scholarly journals Linking hippocampal multiplexed tuning, Hebbian plasticity and navigation

Nature ◽  
2021 ◽  
Author(s):  
Jason J. Moore ◽  
Jesse D. Cushman ◽  
Lavanya Acharya ◽  
Briana Popeney ◽  
Mayank R. Mehta
Keyword(s):  
2001 ◽  
Vol 13 (10) ◽  
pp. 2221-2237 ◽  
Author(s):  
Rajesh P. N. Rao ◽  
Terrence J. Sejnowski

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are potentiated, while those that are activated a few milliseconds after are depressed. We show that such a mechanism can implement a form of temporal difference learning for prediction of input sequences. Using a biophysical model of a cortical neuron, we show that a temporal difference rule used in conjunction with dendritic backpropagating action potentials reproduces the temporally asymmetric window of Hebbian plasticity observed physiologically. Furthermore, the size and shape of the window vary with the distance of the synapse from the soma. Using a simple example, we show how a spike-timing-based temporal difference learning rule can allow a network of neocortical neurons to predict an input a few milliseconds before the input's expected arrival.


Author(s):  
Christian Tetzlaff ◽  
Christoph Kolodziejski ◽  
Marc Timme ◽  
Florentin Wörgötter

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Zuzanna Brzosko ◽  
Sara Zannone ◽  
Wolfram Schultz ◽  
Claudia Clopath ◽  
Ole Paulsen

Spike timing-dependent plasticity (STDP) is under neuromodulatory control, which is correlated with distinct behavioral states. Previously, we reported that dopamine, a reward signal, broadens the time window for synaptic potentiation and modulates the outcome of hippocampal STDP even when applied after the plasticity induction protocol (Brzosko et al., 2015). Here, we demonstrate that sequential neuromodulation of STDP by acetylcholine and dopamine offers an efficacious model of reward-based navigation. Specifically, our experimental data in mouse hippocampal slices show that acetylcholine biases STDP toward synaptic depression, whilst subsequent application of dopamine converts this depression into potentiation. Incorporating this bidirectional neuromodulation-enabled correlational synaptic learning rule into a computational model yields effective navigation toward changing reward locations, as in natural foraging behavior. Thus, temporally sequenced neuromodulation of STDP enables associations to be made between actions and outcomes and also provides a possible mechanism for aligning the time scales of cellular and behavioral learning.


2022 ◽  
Author(s):  
Alberto Lazari ◽  
Piergiorgio Salvan ◽  
Michiel Cottaar ◽  
Daniel Papp ◽  
Matthew FS Rushworth ◽  
...  

Synaptic plasticity is required for learning and follows Hebb's Rule, the computational principle underpinning associative learning. In recent years, a complementary type of brain plasticity has been identified in myelinated axons, which make up the majority of brain's white matter. Like synaptic plasticity, myelin plasticity is required for learning, but it is unclear whether it is Hebbian or whether it follows different rules. Here, we provide evidence that white matter plasticity operates following Hebb's Rule in humans. Across two experiments, we find that co-stimulating cortical areas to induce Hebbian plasticity leads to relative increases in cortical excitability and associated increases in a myelin marker within the stimulated fiber bundle. We conclude that Hebbian plasticity extends beyond synaptic changes, and can be observed in human white matter fibers.


2021 ◽  
Vol 17 (12) ◽  
pp. e1009681
Author(s):  
Michiel W. H. Remme ◽  
Urs Bergmann ◽  
Denis Alevi ◽  
Susanne Schreiber ◽  
Henning Sprekeler ◽  
...  

Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways—two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting—as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.


2017 ◽  
Vol 46 ◽  
pp. 170-177 ◽  
Author(s):  
Łukasz Kuśmierz ◽  
Takuya Isomura ◽  
Taro Toyoizumi
Keyword(s):  

Cell Reports ◽  
2013 ◽  
Vol 3 (5) ◽  
pp. 1407-1413 ◽  
Author(s):  
Dmitrij Ljaschenko ◽  
Nadine Ehmann ◽  
Robert J. Kittel

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