Topic: spike-timing dependent plasticity

The predictive map hypothesis provides a promising framework to model representations in the hippocampal formation. I will introduce a tractable implementation of a predictive map called the successor representation (SR), before presenting data showing that rats and humans display SR-like navigational choices on a novel open-field maze. Next, I will show how such a predictive map could be implemented using spatial representations found in the hippocampal formation, before finally presenting how such learning might be well approximated by phenomena that exist in the spatial memory system - name

The successor representation (SR) is a promising candidate principle for hippocampal function. Theory proposes that each place cell encodes the expected state occupancy of its target location in the near future. This framework has desirable consequences on the generalisability and efficiency of reinforcement learning algorithms operating over these representations and is supported by behavioural and electrophysiological evidence. However, it is unclear how the SR might be learnt in the brain. Temporal difference learning, commonly used to learn SRs in artificial agents, is not known to be impl

All-optical techniques play a pivotal role in the direct interrogation of biological neural networks and the investigation of their computational properties. Such techniques combine spatiotemporally precise optogenetic stimulation at cellular resolution to manipulate neuronal states in the network with optical imaging of fluorescent genetically-encoded indicators for simultaneous readout of neuronal activity [1, 2]. The biophysical models of various optogenetic tools have been studied computationally in single neurons, accurately fitting experimental data [3, 4]. However, the effects of optoge

Inhibitory neurons (I), akin to their excitatory (E) counterparts, adjust synaptic efficacies in response to neural activity. Contrary to the traditional view of inhibition as a purely global activity modulator, recent studies highlighted the importance of specificity in (E/I) wiring and motif structures. These motifs, encompassing mutual and lateral inhibition, take essential functional roles in tuning of receptive fields, learning of representations, predictive coding, and in the regulation of the degrees of freedom of the network’s dynamics (i.e. the network dimensionality). Despite numero

Nonlinear rate-based models, such as stabilized supralinear networks (SSNs), have been crucial in explaining key aspects of cortical dynamics, including the nonlinear integration of visual inputs and the modulation of response variability. Yet, the absence of spike-based signals in these frameworks has hindered the study of millisecond-scale interactions between pairs of neurons, which have been shown to drive synaptic plasticity. For instance, spike-timing dependent plasticity (STDP), a phenomenological description of long-term synaptic plasticity, can shape neural circuits based on spike-bas