The results suggest that competition among dendrites, consistent with resource-limited plasticity mechanisms, can enhance single-cell memory beyond non-interacting schemes.
Abstract
Biological neurons can perform nonlinear computations within their dendrites and support branch-localized plasticity. This raises the possibility that single cells can store memories more efficiently and with less interference by confining synaptic modifications to specific dendrites. We study a parallel-dendrite model performing online familiarity detection and compare three dendrite-update rules during learning: (i) independent thresholding, (ii) an interacting rule that adapts the target local dendritic activation per item, and (iii) an interacting n-winners-take-all (WTA) rule that constrains the number of updated branches per item. The interacting rules substantially improve capacity by limiting variance in memory responses and decorrelating weights across branches — even when inputs are strongly correlated. These results suggest that competition among dendrites, consistent with resource-limited plasticity mechanisms, can enhance single-cell memory beyond non-interacting schemes.
Adaptive behavior requires updating responses when contingencies change while preserving prior associations and the capacity to learn a new. How this trade-off is resolved remains unknown. Here, we combined in vivo imaging of apical tuft spines in the secondary motor cortex (M2) with biologically constrained network mo...
I. Pandi, Spyridon Chavlis, Hatem Oraby et al.· bioRxiv· 0 citations
It is argued that the ability of single neurons to simultaneously encode multiple pieces of information gives synapses local access to more than just the classical Hebbian pre- and postsynaptic terms, and with much greater specificity and reaction speed than permitted by other globally modulated factors.
Ben von Hünerbein, Federico Benitez, Kevin Max et al.· 0 citations
The results suggest that tuft spikes may be particularly driven by inputs from neurons that are both embedded in sparse subnetworks and synchronized through coupling to larger-scale functional networks.
Jacob Gable, Zachary L. Newman, Sarah Young et al.· Journal of Neuroscience· 1 citation
Observations support a view of BTSP as a multi-factor plasticity rule that links synaptic, circuit, and systems-level processes, providing a biologically grounded framework for understanding how the brain rapidly incorporates new information.
L. Wilmerding, Fox Gourianova, Christine Grienberger· Current Research in Neurobio...· 0 citations
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