Hyperpolarization-activated cation (HCN) channels are believed to be involved in the generation of cardiac pacemaker depolarizations as well as in the control of neuronal excitability and plasticity. The contributions of the four individual HCN channel isoforms (HCN1±4) to these diverse functions are not known. Here we show that HCN2-de®cient mice exhibit spontaneous absence seizures. The thalamocortical relay neurons of these mice displayed a near complete loss of the HCN current, resulting in a pronounced hyperpolarizing shift of the resting membrane potential, an altered response to depolarizing inputs and an increased susceptibility for oscillations. HCN2-null mice also displayed cardiac sinus dysrhythmia, a reduction of the sinoatrial HCN current and a shift of the maximum diastolic potential to hyperpolarized values. Mice with cardiomyocytespeci®c deletion of HCN2 displayed the same dysrhythmia as mice lacking HCN2 globally, indicating that the dysrhythmia is indeed caused by sinoatrial dysfunction. Our results de®ne the physiological role of the HCN2 subunit as a major determinant of membrane resting potential that is required for regular cardiac and neuronal rhythmicity.

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Summary A deficient extinction of memory is particularly important in the regime of fear, where it limits the beneficial outcomes of treatments of anxiety disorders. Fear extinction is thought to involve inhibitory influences of the prefrontal cortex on the amygdala, although the detailed synaptic mechanisms remain unknown. Here we report that neuropeptide S (NPS), a recently discovered transmitter of ascending brainstem neurons, evokes anxiolytic effects and facilitates extinction of conditioned fear responses when administered into the amygdala in mice. An NPS receptor antagonist exerts functionally opposing responses, indicating that endogenous NPS is involved in anxiety behavior and extinction. Cellularly, NPS increases glutamatergic transmission to intercalated GABAergic neurons in the amygdala via presynaptic NPS receptors on connected principal neurons. These results identify mechanisms of NPS in the brain, a key role of intercalated neurons in the amygdala for fear extinction, and a potential pharmacological avenue for treating anxiety disorders.

In this paper, we describe a dynamic causal model (DCM) of steady-state responses in electrophysiological data that are summarised in terms of their cross-spectral density. These spectral data-features are generated by a biologically plausible, neural-mass model of coupled electromagnetic sources; where each source comprises three sub-populations. Under linearity and stationarity assumptions, the model's biophysical parameters (e.g., post-synaptic receptor density and time constants) prescribe the cross-spectral density of responses measured directly (e.g., local field potentials) or indirectly through some lead-field (e.g., electroencephalographic and magnetoencephalographic data). Inversion of the ensuing DCM provides conditional probabilities on the synaptic parameters of intrinsic and extrinsic connections in the underlying neuronal network. This means we can make inferences about synaptic physiology, as well as changes induced by pharmacological or behavioural manipulations, using the cross-spectral density of invasive or non-invasive electrophysiological recordings. In this paper, we focus on the form of the model, its inversion and validation using synthetic and real data. We conclude with an illustrative application to multi-channel local field potential data acquired during a learning experiment in mice.