Oren Amsalem

EASI-PASS: An accessible pipeline for linking functional imaging and mRNA profiling

Matching cell masks between two-photon calcium images and thick, expanded EASI-FISH volumes recovers molecular identity for 72% (slice) to 83% (in vivo) of imaged neurons on conventional microscopes.

Simultaneous, real-time tracking of many neuromodulatory signals with Multiplexed Optical Recording of Sensors on a micro-Endoscope

This paper develops a micro-endoscope probe to simultaneously track multiple neuromodulators in real time using fluorescent sensors, demonstrating its use in brain slices and awake mice.

Brainstem sensing of multiple body signals during food consumption

The paper maps neural activity in the mouse brainstem during food consumption, showing how different body signals are integrated across spatially clustered neurons.

Sub-threshold neuronal activity and the dynamical regime of cerebral cortex

The paper evaluates whether the cerebral cortex operates in a fluctuation-driven regime by analyzing spiking and sub-threshold membrane potentials in different cortical areas.

A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution

This study creates a spatially-resolved transcriptional atlas of the murine dorsal pons using snRNA-seq and MERFISH, identifying 120 neuronal subtypes and their spatial distribution.

Cortical reactivations predict future sensory responses

The paper shows that cortical reactivations predict future sensory responses and representational drift in mice.

Chronic stress triggers seeking of a starvation-like state in anxiety-prone female mice

This study shows chronic stress can lead anxious female mice to prefer a starvation-like state induced by AgRP neuron activation.

Thalamic control of sensory enhancement and sleep spindle properties in a biophysical model of thalamoreticular microcircuitry

The paper develops a computational model of mouse thalamoreticular microcircuitry to study sensory enhancement and sleep spindle properties, revealing mechanisms of network-level activity across brain states.

A calcium-based plasticity model predicts long-term potentiation and depression in the neocortex

The paper proposes a calcium-based plasticity model that predicts LTP and LTD dynamics across multiple pyramidal connections in the neocortex.

Visual association cortex links cues with conjunctions of reward and locomotor contexts

The paper tracks POR neuron responses in mice during learning to show how neurons encode cues in specific reward and locomotion contexts.

Realistic retinal modeling unravels the differential role of excitation and inhibition to starburst amacrine cells in direction selectivity

The paper develops a retinal model to show that excitatory input kinetics and SAC-SAC inhibition are critical for SAC centrifugal preference and direction selectivity.

The role of hub neurons in modulating cortical dynamics

The paper identifies hub neurons in a rodent neocortical microcircuit and shows that their removal disrupts network topology and dynamics more than random neuron removal.

Morphometric reconstructions atlas shows insult-driven plasticity in cortical VIP/ChAT interneurons

The paper develops a morphometric reconstruction pipeline to analyze cortical VIP/ChAT interneurons and finds insult-driven plasticity in their morphology and gene expression.

Dense Computer Replica of Cortical Microcircuits Unravels Cellular Underpinnings of Auditory Surprise Response

The paper uses a biologically-detailed in-silico model of a neocortical microcircuit to study stimulus-specific adaptation in the auditory cortex and identifies key mechanisms underlying the response to surprising sensory inputs.

Using subthreshold events to characterize the functional architecture of electrically coupled networks

This study characterizes subthreshold events in the inferior olive nucleus of mice to understand electrical coupling and network organization.

An efficient analytical reduction of detailed nonlinear neuron models

The paper introduces Neuron_Reduce, an analytical method that significantly speeds up nonlinear neuron simulations while preserving key dynamics and dendritic computations.