Distribution Of Synaptic Inputs Research Articles

Inhibiting presynaptic calcium channel motility in the auditory cortex suppresses synchronized input processing.

The emergent coherent population activity from thousands of stochastic neurons in the brain is believed to constitute a key neuronal mechanism for salient processing of external stimuli and its link to internal states like attention and perception. In the sensory cortex, functional cell assemblies are formed by recurrent excitation and inhibitory influences. The stochastic dynamics of each cell involved is largely orchestrated by presynaptic CAV2.1 voltage-gated calcium channels (VGCCs). Cav2.1 VGCCs initiate the release of neurotransmitters from the presynaptic compartment and are therefore able to add variability into synaptic transmission which can be partly explained by their mobile organization around docked vesicles. To investigate the relevance of Cav2.1 channel surface motility for the input processing in the primary auditory cortex (A1) in vivo, we make use of a new optogenetic system which allows for acute, reversable cross-linking Cav2.1 VGCCs via a photo-cross-linkable cryptochrome mutant, CRY2olig. In order to map neuronal activity across all cortical layers of the A1, we performed laminar current-source density (CSD) recordings with varying auditory stimulus sets in transgenic mice with a citrine tag on the N-terminus of the VGCCs. Clustering VGCCs suppresses overall sensory-evoked population activity, particularly when stimuli lead to a highly synchronized distribution of synaptic inputs. Our findings reveal the importance of membrane dynamics of presynaptic calcium channels for sensory encoding by dynamically adjusting network activity across a wide range of synaptic input strength.

Cellular and Molecular Analysis of Dendritic Morphogenesis in a Retinal Cell Type That Senses Color Contrast and Ventral Motion.

As neuronal dendrites develop, they acquire cell-type-specific features including characteristic size, shape, arborization, location and synaptic patterns. These features, in turn, are major determinants of type-specific neuronal function. Because neuronal diversity complicates the task of relating developmental programs to adult structure and function, we analyzed dendritic morphogenesis in a single retinal ganglion cell (RGC) type in mouse called J-RGC. We documented the emergence of five dendritic features that underlie J-RGC physiology: (1) dendritic field size, which approximate receptive field size; (2) dendritic complexity, which affects how J-RGCs sample space; (3) asymmetry, which contributes to direction-selectivity; (4) restricted lamination within the inner plexiform layer (IPL), which renders J-RGCs responsive to light decrements; and (5) distribution of synaptic inputs, which generate a color-opponent receptive field. We found dendritic growth in J-RGCs is accompanied by a refinement in dendritic self-crossing. Asymmetry arises by a combination of selective pruning and elaboration, whereas laminar restriction results from biased outgrowth toward the outermost IPL. Interestingly, asymmetry develops in a protracted dorsoventral wave, whereas lamination does so in a rapid centrifugal wave. As arbors mature, they acquire excitatory and inhibitory synapses, with the latter forming first and being concentrated in proximal dendrites. Thus, distinct mechanisms operate in different spatiotemporal dimensions of J-RGC dendritic patterning to generate the substrate for specific patterns of synaptogenesis. Finally, we asked whether the defining molecular signature of J-RGCs, the adhesion molecule JAM-B, regulates morphogenesis, and showed that it promotes dendro-dendritic interactions. Our results reveal multiple mechanisms that shape a dendritic arbor.SIGNIFICANCE STATEMENT Visual perception begins in the retina, where distinct types of retinal ganglion cells (RGCs) are tuned to specific visual features such as direction of motion. The features to which each RGC type responds are determined largely by the number and type of synaptic inputs it receives, and these, in turn, are greatly influenced by the size, shape, arborization pattern, and location of its dendrites. We analyzed dendritic morphogenesis in a functionally characterized RGC type, the J-RGC, demonstrating distinct mechanisms that operate in different dimensions to generate the dendritic scaffold and synaptic patterns for feature detection. Our work elucidates cellular and molecular mechanisms that shape dendritic arbors and synaptic distribution, enabling J-RGC connectivity and thus, function.

Patterns and distribution of presynaptic and postsynaptic elements within serial electron microscopic reconstructions of neuronal arbors from the medicinal leech Hirudo verbana.

Microscale connectomics involves the large-scale acquisition of high-resolution serial electron micrographs from which neuronal arbors can be reconstructed and synapses can be detected. In addition to connectivity information, these data sets are also rich with structural information, including vesicle types, number of postsynaptic partners at a given presynaptic site, and spatial distribution of synaptic inputs and outputs. This study uses serial block-face scanning electron microscopy (EM) to collect two volumes of serial EM data from ganglia of the medicinal leech. For the first volume, we sampled a small fraction of the neuropil belonging to an adult ganglion. From this data set we measured the proportion of arbors that contained vesicles and the types of vesicles contained and developed criteria to identify synapses and to measure the number of apparent postsynaptic partners in apposition to presynaptic boutons. For the second data set, we sampled an entire juvenile ganglion, which included the somata and arbors of all the neurons. We used this data set to placd our findings from mature tissue in the context of fully reconstructed arbors and to explore the spatial distribution of synaptic inputs and outputs on these arbors. We observed that some neurons segregated their arbors into input only and mixed input/output zones, that other neurons contained exclusively mixed input/output zones, and that still others contained only input zones. These results provide the groundwork for future behavioral studies. J. Comp. Neurol. 524:3677-3695, 2016. © 2016 Wiley Periodicals, Inc.

Patterns and Distribution of Presynaptic and Postsynaptic Elements Within Serial Electron Microscopic Reconstructions of Neuronal Arbors From the Medicinal Leech Hirudo verbana

ABSTRACTMicroscale connectomics involves the large‐scale acquisition of high‐resolution serial electron micrographs from which neuronal arbors can be reconstructed and synapses can be detected. In addition to connectivity information, these data sets are also rich with structural information, including vesicle types, number of postsynaptic partners at a given presynaptic site, and spatial distribution of synaptic inputs and outputs. This study uses serial block‐face scanning electron microscopy (EM) to collect two volumes of serial EM data from ganglia of the medicinal leech. For the first volume, we sampled a small fraction of the neuropil belonging to an adult ganglion. From this data set we measured the proportion of arbors that contained vesicles and the types of vesicles contained and developed criteria to identify synapses and to measure the number of apparent postsynaptic partners in apposition to presynaptic boutons. For the second data set, we sampled an entire juvenile ganglion, which included the somata and arbors of all the neurons. We used this data set to placd our findings from mature tissue in the context of fully reconstructed arbors and to explore the spatial distribution of synaptic inputs and outputs on these arbors. We observed that some neurons segregated their arbors into input only and mixed input/output zones, that other neurons contained exclusively mixed input/output zones, and that still others contained only input zones. These results provide the groundwork for future behavioral studies. J. Comp. Neurol. 524:1–1, 2016. © 2016 Wiley Periodicals, Inc.

Changes in ganglion cells during retinal degeneration

Inherited retinal degeneration such as retinitis pigmentosa (RP) is associated with photoreceptor loss and concomitant morphological and functional changes in the inner retina. It is not known whether these changes are associated with changes in the density and distribution of synaptic inputs to retinal ganglion cells (RGCs). We quantified changes in ganglion cell density in rd1 and age-matched C57BL/6J-(wildtype, WT) mice using the immunocytochemical marker, RBPMS. Our data revealed that following complete loss of photoreceptors, (∼3months of age), there was a reduction in ganglion cell density in the peripheral retina. We next examined changes in synaptic inputs to A type ganglion cells by performing double labeling experiments in mice with the ganglion cell reporter lines, rd1-Thy1 and age-matched wildtype-Thy1. Ribbon synapses were identified by co-labelling with CtBP2 (RIBEYE) and conventional synapses with the clustering molecule, gephyrin. ON RGCs showed a significant reduction in RIBEYE-immunoreactive synapse density while OFF RGCs showed a significant reduction in the gephyrin-immmunoreactive synapse density. Distribution patterns of both synaptic markers across the dendritic trees of RGCs were unchanged. The change in synaptic inputs to RGCs was associated with a reduction in the number of immunolabeled rod bipolar and ON cone bipolar cells. These results suggest that functional changes reported in ganglion cells during retinal degeneration could be attributed to loss of synaptic inputs.

A Role for Synaptic Input Distribution in a Dendritic Computation of Motion Direction in the Retina

The starburst amacrine cell in the mouse retina presents an opportunity to examine the precise role of sensory input location on neuronal computations. Using visual receptive field mapping, glutamate uncaging, two-photon Ca(2+) imaging, and genetic labeling of putative synapses, we identify a unique arrangement of excitatory inputs and neurotransmitter release sites on starburst amacrine cell dendrites: the excitatory input distribution is skewed away from the release sites. By comparing computational simulations with Ca(2+) transients recorded near release sites, we show that this anatomical arrangement of inputs and outputs supports a dendritic mechanism for computing motion direction. Direction-selective Ca(2+) transients persist in the presence of a GABA-A receptor antagonist, though the directional tuning is reduced. These results indicate a synergistic interaction between dendritic and circuit mechanisms for generating direction selectivity in the starburst amacrine cell.

Dendritic distribution of synaptic input creates a trade-off between input selectivity and flexibility

Information processing by cortical pyramidal neurons is shaped by the spatial distribution of synapses across the dendrites. A prominent hypothesis is that synapses with similar selectivities cluster on dendritic branches. This enables cooperative interactions between neighboring synapses through activation of voltage-dependent membrane currents, and helps establish independent integrative subunits, thereby expanding the computational power of a single neuron [1]. Some recent in vivo recordings argue against this hypothesis, suggesting that inputs that share the same stimulus selectivity are randomly distributed throughout the dendritic tree (e.g., [2]). Other studies seem to support clustered configurations of input selectivities, showing for example that the activity of a synaptic input is more strongly correlated with its neighbors than with more distant inputs [3]. One fundamental feature of the nervous system that has received little attention in this ongoing discussion is learning; specifically, how is the ability to change a neuron's selectivity (i.e., its flexibility) affected by the spatial distribution of synapses? This is highly relevant because the selectivity of many cortical pyramidal neurons is subject to ongoing modification, not only during development, but throughout adulthood (e.g., [4]). Here, we show that the distribution of synapses across active dendrites shapes both the stimulus selectivity of the neuron, as well as the flexibility of the neuron's selectivity. Using cable theoretic analysis and numerical simulations of detailed neuron models we show that synapses that are randomly distributed across the dendrites allow for a modest stimulus selectivity that can be flexibly modified through synaptic plasticity. In contrast, a clustered distribution of synapses that encode the same stimulus allows for very strong stimulus selectivity, however, it hinders adjustment of this selectivity through synaptic plasticity, which requires slow and metabolically costly rearrangement of synaptic projections. Hence, the distribution of synapses across active dendrites creates a trade-off between selectivity and plasticity. We suggest that pyramidal neurons with different functions in the cortical information processing hierarchy exploit different ends of this spectrum.

Estimating reflex responses in large populations of motor units by decomposition of the high-density surface electromyogram.

Reflex responses of single motor units have been used for the study of spinal circuitries but the methods employed are invasive and limited to the assessment of a relatively small number of motor units. We propose a new approach to investigate reflexes on individual motor units based on high-density surface electromyography (HDsEMG) decomposition. The decomposition of HDsEMG has been previously validated in voluntary isometric contractions but never during reflex activities. The use of HDsEMG decomposition for reflex studies at the individual motor unit level, during constant force contractions, with excitatory and inhibitory stimuli, was validated here by the comparison of results with concurrently recorded intramuscular EMG signals. The validation results showed that HDsEMG decomposition allows an accurate quantification of reflex responses for a large number of individual motor units non-invasively, for both excitatory and inhibitory stimuli. We propose and validate a non-invasive method that enables accurate detection of the discharge times of a relatively large number of motor units during excitatory and inhibitory reflex stimulations. High-density surface electromyography (HDsEMG) and intramuscular EMG (iEMG) were recorded from the tibialis anterior muscle during ankle dorsiflexions performed at 5%, 10% and 20% of the maximum voluntary contraction (MVC) force, in nine healthy subjects. The tibial nerve (inhibitory reflex) and the peroneal nerve (excitatory reflex) were stimulated with constant current stimuli. In total, 416 motor units were identified from the automatic decomposition of the HDsEMG. The iEMG was decomposed using a state-of-the-art decomposition tool and provided 84 motor units (average of two recording sites). The reflex responses of the detected motor units were analysed using the peri-stimulus time histogram (PSTH) and the peri-stimulus frequencygram (PSF). The reflex responses of the common motor units identified concurrently from the HDsEMG and the iEMG signals showed an average disagreement (the difference between number of observed spikes in each bin relative to the mean) of 8.2±2.2% (5% MVC), 6.8±1.0% (10% MVC) and 7.5±2.2% (20% MVC), for reflex inhibition, and 6.5±4.1%, 12.0±1.8% and 13.9±2.4%, for reflex excitation. There was no significant difference between the characteristics of the reflex responses, such as latency, amplitude and duration, for the motor units identified by both techniques. Finally, reflex responses could be identified at higher force (4 of the 9 subjects performed contraction up to 50% MVC) using HDsEMG but not iEMG, because of the difficulty in decomposing the iEMG at high forces. In conclusion, single motor unit reflex responses can be estimated accurately and non-invasively in relatively large populations of motor units using HDsEMG. This non-invasive approach may enable a more thorough investigation of the synaptic input distribution on active motor units at various force levels.

Contribution of sublinear and supralinear dendritic integration to neuronal computations.

Nonlinear dendritic integration is thought to increase the computational ability of neurons. Most studies focus on how supralinear summation of excitatory synaptic responses arising from clustered inputs within single dendrites result in the enhancement of neuronal firing, enabling simple computations such as feature detection. Recent reports have shown that sublinear summation is also a prominent dendritic operation, extending the range of subthreshold input-output (sI/O) transformations conferred by dendrites. Like supralinear operations, sublinear dendritic operations also increase the repertoire of neuronal computations, but feature extraction requires different synaptic connectivity strategies for each of these operations. In this article we will review the experimental and theoretical findings describing the biophysical determinants of the three primary classes of dendritic operations: linear, sublinear, and supralinear. We then review a Boolean algebra-based analysis of simplified neuron models, which provides insight into how dendritic operations influence neuronal computations. We highlight how neuronal computations are critically dependent on the interplay of dendritic properties (morphology and voltage-gated channel expression), spiking threshold and distribution of synaptic inputs carrying particular sensory features. Finally, we describe how global (scattered) and local (clustered) integration strategies permit the implementation of similar classes of computations, one example being the object feature binding problem.

Subpopulation‐specific patterns of intrinsic connectivity in mouse superficial dorsal horn as revealed by laser scanning photostimulation

The primary goal of this study was to map the transverse distribution of local excitatory and inhibitory synaptic inputs to mouse lamina I spinal dorsal horn neurons, using laser scanning photostimulation. A sample of lamina II neurons was also studied for comparison. Lamina I neurons received excitatory synaptic input from both laminae I-II and the outer part of III-IV, especially the II/III border region, while the inhibitory input zones were mostly confined within I-II. The excitatory synaptic input zones showed a pronounced medial asymmetry, which was correlated with a matching asymmetry in the dendritic fields of the neurons. Inhibitory input from laminae III-IV was found in a subpopulation of neurons occupying a highly restricted zone, essentially one cell layer thick, immediately below the lamina I/II border, with morphological and physiological properties that were distinct from other laminar populations in the superficial dorsal horn, and that suggest a critical role in interlaminar communication. This subpopulation also received excitatory input from laminae III-IV. Within this subpopulation, inhibitory III-IV input was correlated with the presence of long ventral dendrites. Correlations between the distribution of synaptic input zones and dendritic fields support the concept that interlaminar communication is mediated in part via contacts made onto ventrally extending dendrites of superficial laminae neurons. The results point to the presence of cell type specificity in dorsal horn circuitry, and show how the study of connectivity can itself help identify previously unrecognized neuronal populations.

Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian mixture Kalman filtering

Time-varying excitatory and inhibitory synaptic inputs govern activity of neurons and process information in the brain. The importance of trial-to-trial fluctuations of synaptic inputs has recently been investigated in neuroscience. Such fluctuations are ignored in the most conventional techniques because they are removed when trials are averaged during linear regression techniques. Here, we propose a novel recursive algorithm based on Gaussian mixture Kalman filtering (GMKF) for estimating time-varying excitatory and inhibitory synaptic inputs from single trials of noisy membrane potential in current clamp recordings. The KF is followed by an expectation maximization (EM) algorithm to infer the statistical parameters (time-varying mean and variance) of the synaptic inputs in a non-parametric manner. As our proposed algorithm is repeated recursively, the inferred parameters of the mixtures are used to initiate the next iteration. Unlike other recent algorithms, our algorithm does not assume an a priori distribution from which the synaptic inputs are generated. Instead, the algorithm recursively estimates such a distribution by fitting a Gaussian mixture model (GMM). The performance of the proposed algorithms is compared to a previously proposed PF-based algorithm (Paninski et al., 2012) with several illustrative examples, assuming that the distribution of synaptic input is unknown. If noise is small, the performance of our algorithms is similar to that of the previous one. However, if noise is large, they can significantly outperform the previous proposal. These promising results suggest that our algorithm is a robust and efficient technique for estimating time varying excitatory and inhibitory synaptic conductances from single trials of membrane potential recordings.

Compound group I excitatory input is differentially distributed to human soleus motoneurons

ObjectiveWe studied whether the distribution of synaptic input from compound group I afferents onto the various-sized motoneurons in the human soleus muscle supports the size principle. MethodsThe subject lay prone on a physiotherapy table and electrical stimuli were delivered to the tibial nerve. The recordings were taken with surface electromyography (SEMG) and single motor unit (SMU) potentials. The relative sizes of SMUs were estimated using four different methods. After identifying the relative size of each SMU of the pair, normalised size of the H-reflex was determined using the extra spike per trigger (ESPT) method. ResultsIn total 33 SMU pairs were studied to compare results obtained in each pair. It was found that, although the stimulus intensity was identical for each pair, the ESPT values were statistically larger in the bigger SMUs compared with the relatively smaller SMUs (p<0.05). ConclusionsWe conclude that, within the limits of this study, compound group I excitatory input to soleus motoneurons in human subjects does not support the size principle which governs the recruitment order of motoneurons in the reduced animal preparations. SignificanceThis study illustrates the importance of performing human experiments to confirm or reject principles obtained using reduced animal preparations.

Localization of presynaptic inputs on dendrites of individually labeled neurons in three dimensional space using a center distance algorithm

The spatial distribution of synaptic inputs on the dendritic tree of a neuron can have significant influence on neuronal function. Consequently, accurate anatomical reconstructions of neuron morphology and synaptic localization are critical when modeling and predicting physiological responses of individual neurons. Historically, generation of three-dimensional (3D) neuronal reconstructions together with comprehensive mapping of synaptic inputs has been an extensive task requiring manual identification of putative synaptic contacts directly from tissue samples or digital images. Recent developments in neuronal tracing software applications have improved the speed and accuracy of 3D reconstructions, but localization of synaptic sites through the use of pre- and/or post-synaptic markers has remained largely a manual process. To address this problem, we have developed an algorithm, based on 3D distance measurements between putative pre-synaptic terminals and the post-synaptic dendrite, to automate synaptic contact detection on dendrites of individually labeled neurons from 3D immunofluorescence image sets. In this study, the algorithm is implemented with custom routines in Matlab, and its effectiveness is evaluated through analysis of primary sensory afferent terminals on motor neurons. Optimization of algorithm parameters enabled automated identification of synaptic contacts that matched those identified by manual inspection with low incidence of error. Substantial time savings and the elimination of variability in contact detection introduced by different users are significant advantages of this method.

The subcellular organization of neocortical excitatory connections.

Understanding cortical circuits will require mapping the connections between specific populations of neurons, as well as determining the dendritic locations where the synapses occur. The dendrites of individual cortical neurons overlap with numerous types of local and long-range excitatory axons, but axodendritic overlap is not always a good predictor of actual connection strength. Here we developed an efficient channelrhodopsin-2 (ChR2)-assisted method to map the spatial distribution of synaptic inputs, defined by presynaptic ChR2 expression, within the dendritic arborizations of recorded neurons. We expressed ChR2 in two thalamic nuclei, the whisker motor cortex and local excitatory neurons and mapped their synapses with pyramidal neurons in layers 3, 5A and 5B (L3, L5A and L5B) in the mouse barrel cortex. Within the dendritic arborizations of L3 cells, individual inputs impinged onto distinct single domains. These domains were arrayed in an orderly, monotonic pattern along the apical axis: axons from more central origins targeted progressively higher regions of the apical dendrites. In L5 arborizations, different inputs targeted separate basal and apical domains. Input to L3 and L5 dendrites in L1 was related to whisker movement and position, suggesting that these signals have a role in controlling the gain of their target neurons. Our experiments reveal high specificity in the subcellular organization of excitatory circuits.

Contacts among non-sister dendritic branches at bifurcations shape neighboring dendrites and pattern their synaptic inputs

The size and shape of neuronal dendritic arbors affect the number and pattern of synaptic inputs, as well as the complexity and function of brain circuits. However, the means by which different dendritic arbors take their final shape and how these shapes are associated with distinct synaptic patterns is still largely unknown. Dendritic ramification is influenced by dendrite-dendrite interactions that stabilize specific branching directions and ensure appropriate synaptic contacts. Yet, it is not clear by which mechanism these contacts are allocated. We found that stable dendro-dendritic contacts occur preferentially between non-sister dendritic branches at sites of bifurcations, and that this process is promoted by synaptic activity. Moreover, these contacts are associated with synaptic connections of higher density, higher level of synaptophysin, NR1, GluR2 subunits of glutamate receptors and elevated secretion capability than synaptic connections found on contacts made by non-bifurcating branches or along non-contacting parts of the dendrites. Thus, in cultured neurons, stabilization of hetero-neuronal dendro-dendritic contacts at bifurcations is a new mean to pattern and associate morphogenesis and synaptic input distribution in neighboring dendritic trees.

Common input to different regions of biceps brachii long head

The purpose of the experiment was to compare the level of synchronization exhibited by pairs of motor units located within and between functionally distinct regions of the biceps brachii muscle. Pairs of single motor units were recorded from seven subjects using separate electrodes located in the lateral and medial aspects of the long head of biceps brachii. Participants were required to exert a combination of flexion and supination torques so that both motor units discharged at approximately 10 pps for >/=200 s and the level of motor unit synchronization could be quantified. When motor unit recordings were sufficiently stable at the completion of this synchrony task, a series of ramp contractions with multiple combinations of flexion and supination torques were performed to characterize the recruitment thresholds of the motor units. Common input strength (CIS) was significantly greater (P < 0.01) for the within-region pairs of motor units (0.28 extra sync. imps/s, n = 26) than for the between-region pairs (0.13 extra sync. imps/s, n = 18), but did not differ significantly for the 12 within-region pairs from the lateral head and 14 from the medial head (0.27 vs. 0.29 extra sync. imps/s; P = 0.83). Recruitment thresholds were measured for 33 motor units, but there was only a weak association between CIS and the respective recruitment patterns for motor unit pairs (n = 9). The present investigation provides evidence of a differential distribution of synaptic input across the biceps brachii motor neuron pool, but this appears to have minimal association with the recruitment patterns for individual motor units.

Sexual Dimorphism in the Hoverfly Motion Vision Pathway

Many insects perform high-speed aerial maneuvers in which they navigate through visually complex surrounds. Among insects, hoverflies stand out, with males switching from stationary hovering to high-speed pursuit at extreme angular velocities [1]. In dipterans, 50-60 large interneurons -- the lobula-plate tangential cells (LPTCs) -- detect changes in optic flow experienced during flight [2-5]. It has been predicted that large LPTC receptive fields are a requirement of accurate "matched filters" of optic flow [6]. Whereas many fly taxa have three horizontal system (HS) LPTC neurons in each hemisphere, hoverflies have four [7], possibly reflecting the more sophisticated flight behavior. We here show that the most dorsal hoverfly neuron (HS north [HSN]) is sexually dimorphic, with the male receptive field substantially smaller than in females or in either sex of blowflies. The (hoverfly-specific) HSN equatorial (HSNE) is, however, sexually isomorphic. Using complex optic flow, we show that HSN, despite its smaller receptive field, codes yaw velocity as well as HSNE. Responses to a target moving against a plain or textured background suggest that the male HSN could potentially play a role in target pursuit under some conditions.

Distribution of bipolar input to midget and parasol ganglion cells in marmoset retina

Different types of retinal ganglion cell show differences in their response properties. Here we investigated the question of whether these differences are related to the distribution of the synaptic input to the dendritic tree. We measured the distribution and density of synaptic input to the dendrites of midget and parasol ganglion cells in the retina of a New World monkey, the marmoset, Callithrix jacchus. Ganglion cells were retrogradely labeled by dye injection into parvocellular or magnocellular regions of the lateral geniculate nucleus and subsequently photo-filled. Presumed bipolar cell synapses were identified immunocytochemically using antibodies against the ribbon protein CtBP2 or the GluR4 subunit of the AMPA receptor. For all cells, colocalized immunoreactive puncta were distributed across the entire dendritic tree. The density of the presumed bipolar input to midget ganglion cells was comparable for both synaptic markers, suggesting that the AMPA receptor GluR4 subunit is expressed at all synapses between midget bipolar and midget ganglion cells. Midget ganglion cells had an average of nine colocalized immunoreactive puncta per 100 microm2 dendritic surface, and parasol cells had an average of seven colocalized immunoreactive puncta per 100 microm2 dendritic surface. The densities were comparable in different regions of the dendritic tree and were not influenced by the location of the cells with respect to the fovea. Our findings suggest that the differences in the response characteristics of midget and parasol cells are not due to differences in the density of synaptic input to their dendritic tree.

Differential activation of regions within the biceps brachii muscle during fatigue

To examine the occurrence of repeated differential activation between the heads of the biceps brachii muscle and its relation to fatigue prevention during a submaximal contraction. Thirty-nine subjects carried out an isometric contraction of elbow flexion at 25% of maximal voluntary contraction (MVC) until exhaustion. A grid of 13 by 10 electrodes was used to record surface electromyographic signals from both heads of the biceps brachii. The root-mean-square of signals recorded from electrodes located medially and laterally was used to analyse activation differences. Differential activation was defined as periods of 33% different activation level between the two heads of the biceps brachii muscle. Differential muscle activation was demonstrated in 30 of 33 subjects with appropriate data quality. The frequency of differential activation increased from 4.9 to 6.6 min(-1) at the end of the contractions with no change in duration of the differential activations (about 1.4 s). Moreover, the frequency of differential activation was, in general, negatively correlated with time to exhaustion. The observed differential activation between the heads of the biceps brachii can be explained by an uneven distribution of synaptic input to the motor neurone pool. The findings of this study indicate that differential activation of regions within a muscle does not prevent fatigue at a contraction level of 25% of MVC.

Timing and Location of Synaptic Inputs Determine Modes of Subthreshold Integration in Striatal Medium Spiny Neurons

Medium spiny neurons (MSNs) are the principal cells of the striatum and perform a central role in sensorimotor processing. MSNs must integrate many excitatory inputs located across their dendrites to fire action potentials and enable striatal function. However, the dependence of synaptic responses on the temporal and spatial distribution of these inputs remains unknown. Here, we use whole-cell recordings, two-photon microscopy, and two-photon glutamate uncaging to examine subthreshold synaptic integration in MSNs from acute rat brain slices. We find that synaptic responses can summate sublinearly, linearly, or supralinearly depending on the spatiotemporal pattern of activity. Repetitive activity at single inputs leads to sublinear summation, reflecting long-lived AMPA receptor desensitization. In contrast, asynchronous activity at multiple inputs generates linear summation, with synapses on neighboring spines functioning independently. Finally, synchronous activity at multiple inputs triggers supralinear summation at depolarized potentials, reflecting activation of NMDA receptors and L-type calcium channels. Thus, the properties of subthreshold integration in MSNs are determined by the distribution of synaptic inputs and the differential activation of multiple postsynaptic conductances.