◽  
Postnatal Period ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Hippocampal Pyramidal Neurons ◽  
Activity Dependent

Development of the neuronal circuitry involves both Hebbian and homeostatic plasticity mechanisms that orchestrate activity-dependent refinement of the synaptic connectivity. AMPA receptor subunit GluA4 is expressed in hippocampal pyramidal neurons during early postnatal period and is critical for neonatal long-term potentiation; however, its role in homeostatic plasticity is unknown. Here we show that GluA4-dependent plasticity mechanisms allow immature synapses to promptly respond to alterations in network activity. In the neonatal CA3, the threshold for homeostatic plasticity is low, and a 15-h activity blockage with tetrodotoxin triggers homeostatic upregulation of glutamatergic transmission. On the other hand, attenuation of the correlated high-frequency bursting in the CA3-CA1 circuitry leads to weakening of AMPA transmission in CA1, thus reflecting a critical role for Hebbian synapse induction in the developing CA3-CA1. Both of these developmentally restricted forms of plasticity were absent in GluA4 −/− mice. These data suggest that GluA4 enables efficient homeostatic upscaling and responsiveness to temporal activity patterns during the critical period of activity-dependent refinement of the circuitry.

scholarly journals Analytical investigation of self-organized criticality in neural networks

2013 ◽  
Vol 10 (78) ◽  
pp. 20120558 ◽  
Author(s):  
Felix Droste ◽  
Anne-Ly Do ◽  
Thilo Gross
Keyword(s):  
Neural Networks ◽  
Stochastic Dynamics ◽  
Analytical Investigation ◽  
Homeostatic Plasticity ◽  
Dynamical Phase Transition ◽  
Discrete State ◽  
Dynamical Phase ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Activity Dependent

Dynamical criticality has been shown to enhance information processing in dynamical systems, and there is evidence for self-organized criticality in neural networks. A plausible mechanism for such self-organization is activity-dependent synaptic plasticity. Here, we model neurons as discrete-state nodes on an adaptive network following stochastic dynamics. At a threshold connectivity, this system undergoes a dynamical phase transition at which persistent activity sets in. In a low-dimensional representation of the macroscopic dynamics, this corresponds to a transcritical bifurcation. We show analytically that adding activity-dependent rewiring rules, inspired by homeostatic plasticity, leads to the emergence of an attractive steady state at criticality and present numerical evidence for the system's evolution to such a state.

scholarly journals Predictive learning as a network mechanism for extracting low-dimensional latent space representations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Stefano Recanatesi ◽  
Matthew Farrell ◽  
Guillaume Lajoie ◽  
Sophie Deneve ◽  
Mattia Rigotti ◽  
...  
Keyword(s):  
Latent Variables ◽  
Latent Structure ◽  
Network Activity ◽  
Semantic Organization ◽  
Sequential Processing ◽  
Predictive Learning ◽  
Neural Representations ◽  
Latent Space ◽  
Low Dimensional ◽  
Sensory Prediction

AbstractArtificial neural networks have recently achieved many successes in solving sequential processing and planning tasks. Their success is often ascribed to the emergence of the task’s low-dimensional latent structure in the network activity – i.e., in the learned neural representations. Here, we investigate the hypothesis that a means for generating representations with easily accessed low-dimensional latent structure, possibly reflecting an underlying semantic organization, is through learning to predict observations about the world. Specifically, we ask whether and when network mechanisms for sensory prediction coincide with those for extracting the underlying latent variables. Using a recurrent neural network model trained to predict a sequence of observations we show that network dynamics exhibit low-dimensional but nonlinearly transformed representations of sensory inputs that map the latent structure of the sensory environment. We quantify these results using nonlinear measures of intrinsic dimensionality and linear decodability of latent variables, and provide mathematical arguments for why such useful predictive representations emerge. We focus throughout on how our results can aid the analysis and interpretation of experimental data.

scholarly journals Homeostatic plasticity rules control the wiring of axo-axonic synapses at the axon initial segment

2018 ◽  
Author(s):  
Alejandro Pan-Vazquez ◽  
Winnie Wefelmeyer ◽  
Victoria Gonzalez Sabater ◽  
Juan Burrone
Keyword(s):  
Initial Segment ◽  
Pyramidal Cells ◽  
Axon Initial Segment ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Gabaergic Interneuron ◽  
Chandelier Cells ◽  
Local Circuits ◽  
And Function

AbstractGABAergic interneurons are chiefly responsible for controlling the activity of local circuits in the cortex1,2. However, the rules that govern the wiring of interneurons are not well understood3. Chandelier cells (ChCs) are a type of GABAergic interneuron that control the output of hundreds of neighbouring pyramidal cells through axo-axonic synapses which target the axon initial segment (AIS)4. Despite their importance in modulating circuit activity, our knowledge of the development and function of axo-axonic synapses remains elusive. In this study, we investigated the role of activity in the formation and plasticity of ChC synapses. In vivo imaging of ChCs during development uncovered a narrow window (P12-P18) over which axons arborized and formed connections. We found that increases in the activity of either pyramidal cells or individual ChCs during this temporal window resulted in a reversible decrease in axo-axonic connections. Voltage imaging of GABAergic transmission at the AIS showed that axo-axonic synapses were depolarising during this period. Identical manipulations of network activity in older mice (P40-P46), when ChC synapses are inhibitory, resulted in an increase in axo-axonic synapses. We propose that the direction of ChC plasticity follows homeostatic rules that depend on the polarity of axo-axonic synapses.

Can neural models of cognition benefit from the advantages of connectionism?

2006 ◽  
Vol 29 (1) ◽  
pp. 86-87 ◽  
Author(s):  
Friedrich T. Sommer ◽  
Pentti Kanerva
Keyword(s):  
Language Processing ◽  
Associative Memories ◽  
Cognitive Computing ◽  
Neural Models ◽  
Combinatorial Structures ◽  
Mathematical Properties ◽  
Neural Representations ◽  
Target Article ◽  
Representational Power ◽  
Reduced Representations

Cognitive function certainly poses the biggest challenge for computational neuroscience. As we argue, past efforts to build neural models of cognition (the target article included) had too narrow a focus on implementing rule-based language processing. The problem with these models is that they sacrifice the advantages of connectionism rather than building on them. Recent and more promising approaches for modeling cognition build on the mathematical properties of distributed neural representations. These approaches truly exploit the key advantages of connectionism, that is, the high representational power of distributed neural codes and similarity-based pattern recognition. The architectures for cognitive computing that emerge from these approaches are neural associative memories endowed with additional mapping operations to handle invariances and to form reduced representations of combinatorial structures.

scholarly journals Rapid and sustained homeostatic control of presynaptic exocytosis at a central synapse

2019 ◽  
Vol 116 (47) ◽  
pp. 23783-23789 ◽  
Author(s):  
Igor Delvendahl ◽  
Katarzyna Kita ◽  
Martin Müller
Keyword(s):  
Time Scales ◽  
Neural Circuit ◽  
Mossy Fiber ◽  
Pool Size ◽  
Homeostatic Plasticity ◽  
Experimental Conditions ◽  
Central Synapse ◽  
Circuit Function ◽  
Vesicle Pool ◽  
Activity Dependent

Animal behavior is remarkably robust despite constant changes in neural activity. Homeostatic plasticity stabilizes central nervous system (CNS) function on time scales of hours to days. If and how CNS function is stabilized on more rapid time scales remains unknown. Here, we discovered that mossy fiber synapses in the mouse cerebellum homeostatically control synaptic efficacy within minutes after pharmacological glutamate receptor impairment. This rapid form of homeostatic plasticity is expressed presynaptically. We show that modulations of readily releasable vesicle pool size and release probability normalize synaptic strength in a hierarchical fashion upon acute pharmacological and prolonged genetic receptor perturbation. Presynaptic membrane capacitance measurements directly demonstrate regulation of vesicle pool size upon receptor impairment. Moreover, presynaptic voltage-clamp analysis revealed increased Ca2+-current density under specific experimental conditions. Thus, homeostatic modulation of presynaptic exocytosis through specific mechanisms stabilizes synaptic transmission in a CNS circuit on time scales ranging from minutes to months. Rapid presynaptic homeostatic plasticity may ensure stable neural circuit function in light of rapid activity-dependent plasticity.

Homeostatic Plasticity in the CNS

2019 ◽  
Author(s):  
Peter Wenner ◽  
Pernille Bülow
Keyword(s):  
Homeostatic Plasticity ◽  
Network Activity ◽  
Signaling Cascades ◽  
Neural Function ◽  
Activity Levels ◽  
Membrane Excitability ◽  
Activity Burst ◽  
Intrinsic Plasticity

Homeostatic plasticity refers to a collection of mechanisms that function to homeostatically maintain some feature of neural function. The field began with the view that homeostatic plasticity exists predominantly for the maintenance of spike rate. However, it has become clear that multiple features undergo some form of homeostatic control, including network activity, burst rate, or synaptic strength. There are several different forms of homeostatic plasticity, which are typically triggered following perturbations in activity levels. Homeostatic intrinsic plasticity (HIP) appears to compensate for the perturbation with changes in membrane excitability (voltage-gated conductances); synaptic scaling is thought to be a multiplicative increase or decrease of synaptic strengths throughout the cell following an activity perturbation; presynaptic homeostatic plasticity is a change in probability of release following a perturbation to postsynaptic receptor activity. Each form of homeostatic plasticity can be different in terms of the mechanisms that are engaged, the feature that is homeostatically regulated, the trigger that initiates the compensation, and the signaling cascades that mediate these processes. Homeostatic plasticity is often described in development, but can extend into maturity and has been described in vitro and in vivo.

scholarly journals Ketamine and Serotonergic Psychedelics: Common Mechanisms Underlying the Effects of Rapid-Acting Antidepressants

2020 ◽  
Author(s):  
Bashkim Kadriu ◽  
Maximillian Greenwald ◽  
Ioline D Henter ◽  
Jessica R Gilbert ◽  
Christoph Kraus ◽  
...  
Keyword(s):  
Therapeutic Response ◽  
Network Activity ◽  
Dependent Manner ◽  
Network Efficiency ◽  
Rigorous Research ◽  
Antidepressant Effects ◽  
Psychoactive Effects ◽  
Antidepressant Efficacy ◽  
Molecular Effects ◽  
Activity Dependent

Abstract Background The glutamatergic modulator ketamine has created a blueprint for studying novel pharmaceuticals in the field. Recent studies suggest that “classic” serotonergic psychedelics (SPs) may also have antidepressant efficacy. Both ketamine and SPs appear to produce rapid, sustained antidepressant effects after a transient psychoactive period. Methods This review summarizes areas of overlap between SP and ketamine research and considers the possibility of a common, downstream mechanism of action. The therapeutic relevance of the psychoactive state, overlapping cellular and molecular effects, and overlapping electrophysiological and neuroimaging observations are all reviewed. Results Taken together, the evidence suggests a potentially shared mechanism wherein both ketamine and SPs may engender rapid neuroplastic effects in a glutamatergic activity-dependent manner. It is postulated that, though distinct, both ketamine and SPs appear to produce acute alterations in cortical network activity that may initially produce psychoactive effects and later produce milder, sustained changes in network efficiency associated with therapeutic response. However, despite some commonalities between the psychoactive component of these pharmacologically distinct therapies—such as engagement of the downstream glutamatergic pathway—the connection between psychoactive impact and antidepressant efficacy remains unclear and requires more rigorous research. Conclusions Rapid-acting antidepressants currently under investigation may share some downstream pharmacological effects, suggesting that their antidepressant effects may come about via related mechanisms. Given the prototypic nature of ketamine research and recent progress in this area, this platform could be used to investigate entirely new classes of antidepressants with rapid and robust actions.

Sign in / Sign up

Export Citation Format

Share Document