Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison

Chronic Pancreatitis in the 21st Century - Research Challenges and Opportunities:Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop

A workshop was sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to focus on research gaps and opportunities in chronic pancreatitis (CP) and its sequelae. This conference marked the 20(th) year anniversary of the discovery of the cationic trypsinogen (PRSS1) gene mutation for hereditary pancreatitis. The event was held on July 27, 2016, and structured into 4 sessions: (1) pathophysiology; (2) exocrine complications; (3) endocrine complications; and (4) pain. The current state of knowledge was reviewed; many knowledge gaps and research needs were identified that require further investigation. Common themes included the need to design better tools to diagnose CP and its sequelae early and reliably, identify predisposing risk factors for disease progression, develop standardized protocols to distinguish type 3c diabetes mellitus from other types of diabetes and design effective therapeutic strategies through novel cell culture technologies, animal models mimicking human disease, and pain management tools. Gene therapy and cystic fibrosis conductance regulator (CFTR) potentiators as possible treatments for CP were discussed. Importantly, the need for chronic pancreatitis endpoints and intermediate targets for future drug trials was emphasized