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SummaryBrain activity is highly regulated by GABAergic activity, which acts via GABAARs to suppress somatic spike generation as well as dendritic synaptic integration and calcium signaling. Tonic GABAergic conductances mediated by distinct receptor subtypes can also inhibit neuronal excitability and spike output, though the consequences for dendritic calcium signaling are unclear. Here, we use 2-photon calcium imaging in cortical pyramidal neurons and computational modeling to show that low affinity GABAARs containing an α5 subunit mediate a tonic hyperpolarization of the dendritic membrane potential, resulting in deinactivation of voltage-gated calcium channels and a paradoxical boosting of action potential-evoked calcium influx. We also find that GABAergic enhancement of calcium signaling modulates short-term synaptic plasticity, augmenting depolarization-induced suppression of inhibition. These results demonstrate a novel role for GABA in the control of dendritic activity and suggest a mechanism for differential modulation of electrical and biochemical signaling.

Deployment of covert attention to a spatial location can cause large decreases in low-frequency correlated variability among neurons in macaque area V4 whose receptive-fields lie at the attended location. It has been estimated that this reduction accounts for a substantial fraction of the attention-mediated improvement in sensory processing. These estimates depend on assumptions about how population signals are decoded and the conclusion that correlated variability impairs perception, is purely hypothetical. Here we test this proposal directly by optogenetically inducing low-frequency fluctuations, to see if this interferes with performance in an attention-demanding task. We find that low-frequency optical stimulation of neurons in V4 elevates correlations among pairs of neurons and impairs the animal’s ability to make fine sensory discriminations. Stimulation at higher frequencies does not impair performance, despite comparable modulation of neuronal responses. These results support the hypothesis that attention-dependent reductions in correlated variability contribute to improved perception of attended stimuli.

N-methyl-D-aspartate receptor (NMDAR) hypofunction in parvalbumin-expressing (PV+) inhibitory neurons (INs) may contribute to symptoms in patients with schizophrenia (SZ). This hypothesis was inspired by studies in humans involving NMDAR antagonists that trigger SZ symptoms. Animal models of SZ using neuropharmacology and genetic knockouts have successfully replicated some of the key observations in human subjects involving alteration of gamma band oscillations (GBO) observed in electroencephalography and magnetoencephalography signals. However, it remains to be seen if NMDAR hypofunction in PV+ neurons is fundamental to the phenotype observed in these models. In this review, we discuss some of the key computational models of GBO and their predictions in the context of NMDAR hypofunction in INs. While PV+ INs have been the main focus of SZ studies in animal models, we also discuss the implications of NMDAR hypofunction in other types of INs using computational models for GBO modulation in the visual cortex.

A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange “contextual” information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by “asking” natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The “answer” was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the “multiplicative” center-flanker interactions previously reported in V1 neurons (Kapadia et al. 1995, 2000; Polat et al. 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed with near perfect accuracy by NMDAR-dependent spatial synaptic interactions within PN dendrites – the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.Significance StatementIn addition to the driver inputs that establish their classical receptive fields, cortical pyramidal neurons (PN) receive a much larger number of “contextual” inputs from other PNs through a dense plexus of horizontal connections (HCs). However by what mechanisms, and for what behavioral purposes, HC’s modulate PN responses remains unclear. We pursued these questions in the context of object boundary detection in visual cortex, by combining an analysis of natural boundary statistics with detailed modeling PNs and local circuits. We found that nonlinear synaptic interactions in PN dendrites are ideally suited to solve the boundary detection problem. We propose that PN dendrites provide the core computing substrate through which cortical neurons modulate each other’s responses depending on context.

Gamma band rhythms may synchronize distributed cell assemblies to facilitate information transfer within and across brain areas, yet their underlying mechanisms remain hotly debated. Most circuit models postulate that soma-targeting parvalbumin-positive GABAergic neurons are the essential inhibitory neuron subtype necessary for gamma rhythms. Using cell-type-specific optogenetic manipulations in behaving animals, we show that dendrite-targeting somatostatin (SOM) interneurons are critical for a visually induced, context-dependent gamma rhythm in visual cortex. A computational model independently predicts that context-dependent gamma rhythms depend critically on SOM interneurons. Further in vivo experiments show that SOM neurons are required for long-distance coherence across the visual cortex. Taken together, these data establish an alternative mechanism for synchronizing distributed networks in visual cortex. By operating through dendritic and not just somatic inhibition, SOM-mediated oscillations may expand the computational power of gamma rhythms for optimizing the synthesis and storage of visual perceptions.

To deepen our understanding of object recognition, it is critical to understand the nature of transformations that occur in intermediate stages of processing in the ventral visual pathway, such as area V4. Neurons in V4 are selective to local features of global shape, such as extended contours. Previously, we found that V4 neurons selective for curved elements exhibit a high degree of spatial variation in their preference. If spatial variation in curvature selectivity was also marked by distinct temporal response patterns at different spatial locations, then it might be possible to untangle this information in subsequent processing based on temporal responses. Indeed, we find that V4 neurons whose receptive fields exhibit intricate selectivity also show variation in their temporal responses across locations. A computational model that decodes stimulus identity based on population responses benefits from using this temporal information, suggesting that it could provide a multiplexed code for spatio-temporal features.

Neuromodulatory signaling is generally considered broad in its impact across cortex. However, variations in the characteristics of cortical circuits may introduce regionally-specific responses to diffuse modulatory signals. Features such as patterns of axonal innervation, tissue tortuosity and molecular diffusion, effectiveness of degradation pathways, subcellular receptor localization, and patterns of receptor expression can lead to local modification of modulatory inputs. We propose that modulatory compartments exist in cortex and can be defined by variation in structural features of local circuits. Further, we argue that these compartments are responsible for local regulation of neuromodulatory tone. For the cholinergic system, these modulatory compartments are regions of cortical tissue within which signaling conditions for acetylcholine are relatively uniform, but between which signaling can vary profoundly. In the visual system, evidence for the existence of compartments indicates that cholinergic modulation likely differs across the visual pathway. We argue that the existence of these compartments calls for thinking about cholinergic modulation in terms of finer-grained control of local cortical circuits than is implied by the traditional view of this system as a diffuse modulator. Further, an understanding of modulatory compartments provides an opportunity to better understand and perhaps correct signal modifications that lead to pathological states.

Cortical computations are critically dependent on interactions between pyramidal neurons (PNs) and a menagerie of inhibitory interneuron types. A key feature distinguishing interneuron types is the spatial distribution of their synaptic contacts onto PNs, but the location-dependent effects of inhibition are mostly unknown, especially under conditions involving active dendritic responses. We studied the effect of somatic vs. dendritic inhibition on local spike generation in basal dendrites of layer 5 PNs both in neocortical slices and in simple and detailed compartmental models, with equivalent results: somatic inhibition divisively suppressed the amplitude of dendritic spikes recorded at the soma while minimally affecting dendritic spike thresholds. In contrast, distal dendritic inhibition raised dendritic spike thresholds while minimally affecting their amplitudes. On-the-path dendritic inhibition modulated both the gain and threshold of dendritic spikes depending on its distance from the spike initiation zone. Our findings suggest that cortical circuits could assign different mixtures of gain vs. threshold inhibition to different neural pathways, and thus tailor their local computations, by managing their relative activation of soma- vs. dendrite-targeting interneurons., Author Summary Establishing how inhibitory neurons shape the computing functions of neural circuits is crucial to understanding both normal function and dysfunction in the human brain. It has been known for over a century that different classes of inhibitory interneurons project to different sub-regions of the neurons they contact – some primarily target cell bodies, others the dendrites, still others the axon. It remains poorly understood, however, how these different projection patterns influence synaptic integration in the target neuron populations. By providing new data from intracellular recordings in brain slices, and a simple but powerful model of the location-dependent effects of inhibition on dendritic spike generation, our study (1) demonstrates the importance of the absolute and relative locations of excitatory and inhibitory inputs to pyramidal neurons, the principal cells of the cerebral cortex, and (2) helps to establish a more solid theoretical understanding of these complex integrative phenomena. As high resolution mapping of the cortical “connectome” becomes available in the coming years, our work will be helpful in interpreting the computing functions of cortical tissue both at the single neuron and circuit levels.

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors., Author Summary Pyramidal neurons (PNs) are the principal neurons of the cerebral cortex and therefore lie at the heart of the brain's higher sensory, motor, affective, memory, and executive functions. But how do they work? In particular, how do they manage interactions between the classical “driver” inputs that give rise to their basic response properties, and “contextual” inputs that nonlinearly modulate those responses? It is known that PNs are contacted by thousands of excitatory synapses scattered about their dendrites, but despite decades of research, the “rules” that govern how inputs at different locations in the dendritic tree combine to influence the cell's firing rate remain poorly understood. We show here that two excitatory inputs contacting the same dendrite interact in an asymmetric nonlinear way that depends on their absolute and relative locations, where the resulting spectrum of location-dependent synaptic interactions constitutes a previously unknown form of spatial analog computation. In addition to suggesting a possible substrate for classical-contextual interactions in PN dendrites, our results imply that the computing functions of cortical circuits can only be fully understood when the detailed map of synaptic connectivity – the cortical connectome – is known down to the subdendritic level.