High-Throughput Task to Study Memory Recall During Spatial Navigation in Rodents

© Copyright © 2020 Morales, Tomàs, Dalmau, de la Rocha and Jercog. Spatial navigation is one of the most frequently used behavioral paradigms to study memory formation in rodents. Commonly used tasks to study memory are labor-intensive, preventing the simultaneous testing of multiple animals with the tendency to yield a low number of trials, curtailing the statistical power. Moreover, they are not tailored to be combined with neurophysiology recordings because they are not based on overt stereotyped behavioral responses that can be precisely timed. Here we present a novel task to study long-term memory formation and recall during spatial navigation. The task consists of learning sessions during which mice need to find the rewarding port that changes from day to day. Hours after learning, there is a recall session during which mice search for the location of the memorized rewarding port. During the recall sessions, the animals repeatedly poke the remembered port over many trials (up to ∼20) without receiving a reward (i.e., no positive feedback) as a readout of memory. In this task, mice show memory of port locations learned on up to three previous days. This eight-port maze task requires minimal human intervention, allowing for simultaneous and unsupervised testing of several mice in parallel, yielding a high number of recall trials per session over many days, and compatible with recordings of neural activity

Asymmetric Excitatory Synaptic Dynamics Underlie Interaural Time Difference Processing in the Auditory System

In order to localize sounds in the environment, the auditory system detects and encodes differences in signals between each ear. The exquisite sensitivity of auditory brain stem neurons to the differences in rise time of the excitation signals from the two ears allows for neuronal encoding of microsecond interaural time differences

Control of submillisecond synaptic timing in binaural coincidence detectors by Kv1 channels

0 1 a r t I C l e S The temporal relationship between excitatory synaptic input and action potential output is critical for sensory encoding as well as for the induction of some forms of synaptic plasticity 1,2 . However, in the majority of neurons in which excitatory inputs sum in the dendritic arbor, the relative timing of synaptic input is subject to distortions in both time and amplitude as a result of dendritic cable filtering At the cellular level, discrimination of ITDs in mammals involves the spatial and temporal summation of time-locked glutamatergic excitation and glycinergic inhibition in MSO principal neurons. Excitatory synaptic inputs from spherical bushy cells of the cochlear nucleus are segregated onto different branches of bipolar dendritic arbors 8 . The axon, where action potential initiation occurs, emerges from the soma or proximal dendrite To understand how MSO dendrites influence synaptic coincidence detection, we combined simultaneous dendritic and somatic current-clamp recordings, both whole-cell and excised patch voltageclamp recordings, and computational modeling to explore how the properties of MSO dendrites influence binaural coincidence detection and temporal coding. We found that dendritic EPSPs activated a somatically biased population of low voltage-activated K + channels (K LVA ), which accelerated membrane repolarization. The presence of K LVA approximately doubled the temporal resolution of binaural coincidence detection as compared with a passive leak conductance of the same density and imposed a uniform somatic time course of EPSPs propagating from disparate dendritic locations. Thus, both the biophysical properties and spatial distribution of K LVA are critical determinants of the high resolution of binaural coincidence detection in the MSO. RESULTS MSO principal cells were identified in brainstem slices by the bipolar morphology of their dendrites when viewed under infrared differential interference contrast optics 9 , and by the characteristic onset (single spike) firing pattern and unusually low input resistance these cells exhibit electrophysiologically (average of 12.0 ± 0.69 MΩ for postnatal day 16-19 (P16-19) gerbils, n = 20). To examine how EPSPs are shaped as they propagate from known locations in the dendrites to the soma, we made simultaneous somatic and dendritic currentclamp recordings, injected simulated excitatory postsynaptic currents (sEPSCs, see Online Methods) into the dendrites and varied current amplitude to elicit depolarizations encompassing the entire subthreshold voltage rang

Dynamical prefrontal population coding during defensive behaviours

Coping with threatening situations requires both identifying stimuli that predict danger and selecting adaptive behavioural responses to survive1. The dorsomedial prefrontal cortex (dmPFC) is a critical structure that is involved in the regulation of threat-related behaviour2,3,4. However, it is unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks to successfully drive adaptive responses. Here we used a combination of extracellular recordings, neuronal decoding approaches, pharmacological and optogenetic manipulations to show that, in mice, threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. Our data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations driven by the amygdala, it does not predict action outcome. By contrast, transient dmPFC population activity before the initiation of action reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of defensive responses relies on a dynamic process of information linking threats with defensive actions, unfolding within prefrontal networks.Rôle de la signalisation dopaminergique dans l'amygdale étendue dans le contrôle de la peur généralisée.Role des projections inhibitrices provenant du cortex préfrontal dans l'expression de la peur conditionnéeInnovations instrumentales et procédurales en psychopathologie expérimentale chez le rongeu

Noise correlations in neural ensemble activity limit the accuracy of hippocampal spatial representations

Neurons in the CA1 area of the mouse hippocampus encode the position of the animal in an environment. However, given the variability in individual neurons responses, the accuracy of this code is still poorly understood. It was proposed that downstream areas could achieve high spatial accuracy by integrating the activity of thousands of neurons, but theoretical studies point to shared fluctuations in the firing rate as a potential limitation. Using high-throughput calcium imaging in freely moving mice, we demonstrated the limiting factors in the accuracy of the CA1 spatial code. We found that noise correlations in the hippocampus bound the estimation error of spatial coding to ~10 cm (the size of a mouse). Maximal accuracy was obtained using approximately [300-1400] neurons, depending on the animal. These findings reveal intrinsic limits in the brain's representations of space and suggest that single neurons downstream of the hippocampus can extract maximal spatial information from several hundred inputs

Neural dynamics underlying a long-term associative memory

The brain’s ability to associate different stimuli is vital for long-term memory, but how neural ensembles encode associative memories is unknown. Here we studied how cell ensembles in the basal and lateral amygdala encode associations between conditioned and unconditioned stimuli (CS and US, respectively). Using a miniature fluorescence microscope, we tracked the Ca2+ dynamics of ensembles of amygdalar neurons during fear learning and extinction over 6 days in behaving mice. Fear conditioning induced both up- and down-regulation of individual cells’ CS-evoked responses. This bi-directional plasticity mainly occurred after conditioning, and reshaped the neural ensemble representation of the CS to become more similar to the US representation. During extinction training with repetitive CS presentations, the CS representation became more distinctive without reverting to its original form. Throughout the experiments, the strength of the ensemble-encoded CS–US association predicted the level of behavioural conditioning in each mouse. These findings support a supervised learning model in which activation of the US representation guides the transformation of the CS representation