Biology subjects

Clopath, C.

Publications and source records attributed to Clopath, C..

6 recordsLinked to original sources

bioRxiv2018

The Dance of the Interneurons: How Inhibition Facilitates Fast Compressible and Reversible Learning in Hippocampus

The hippocampus is capable of rapidly learning incoming information, even if that information is only observed once. Further, this information can be replayed in a compressed format in either forward or reversed modes during Sharp Wave Ripples (SPW-R). We leveraged state-of-the-art techniques in training recurrent spiking networks to demonstrate how primarily inhibitory networks of neurons in CA3 and CA1 can: 1) generate internal theta sequences or \"time-cells\" to bind externally elicited spikes in the presence of septal inhibition, 2) reversibly compress the learned representation in the form of a SPW-R when septal inhibition is removed, 3) generate and refine gamma-assemblies during SPW-R mediated compression, and 4) regulate the inter-ripple-interval timing between SPW-Rs in ripple clusters. From the fast time scale of neurons to the slow time scale of behaviors, inhibitory networks serve as the scaffolding for one-shot learning by replaying, reversing, refining, and regulating spike sequences.

neuroscience↗

bioRxiv2018

Diverse homeostatic responses to visual deprivation by uncovering recurrent subnetworks

Multiple homeostatic plasticity mechanisms are thought to be critical for the prevention of excessively high or aberrantly low neural activity in the adult cortex. In L2/3 of adult mouse visual cortex the interplay between disinhibition and local functional interactions may support homeostatic recovery following visual deprivation. Despite blanket disinhibition only a subset of L2/3 excitatory neurons are observed to exhibit homeostatic recovery. Recovering neurons tend to be correlated with each other, forming functional networks prior to deprivation. How homeostatic recovery occurs in this way is therefore unclear, particularly in conditions of global disinhibition.\n\nHere, we employ a computational modelling approach to investigate the origin of diverse homeostatic responses in the cortex. This model finds network size to be a critical determinant of the diverse homeostatic activity profiles observed following visual deprivation, as neurons which belong to larger networks exhibit a stronger homeostatic response. Our simulations provide mechanistic insights into the emergence of diverse homeostatic responses, and predict that neurons with a high proportion of enduring functional associations will exhibit the strongest homeostatic recovery. We test and confirm these predictions experimentally.

neuroscience↗

bioRxiv2018

Synaptic plasticity onto inhibitory neurons as a mechanism for ocular dominance plasticity.

Ocular dominance plasticity is a well-documented phenomenon allowing us to study properties of cortical maturation. Understanding this maturation might be an important step towards unravelling how cortical circuits function. However, it is still not fully understood which mechanisms are responsible for the opening and closing of the critical period for ocular dominance and how changes in cortical responsiveness arise after visual deprivation. In this article, we present a theory of ocular dominance plasticity. Following recent experimental work, we propose a framework where a reduction in inhibition is necessary for ocular dominance plasticity in both juvenile and adult animals. In this framework, two ingredients are crucial to observe ocular dominance shifts: a sufficient level of inhibition as well as excitatory-to-inhibitory synaptic plasticity. In our model, the former is responsible for the opening of the critical period, while the latter limits the plasticity in adult animals. Finally, we also provide a possible explanation for the variability in ocular dominance shifts observed in individual neurons and for the counter-intuitive shifts towards the closed eye.

neuroscience↗

bioRxiv2018

Population coupling predicts the plasticity of stimulus responses in cortical circuits

Long-term imaging of sensory cortex reveals a diverse range of stimulus response stability: some neurons retain stimulus responses that are stable over days whereas other neurons have highly plastic stimulus responses. Using a recurrent network model, we explore whether this observation could be due to an underlying diversity in the synaptic plasticity of neurons. We find that, in a network with diverse learning rates, neurons with fast rates are more coupled to population activity than neurons with slow rates. This phenomenon, which we call a plasticity-coupling link, surprisingly predicts that neurons with high population coupling exhibit more long-term stimulus response variability than neurons with low population coupling. We substantiate this prediction using recordings from the Allen Brain Observatory which track the orientation preferences of 15,000 neurons in mouse visual cortex. In agreement with our model, a neurons population coupling is correlated with the plasticity of its orientation preference. Finally, we show that high population coupling helps plastic neurons alter their stimulus preference during a simple perceptual learning task, but hinders the ability of stable neurons to provide an instructive signal for learning. This suggests a particular functional architecture: a stable backbone of stimulus representation formed by neurons with slow synaptic plasticity and low population coupling, on top of which lies a flexible substrate of neurons with fast synaptic plasticity and high population coupling.

neuroscience↗

bioRxiv2017

Acetylcholine reconfigures hippocampal circuits to enable rapid formation of overlapping memory ensembles

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. Since CA3 network capacity is finite, a mechanism for enhancing memory encoding during important events would ensure greater efficiency, but the salient signal that might determine this memory selectivity filter is unknown. Using experimental and computational methods we show that the cholinergic system can operate as a memory selectivity filter by combining 3 separate mechanisms: disinhibition of feed-forward mossy fiber inhibition enables synaptic plasticity at CA3-CA3 recurrent synapses; Increasing cellular excitability lowers the threshold for ensemble formation; Reduction of overall CA3-CA3 recurrent synapse strength allows for an increase in overlap between ensembles. Thus, we show that acetylcholine release enables the selective encoding of salient high-density episodic memories in the hippocampus.

neuroscience↗

bioRxiv2017

Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks

Pattern separation is a fundamental function of the brain. Divergent feedforward networks separate overlapping activity patterns by mapping them onto larger numbers of neurons, aiding learning in downstream circuits. However, the relationship between the synaptic connectivity within these circuits and their ability to separate patterns is poorly understood. To investigate this we built simplified and biologically detailed models of the cerebellar input layer and systematically varied the spatial correlation of their inputs and their synaptic connectivity. Performance was quantified by the learning speed of a classifier trained on either the mossy fiber input or granule cell output patterns. Our results establish that the extent of synaptic connectivity governs the pattern separation performance of feedforward networks by counteracting the beneficial effects of expanding coding space and threshold-mediated decorrelation. The sparse synaptic connectivity in the cerebellar input layer provides an optimal solution to this trade-off, enabling efficient pattern separation and faster learning.

neuroscience↗