In order to enable an iCal export link, your account needs to have an API key created. This key enables other applications to access data from within Indico even when you are neither using nor logged into the Indico system yourself with the link provided. Once created, you can manage your key at any time by going to 'My Profile' and looking under the tab entitled 'HTTP API'. Further information about HTTP API keys can be found in the Indico documentation.
Additionally to having an API key associated with your account, exporting private event information requires the usage of a persistent signature. This enables API URLs which do not expire after a few minutes so while the setting is active, anyone in possession of the link provided can access the information. Due to this, it is extremely important that you keep these links private and for your use only. If you think someone else may have acquired access to a link using this key in the future, you must immediately create a new key pair on the 'My Profile' page under the 'HTTP API' and update the iCalendar links afterwards.
Permanent link for public information only:
Permanent link for all public and protected information:
Spike-Based Bayesian Learning in Neocortical Microcircuits
(CB/CSC/KTH and Institute for Adaptive and Neural Computation, University of Edinburgh)
Large-scale, recurrently connected cortical circuits exhibit complex dynamical interactions, and play host to many plastic mechanisms that can sculpt and be sculpted by ongoing activity. But how can we begin to understand these intricate synergies in a principled way? We propose that the connectivity of a biophysical attractor memory network could be learned using the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. Although the approach encompasses a diversity of mechanisms including Hebbian, homeostatic synaptic, intrinsic, and neuromodulated plasticity, it is straightforwardly understood since it is neatly encapsulated within the framework of probabilistic inference .
In this talk I will focus on spike-based BCPNN learning using different time scales. I'll show how fast AMPA connections provide the recurrent excitation necessary for assembling neurons into stable groups, i.e. attractors, while slowly decaying NMDA receptor (NMDAR) conductances provide prolonged activations that act as bridges for connecting different attractors. Thus, NMDAR allows for the passage of representational content from one ensemble to the next in sequence, and propels the network along a trajectory through attractor state space. The resulting spatiotemporal activity patterns consist of intermittent population bursts with abrupt sequential transitions occurring on the order of hundreds of milliseconds, resembling dynamics widely observed across motor , sensory , memory  and decision-making  tasks. Overall, our work implies that the presence of a spike, or lack thereof, not only enacts measurable changes in the biochemical makeup of synapses and cells, but moreover contributes to an underlying, ongoing probabilistic inference process. We provide a biophysical realization of Bayes' Rule by reconciling several observed neural phenomena whose functional effects are only partially understood in concert.
1. Synaptic and nonsynaptic plasticity approximating probabilistic inference. Tully, Hennig & Lansner, Frontiers in Synaptic Neuroscience 6:8, 2014.
2. Parallel processing of serial movements in prefrontal cortex. Averbeck et. al., Proc. Natl. Acad. Sci. USA 99:20, 13172-13177, 2002.
3. Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles. Jones et. al., Proc. Natl. Acad. Sci. USA 104:47, 18772-18777, 2007.
4. Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex. Fujisawa et. al., Nature Neuroscience 11:7, 2008.
5. Successful choice behavior in associated with distinct and coherent network states in anterior cingulate cortex. Lapish et. al., Proc. Natl. Acad. Sci. USA, 105:33, 2008.