Partial Breakdown of Input Specificity of STDP at Individual Synapses Promotes New Learning

Abstract

Hebbian-type learning rules, which underlie learning and refinement of neuronal connectivity, postulate input specificity of synaptic changes. However, theoretical analyses have long appreciated that additional mechanisms, not restricted to activated synapses, are needed to counteract positive feedback imposed by Hebbian-type rules on synaptic weight changes and to achieve stable operation of learning systems. The biological basis of such mechanisms has remained elusive. Here we show that, in layer 2/3 pyramidal neurons from slices of visual cortex of rats, synaptic changes induced at individual synapses by spike timing-dependent plasticity do not strictly follow the input specificity rule. Spike timing-dependent plasticity is accompanied by changes in unpaired synapses: heterosynaptic plasticity. The direction of heterosynaptic changes is weight-dependent, with balanced potentiation and depression, so that the total synaptic input to a cell remains preserved despite potentiation or depression of individual synapses. Importantly, this form of heterosynaptic plasticity is induced at unpaired synapses by the same pattern of postsynaptic activity that induces homosynaptic changes at paired synapses. In computer simulations, we show that experimentally observed heterosynaptic plasticity can indeed serve the theoretically predicted role of robustly preventing runaway dynamics of synaptic weights and activity. Moreover, it endows model neurons and networks with essential computational features: enhancement of synaptic competition, facilitation of the development of specific intrinsic connectivity, and the ability for relearning. We conclude that heterosynaptic plasticity is an inherent property of plastic synapses, crucial for normal operation of learning systems.

Modelling the Replay of Dynamic Memories from Cortical Alpha Oscillations with the Sync-Fire / deSync Model

“…Diminished internal weights also ensures that active neurons are less able to affect one another over time and activation within the group recedes. As this process occurs simultaneously with the long-term potentiation of other synapses within these active neurons, this mechanism effectively models a form of heterosynaptic LTD, as observed experimentally and in other models (Volgushev, et al, 2016). This process entails a balancing act where pre-existing synaptic pathways are diminished when new connections are strengthened through STDP.…”

“…Conversely, LTD occurs within active binding pool assemblies, diminishing the likelihood that they would be able to compete for the indexing of subsequent stimuli. To simplify our model, we here adapt our STDP rule by shifting the parameter subspace such that only LTD can occur between active binding units, though in reality we imagine this process to be caused by hetero-synaptic LTD in response to the LTP occurring on other dendrites (Volgushev, et al, 2016) to be bound relative to a temporal rhythm (B; cyan top-down arrows), ensuring that they can be recalled (B; green bottom-up arrows) with the correct absolute timing between events. We assume the presence of a neuro-modulator that switches information processing between the encoding direction (cyan top-down arrows) and the retrieval direction (green bottom-up arrows), which is important to prevent cross-communication from contaminating encoding and recall processes.…”

“…During the binding process, a group of unique binding pool units are associated to any active cortical unit via a calcium dependent learning rule (Graupner & Brunel, 2012). As their local weights decrease during this process, which effectively models a form of hetero-synaptic long-term-depression (Volgushev, et al, 2016), active binding groups diminish the likelihood that they will be able to compete during successive events. Thus, active bindings are unique to the bound event.…”

“…Conversely, LTD occurs within active binding pool assemblies, diminishing the likelihood that they would be able to compete for the indexing of subsequent stimuli. To simplify our model, we here adapt our STDP rule by shifting the parameter subspace such that only LTD can occur between active binding units, though in reality we imagine this process to be caused by hetero-synaptic LTD in response to the LTP occurring on other dendrites (Volgushev, et al, 2016). Content specificity over several patterns comprising 3 distinct events.…”

The temporal paradox of Hebbian learning and homeostatic plasticity

“…Its viability as putative RCP arises from the fact that some forms of heterosynaptic plasticity can be induced rapidly, and moreover, similar to synaptic scaling, can show aspects of weight normalization [106]. For instance, a rapid form of heterosynaptic plasticity, in which neuronal bursting causes bi-directional weight-dependent changes in afferent synapses, has been observed recently [107,109]. While the observed weight-dependence is reminiscent of Oja's rule [8], as strong synapses weaken, it is not identical because weak synapses can also strengthen.…”