Spontaneous neuronal activity is a ubiquitous feature of cortex. Its spatiotemporal organization reflects past input and modulates future network output. Here we study whether a particular type of spontaneous activity is generated by a network that is optimized for input processing. Neuronal avalanches are a type of spontaneous activity observed in superficial cortical layers in vitro and in vivo with statistical properties expected from a network operating at "criticality." Theory predicts that criticality and, therefore, neuronal avalanches are optimal for input processing, but until now, this has not been tested in experiments. Here, we use cortex slice cultures grown on planar microelectrode arrays to demonstrate that cortical networks that generate neuronal avalanches benefit from a maximized dynamic range, i.e., the ability to respond to the greatest range of stimuli. By changing the ratio of excitation and inhibition in the cultures, we derive a network tuning curve for stimulus processing as a function of distance from criticality in agreement with predictions from our simulations. Our findings suggest that in the cortex, (1) balanced excitation and inhibition establishes criticality, which maximizes the range of inputs that can be processed, and (2) spontaneous activity and input processing are unified in the context of critical phenomena.

The repertoire of neural activity patterns that a cortical network can produce constrains the ability of the network to transfer and process information. Here, we measured activity patterns obtained from multisite local field potential recordings in cortex cultures, urethaneanesthetized rats, and awake macaque monkeys. First, we quantified the information capacity of the pattern repertoire of ongoing and stimulus-evoked activity using Shannon entropy. Next, we quantified the efficacy of information transmission between stimulus and response using mutual information. By systematically changing the ratio of excitation/inhibition (E/I) in vitro and in a network model, we discovered that both information capacity and information transmission are maximized at a particular intermediate E/I, at which ongoing activity emerges as neuronal avalanches. Next, we used our in vitro and model results to correctly predict in vivo information capacity and interactions between neuronal groups during ongoing activity. Close agreement between our experiments and model suggest that neuronal avalanches and peak information capacity arise because of criticality and are general properties of cortical networks with balanced E/I.

Two peptides that crossreact with an antiserum raised against Phe-Met-Arg-Phe-NH2 were purified from bovine brain extract. Their structures were determined to be Ala-Gly-Glu-Gly-Leu-Ser-Ser-Pro-Phe-Trp-Ser-Leu-Ala-AlaPro-Gln-Arg-Phe-NH2 and Phe-Leu-Phe-Gln-Pro-Gln-ArgPhe-NH2. The sequences were determined by gas-phase sequencing, except for the COOH-terminal phenylalaninamides. These were assigned on the basis of the reactivity of the peptides with the anti-Phe-Met-Arg-Phe-NH2 antiserum, which appears to recognize the determinant -Arg-Phe-NH2. Both peptides were synthesized, and the synthetic peptides were found to have the same HPLC retention times as the endogenous Phe-MetArg-Phe-NH2-immunoreactive peptides, thus confirming the assignment of phenylalaninamide to the COOH-terminal positions. Both of the synthetic peptides were found to decrease tail-flick latency in rats, and the octapeptide was more active than the octadecapeptide. The octapeptide was found also to attenuate the prolongation of the tail-flick latency induced by morphine.The cardioexcitatory peptide Phe-Met-Arg-Phe-NH2 (FMRF-NH2) was originally isolated from the ganglia ofthe venus clam, Macrocallista nimbosa, by Price and Greenberg in 1977 (1). Subsequently, FMRF-NH2-like immunoreactivity was detected in central nervous system neurons of many mammalian species (2,3). The biological roles of FMRF-NH2 have been investigated extensively in molluscs (4), but the function of the FMRF-NH2-like immunoreactive species in the mammalian central nervous system is unknown. lontophoretically applied FMRF-NH2 has an excitatory effect on rat brain medullary neurons (5). FMRF-NH2 injected intrathecally or intraventricularly can reduce opiate-induced analgesia (6). Furthermore, intrathecal or intraventricular administration of IgG prepared from FMRF-NH2 antiserum was found to potentiate morphine analgesia and also to induce a moderate analgesia when given at a higher dose. These observations suggest that endogenous FMRF-NH2-like immunoreactive peptide(s) may have a role in modulating antinociception by endogenous opioid peptides. To increase our understanding of this interaction between FMRF-NH2-like immunoreactive material and opioid peptides, we have purified and chemically characterized the mammalian FMRF-NH2-like immunoreactive species, which is known to be structurally different from the tetrapeptide FMRF-NH2 (2).MATERIALS AND METHODS FMRF-NH2 Antiserum and Radioimmunoassay. An antiserum to FMRF-NH2 was prepared from rabbits injected with FMRF-NH2 conjugated to succinylated hemocyanin by carbodiimide, as described (7). The radioimmunoassay used 125I-labeled Tyr-Phe-Met-Arg-Phe-NH2 as a tracer. The antiserum crossreacts with FMRF-NH2 and yl-melanotropin with high affinity but shows very weak affinity for neuropeptide Y (0.1%), y-melanotropin (<0.01%), and [Met5]enkephalin-Arg6-Phe7 (<0.01%). Cholecystokinin and substance P were not recognized at all by the antiserum. These results suggest that -Arg-Phe-NH2 is the determinant recognized by the antis...

In the cortex, the interactions among neurons give rise to transient coherent activity patterns that underlie perception, cognition, and action. Recently, it was actively debated whether the most basic interactions, i.e., the pairwise correlations between neurons or groups of neurons, suffice to explain those observed activity patterns. So far, the evidence reported is controversial. Importantly, the overall organization of neuronal interactions and the mechanisms underlying their generation, especially those of high-order interactions, have remained elusive. Here we show that higher-order interactions are required to properly account for cortical dynamics such as ongoing neuronal avalanches in the alert monkey and evoked visual responses in the anesthetized cat. A Gaussian interaction model that utilizes the observed pairwise correlations and event rates and that applies intrinsic thresholding identifies those higher-order interactions correctly, both in cortical local field potentials and spiking activities. This allows for accurate prediction of large neuronal population activities as required, e.g., in brain-machine interface paradigms. Our results demonstrate that higher-order interactions are inherent properties of cortical dynamics and suggest a simple solution to overcome the apparent formidable complexity previously thought to be intrinsic to those interactions.

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