A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.This work was funded by K23NS104252 (A.A.L.) R01 MH117777 (E.B., J.W.R.) Whitehall Foundation (KH) 5F31NS120783-02 (Z.L.) 1U19NS104590 (A.L.) R01NS106611-02 (J.S., M.K.) MTEC-20-06-MOM013 (J.S., M.K.) 1U19NS107609-01 (I.S., J.L.) 1U19NS104590 (A.L., J.S.F., I.S.) 1U19NS107609 (E.A.B., J.W.R., J.J.L., I.S.) La Caixa LCF/PR/HR21/52410030 (A.N.O., L.dl.P) European Research Council Consolidator Grant 101001121 (B.P.S.) U.S.-Israel BSF grant 2017015 (RM)U01-NS113198 (J.J.) NSF CAREER IOS-1844935 (M.vdM.) 1R01NS121764-01 (B.L.M.) R01 MH122391 (G.B.) 30MH126483 (J.A.G.) Fondation pour la Recherche Médicale EQU202103012768 (M.Z.) 1R16-NS131108-01 (L.L.)

Spatial Representation and Navigation in a Bio-inspired Robot

A biologically inspired computational model of rodent repre-sentation?based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated place and head direction cells via Hebbian synapses. The space representation is built incrementally and on-line without any prior information about the environment and consists of a large population of location-sensitive units (place cells) with overlapping receptive fields. Goal navigation is performed using reinforcement learning in continuous state and action spaces, where the state space is represented by population activity of the place cells. The model is able to reproduce a number of behavioral and neuro-physiological data on rodents. Performance of the model was tested on both simulated and real mobile Khepera robots in a set of behavioral tasks and is comparable to the performance of animals in similar tasks

Local sensory cues and place cell directionality: Additional evidence of prospective coding in the hippocampus

Contains fulltext : 201424.pdf (publisher's version ) (Open Access

Path integration and the neural basis of the 'cognitive map'.

Item does not contain fulltex