Coupled variability in primary sensory areas and the hippocampus during spontaneous activity

Signatures of brain criticality unveiled by maximum entropy analysis across cortical states

It has recently been reported that statistical signatures of brain criticality, obtained from distributions of neuronal avalanches, can depend on the cortical state. We revisit these claims with a completely different and independent approach, employing a maximum entropy model to test whether signatures of criticality appear in urethane-anesthetized rats. To account for the spontaneous variation of cortical states, we parse the time series and perform the maximum entropy analysis as a function of the variability of the population spiking activity. To compare data sets with different numbers of neurons, we define a normalized distance to criticality that takes into account the peak and width of the specific heat curve. We found a universal collapse of the normalized distance to criticality dependence on the cortical state, on an animal by animal basis. This indicates a universal dynamics and a critical point at an intermediate value of spiking variability.

Subsampled Directed-Percolation Models Explain Scaling Relations Experimentally Observed in the Brain

Recent experimental results on spike avalanches measured in the urethane-anesthetized rat cortex have revealed scaling relations that indicate a phase transition at a specific level of cortical firing rate variability. The scaling relations point to critical exponents whose values differ from those of a branching process, which has been the canonical model employed to understand brain criticality. This suggested that a different model, with a different phase transition, might be required to explain the data. Here we show that this is not necessarily the case. By employing two different models belonging to the same universality class as the branching process (mean-field directed percolation) and treating the simulation data exactly like experimental data, we reproduce most of the experimental results. We find that subsampling the model and adjusting the time bin used to define avalanches (as done with experimental data) are sufficient ingredients to change the apparent exponents of the critical point. Moreover, experimental data is only reproduced within a very narrow range in parameter space around the phase transition.

Low-cost open hardware system for behavioural experiments simultaneously with electrophysiological recordings

A major frontier in neuroscience is to find neural correlates of perception, learning, decision making, and a variety of other types of behavior. In the last decades, modern devices allow simultaneous recordings of different operant responses and the electrical activity of large neuronal populations. However, the commercially available instruments for studying operant conditioning are expensive, and the design of low-cost chambers has emerged as an appealing alternative to resource-limited laboratories engaged in animal behavior. In this article, we provide a full description of a platform that records the operant behavior and synchronizes it with the electrophysiological activity. The programming of this platform is open source, flexible, and adaptable to a wide range of operant conditioning tasks. We also show results of operant conditioning experiments with freely moving rats with simultaneous electrophysiological recordings.

Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

Criticality between Cortical States

Since the first measurements of neuronal avalanches, the critical brain hypothesis has gained traction. However, if the brain is critical, what is the phase transition? For several decades, it has been known that the cerebral cortex operates in a diversity of regimes, ranging from highly synchronous states (with higher spiking variability) to desynchronized states (with lower spiking variability). Here, using both new and publicly available data, we test independent signatures of criticality and show that a phase transition occurs in an intermediate value of spiking variability, in both anesthetized and freely moving animals. The critical exponents point to a universality class different from mean-field directed percolation. Importantly, as the cortex hovers around this critical point, the avalanche exponents follow a linear relation that encompasses previous experimental results from different setups and is reproduced by a model.

Bisphenol A exposure remodels cognition of male rats attributable to excitatory alterations in the hippocampus and visual cortex

Bisphenol A, an environmental xenoestrogen, has been shown sex-specific adverse effects on cognitive function of rodents. However, the specific mechanisms underlying these outcomes remain elusive, limiting our understanding the differences in behavioral impairments due to BPA exposure between genders in humans. The present study chose the juvenile stage (with a stable estrogen level) as the exposure window to explore BPA effects on cognitive behaviors of male and female Sprague-Dawley (SD) rats and related mechanisms. Three dosages of BPA (0.04, 0.4 and 4 mg/kg/day) were chose to make BPA-exposed models. Especially, the mid-dose for rats was close to the current reference daily limit for human exposure given by the U.S. Environmental Protection Agency. Our results showed that male but not female juvenile rats had a marked decline in spatial memory after 0.4 mg/kg/day BPA exposure, which accompanied with downregulation of glutamate receptor (NR2) expression in their hippocampus and primary visual cortex (V1). In the high-dose BPA exposed groups (4 mg/kg/day), there was not only a deficit of spatial memory, but also an anxiety-like behavior of male rats. Additionally, those rats had a significant decline in spine density of pyramidal neurons and a decreased expression of glutamate receptor subtypes (NR2 and GluR1) in the hippocampus. Importantly, such impairments in the hippocampus of male rats were associated with a decrease of glutamate receptor (NR2) expression in the V1, which could perturb the visual information inputs. To some extent, altered ERβ expression within their hypothalamus could contribute to the anxiety-like behavior after high-dose BPA exposure. However, the low-dose BPA exposed juvenile rats didn't present any structural and behavioral changes in our present study. Those results suggests that BPA exerts dose dependent and gender-specific effects on the cognition of juvenile animals. Our findings shed light on mechanisms underlying BPA effects on the juvenile animals.