Quantitative unit classification of ventral tegmental area neurons in vivo

• Published in: Journal of neurophysiology Vol. 107; no. 10; pp. 2808 - 2820
• Main Authors: Li, Wei, Doyon, William M, Dani, John A
• Format: Journal Article
• Language: English
• Published: United States American Physiological Society 15.05.2012
• Subjects: Action Potentials - drug effects; Action Potentials - physiology; Animals; Dopamine - metabolism; Dopamine Agonists - pharmacology; Dopamine Antagonists - pharmacology; gamma-Aminobutyric Acid - metabolism; Glutamic Acid - metabolism; Male; Neurons - cytology; Neurons - drug effects; Neurons - physiology; Quinpirole - pharmacology; Rats; Rats, Long-Evans; Salicylamides - pharmacology; Ventral Tegmental Area - cytology; Ventral Tegmental Area - drug effects; Ventral Tegmental Area - physiology
• ISSN: 0022-3077; 1522-1598
• DOI: 10.1152/jn.00575.2011

Neurons in the ventral tegmental area (VTA) synthesize several major neurotransmitters, including dopamine (DA), GABA, and glutamate. To classify VTA single-unit neural activity from freely moving rats, we used hierarchical agglomerative clustering and probability distributions as quantitative methods. After many parameters were examined, a firing rate of 10 Hz emerged as a transition frequency between clusters of low-firing and high-firing neurons. To form a subgroup identified as high-firing neurons with GABAergic characteristics, the high-firing classification was sorted by spike duration. To form a subgroup identified as putative DA neurons, the low-firing classification was sorted by DA D2-type receptor pharmacological responses to quinpirole and eticlopride. Putative DA neurons were inhibited by the D2-type receptor agonist quinpirole and returned to near-baseline firing rates or higher following the D2-type receptor antagonist eticlopride. Other unit types showed different responses to these D2-type receptor drugs. A multidimensional comparison of neural properties indicated that these subgroups often clustered independently of each other with minimal overlap. Firing pattern variability reliably distinguished putative DA neurons from other unit types. A combination of phasic burst properties and a low skew in the interspike interval distribution produced a neural population that was comparable to the one sorted by D2 pharmacology. These findings provide a quantitative statistical approach for the classification of VTA neurons in unanesthetized animals.