Alessandro Treves

This study establishes a rodent model of supraspan memory and shows that dorsal hippocampus supports high-load memory while ventral hippocampus supports egocentric strategies.

The paper investigates whether variable hippocampal place fields in bats can be stored as spatial memory through Hebbian plasticity and retrieved from partial cues, finding a variability range for successful memory storage.

The paper uses a simplified Potts model to show how prefrontal cortex can direct the composition of brain states into coherent thought sequences based on microcircuit parameters.

The paper analyzes a Potts glass model of cortical dynamics, showing that a frontal network with more attractor states becomes faster than a posterior network when interacting.

The paper models associative memory storage and retrieval in a cortical network, showing lower storage capacity for compositional memories and the role of hippocampal input in retrieval.

The paper identifies neurons coding for angular and linear velocity in parahippocampal circuits and shows they conjunctively encode position and direction, challenging current continuous attractor network models.

The paper models short-term memory using latching dynamics, showing interference limits capacity and sublinear scaling in memory tasks.

This paper introduces a continuous attractor network model that dynamically retrieves memories by breaking equilibrium through memory-dependent synaptic asymmetry, showing robust retrieval and potential enhanced memory capacity.

The paper shows that sex-dependent activation of the thalamo-hippocampal pathway affects incidental memory load in mice.

The paper tests if poetic meter aids memory by manipulating meter components in Italian poetry and finding mixed effects on memory and reaction times.

This paper demonstrates that Hebbian learning in threshold-linear associative networks can achieve higher storage capacity than binary networks and surpass theoretical bounds through pattern sparsification.

This paper shows that grid cell ensembles can represent multiple spatial maps, challenging the idea that they encode only a single universal grid map.

The paper predicts how grid cell activity patterns change on spherical environments compared to flat ones, finding partial coherence and clustering similar to disordered materials.

The paper explores how semantic memory is represented in the cortex and contrasts it with the simpler structure of the hippocampus for episodic memory.

The paper shows that rodents raised in hyperbolic environments could develop hyperbolic grid cell patterns, suggesting a flexible neuronal metric beyond Euclidean space.