Hippocampal hyperactivity in a rat model of Alzheimer's disease.

Neuronal network dysfunction is a hallmark of Alzheimer's disease (AD). However, the underlying pathomechanisms remain unknown. We analyzed the hippocampal micronetwork in transgenic McGill-R-Thy1-APP rats (APPtg) at the beginning of extracellular amyloid beta (Aß) deposition. We established two-photon Ca2+ -imaging in vivo in the hippocampus of rats and found hyperactivity of CA1 neurons. Patch-clamp recordings in brain slices in vitro revealed increased neuronal input resistance and prolonged action potential width in CA1 pyramidal neurons. We did neither observe changes in synaptic inhibition, nor in excitation. Our data support the view that increased intrinsic excitability of CA1 neurons may precede inhibitory dysfunction at an early stage of Aß-deposition and disease progression.

A septal-ventral tegmental area circuit drives exploratory behavior.

To survive, animals need to balance their exploratory drive with their need for safety. Subcortical circuits play an important role in initiating and modulating movement based on external demands and the internal state of the animal; however, how motivation and onset of locomotion are regulated remain largely unresolved. Here, we show that a glutamatergic pathway from the medial septum and diagonal band of Broca (MSDB) to the ventral tegmental area (VTA) controls exploratory locomotor behavior in mice. Using a self-supervised machine learning approach, we found an overrepresentation of exploratory actions, such as sniffing, whisking, and rearing, when this projection is optogenetically activated. Mechanistically, this role relies on glutamatergic MSDB projections that monosynaptically target a subset of both glutamatergic and dopaminergic VTA neurons. Taken together, we identified a glutamatergic basal forebrain to midbrain circuit that initiates locomotor activity and contributes to the expression of exploration-associated behavior.

Identifying behavioral structure from deep variational embeddings of animal motion.

Quantification and detection of the hierarchical organization of behavior is a major challenge in neuroscience. Recent advances in markerless pose estimation enable the visualization of high-dimensional spatiotemporal behavioral dynamics of animal motion. However, robust and reliable technical approaches are needed to uncover underlying structure in these data and to segment behavior into discrete hierarchically organized motifs. Here, we present an unsupervised probabilistic deep learning framework that identifies behavioral structure from deep variational embeddings of animal motion (VAME). By using a mouse model of beta amyloidosis as a use case, we show that VAME not only identifies discrete behavioral motifs, but also captures a hierarchical representation of the motif's usage. The approach allows for the grouping of motifs into communities and the detection of differences in community-specific motif usage of individual mouse cohorts that were undetectable by human visual observation. Thus, we present a robust approach for the segmentation of animal motion that is applicable to a wide range of experimental setups, models and conditions without requiring supervised or a-priori human interference.

Glutamatergic synaptic integration of locomotion speed via septoentorhinal projections.

The medial septum and diagonal band of Broca (MSDB) send glutamatergic axons to medial entorhinal cortex (MEC). We found that this pathway provides speed-correlated input to several MEC cell-types in layer 2/3. The speed signal is integrated most effectively by pyramidal cells but also excites stellate cells and interneurons. Thus, the MSDB conveys speed information that can be used by MEC neurons for spatial representation of self-location.

Locomotion, Theta Oscillations, and the Speed-Correlated Firing of Hippocampal Neurons Are Controlled by a Medial Septal Glutamatergic Circuit.

Before the onset of locomotion, the hippocampus undergoes a transition into an activity-state specialized for the processing of spatially related input. This brain-state transition is associated with increased firing rates of CA1 pyramidal neurons and the occurrence of theta oscillations, which both correlate with locomotion velocity. However, the neural circuit by which locomotor activity is linked to hippocampal oscillations and neuronal firing rates is unresolved. Here we reveal a septo-hippocampal circuit mediated by glutamatergic (VGluT2(+)) neurons that is activated before locomotion onset and that controls the initiation and velocity of locomotion as well as the entrainment of theta oscillations. Moreover, via septo-hippocampal projections onto alveus/oriens interneurons, this circuit regulates feedforward inhibition of Schaffer collateral and perforant path input to CA1 pyramidal neurons in a locomotion-dependent manner. With higher locomotion speed, the increased activity of medial septal VGluT2 neurons is translated into increased axo-somatic depolarization and higher firing rates of CA1 pyramidal neurons. VIDEO ABSTRACT.