Abnormal cell-intrinsic and network excitability in the neocortex of serotonin-deficient Pet-1 knockout mice.

Neurons originating from the raphe nuclei of the brain stem are the exclusive source of serotonin (5-HT) to the cortex. Their serotonergic phenotype is specified by the transcriptional regulator Pet-1, which is also necessary for maintaining their neurotransmitter identity across development. Transgenic mice in which Pet-1 is genetically ablated (Pet-1(-/-)) show a dramatic reduction (∼80%) in forebrain 5-HT levels, yet no investigations have been carried out to assess the impact of such severe 5-HT depletion on the function of target cortical neurons. Using whole cell patch-clamp methods, two-dimensional (2D) multielectrode arrays (MEAs), 3D morphological neuronal reconstructions, and animal behavior, we investigated the impact of 5-HT depletion on cortical cell-intrinsic and network excitability. We found significant changes in several parameters of cell-intrinsic excitability in cortical pyramidal cells (PCs) as well as an increase in spontaneous synaptic excitation through 5-HT3 receptors. These changes are associated with increased local network excitability and oscillatory activity in a 5-HT2 receptor-dependent manner, consistent with previously reported hypersensitivity of cortical 5-HT2 receptors. PC morphology was also altered, with a significant reduction in dendritic complexity that may possibly act as a compensatory mechanism for increased excitability. Consistent with this interpretation, when we carried out experiments with convulsant-induced seizures to asses cortical excitability in vivo, we observed no significant differences in seizure parameters between wild-type and Pet-1(-/-) mice. Moreover, MEA recordings of propagating field potentials showed diminished propagation of activity across the cortical sheath. Together these findings reveal novel functional changes in neuronal and cortical excitability in mice lacking Pet-1.

Axon targeting of the alpha 7 nicotinic receptor in developing hippocampal neurons by Gprin1 regulates growth.

Cholinergic signaling plays an important role in regulating the growth and regeneration of axons in the nervous system. The α7 nicotinic receptor (α7) can drive synaptic development and plasticity in the hippocampus. Here, we show that activation of α7 significantly reduces axon growth in hippocampal neurons by coupling to G protein-regulated inducer of neurite outgrowth 1 (Gprin1), which targets it to the growth cone. Knockdown of Gprin1 expression using RNAi is found sufficient to abolish the localization and calcium signaling of α7 at the growth cone. In addition, an α7/Gprin1 interaction appears intimately linked to a Gαo, growth-associated protein 43, and CDC42 cytoskeletal regulatory pathway within the developing axon. These findings demonstrate that α7 regulates axon growth in hippocampal neurons, thereby likely contributing to synaptic formation in the developing brain.

Fluctuation Scaling of Neuronal Firing and Bursting in Spontaneously Active Brain Circuits.

We employed high-density microelectrode arrays to investigate spontaneous firing patterns of neurons in brain circuits of the primary somatosensory cortex (S1) in mice. We recorded from over 150 neurons for 10min in each of eight different experiments, identified their location in S1, sorted their action potentials (spikes), and computed their power spectra and inter-spike interval (ISI) statistics. Of all persistently active neurons, 92% fired with a single dominant frequency - regularly firing neurons (RNs) - from 1 to 8Hz while 8% fired in burst with two dominant frequencies - bursting neurons (BNs) - corresponding to the inter-burst (2-6Hz) and intra-burst intervals (20-160Hz). RNs were predominantly located in layers 2/3 and 5/6 while BNs localized to layers 4 and 5. Across neurons, the standard deviation of ISI was a power law of its mean, a property known as fluctuation scaling, with a power law exponent of 1 for RNs and 1.25 for BNs. The power law implies that firing and bursting patterns are scale invariant: the firing pattern of a given RN or BN resembles that of another RN or BN, respectively, after a time contraction or dilation. An explanation for this scale invariance is discussed in the context of previous computational studies as well as its potential role in information processing.

Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales.

In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.