Summary The hippocampus is critical to remembering the flow of events in distinct experiences and, in doing so, bridges temporal gaps between discontiguous events. Here we report a robust hippocampal representation of sequence memories, highlighted by “time cells” that encode successive moments during an empty temporal gap between the key events, while at the same times encoding location and ongoing behavior. Furthermore, just as most place cells “remap” when a salient spatial cue is altered, most time cells form qualitatively different representations (“re-time”) when the main temporal parameter is altered. Hippocampal neurons also differentially encode the key events and disambiguate different event sequences to compose unique, temporally organized representations of specific experiences. These findings suggest that hippocampal neural ensembles segment temporally organized memories much the same as they represent locations of important events in spatially defined environments.

Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by an increase in spontaneous, noisy baseline neural activity. Here we analyze data from two different groups of human subjects: intracranial electrocorticography from 15 participants over a 38 year age range (15-53 years) and scalp EEG data from healthy younger (20 -30 years) and older (60 -70 years) adults to test the neural noise hypothesis from a 1/f noise perspective. Many natural phenomena, including electrophysiology, are characterized by 1/f noise. The defining characteristic of 1/f is that the power of the signal frequency content decreases rapidly as a function of the frequency ( f) itself. The slope of this decay, the noise exponent (), is often ϽϪ1 for electrophysiological data and has been shown to approach white noise (defined as ϭ 0) with increasing task difficulty. We observed, in both electrophysiological datasets, that aging is associated with a flatter (more noisy) 1/f power spectral density, even at rest, and that visual cortical 1/f noise statistically mediates age-related impairments in visual working memory. These results provide electrophysiological support for the neural noise hypothesis of aging.

We present maps, source catalogue and number counts of the largest, most complete and unbiased extragalactic submillimetre survey: the 850‐μm SCUBA Half‐Degree Extragalactic Survey (SHADES). Using the Submillimetre Common‐User Bolometer Array (SCUBA) on the James Clerk Maxwell Telescope (JCMT), SHADES mapped two separate regions of sky: the Subaru/XMM–Newton Deep Field (SXDF) and the Lockman Hole East (LH). Encompassing 93 per cent of the overall acquired data (i.e. data taken up to 2004 February 1), these SCUBA maps cover 720 arcmin2 with a rms noise level of about 2 mJy and have uncovered >100 submillimetre galaxies. In order to ensure the utmost robustness of the resulting source catalogue, data reduction was independently carried out by four subgroups within the SHADES team, providing an unprecedented degree of reliability with respect to other SCUBA catalogues available from the literature. Individual source lists from the four groups were combined to produce a robust 120‐object SHADES catalogue; an invaluable resource for follow‐up campaigns aiming to study the properties of a complete and consistent sample of submillimetre galaxies. For the first time, we present deboosted flux densities for each submillimetre galaxy found in a large survey. Extensive simulations and tests were performed separately by each group in order to confirm the robustness of the source candidates and to evaluate the effects of false detections, completeness and flux density boosting. Corrections for these effects were then applied to the data to derive the submillimetre galaxy source counts. SHADES has a high enough number of detected sources that meaningful differential counts can be estimated, unlike most submillimetre surveys which have to consider integral counts. We present differential and integral source number counts and find that the differential counts are better fit with a broken power law or a Schechter function than with a single power law; the SHADES data alone significantly show that a break is required at several mJy, although the precise position of the break is not well constrained. We also find that a 850‐μm survey complete down to 2 mJy would resolve 20–30 per cent of the far‐infrared background into point sources.

Why seizures spontaneously terminate remains an unanswered fundamental question of epileptology. Here we present evidence that seizures self-terminate via a discontinuous critical transition or bifurcation. We show that human brain electrical activity at various spatial scales exhibits common dynamical signatures of an impending critical transition-slowing, increased correlation, and flickering-in the approach to seizure termination. In contrast, prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. To support these results, we implement a computational model that demonstrates that alternative stable attractors, representing the ictal and postictal states, emulate the observed dynamics. These results suggest that self-terminating seizures end through a common dynamical mechanism. This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature.critical slowing down | epilepsy | electrocorticogram | local field potential A lthough extensive observations and research have elucidated some mechanism of seizure initiation and maintenance, how seizures spontaneously terminate remains one of the most important, but still unanswered, questions in epileptology (1). Some of the potential mechanisms of seizure termination (2) include glutamate depletion (3), dynamic changes in ion concentrations (4-6), persistent activation of a hyperpolarization-activated cation conductance (7), changing synaptic effectiveness (5, 8), modulatory effects from subcortical structures and the cerebellum (9), and reduced pH (10). Together, these studies suggest distinct pathways to seizure termination through specific biophysical mechanisms.We propose here a dynamical understanding of seizure termination that encompasses and constrains these and other hypothesized biophysical mechanisms. Specifically, we propose that focal seizures with secondary generalization terminate in a manner consistent with crossing a critical transition or bifurcation in which the system traverses a critical threshold and shifts suddenly to an alternative, attracting dynamical regime (11). Such regime shifts between alternative stable states have been described in many real-world systems (12-14) and exhibit a repertoire of early warning indicators (15-17). The seizing brain provides a unique living system for studying the signatures of an impending critical transition as well as one in which interventions can have profound practical import.We characterize the features of seizure termination in both multiscale in vivo data from patients with epilepsy and a computational model of cortical field activity. We show that population electrical activity-observed at macroscopic spatial scales-exhibits numerous signatures of an impending critical transition, whereas spatially localized recordings of neural spiking activity possess different dynamics. These insi...

Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time. To address this we examine functional connectivity networks deduced from continuous long-term electrocorticogram (ECoG) recordings. For a population of 6 human patients, we identify a persistent pattern of connections that form a frequency-band dependent network template, and a set of core connections that appear frequently and together. These structures are robust, emerging from brief time intervals (~100s) regardless of cognitive state. These results suggest that a metastable, frequency-band dependent scaffold of brain connectivity exists from which transient activity emerges and recedes.