Local Inhibitory Connections Research Articles

Striatal lateral inhibition regulates action selection in a mouse model of levodopa-induced dyskinesia.

Striatal medium spiny neurons (MSNs) integrate multiple external inputs to shape motor output. In addition, MSNs form local inhibitory synaptic connections with one another. The function of striatal lateral inhibition is unknown, but one possibility is in selecting an intended action while suppressing alternatives. Action selection is disrupted in several movement disorders, including levodopa-induced dyskinesia (LID), a complication of Parkinson's disease (PD) therapy characterized by involuntary movements. Here, we identify chronic changes in the strength of striatal lateral inhibitory synapses in a mouse model of PD/LID. These synapses are also modulated by acute dopamine signaling. Chemogenetic suppression of lateral inhibition originating from dopamine D2 receptor-expressing MSNs lowers the threshold to develop involuntary movements in vivo , supporting a role in motor control. By examining the role of lateral inhibition in basal ganglia function and dysfunction, we expand the framework surrounding the role of striatal microcircuitry in action selection.

Fast, high-throughput production of improved rabies viral vectors for specific, efficient and versatile transsynaptic retrograde labeling.

To understand the function of neuronal circuits, it is crucial to disentangle the connectivity patterns within the network. However, most tools currently used to explore connectivity have low throughput, low selectivity, or limited accessibility. Here, we report the development of an improved packaging system for the production of the highly neurotropic RVdGenvA-CVS-N2c rabies viral vectors, yielding titers orders of magnitude higher with no background contamination, at a fraction of the production time, while preserving the efficiency of transsynaptic labeling. Along with the production pipeline, we developed suites of 'starter' AAV and bicistronic RVdG-CVS-N2c vectors, enabling retrograde labeling from a wide range of neuronal populations, tailored for diverse experimental requirements. We demonstrate the power and flexibility of the new system by uncovering hidden local and distal inhibitory connections in the mouse hippocampal formation and by imaging the functional properties of a cortical microcircuit across weeks. Our novel production pipeline provides a convenient approach to generate new rabies vectors, while our toolkit flexibly and efficiently expands the current capacity to label, manipulate and image the neuronal activity of interconnected neuronal circuits in vitro and in vivo.

A brainstem circuit for nausea suppression.

SUMMARYNausea is a discomforting sensation of gut malaise that remains a major clinical challenge. Several visceral poisons induce nausea through the area postrema, a sensory circumventricular organ that detects blood-borne factors. Here, we use genetic approaches based on an area postrema cell atlas to reveal inhibitory neurons that counteract nausea-associated poison responses. The gut hormone glucose insulinotropic peptide (GIP) activates area postrema inhibitory neurons that project locally and elicit inhibitory currents in nausea-promoting excitatory neurons through γ-aminobutyric acid (GABA) receptors. Moreover, GIP blocks behavioral responses to poisons in wild-type mice, with protection eliminated by targeted area postrema neuron ablation. These findings provide insights into the basic organization of nausea-associated brainstem circuits and reveal that area postrema inhibitory neurons are an effective pharmacological target for nausea intervention.

Microglia Elimination Increases Neural Circuit Connectivity and Activity in Adult Mouse Cortex.

Microglia have crucial roles in sculpting synapses and maintaining neural circuits during development. To test the hypothesis that microglia continue to regulate neural circuit connectivity in adult brain, we have investigated the effects of chronic microglial depletion, via CSF1R inhibition, on synaptic connectivity in the visual cortex in adult mice of both sexes. We find that the absence of microglia dramatically increases both excitatory and inhibitory synaptic connections to excitatory cortical neurons assessed with functional circuit mapping experiments in acutely prepared adult brain slices. Microglia depletion leads to increased densities and intensities of perineuronal nets. Furthermore, in vivo calcium imaging across large populations of visual cortical neurons reveals enhanced neural activities of both excitatory neurons and parvalbumin-expressing interneurons in the visual cortex following microglia depletion. These changes recover following adult microglia repopulation. In summary, our new results demonstrate a prominent role of microglia in sculpting neuronal circuit connectivity and regulating subsequent functional activity in adult cortex.SIGNIFICANCE STATEMENT Microglia are the primary immune cell of the brain, but recent evidence supports that microglia play an important role in synaptic sculpting during development. However, it remains unknown whether and how microglia regulate synaptic connectivity in adult brain. Our present work shows chronic microglia depletion in adult visual cortex induces robust increases in perineuronal nets, and enhances local excitatory and inhibitory circuit connectivity to excitatory neurons. Microglia depletion increases in vivo neural activities of both excitatory neurons and parvalbumin inhibitory neurons. Our new results reveal new potential avenues to modulate adult neural plasticity by microglia manipulation to better treat brain disorders, such as Alzheimer's disease.

Ultra-sparse Connectivity within the Lateral Hypothalamus

SummaryThe lateral hypothalamic area (LH) is a vital controller of arousal, feeding, and metabolism [1, 2], which integrates external and internal sensory information. Whereas sensory and whole-body output properties of LH cell populations have received much interest, their intrinsic synaptic organization has remained largely unstudied. Local inhibitory and excitatory connections could help integrate and filter sensory information and mutually inhibitory connections [3] could allow coordinating activity between LH cell types, some of which have mutually exclusive behavioral effects, such as LH VGLUT2 and VGAT neurons [4, 5, 6, 7] and orexin- (ORX) and melanin-concentrating hormone (MCH) neurons [8, 9, 10]. However, classical Golgi staining studies did not find interneurons with locally ramifying axons in the LH [11, 12], and nearby subthalamic and thalamic areas lack local synaptic connectivity [13, 14]. Studies with optogenetic circuit mapping within the LH have demonstrated only a minority of connections when a large pool of presynaptic neurons was activated [15, 16, 17, 18, 19]. Because multiple patch clamp has not been used to study LH connectivity, aside from a limited dataset of MCH neurons where no connections were discovered [15], we used quadruple whole-cell recordings to screen connectivity within the LH with standard methodology we previously used in the neocortex [20, 21, 22]. Finding a lack of local connectivity, we used optogenetic circuit mapping to study the strength of LH optogenetic responses and network oscillations, which were consistent with ultra-sparse intrinsic connectivity within the LH. These results suggest that input from other brain structures is decisive for selecting active populations in the LH.

Dynamic postnatal development of the cellular and circuit properties of striatal D1 and D2 spiny projection neurons.

Key points Imbalances in the activity of the D1‐expressing direct pathway and D2‐expressing indirect pathway striatal projection neurons (SPNs) are thought to contribute to many basal ganglia disorders, including early‐onset neurodevelopmental disorders such as obsessive–compulsive disorder, attention deficit hyperactivity disorder and Tourette's syndrome.This study provides the first detailed quantitative investigation of development of D1 and D2 SPNs, including their cellular properties and connectivity within neural circuits, during the first postnatal weeks.This period is highly dynamic with many properties changing, but it is possible to make three main observations: many aspects of D1 and D2 SPNs progressively mature in parallel; there are notable exceptions when they diverge; and many of the defining properties of mature striatal SPNs and circuits are already established by the first and second postnatal weeks, suggesting guidance through intrinsic developmental programmes.These findings provide an experimental framework for future studies of striatal development in both health and disease. Many basal ganglia neurodevelopmental disorders are thought to result from imbalances in the activity of the D1‐expressing direct pathway and D2‐expressing indirect pathway striatal projection neurons (SPNs). Insight into these disorders is reliant on our understanding of normal D1 and D2 SPN development. Here we provide the first detailed study and quantification of the striatal cellular and circuit changes occurring for both D1 and D2 SPNs in the first postnatal weeks using in vitro whole‐cell patch‐clamp electrophysiology. Characterization of their intrinsic electrophysiological and morphological properties, the excitatory long‐range inputs coming from cortex and thalamus, as well their local gap junction and inhibitory synaptic connections reveals this period to be highly dynamic with numerous properties changing. However it is possible to make three main observations. Firstly, many aspects of SPNs mature in parallel, including intrinsic membrane properties, increases in dendritic arbours and spine densities, general synaptic inputs and expression of specific glutamate receptors. Secondly, there are notable exceptions, including a transient stronger thalamic innervation of D2 SPNs and stronger cortical NMDA receptor‐mediated inputs to D1 SPNs, both in the second postnatal week. Thirdly, many of the defining properties of mature D1 and D2 SPNs and striatal circuits are already established by the first and second postnatal weeks, including different electrophysiological properties as well as biased local inhibitory connections between SPNs, suggesting this is guided through intrinsic developmental programmes. Together these findings provide an experimental framework for future studies of D1 and D2 SPN development in health and disease.

The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding.

Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections (“Mexican hat” connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range (“inverse Mexican hat” connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons.

Layer-Specific Organization of Local Excitatory and Inhibitory Synaptic Connectivity in the Rat Presubiculum.

The presubiculum is part of the parahippocampal spatial navigation system and contains head direction and grid cells upstream of the medial entorhinal cortex. This position within the parahippocampal cortex renders the presubiculum uniquely suited for analyzing the circuit requirements underlying the emergence of spatially tuned neuronal activity. To identify the local circuit properties, we analyzed the topology of synaptic connections between pyramidal cells and interneurons in all layers of the presubiculum by testing 4250 potential synaptic connections using multiple whole-cell recordings of up to 8 cells simultaneously. Network topology showed layer-specific organization of microcircuits consistent with the prevailing distinction of superficial and deep layers. While connections among pyramidal cells were almost absent in superficial layers, deep layers exhibited an excitatory connectivity of 3.9%. In contrast, synaptic connectivity for inhibition was higher in superficial layers though markedly lower than in other cortical areas. Finally, synaptic amplitudes of both excitatory and inhibitory connections showed log-normal distributions suggesting a nonrandom functional connectivity. In summary, our study provides new insights into the microcircuit organization of the presubiculum by revealing area- and layer-specific connectivity rules and sets new constraints for future models of the parahippocampal navigation system.

A competitive inhibitory circuit for selection of active and passive fear responses.

When faced with threat, the survival of an organism is contingent upon the selection of appropriate active or passive behavioural responses. Freezing is an evolutionarily conserved passive fear response that has been used extensively to study the neuronal mechanisms of fear and fear conditioning in rodents. However, rodents also exhibit active responses such as flight under natural conditions. The central amygdala (CEA) is a forebrain structure vital for the acquisition and expression of conditioned fear responses, and the role of specific neuronal sub-populations of the CEA in freezing behaviour is well-established. Whether the CEA is also involved in flight behaviour, and how neuronal circuits for active and passive fear behaviour interact within the CEA, are not yet understood. Here, using in vivo optogenetics and extracellular recordings of identified cell types in a behavioural model in which mice switch between conditioned freezing and flight, we show that active and passive fear responses are mediated by distinct and mutually inhibitory CEA neurons. Cells expressing corticotropin-releasing factor (CRF+) mediate conditioned flight, and activation of somatostatin-positive (SOM+) neurons initiates passive freezing behaviour. Moreover, we find that the balance between conditioned flight and freezing behaviour is regulated by means of local inhibitory connections between CRF+ and SOM+ neurons, indicating that the selection of appropriate behavioural responses to threat is based on competitive interactions between two defined populations of inhibitory neurons, a circuit motif allowing for rapid and flexible action selection.

High-resolution and cell-type-specific photostimulation mapping shows weak excitatory vs. strong inhibitory inputs in the bed nucleus of the stria terminalis.

The bed nucleus of the stria terminalis (BNST) is a key component of the extended amygdala and has been implicated in anxiety and addiction. As individual neurons function within neural circuits, it is important to understand local microcircuits and larger network connections of identified neuronal types and understand how maladaptive changes in the BNST neural networks are induced by stress and drug abuse. However, due to limitations of classic anatomical and physiological methods, the local circuit organization of synaptic inputs to specific BNST neuron types is not well understood. In this study, we report on the application of high-resolution and cell-type-specific photostimulation methodology developed in our laboratory to local circuit mapping in the BNST. Under calibrated experimental conditions, laser photostimulation via glutamate uncaging or channelrhodopsin-2 photoactivation evokes spiking of BNST neurons perisomatically, without activating spikes from axons of passage or distal dendrites. Whole cell recordings, combined with spatially restricted photostimulation of presynaptic neurons at many different locations over a large region, allow high-resolution mapping of presynaptic input sources to single recorded neurons in the BNST. We constructed maps of synaptic inputs impinging onto corticotrophin-releasing hormone-expressing (CRH+) BNST neurons in the dorsolateral BNST and found that the CRH+ neurons receive predominant local inhibitory synaptic connections with very weak excitatory connections. Through cell-type-specific optogenetic stimulation mapping, we generated maps of somatostatin-expressing neuron-specific inhibitory inputs to BNST neurons. Taken together, the photostimulation-based techniques offer us powerful tools for determining the functional organization of local circuits of specific BNST neuron types.

Primary visual cortex shows laminar-specific and balanced circuit organization of excitatory and inhibitory synaptic connectivity.

Using functional mapping assays, we conducted a quantitative assessment of both excitatory and inhibitory synaptic laminar connections to excitatory neurons in layers 2/3-6 of the mouse visual cortex (V1). Laminar-specific synaptic wiring diagrams of excitatory neurons were constructed on the basis of circuit mapping. The present study reveals that that excitatory and inhibitory synaptic connectivity is spatially balanced across excitatory neuronal networks in V1. In the mammalian neocortex, excitatory neurons provide excitation in both columnar and laminar dimensions, which is modulated further by inhibitory neurons. However, our understanding of intracortical excitatory and inhibitory synaptic inputs in relation to principal excitatory neurons remains incomplete, and it is unclear how local excitatory and inhibitory synaptic connections to excitatory neurons are spatially organized on a layer-by-layer basis. In the present study, we combined whole cell recordings with laser scanning photostimulation via glutamate uncaging to map excitatory and inhibitory synaptic inputs to single excitatory neurons throughout cortical layers 2/3-6 in the mouse primary visual cortex (V1). We find that synaptic input sources of excitatory neurons span the radial columns of laminar microcircuits, and excitatory neurons in different V1 laminae exhibit distinct patterns of layer-specific organization of excitatory inputs. Remarkably, the spatial extent of inhibitory inputs of excitatory neurons for a given layer closely mirrors that of their excitatory input sources, indicating that excitatory and inhibitory synaptic connectivity is spatially balanced across excitatory neuronal networks. Strong interlaminar inhibitory inputs are found, particularly for excitatory neurons in layers 2/3 and 5. This differs from earlier studies reporting that inhibitory cortical connections to excitatory neurons are generally localized within the same cortical layer. On the basis of the functional mapping assays, we conducted a quantitative assessment of both excitatory and inhibitory synaptic laminar connections to excitatory cells at single cell resolution, establishing precise layer-by-layer synaptic wiring diagrams of excitatory neurons in the visual cortex.

Local and Distant Input Controlling Excitation in Layer II of the Medial Entorhinal Cortex

SummaryLayer II (LII) of the medial entorhinal cortex (MEC) comprises grid cells that support spatial navigation. The firing pattern of grid cells might be explained by attractor dynamics in a network, which requires either direct excitatory connectivity between phase-specific grid cells or indirect coupling via interneurons. However, knowledge regarding local networks that support in vivo activity is incomplete. Here we identified essential components of LII networks in the MEC. We distinguished four types of excitatory neurons that exhibit cell-type-specific local excitatory and inhibitory connectivity. Furthermore, we found that LII neurons contribute to the excitation of contralateral neurons in the corresponding layer. Finally, we demonstrated that the medial septum controls excitation in the MEC via two subpopulations of long-range GABAergic neurons that target distinct interneurons in LII, thereby disinhibiting local circuits. We thus identified local connections that could support attractor dynamics and external inputs that likely govern excitation in LII.

Modeling thalamic dynamics with a network of integrate and fire neurons

Spindle oscillations are rhythmic oscillations at 8-14 Hz originated in the thalamus during slow-wave sleep. The generation of this rhythm is due to the rebound bursting properties of thalamo-cortical (TC) relay cells, which are mutually connected with the thalamic reticular neurons (RE). Several experiments have shown that during sleep TC neurons can produce bursts of action potentials due to disinhibition from RE neurons. These bursts in turn trigger an inhibitory rebound in TC neurons thus giving rise to an endogenous oscillatory activity [1,2]. Various sophisticated HH-based models have described in detail the electrophysiological properties of these neurons and replicate most of the experimental observations made in-vivo and in-vitro [2]. However these types of models are computationally very expensive, thus raising the question of whether this dynamical behavior can be reproduced in simpler models. To address this question, we used an adaptive exponential integrate and fire model (aEIF) [3] and studied the conditions under which spindle oscillations appear in large neuronal networks. The aEIF model can reproduce the rebound bursting properties of thalamic cells and has been reported to replicate the self-sustained oscillatory behavior in a minimal 4-neuron circuit [4]. In this minimal motif, RE cells exhibit periodic sequences of bursts at 10 Hz (spindles) and recruit TC neurons, which oscillate in anti-phase at half the frequency (cycle skipping) tightly correlated with IPSP bursts. However, it is unclear whether these spindle oscillations are preserved when the neurons are interconnected in a larger network, while keeping their intrinsic properties. In order to examine this issue, we have systematically extended the size of the network of TC and RE neurons, and checked whether the features of the above-described oscillatory activity hold out. We found the reciprocal interaction between TC and RE to be essential for sustaining this activity, coherently with experimental results [5]. Furthermore, some of the RE neurons exhibit periodic bursting at the spindle frequency, provided they are not connected to TC neurons directly, but only indirectly through local inhibitory connections with RE neighbors. Interestingly, this behavior seems to require that the RE layer has a certain degree of clustering. Under these conditions, a few TC neurons in the network respond with a burst every two cycles (cycle skipping). The fact that most TC do not exhibit cycle skipping could associated with a large strength of GABA IPSPs impinging on them, according to results of HH kinetic models [6]. In summary, our aEIF network model provides a computationally efficient description of the dynamical features of the thalamus while preserving the properties of the individual neurons.

GABAergic and glutamatergic efferents of the mouse ventral tegmental area

The role of dopaminergic (DA) projections from the ventral tegmental area (VTA) in appetitive and rewarding behavior has been widely studied, but the VTA also has documented DA-independent functions. Several drugs of abuse, act on VTA GABAergic neurons, and most studies have focused on local inhibitory connections. Relatively little is known about VTA GABA projection neurons and their connections to brain sites outside the VTA. This study employed viral-vector-mediated cell-type-specific anterograde tracing, classical retrograde tracing, and immunohistochemistry to characterize VTA GABA efferents throughout the brain. We found that VTA GABA neurons project widely to forebrain and brainstem targets, including the ventral pallidum, lateral and magnocellular preoptic nuclei, lateral hypothalamus, and lateral habenula. Minor projections also go to central amygdala, mediodorsal thalamus, dorsal raphe, and deep mesencephalic nuclei, and sparse projections go to prefrontal cortical regions and to nucleus accumbens shell and core. These projections differ from the major VTA DA target regions. Retrograde tracing studies confirmed results from the anterograde experiments and differences in projections from VTA subnuclei. Retrogradely labeled GABA neurons were not numerous, and most non-tyrosine hydroxylase/retrogradely labeled cells lacked GABAergic markers. Many non-TH/retrogradely labeled cells projecting to several areas expressed VGluT2. VTA GABA and glutamate neurons project throughout the brain, most prominently to regions with reciprocal connections to the VTA. These data indicate that VTA GABA and glutamate neurons may have more DA-independent functions than previously recognized.

Measuring predictability of autonomous network transitions into bursting dynamics

Understanding spontaneous transitions between dynamical modes in the neuronal networks is of great importance. For example, such transitions separate pathological and normal function of the brain. In this study, we developed a metric to capture the characteristics of such spontaneous transitions from asynchronous to synchronous dynamics and predict occurrence of these transitions in a simplified neuronal network. In this work we simulate excitatory and excitatory-inhibitory network and in these neuronal networks we examine how inhibition, network topology, noise level, and cellular heterogeneity affect network dynamics. In case of excitatory network, we saw three different types of dynamics depending on its underlying structure: 1) local connectivity leads to long propagating waves of activity, 2) small-world connectivity results in two coexisting phases of short waves of activity and episodes of synchronous activity, and 3) random connectivity pattern that provides synchronous dynamics. When the connectivity pattern is within the small-world region (Pe=0.1-0.2), firing rate is optimum and transitions into and out of the synchronous activity are frequent. Here noise is another factor that can shape dynamics, as our results indicate substantial increase in the noise level can prevent occurring of spontaneous transitions from asynchronous to synchronous dynamics. Then, we investigated how various topologies of inhibitory connectivity affect the network’s spatio-temporal patterning. When the excitatory network has a fixed small world connectivity pattern (Pe=0.15), local inhibitory connectivity pattern significantly suppresses propagating chains of activity, even though the firing rate does not change remarkably. However, when inhibitory cells are connected randomly to other inhibitory and excitatory cells, network dynamics adopts long local traveling chains of activity with low frequency and the synchronous activity of the network was suppressed completely. Interestingly we learned that for a fixed connectivity pattern of excitatory network, when inhibition topology is in small-world region the probability that network goes under synchronous activity is maximized compare to the local and random connectivity pattern. Ultimately, we developed and utilized different measures based on the spike timings to detect early sings of possible transitions into the bursting regime. These measures go through systematic changes prior to the onset of transitions into the bursting that can be interpreted as the early signs of incoming transition and based on that we can obtain a lead-time to predict future transitions. We show that this lead-time is a function of connectivity pattern of excitatory and inhibitory cells, and our predictability is higher when inhibitory neurons have small-world connectivity pattern rather than solely local or random connectivity.

Changes in Effective Connectivity by Propofol Sedation

Mechanisms of propofol-induced loss of consciousness remain poorly understood. Recent fMRI studies have shown decreases in functional connectivity during unconsciousness induced by this anesthetic agent. Functional connectivity does not provide information of directional changes in the dynamics observed during unconsciousness. The aim of the present study was to investigate, in healthy humans during an auditory task, the changes in effective connectivity resulting from propofol induced loss of consciousness. We used Dynamic Causal Modeling for fMRI (fMRI-DCM) to assess how causal connectivity is influenced by the anesthetic agent in the auditory system. Our results suggest that the dynamic observed in the auditory system during unconsciousness induced by propofol, can result in a mixture of two effects: a local inhibitory connectivity increase and a decrease in the effective connectivity in sensory cortices.

Circuits supporting the grid

Two studies show that local inhibitory connectivity and hippocampal excitatory input support the spatial firing patterns of entorhinal grid cells, providing support for continuous attractor model of grid cell firing.

In vivo optogenetic control of striatal and thalamic neurons in non-human primates.

Electrical and pharmacological stimulation methods are commonly used to study neuronal brain circuits in vivo, but are problematic, because electrical stimulation has limited specificity, while pharmacological activation has low temporal resolution. A recently developed alternative to these methods is the use of optogenetic techniques, based on the expression of light sensitive channel proteins in neurons. While optogenetics have been applied in in vitro preparations and in in vivo studies in rodents, their use to study brain function in nonhuman primates has been limited to the cerebral cortex. Here, we characterize the effects of channelrhodopsin-2 (ChR2) transfection in subcortical areas, i.e., the putamen, the external globus pallidus (GPe) and the ventrolateral thalamus (VL) of rhesus monkeys. Lentiviral vectors containing the ChR2 sequence under control of the elongation factor 1α promoter (pLenti-EF1α -hChR2(H134R)-eYFP-WPRE, titer 109 particles/ml) were deposited in GPe, putamen and VL. Four weeks later, a probe combining a conventional electrode and an optic fiber was introduced in the previously injected brain areas. We found light-evoked responses in 31.5% and 32.7% of all recorded neurons in the striatum and thalamus, respectively, but only in 2.5% of recorded GPe neurons. As expected, most responses were time-locked increases in firing, but decreases or mixed responses were also seen, presumably via ChR2-mediated activation of local inhibitory connections. Light and electron microscopic analyses revealed robust expression of ChR2 on the plasma membrane of cell somas, dendrites, spines and terminals in the striatum and VL. This study demonstrates that optogenetic experiments targeting the striatum and basal ganglia-related thalamic nuclei can be successfully achieved in monkeys. Our results indicate important differences of the type and magnitude of responses in each structure. Experimental conditions such as the vector used, the number and rate of injections, or the light stimulation conditions have to be optimized for each structure studied.

Sensory versus motor loci for integration of multiple motion signals in smooth pursuit eye movements and human motion perception

We have investigated how visual motion signals are integrated for smooth pursuit eye movements by measuring the initiation of pursuit in monkeys for pairs of moving stimuli of the same or differing luminance. The initiation of pursuit for pairs of stimuli of the same luminance could be accounted for as a vector average of the responses to the two stimuli singly. When stimuli comprised two superimposed patches of moving dot textures, the brighter stimulus suppressed the inputs from the dimmer stimulus, so that the initiation of pursuit became winner-take-all when the luminance ratio of the two stimuli was 8 or greater. The dominance of the brighter stimulus could be not attributed to either the latency difference or the ratio of the eye accelerations for the bright and dim stimuli presented singly. When stimuli comprised either spot targets or two patches of dots moving across separate locations in the visual field, the brighter stimulus had a much weaker suppressive influence; the initiation of pursuit could be accounted for by nearly equal vector averaging of the responses to the two stimuli singly. The suppressive effects of the brighter stimulus also appeared in human perceptual judgments, but again only for superimposed stimuli. We conclude that one locus of the interaction of two moving visual stimuli is shared by perception and action and resides in local inhibitory connections in the visual cortex. A second locus resides deeper in sensory-motor processing and may be more closely related to action selection than to stimulus selection.

Dense Inhibitory Connectivity in Neocortex

The connectivity diagram of neocortical circuits is still unknown, and there are conflicting data as to whether cortical neurons are wired specifically or not. To investigate the basic structure of cortical microcircuits, we use a two-photon photostimulation technique that enables the systematic mapping of synaptic connections with single-cell resolution. We map the inhibitory connectivity between upper layers somatostatin-positive GABAergic interneurons and pyramidal cells in mouse frontal cortex. Most, and sometimes all, inhibitory neurons are locally connected to every sampled pyramidal cell. This dense inhibitory connectivity is found at both young and mature developmental ages. Inhibitory innervation of neighboring pyramidal cells is similar, regardless of whether they are connected among themselves or not. We conclude that local inhibitory connectivity is promiscuous, does not form subnetworks, and can approach the theoretical limit of a completely connected synaptic matrix.