State-dependent complexity of the local field potential in the primary visual cortex.

The local field potential (LFP) is as a measure of the combined activity of neurons within a region of brain tissue. While biophysical modeling schemes for LFP in cortical circuits are well established, there is a paramount lack of understanding regarding the LFP properties along the states assumed in cortical circuits over long periods. Here we use a symbolic information approach to determine the statistical complexity based on Jensen disequilibrium measure and Shannon entropy of LFP data recorded from the primary visual cortex (V1) of urethane-anesthetized rats and freely moving mice. Using these information quantifiers, we find consistent relations between LFP recordings and measures of cortical states at the neuronal level. More specifically, we show that LFP's statistical complexity is sensitive to cortical state (characterized by spiking variability), as well as to cortical layer. In addition, we apply these quantifiers to characterize behavioral states of freely moving mice, where we find indirect relations between such states and spiking variability.

Distinct role of nucleus accumbens D2-MSN projections to ventral pallidum in different phases of motivated behavior.

The nucleus accumbens (NAc) is a key region in motivated behaviors. NAc medium spiny neurons (MSNs) are divided into those expressing dopamine receptor D1 or D2. Classically, D1- and D2-MSNs have been described as having opposing roles in reinforcement, but recent evidence suggests a more complex role for D2-MSNs. Here, we show that optogenetic modulation of D2-MSN to ventral pallidum (VP) projections during different stages of motivated behavior has contrasting effects in motivation. Activation of D2-MSN-VP projections during a reward-predicting cue results in increased motivational drive, whereas activation at reward delivery decreases motivation; optical inhibition triggers the opposite behavioral effect. In addition, in a free-choice instrumental task, animals prefer the lever that originates one pellet in opposition to pellet plus D2-MSN-VP optogenetic activation and vice versa for optogenetic inhibition. In summary, D2-MSN-VP projections play different, and even opposing, roles in distinct phases of motivated behavior.

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.

Correction: Nucleus accumbens medium spiny neurons subtypes signal both reward and aversion.

A correction to this paper has been published and can be accessed via a link at the top of the paper.

Nucleus accumbens medium spiny neurons subtypes signal both reward and aversion.

Deficits in decoding rewarding (and aversive) signals are present in several neuropsychiatric conditions such as depression and addiction, emphasising the importance of studying the underlying neural circuits in detail. One of the key regions of the reward circuit is the nucleus accumbens (NAc). The classical view on the field postulates that NAc dopamine receptor D1-expressing medium spiny neurons (D1-MSNs) convey reward signals, while dopamine receptor D2-expressing MSNs (D2-MSNs) encode aversion. Here, we show that both MSN subpopulations can drive reward and aversion, depending on their neuronal stimulation pattern. Brief D1- or D2-MSN optogenetic stimulation elicited positive reinforcement and enhanced cocaine conditioning. Conversely, prolonged activation induced aversion, and in the case of D2-MSNs, decreased cocaine conditioning. Brief stimulation was associated with increased ventral tegmenta area (VTA) dopaminergic tone either directly (for D1-MSNs) or indirectly via ventral pallidum (VP) (for D1- and D2-MSNs). Importantly, prolonged stimulation of either MSN subpopulation induced remarkably distinct electrophysiological effects in these target regions. We further show that blocking κ-opioid receptors in the VTA (but not in VP) abolishes the behavioral effects induced by D1-MSN prolonged stimulation. In turn, blocking δ-opioid receptors in the VP (but not in VTA) blocks the behavioral effects elicited by D2-MSN prolonged stimulation. Our findings demonstrate that D1- and D2-MSNs can bidirectionally control reward and aversion, explaining the existence of controversial studies in the field, and highlights that the proposed striatal functional opposition needs to be reconsidered.

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.

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.

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

The cerebral cortex is an anatomically divided and functionally specialized structure. It includes distinct areas, which work on different states over time. The structural features of spiking activity in sensory cortices have been characterized during spontaneous and evoked activity. However, the coordination among cortical and sub-cortical neurons during spontaneous activity across different states remains poorly characterized. We addressed this issue by studying the temporal coupling of spiking variability recorded from primary sensory cortices and hippocampus of anesthetized or freely behaving rats. During spontaneous activity, spiking variability was highly correlated across primary cortical sensory areas at both small and large spatial scales, whereas the cortico-hippocampal correlation was modest. This general pattern of spiking variability was observed under urethane anesthesia, as well as during waking, slow-wave sleep and rapid-eye-movement sleep, and was unchanged by novel stimulation. These results support the notion that primary sensory areas are strongly coupled during spontaneous activity.