Prefrontal Activity Links Nonoverlapping Events in Memory

The medial prefrontal cortex (mPFC) plays an important role in memory. By maintaining a working memory buffer, neurons in prelimbic (PL) mPFC may selectively contribute to learning associations between stimuli that are separated in time, as in trace fear conditioning (TFC). Until now, evidence for this bridging role was largely descriptive. Here we used optogenetics to silence neurons in the PL mPFC of rats during learning in TFC. Memory formation was prevented when mPFC was silenced specifically during the interval separating the cue and shock. Our results provide support for a working memory function for these cells and indicate that associating two noncontiguous stimuli requires bridging activity in PL mPFC

Intrinsic Noise in Cultured Hippocampal Neurons: Experiment and Modeling

Ion channels open and close stochastically. The fluctuation of these channels represents an intrinsic source of noise that affects the input-output properties of the neuron. We combined whole-cell measurements with biophysical modeling to characterize the intrinsic stochastic and electrical properties of single neurons as observed at the soma. We measured current and voltage noise in 18 d postembryonic cultured neurons from the rat hippocampus, at various subthreshold and near-threshold holding potentials in the presence of synaptic blockers. The observed current noise increased with depolarization, as ion channels were activated, and its spectrum demonstrated generalized 1/fbehavior. Exposure to TTX removed a significant contribution from Na^+ channels to the noise spectrum, particularly at depolarized potentials, and the resulting spectrum was now dominated by a single Lorentzian (1/f^2) component. By replacing the intracellular K^+ with Cs^+, we demonstrated that a major portion of the observed noise was attributable to K^+ channels. We compared the measured power spectral densities to a 1-D cable model of channel fluctuations based on Markov kinetics. We found that a somatic compartment, in combination with a single equivalent cylinder, described the effective geometry from the viewpoint of the soma. Four distinct channel populations were distributed in the membrane and modeled as Lorentzian current noise sources. Using the NEURON simulation program, we summed up the contributions from the spatially distributed current noise sources and calculated the total voltage and current noise. Our quantitative model reproduces important voltage- and frequency-dependent features of the data, accounting for the 1/f behavior, as well as the effects of various blockers

Low activity microstates during sleep

Study Objectives: To better understand the distinct activity patterns of the brain during sleep, we observed and investigated periods of diminished oscillatory and population spiking activity lasting for seconds during non-rapid eye movement (non-REM) sleep, which we call “LOW” activity sleep. Methods: We analyzed spiking and local field potential (LFP) activity of hippocampal CA1 region alongside neocortical electroencephalogram (EEG) and electromyogram (EMG) in 19 sessions from four male Long-Evans rats (260–360 g) during natural wake/sleep across the 24-hr cycle as well as data from other brain regions obtained from http://crcns.org. Results: LOW states lasted longer than OFF/DOWN states and were distinguished by a subset of “LOW-active” cells. LOW activity sleep was preceded and followed by increased sharp-wave ripple activity. We also observed decreased slow-wave activity and sleep spindles in the hippocampal LFP and neocortical EEG upon LOW onset, with a partial rebound immediately after LOW. LOW states demonstrated activity patterns consistent with sleep but frequently transitioned into microarousals and showed EMG and LFP differences from small-amplitude irregular activity during quiet waking. Their likelihood decreased within individual non-REM epochs yet increased over the course of sleep. By analyzing data from the entorhinal cortex of rats,1 as well as the hippocampus, the medial prefrontal cortex, the postsubiculum, and the anterior thalamus of mice,2 obtained from http://crcns.org, we confirmed that LOW states corresponded to markedly diminished activity simultaneously in all of these regions. Conclusions: We propose that LOW states are an important microstate within non-REM sleep that provide respite from high-activity sleep and may serve a restorative function

Monosynaptic Functional Connectivity in Cerebral Cortex During Wakefulness and Under Graded Levels of Anesthesia

The balance between excitation and inhibition is considered to be of significant importance for neural computation and cognitive function. Excitatory and inhibitory functional connectivity in intact cortical neuronal networks in wakefulness and graded levels of anesthesia has not been systematically investigated. We compared monosynaptic excitatory and inhibitory spike transmission probabilities using pairwise cross-correlogram (CCG) analysis. Spikes were measured at 64 sites in the visual cortex of rats with chronically implanted microelectrode arrays during wakefulness and three levels of anesthesia produced by desflurane. Anesthesia decreased the number of active units, the number of functional connections, and the strength of excitatory connections. Connection probability (number of connections per number of active unit pairs) was unaffected until the deepest anesthesia level, at which a significant increase in the excitatory to inhibitory ratio of connection probabilities was observed. The results suggest that the excitatory–inhibitory balance is altered at an anesthetic depth associated with unconsciousness

Single-Trial Phase Precession in the Hippocampus

During the crossing of the place field of a pyramidal cell in the rat hippocampus, the firing phase of the cell decreases with respect to the local theta rhythm. This phase precession is usually studied on the basis of data in which many place field traversals are pooled together. Here we study properties of phase precession in single trials. We found that single-trial and pooled-trial phase precession were different with respect to phase-position correlation, phase-time correlation, and phase range. Whereas pooled-trial phase precession may span 360°, the most frequent single-trial phase range was only ∼180°. In pooled trials, the correlation between phase and position (r = −0.58) was stronger than the correlation between phase and time (r = −0.27), whereas in single trials these correlations (r = −0.61 for both) were not significantly different. Next, we demonstrated that phase precession exhibited a large trial-to-trial variability. Overall, only a small fraction of the trial-to-trial variability in measures of phase precession (e.g., slope or offset) could be explained by other single-trial properties (such as running speed or firing rate), whereas the larger part of the variability remains to be explained. Finally, we found that surrogate single trials, created by randomly drawing spikes from the pooled data, are not equivalent to experimental single trials: pooling over trials therefore changes basic measures of phase precession. These findings indicate that single trials may be better suited for encoding temporally structured events than is suggested by the pooled data

Local Field Potentials Encode Place Cell Ensemble Activation during Hippocampal Sharp Wave Ripples

Whether the activation of spiking cell ensembles can be encoded in the local field potential (LFP) remains unclear. We address this question by combining in vivo electrophysiological recordings in the rat hippocampus with realistic biophysical modeling, and explore the LFP of place cell sequence spiking (“replays”) during sharp wave ripples. We show that multi-site perisomatic LFP amplitudes, in the ∼150–200 Hz frequency band, reliably reflect spatial constellations of spiking cells, embedded within non-spiking populations, and encode activation of local place cell ensembles during in vivo replays. We find spatiotemporal patterns in the LFP, which remain consistent between sequence replays, in conjunction with the ordered activation of place cell ensembles. Clustering such patterns provides an efficient segregation of replay events from non-replay-associated ripples. This work demonstrates how spatiotemporal ensemble spiking is encoded extracellularly, providing a window for efficient, LFP-based detection and monitoring of structured population activity in vivo

Uncovering temporal structure in hippocampal output patterns.

Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. PBE activity has historically been analyzed as a phenomenon subordinate to the place code. Here, we use hidden Markov models to study PBEs observed in rats during exploration of both linear mazes and open fields. We demonstrate that estimated models are consistent with a spatial map of the environment, and can even decode animals' positions during behavior. Moreover, we demonstrate the model can be used to identify hippocampal replay without recourse to the place code, using only PBE model congruence. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Additionally, by forming models independent of animal behavior, we lay the groundwork for studies of non-spatial memory

Extracellular field signatures of CA1 spiking cell assemblies during sharp wave-ripple complexes

Although postsynaptic and transmembrane currents over local neuronal populations are considered the main factors for shaping local field potential (LFP) and current source density (CSD) fluctuations [1], high-frequency oscillatory LFPs can also be shaped by extracellular action potentials of pyramidal cell populations [2]. Sharp wave-ripple complexes (SWRs) are typical examples of such high-frequency oscillatory events, observed in hippocampal LFPs during deep sleep and awake immobility. They consist of an extensive depolarization in the CA1 dendritic layer (sharp wave) arising from population bursts in CA3, accompanied by a ~150-200 Hz LFP oscillation in the CA1 pyramidal layer (ripple). During SWRs, temporal firing patterns of correlated place cells, acquired during wakeful exploration, are replayed in fast-scale, providing a strong indication for the participation of SWRs in memory consolidation. Yet the particular effects of these pattern replays on the hippocampal extracellular field are largely unknown. How are the different ensembles of spiking cells encoded in the emerging ripple-LFPs? Here, we study this association through both a modeling and an experimental approach

The Stress-Energy Tensor in Soluble Models of Spherically Symmetric Charged Black Hole Evaporation

We study the decay of a near-extremal black hole in AdS$_2$, related to the near-horizon region of 3+1-dimensional Reissner-Nordstr\"om spacetime, following Fabbri, Navarro, and Navarro-Salas. Back-reaction is included in a semiclassical approximation. Calculations of the stress-energy tensor of matter coupled to the physical spacetime for an affine null observer demonstrate that the black hole evaporation proceeds smoothly and the near-extremal black hole evolves back to an extremal ground state, until this approximation breaks down.Comment: 19 pages, 14 figure

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)