Exact Analysis of the Subthreshold Variability for Conductance-Based Neuronal Models with Synchronous Synaptic Inputs.

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state, neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically, we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects postspiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime yields realistic subthreshold variability (voltage variance ≃4-9 mV2) only when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that, without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

Clinically Translatable Solid-State Dye for NIR-II Imaging of Medical Devices.

Medical devices are commonly implanted underneath the skin, but how to real-time noninvasively monitor their migration, integrity, and biodegradation in human body is still a formidable challenge. Here, the study demonstrates that benzyl violet 4B (BV-4B), a main component in the FDA-approved surgical suture, is found to produce fluorescence signal in the first near-infrared window (NIR-I, 700-900 nm) in polar solutions, whereas BV-4B self-assembles into highly crystalline aggregates upon a formation of ultrasmall nanodots and can emit strong fluorescence in the second near-infrared window (NIR-II, 1000-1700 nm) with a dramatic bathochromic shift in the absorption spectrum of ≈200 nm. Intriguingly, BV-4B-involved suture knots underneath the skin can be facilely monitored during the whole degradation process in vivo, and the rupture of the customized BV-4B-coated silicone catheter is noninvasively diagnosed by NIR-II imaging. Furthermore, BV-4B suspended in embolization glue achieves hybrid fluorescence-guided surgery (hybrid FGS) for arteriovenous malformation. As a proof-of-concept study, the solid-state BV-4B is successfully used for NIR-II imaging of surgical sutures in operations of patients. Overall, as a clinically translatable solid-state dye, BV-4B can be applied for in vivo monitoring the fate of medical devices by NIR-II imaging.

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs.

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≅ 4-9mV 2 ) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs.

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≃4-9mV2) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

In vivo evaluation of integrin αvß6-targeting peptide in NSCLC and brain metastasis.

Introduction: Integrin αvß6, which is upregulated in malignancies and remains absent or weak in normal tissue, is a promising target in molecular imaging therapeutics. In vivo imaging of integrin αvß6 could therefore be valuable for early tumor detection and intraoperative guidance. Methods: In this study, integrin αvß6-targeting probe G2-SFLAP3 was labeled with near-infrared (NIR) dye Cy5.5 or radioisotope 68Ga. The resulting probes were evaluated in integrin αvß6-positive A549 and αvß6-negative H1703 xenograft mice models. Results: The cellar uptake of G2-SFLAP3-Cy5.5 was consistent with the expression of integrin αvß6. Both subcutaneous and brain metastatic A549 tumors could be clearly visualized by NIR fluorescent imaging of G2-SFLAP3-Cy5.5. A549 tumors demonstrated the highest G2-SFLAP3-Cy5.5 accumulation at 4h post-injection (p.i.) and remain detectable at 84h p.i. The fluorescent signal of G2-SFLAP3-Cy5.5 was significantly reduced in H1703 and A549-blocking groups. Consistently, small-animal PET imaging showed tumor-specific accumulation of 68Ga-DOTA-G2-SFLAP3. Discussion: G2-SFLAP3 represents a promising agent for noninvasive imaging of non-small cell lung cancer (NSCLC) and brain metastases.

Voltage-Gated Intrinsic Conductances Shape the Input-Output Relationship of Cortical Neurons in Behaving Primate V1.

Neurons are input-output (I/O) devices-they receive synaptic inputs from other neurons, integrate those inputs with their intrinsic properties, and generate action potentials as outputs. To understand this fundamental process, we studied the interaction between synaptic inputs and intrinsic properties using whole-cell recordings from V1 neurons of awake, fixating macaque monkeys. Our measurements during spontaneous activity and visual stimulation reveal an intrinsic voltage-gated conductance that profoundly alters the integrative properties and visual responses of cortical neurons. This voltage-gated conductance increases neuronal gain and selectivity with subthreshold depolarization and linearizes the relationship between synaptic input and neural output. This intrinsic conductance is found in layer 2/3 V1 neurons of awake macaques, anesthetized mice, and acute brain slices. These results demonstrate that intrinsic conductances play an essential role in shaping the I/O relationship of cortical neurons and must be taken into account in future models of cortical computations.

Neural-metabolic coupling in the central visual pathway.

Studies are described which are intended to improve our understanding of the primary measurements made in non-invasive neural imaging. The blood oxygenation level-dependent signal used in functional magnetic resonance imaging (fMRI) reflects changes in deoxygenated haemoglobin. Tissue oxygen concentration, along with blood flow, changes during neural activation. Therefore, measurements of tissue oxygen together with the use of a neural sensor can provide direct estimates of neural-metabolic interactions. We have used this relationship in a series of studies in which a neural microelectrode is combined with an oxygen micro-sensor to make simultaneous co-localized measurements in the central visual pathway. Oxygen responses are typically biphasic with small initial dips followed by large secondary peaks during neural activation. By the use of established visual response characteristics, we have determined that the oxygen initial dip provides a better estimate of local neural function than the positive peak. This contrasts sharply with fMRI for which the initial dip is unreliable. To extend these studies, we have examined the relationship between the primary metabolic agents, glucose and lactate, and associated neural activity. For this work, we also use a Doppler technique to measure cerebral blood flow (CBF) together with neural activity. Results show consistent synchronously timed changes such that increases in neural activity are accompanied by decreases in glucose and simultaneous increases in lactate. Measurements of CBF show clear delays with respect to neural response. This is consistent with a slight delay in blood flow with respect to oxygen delivery during neural activation.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

Neurometabolic coupling between neural activity, glucose, and lactate in activated visual cortex.

Neural activity is closely coupled with energy metabolism but details of the association remain to be identified. One basic area involves the relationships between neural activity and the main supportive substrates of glucose and lactate. This is of fundamental significance for the interpretation of non-invasive neural imaging. Here, we use microelectrodes with high spatial and temporal resolution to determine simultaneous co-localized changes in glucose, lactate, and neural activity during visual activation of the cerebral cortex in the cat. Tissue glucose and lactate concentration levels are measured with electrochemical microelectrodes while neural spiking activity and local field potentials are sampled by a microelectrode. These measurements are performed simultaneously while neurons are activated by visual stimuli of different contrast levels, orientations, and sizes. We find immediate decreases in tissue glucose concentration and simultaneous increases in lactate during neural activation. Both glucose and lactate signals return to their baseline levels instantly as neurons cease firing. No sustained changes or initial dips in glucose or lactate signals are elicited by visual stimulation. However, co-localized measurements of cerebral blood flow and neural activity demonstrate a clear delay in the cerebral blood flow signal such that it does not correlate temporally with the neural response. These results provide direct real-time evidence regarding the coupling between co-localized energy metabolism and neural activity during physiological stimulation. They are also relevant to a current question regarding the role of lactate in energy metabolism in the brain during neural activation. Dynamic changes in energy metabolites can be measured directly with high spatial and temporal resolution by use of enzyme-based microelectrodes. Here, to examine neuro-metabolic coupling during brain activation, we use combined microelectrodes to simultaneously measure extracellular glucose, lactate, and neural responses in the primary visual cortex to visual stimulation. We demonstrate rapid decreases in glucose and increases in lactate during neural activation. Changes in glucose and lactate signals are transient and closely coupled with neuronal firing.

Neurometabolic coupling differs for suppression within and beyond the classical receptive field in visual cortex.

Neurons in visual cortex exhibit two major types of stimulus elicited suppression. One, cross-orientation suppression, occurs within the classical receptive field (CRF) when an orthogonal grating is superposed on one at optimal orientation. The second, surround suppression, occurs when the size of an optimally oriented grating extends beyond the CRF. Previous proposals suggest that intracortical inhibition is responsible for surround suppression whereas feedforward processes may underlie cross-orientation suppression. To gain more insight concerning these types of suppression, we have included measurements of metabolic function in addition to neural responses. We made co-localized measurements of multiple unit neural activity and tissue oxygen concentrations in the striate cortex of anaesthetized cats while using visual stimuli to activate the two kinds of suppression. Results show that the amplitude of the initial negative oxygen response increases with stimulus size but neural responses decrease as size extends beyond the CRF. This shows that oxygen consumption increases with stimulus size regardless of reduced neural response. On the other hand, amplitudes of both the initial negative oxygen component and the neural responses are simultaneously attenuated by the orthogonal mask in cross-orientation suppression. These different neurometabolic response patterns are consistent with suggestions that the two types of suppressive processes arise from different neural mechanisms.

Neurometabolic coupling in the lateral geniculate nucleus changes with extended age.

Attempts have been made in various studies to identify and trace changes in function in the aging visual system. Some results are conflicting and we report here a unique approach in an attempt to resolve selected issues. We have estimated neurometabolic coupling in the central visual pathway in young and old cats. Our technique provides high resolution simultaneous measurements of neuronal activity and changes in concentration of tissue oxygen in the thalamus of young and old cats. Following visual stimulation, we find shorter latency and time to peak in tissue oxygen responses in old compared with young animals. Estimates of local activity induced initial negative oxygen response show substantial reductions in older animals. Measurements of neural activity in the form of multiple unit activity are similar in the two age groups. To investigate the mechanisms underlying the changes in tissue oxygen response in older animals, we measured vascular capillary density and found it to be substantially lower in old than that in young animals. Together, these findings suggest that the changes in metabolic responses with age may be largely accounted for by alterations in the cerebral microvasculature rather than by changes in neural activity.

High-resolution neurometabolic coupling in the lateral geniculate nucleus.

The relationships between neural and metabolic processes in activated brain regions are central to the interpretation of noninvasive imaging. To examine this relationship, we have used a specialized sensor to measure simultaneously tissue oxygen changes and neural activity in colocalized regions of the cat's lateral geniculate nucleus (LGN). Previous work with this sensor has shown that a decrease or increase in tissue oxygen can be elicited by selective control of the location and extent of neural activation in the LGN. In the current study, to evaluate the temporal integration and homogeneity of neurometabolic coupling, we have determined the relationship between multiunit extracellular neural activity and tissue oxygen responses to visual stimuli of various durations and contrasts. Our results show that the negative but not the positive oxygen response changes in an approximately linear manner with stimulus duration. The relationship between the negative oxygen response and neural activity is relatively constant with stimulus duration. Moreover, both negative and positive oxygen responses saturate at high stimulus contrast levels. Coupling between neural activity and negative oxygen responses is well described by a power law function. These results help elucidate differences between the initial negative and subsequent positive metabolic responses and may be directly relevant to questions concerning brain mapping with functional magnetic resonance imaging.

Origins of cross-orientation suppression in the visual cortex.

The response of a neuron in striate cortex to an optimally oriented stimulus is suppressed by a superimposed orthogonal stimulus. The neural mechanism underlying this cross-orientation suppression (COS) may arise from intracortical or subcortical processes or from both. Recent studies of the temporal frequency and adaptation properties of COS suggest that depression at thalamo-cortical synapses may be the principal mechanism. To examine the possible role of synaptic depression in relation to COS, we measured the recovery time course of COS. We find it too rapid to be explained by synaptic depression. We also studied potential subcortical processes by measuring single cell contrast response functions for a population of LGN neurons. In general, contrast saturation is a consistent property of LGN neurons. Combined with rectifying nonlinearities in the LGN and spike threshold nonlinearities in visual cortex, contrast saturation in the LGN can account for most of the COS that is observed in the visual cortex.

Direction selectivity of neurons in the striate cortex increases as stimulus contrast is decreased.

Various properties of external scenes are integrated during the transmission of information along central visual pathways. One basic property concerns the sensitivity to direction of a moving stimulus. This direction selectivity (DS) is a fundamental response characteristic of neurons in the visual cortex. We have conducted a neurophysiological study of cells in the visual cortex to determine how DS is affected by changes in stimulus contrast. Previous work shows that a neuron integration time is increased at low contrasts, causing temporal changes of response properties. This leads to the prediction that DS should change with stimulus contrast. However, the change could be in a counterintuitive direction, i.e., DS could increase with reduced contrast. This possibility is of intrinsic interest but it is also of potential relevance to recent behavioral work in which human subjects exhibit increased DS as contrast is reduced. Our neurophysiological results are consistent with this finding, i.e., the degree of DS of cortical neurons is inversely related to stimulus contrast. Temporal phase differences of inputs to cortical cells may account for this result.

Cross-orientation suppression: monoptic and dichoptic mechanisms are different.

The response of a cell in the primary visual cortex to an optimally oriented grating is suppressed by a superimposed orthogonal grating. This cross-orientation suppression (COS) is exhibited when the orthogonal and optimal stimuli are presented to the same eye (monoptically) or to different eyes (dichoptically). A recent study suggested that monoptic COS arises from subcortical processes; however, the mechanisms underlying dichoptic COS were not addressed. We have compared the temporal frequency tuning and stimulus adaptation properties of monoptic and dichoptic COS. We found that dichoptic COS is best elicited with lower temporal frequencies and is substantially reduced after prolonged adaptation to a mask grating. In contrast, monoptic COS is more pronounced with mask gratings at much higher temporal frequencies and is less prone to stimulus adaptation. These results suggest that monoptic COS is mediated by subcortical mechanisms, whereas intracortical inhibition is the mechanism for dichoptic COS.

The derivation of direction selectivity in the striate cortex.

In the central visual pathway of binocular animals, the property of directional selectivity (DS) is first exhibited in striate cortex. In this study, we sought to determine the neural circuitry underlying the transformation from non-DS neurons to DS cortical cells. In a well established model, DS receptive fields (RFs) are derived from the sum of two non-DS inputs with 90 degrees (quadrature) spatiotemporal phase differences. We explored possible input sources for this model, which include non-DS simple cells and lateral geniculate nucleus (LGN) neurons, by examination of spatiotemporal RFs of single cells and of pairs of cells. We find that distributions of non-DS simple RFs do not match the temporal predictions of the quadrature model because of a lack of long-latency responses. The long-latency inputs could potentially arise from lagged LGN afferents. However, analysis of cell pairs indicates that DS cells receive cortical input from non-DS simple cells for both short- and long-latency components, with temporal phase differences typically <90 degrees. Furthermore, the distribution of minimum phase differences needed to generate DS cells overlaps that exhibited by non-DS simple cells. Considered together, these results are consistent with a linear model whereby DS simple cells are formed from simple-cell inputs, with temporal phase differences often less than quadrature.

Oblique effect: a neural basis in the visual cortex.

The details of oriented visual stimuli are better resolved when they are horizontal or vertical rather than oblique. This "oblique effect" has been confirmed in numerous behavioral studies in humans and to some extent in animals. However, investigations of its neural basis have produced mixed and inconclusive results, presumably due in part to limited sample sizes. We have used a database to analyze a population of 4,418 cells in the cat's striate cortex to determine possible differences as a function of orientation. We find that both the numbers of cells and the widths of orientation tuning vary as a function of preferred orientation. Specifically, more cells prefer horizontal and vertical orientations compared with oblique angles. The largest population of cells is activated by orientations close to horizontal. In addition, orientation tuning widths are most narrow for cells preferring horizontal orientations. These findings are most prominent for simple cells tuned to high spatial frequencies. Complex cells and simple cells tuned to low spatial frequencies do not exhibit these anisotropies. For a subset of simple cells from our population (n = 104), we examined the relative contributions of linear and nonlinear mechanisms in shaping orientation tuning curves. We find that linear contributions alone do not account for the narrower tuning widths at horizontal orientations. By modeling simple cells as linear filters followed by static expansive nonlinearities, our analysis indicates that horizontally tuned cells have a greater nonlinear component than those tuned to other orientations. This suggests that intracortical mechanisms play a major role in shaping the oblique effect.

Response properties of cat AMLS neurons to optic flow stimuli.

Spiral and translation stimuli were used to investigate the response properties of cat AMLS (anteromedial lateral suprasylvian area) neurons to optic flow. The overwhelming majority of cells could be significantly excited by the two modes of stimuli and most responsive cells displayed obvious direction selectivity. It is the first time to find a visual area in mammalian brain preferring rotation stimuli. Two representative hypotheses are discussed here on the neural mechanism of optic flow analysis in visual cortex, and some new viewpoints are proposed to explain the experimental results.

[Processing of optic flow information during self-motion].

For human beings and animals, the observer encounters the so-called optic flow during locomotion, the image motion pattern of the environment on the retina, which includes three basic modes of motion: rotation, expansion/contraction and translation. The analysis of optic flow information is vital for determining the direction and velocity of locomotion and has been a hotspot of the studies on visual information processing in recent years. In this article, some progresses in psychophysics and electrophysiology studies on optic flow are introduced and the neural mechanism of optic flow processing in mammalian brain is discussed.