Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 106, Issue 9, Pages 3561-3566Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0813176106
Keywords
compartmental model; GABA; GABA(A) receptor; knockout; network synchrony
Categories
Funding
- VolkswagenStiftung [I/78 554, I/78 563-564]
- Deutsche Forschungsgemeinschaft [WI 1951/2]
- Medical Research Council [G0601498]
- Heidelberg Young Investigator Award
- Royal Society
- German Science Foundation [SFB 505, C6]
- Leibniz Award
- Schilling Foundation
- Burroughs Wellcome Fund
- National Institutes of Health [R01 NS46058]
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brazil
- Medical Research Council [G0601498] Funding Source: researchfish
- MRC [G0601498] Funding Source: UKRI
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Hippocampal theta (5-10 Hz) and gamma (35-85 Hz) oscillations depend on an inhibitory network of GABAergic interneurons. However, the lack of methods for direct and cell-type-specific interference with inhibition has prevented better insights that help link synaptic and cellular properties with network function. Here, we generated genetically modified mice (PV-Delta gamma(2)) in which synaptic inhibition was ablated in parvalbumin-positive (PV+) interneurons. Hippocampal local field potential and unit recordings in the CA1 area of freely behaving mice revealed that theta rhythm was strongly reduced in these mice. The characteristic coupling of theta and gamma oscillations was strongly altered in PV-Delta gamma(2) mice more than could be accounted for by the reduction in theta rhythm only. Surprisingly, gamma oscillations were not altered. These data indicate that synaptic inhibition onto PV+ interneurons is indispensable for theta- and its coupling to gamma oscillations but not for rhythmic gamma activity in the hippocampus. Similar alterations in rhythmic activity were obtained in a computational hippocampal network model mimicking the genetic modification, suggesting that intrahippocampal networks might contribute to these effects.
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