Identification of Mouse Claustral Neuron Types Based on Their Intrinsic Electrical Properties.
Martin GrafAditya NairKelly L L WongYanxia TangGeorge J AugustinePublished in: eNeuro (2020)
Although its dense connections with other brain areas suggests that the claustrum is involved in higher-order brain functions, little is known about the properties of claustrum neurons. Using whole-cell patch clamp recordings in acute brain slices of mice, we characterized the intrinsic electrical properties of more than 300 claustral neurons and used unsupervised clustering of these properties to define distinct cell types. Differences in intrinsic properties permitted separation of interneurons (INs) from projection neurons (PNs). Five subtypes of PNs could be further identified by differences in their adaptation of action potential (AP) frequency and amplitude, as well as their AP firing variability. Injection of retrogradely transported fluorescent beads revealed that PN subtypes differed in their projection targets: one projected solely to subcortical areas while three out of the remaining four targeted cortical areas. INs expressing parvalbumin (PV), somatostatin (SST), or vasoactive intestinal peptide (VIP) formed a heterogenous group. PV-INs were readily distinguishable from VIP-INs and SST-INs, while the latter two were clustered together. To distinguish IN subtypes, an artificial neural network was trained to distinguish the properties of PV-INs, SST-INs, and VIP-INs, as independently identified through their expression of marker proteins. A user-friendly, machine-learning tool that uses intrinsic electrical properties to distinguish these eight different types of claustral cells was developed to facilitate implementation of our classification scheme. Systematic classification of claustrum neurons lays the foundation for future determinations of claustrum circuit function, which will advance our understanding of the role of the claustrum in brain function.
Keyphrases
- machine learning
- resting state
- white matter
- single cell
- spinal cord
- primary care
- functional connectivity
- neural network
- deep learning
- cell therapy
- healthcare
- hepatitis b virus
- induced apoptosis
- magnetic resonance
- spinal cord injury
- cerebral ischemia
- computed tomography
- rna seq
- adipose tissue
- mesenchymal stem cells
- binding protein
- bone marrow
- skeletal muscle
- brain injury
- subarachnoid hemorrhage
- liver failure
- signaling pathway
- quality improvement
- climate change
- mass spectrometry
- blood brain barrier
- image quality
- drug induced
- wild type
- high fat diet induced