Contributions of diverse excitatory and inhibitory neurons to recurrent network activity in cerebral cortex

Spontaneous activations follow a common developmental course across primary sensory areas in mouse neocortex

Spontaneous propagation of spiking within the local neocortical circuits of mature primary sensory areas is highly nonrandom, engaging specific sets of interconnected and functionally related neurons. These spontaneous activations promise insight into neocortical structure and function, but their properties in the first 2 wk of perinatal development are incompletely characterized. Previously, we have found that there is a minimal numerical sample, on the order of 400 cells, necessary to fully capture mature neocortical circuit dynamics. Therefore we maximized our numerical sample by using two-photon calcium imaging to observe spontaneous activity in populations of up to 1,062 neurons spanning multiple columns and layers in 52 acute coronal slices of mouse neocortex at each day from postnatal day (PND) 3 to PND 15. Slices contained either primary auditory cortex (A1) or somatosensory barrel field (S1BF), which allowed us to compare sensory modalities with markedly different developmental timelines. Between PND 3 and PND 8, populations in both areas exhibited activations of anatomically compact subgroups on the order of dozens of cells. Between PND 9 and PND 13, the spatiotemporal structure of the activity diversified to include spatially distributed activations encompassing hundreds of cells. Sparse activations covering the entire field of view dominated in slices taken on or after PND 14. These and other findings demonstrate that the developmental progression of spontaneous activations from active local modules in the first postnatal week to sparse, intermingled groups of neurons at the beginning of the third postnatal week generalizes across primary sensory areas, consistent with an intrinsic developmental trajectory independent of sensory input.

Balanced feedforward inhibition and dominant recurrent inhibition in olfactory cortex

Throughout the brain, the recruitment of feedforward and recurrent inhibition shapes neural responses. However, disentangling the relative contributions of these often-overlapping cortical circuits is challenging. The piriform cortex provides an ideal system to address this issue because the interneurons responsible for feedforward and recurrent inhibition are anatomically segregated in layer (L) 1 and L2/3 respectively. Here we use a combination of optical and electrical activation of interneurons to profile the inhibitory input received by three classes of principal excitatory neuron in the anterior piriform cortex. In all classes, we find that L1 interneurons provide weaker inhibition than L2/3 interneurons. Nonetheless, feedforward inhibitory strength covaries with the amount of afferent excitation received by each class of principal neuron. In contrast, intracortical stimulation of L2/3 evokes strong inhibition that dominates recurrent excitation in all classes. Finally, we find that the relative contributions of feedforward and recurrent pathways differ between principal neuron classes. Specifically, L2 neurons receive more reliable afferent drive and less overall inhibition than L3 neurons. Alternatively, L3 neurons receive substantially more intracortical inhibition. These three features--balanced afferent drive, dominant recurrent inhibition, and differential recruitment by afferent vs. intracortical circuits, dependent on cell class--suggest mechanisms for olfactory processing that may extend to other sensory cortices.

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Propagation of spontaneous slow-wave activity across columns and layers of the adult rat barrel cortex in vivo

During slow-wave sleep, neocortical networks exhibit self-organized activity switching between periods of concurrent spiking (up-states) and periods of network silence (down-states), a phenomenon also occurring under the effects of different anesthetics and in in vitro brain slice preparations. Although this type of ongoing activity has been implicated into important functions such as memory consolidation and learning, the manner in which it propagates across different cortical modules (i.e., columns and layers) has not been fully characterized. In the present study, we investigated this issue by measuring spontaneous activity at large scale in the adult rat barrel cortex under urethane anesthesia by means of voltage-sensitive dye imaging and 128-channel probe recordings. Up to 74 neurons located in all layers of up to four functionally identified barrel-related columns were recorded simultaneously. The spontaneous activity propagated isotropically across the cortical surface with a median speed of ~35 µm/ms. A concomitant radial spread of activation was present from deep to superficial cortical layers. Thus, spontaneous activity occurred rather globally in the barrel cortex, with ≥50 % of the up-states presenting spikes in ≥3 columns and layers. Temporally precise spike sequences, which occurred repeatedly (although sporadically) within the up-states, were typically led by putative excitatory neurons in the infragranular cortical layers. In summary, our data provide for the first time an overall view of the spontaneous slow-wave activity within the barrel cortex circuit, characterizing its propagation across columns and layers at high spatio-temporal resolution.

NOX2 Mediated-Parvalbumin Interneuron Loss Might Contribute to Anxiety-Like and Enhanced Fear Learning Behavior in a Rat Model of Post-Traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a common psychiatric disease following exposure to a severe traumatic event or physiological stress, yet the precise mechanisms underlying PTSD remains largely to be determined. Using an animal model of PTSD induced by a single prolonged stress (SPS), we assessed the role of hippocampal nicotinamide adenosine dinucleotide phosphate (NADPH) oxidase 2 (NOX2) and parvalbumin (PV) interneurons in the development of PTSD symptoms. In the present study, behavioral tests were performed by the open field (day 13 after SPS) and fear conditioning tests (days 13 and 14 after SPS). For the interventional study, rats were chronically treated with a NADPH oxidase inhibitor apocynin either by early or delayed administration. The levels of tumor necrosis factor-alpha, interleukin (IL)-1β, IL-6, IL-10, malondialdehyde, superoxide dismutase, NOX2, 4-hydroxynonenal, and PV in the hippocampus were measured at the indicated time points. In the present study, we showed that SPS rats displayed anxiety-like and enhanced fear learning behavior, which was accompanied by the increased expressions of malondialdehyde, IL-6, NOX2, 4-hydroxynonenal, and decreased PV expression. Notably, early but not delayed treatment with apocynin reversed all these abnormalities after SPS. In conclusion, our results provided evidence that NOX2 activation in the hippocampus, at least in part, contributes to oxidative stress and neuroinflammation, which further results in PV interneuron loss and consequent PTSD symptoms in a rat model of PTSD induced by SPS.

Single Canonical Model of Reflexive Memory and Spatial Attention

Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.

Laminar Neural Field Model of Laterally Propagating Waves of Orientation Selectivity

We construct a laminar neural-field model of primary visual cortex (V1) consisting of a superficial layer of neurons that encode the spatial location and orientation of a local visual stimulus coupled to a deep layer of neurons that only encode spatial location. The spatially-structured connections in the deep layer support the propagation of a traveling front, which then drives propagating orientation-dependent activity in the superficial layer. Using a combination of mathematical analysis and numerical simulations, we establish that the existence of a coherent orientation-selective wave relies on the presence of weak, long-range connections in the superficial layer that couple cells of similar orientation preference. Moreover, the wave persists in the presence of feedback from the superficial layer to the deep layer. Our results are consistent with recent experimental studies that indicate that deep and superficial layers work in tandem to determine the patterns of cortical activity observed in vivo.

Multineuronal activity patterns identify selective synaptic connections under realistic experimental constraints

Structured multineuronal activity patterns within local neocortical circuitry are strongly linked to sensory input, motor output, and behavioral choice. These reliable patterns of pairwise lagged firing are the consequence of connectivity since they are not present in rate-matched but unconnected Poisson nulls. It is important to relate multineuronal patterns to their synaptic underpinnings, but it is unclear how effectively statistical dependencies in spiking between neurons identify causal synaptic connections. To assess the feasibility of mapping function onto structure we used a network model that showed a diversity of multineuronal activity patterns and replicated experimental constraints on data acquisition. Using an iterative Bayesian inference algorithm, we detected a select subset of monosynaptic connections substantially more precisely than correlation-based inference, a common alternative approach. We found that precise inference of synaptic connections improved with increasing numbers of diverse multineuronal activity patterns in contrast to increased observations of a single pattern. Surprisingly, neuronal spiking was most effective and precise at revealing causal synaptic connectivity when the lags considered by the iterative Bayesian algorithm encompassed the timescale of synaptic conductance and integration (∼10 ms), rather than synaptic transmission time (∼2 ms), highlighting the importance of synaptic integration in driving postsynaptic spiking. Last, strong synaptic connections were detected preferentially, underscoring their special importance in cortical computation. Even after simulating experimental constraints, top down approaches to cortical connectivity, from function to structure, identify synaptic connections underlying multineuronal activity. These select connections are closely tied to cortical processing.

Synaptic Mechanisms of Tight Spike Synchrony at Gamma Frequency in Cerebral Cortex

During the generation of higher-frequency (e.g., gamma) oscillations, cortical neurons can exhibit pairwise tight (<10 ms) spike synchrony. To understand how synaptic currents contribute to rhythmic activity and spike synchrony, we performed dual whole-cell recordings in mouse entorhinal cortical slices generating periodic activity (the slow oscillation). This preparation exhibited a significant amount of gamma-coherent spike synchrony during the active phase of the slow oscillation (Up state), particularly among fast-spiking inhibitory interneurons. IPSCs arriving in pairs of either pyramidal or fast-spiking neurons during the Up state were highly synchronized and exhibited significant coherence at frequencies from 10 to 100 Hz, peaking at ∼40 Hz, suggesting both synchronous discharge of, and synaptic divergence from, nearby inhibitory neurons. By inferring synaptic currents related to spike generation in simultaneously recorded pyramidal or fast-spiking neurons, we detected a decay of inhibition ∼20 ms before spiking. In fast-spiking interneurons, this was followed by an even larger excitatory input immediately before spike generation. Consistent with an important role for phasic excitation in driving spiking, we found that the correlation of excitatory inputs was highly predictive of spike synchrony in pairs of fast-spiking interneurons. Interestingly, spike synchrony in fast-spiking interneurons was not related to the strength of gap junctional coupling, and was still prevalent in connexin 36 knock-out animals. Our results support the pyramidal-interneuron gamma model of fast rhythmic oscillation in the cerebral cortex and suggest that spike synchrony and phase preference arises from the precise interaction of excitatory-inhibitory postsynaptic currents.

SIGNIFICANCE STATEMENT

We dissected the cellular and synaptic basis of spike synchrony occurring at gamma frequency (30-80 Hz). We used simultaneous targeted whole-cell recordings in an active slice preparation and analyzed the relationships between synaptic inputs and spike generation. We found that both pyramidal and fast-spiking neurons receive large, coherent inhibitory synaptic inputs at gamma frequency. In addition, we found that fast-spiking interneurons receive large, phasic excitatory synaptic inputs immediately before spike generation followed shortly by synaptic inhibition. These data support the principal-interneuron gamma generation model, and reveal how the synaptic connectivity between excitatory and inhibitory neurons supports the generation of gamma oscillations and spike synchrony.