Cat Primary Visual Cortex Research Articles

A comprehensive data-driven model of cat primary visual cortex.

Knowledge integration based on the relationship between structure and function of the neural substrate is one of the main targets of neuroinformatics and data-driven computational modeling. However, the multiplicity of data sources, the diversity of benchmarks, the mixing of observables of different natures, and the necessity of a long-term, systematic approach make such a task challenging. Here we present a first snapshot of a long-term integrative modeling program designed to address this issue in the domain of the visual system: a comprehensive spiking model of cat primary visual cortex. The presented model satisfies an extensive range of anatomical, statistical and functional constraints under a wide range of visual input statistics. In the presence of physiological levels of tonic stochastic bombardment by spontaneous thalamic activity, the modeled cortical reverberations self-generate a sparse asynchronous ongoing activity that quantitatively matches a range of experimentally measured statistics. When integrating feed-forward drive elicited by a high diversity of visual contexts, the simulated network produces a realistic, quantitatively accurate interplay between visually evoked excitatory and inhibitory conductances; contrast-invariant orientation-tuning width; center surround interactions; and stimulus-dependent changes in the precision of the neural code. This integrative model offers insights into how the studied properties interact, contributing to a better understanding of visual cortical dynamics. It provides a basis for future development towards a comprehensive model of low-level perception.

Data-driven modelling of visual receptive fields: comparison between the generalized quadratic model and the nonlinear input model

Objective: Neurons in primary visual cortex (V1) display a range of sensitivity in their response to translations of their preferred visual features within their receptive field: from high specificity to a precise position through to complete invariance. This visual feature selectivity and invariance is frequently modeled by applying a selection of linear spatial filters to the input image, that define the feature selectivity, followed by a nonlinear function that combines the filter outputs, that defines the invariance, to predict the neural response. We compare two such classes of model, that are both popular and parsimonious, the generalized quadratic model (GQM) and the nonlinear input model (NIM). These two classes of model differ primarily in that the NIM can accommodate a greater diversity in the form of nonlinearity that is applied to the outputs of the filters. Approach: We compare the two model types by applying them to data from multielectrode recordings from cat primary visual cortex in response to spatially white Gaussian noise After fitting both classes of model to a database of 342 single units (SUs), we analyze the qualitative and quantitative differences in the visual feature processing performed by the two models and their ability to predict neural response. Main results: We find that the NIM predicts response rates on a held-out data at least as well as the GQM for 95% of SUs. Superior performance occurs predominantly for those units with above average spike rates and is largely due to the NIMs ability to capture aspects of the model’s nonlinear function cannot be captured with the GQM rather than differences in the visual features being processed by the two different models. Significance: These results can help guide model choice for data-driven receptive field modelling.

A strong direct link from the layer 3/4 border to layer 6 of cat primary visual cortex

The cat primary visual cortex (V1) is a cortical area for which we have one of the most detailed estimates of the connection ‘weights’ (expressed as number of synapses) between different neural populations in different layers (Binzegger et al in J Neurosci 24:8441–8453, 2004). Nevertheless, the majority of excitatory input sources to layer 6, the deepest layer in a local translaminar excitatory feedforward loop, was not accounted for by the known neuron types used to generate the quantitative Binzegger diagram. We aimed to fill this gap by using a retrograde tracer that would label neural cell bodies in and outside V1 that directly connect to layer 6 of V1. We found that more than 80% of labeled neurons projecting to layer 6 were within V1 itself. Our data indicate that a substantial fraction of the missing input is provided by a previously unidentified population of layer 3/4 border neurons, laterally distributed and connecting more strongly to layer 6 than the typical superficial layer pyramidal neurons considered by Binzegger et al. (Binzegger et al in J Neurosci 24:8441–8453, 2004). This layer 3/4 to layer 6 connection may be a parallel route to the layer 3 – layer 5 – layer 6 feedforward pathway, be associated with the fast-conducting, movement-related Y pathway and provide convergent input from distant (5–10 degrees) regions of the visual field.

Invited Session IV: Studies of the visual cortex with sub-millimeter resolution: Imaging the visual brain at high spatiotemporal resolution.

Since the discovery of orientation-selective neurons in the cat primary visual cortex (V1), how the mammalian nervous system computes the orientation of visual stimuli has been a flagship question in neuroscience. With the recent advances in in vivo imaging of neural activity using genetically encoded indicators and two-photon fluorescence microscopy, we can now achieve synapse-resolving functional imaging and kilohertz imaging of membrane voltage in the mouse V1. I will describe our recent advancements in imaging visual processing at high spatiotemporal resolution, as well as two studies on the orientation selectivity of neurons in the mouse visual pathway.

Cortical recurrence supports resilience to sensory variance in the primary visual cortex

Our daily endeavors occur in a complex visual environment, whose intrinsic variability challenges the way we integrate information to make decisions. By processing myriads of parallel sensory inputs, our brain is theoretically able to compute the variance of its environment, a cue known to guide our behavior. Yet, the neurobiological and computational basis of such variance computations are still poorly understood. Here, we quantify the dynamics of sensory variance modulations of cat primary visual cortex neurons. We report two archetypal neuronal responses, one of which is resilient to changes in variance and co-encodes the sensory feature and its variance, improving the population encoding of orientation. The existence of these variance-specific responses can be accounted for by a model of intracortical recurrent connectivity. We thus propose that local recurrent circuits process uncertainty as a generic computation, advancing our understanding of how the brain handles naturalistic inputs.

Study on the mechanism of visual aging in cats’ primary visual cortex based on BDNF-TrkB signal pathway

To explore the expression of brain-derived neurotrophic factor (BDNF) and specific receptor tyrosine kinase receptor B (TrkB) in the primary visual cortex of young and old cats, especially to reveal the age-related differences in the mediating mechanism of BDNF-TrkB signaling pathway in cats’ visual cortex and their possible effects on synaptic plasticity, Nissl staining was used to display neurons in each layer of cats’ primary visual cortex, and immunohistochemical ABC method was used to label BDNF and TrkB immunopositive cells in each layer of cats’ primary visual cortex. The BDNF and TrkB receptor immunoreactive neurons and non-neurons were observed and photographed. Their density and immunoreactive intensity were measured. Results showed that BDNF and TrkB were widely expressed in all layers of visual cortex in young and old cats. Compared with the young group, the density and intensity of BDNF and TrkB positive cells in each layer of primary visual cortex in the old group decreased significantly (P < 0.01). The findings indicate that the expression levels of BDNF and TrkB in the primary visual cortex of cats decrease with age, suggesting that the change of BDNF-TrkB signal pathway caused by the weakening of brain-derived neurotrophic factor activity may be one of the important reasons for the decline of visual function.

An Anatomically Constrained Model of V1 Simple Cells Predicts the Coexistence of Push-Pull and Broad Inhibition.

The spatial organization and dynamic interactions between excitatory and inhibitory synaptic inputs that define the receptive field (RF) of simple cells in the cat primary visual cortex (V1) still raise the following paradoxical issues: (1) stimulation of simple cells in V1 with drifting gratings supports a wiring schema of spatially segregated sets of excitatory and inhibitory inputs activated in an opponent way by stimulus contrast polarity and (2) in contrast, intracellular studies using flashed bars suggest that although ON and OFF excitatory inputs are indeed segregated, inhibitory inputs span the entire RF regardless of input contrast polarity. Here, we propose a biologically detailed computational model of simple cells embedded in a V1-like network that resolves this seeming contradiction. We varied parametrically the RF-correlation-based bias for excitatory and inhibitory synapses and found that a moderate bias of excitatory neurons to synapse onto other neurons with correlated receptive fields and a weaker bias of inhibitory neurons to synapse onto other neurons with anticorrelated receptive fields can explain the conductance input, the postsynaptic membrane potential, and the spike train dynamics under both stimulation paradigms. This computational study shows that the same structural model can reproduce the functional diversity of visual processing observed during different visual contexts.SIGNIFICANCE STATEMENT Identifying generic connectivity motives in cortical circuitry encoding for specific functions is crucial for understanding the computations implemented in the cortex. Indirect evidence points to correlation-based biases in the connectivity pattern in V1 of higher mammals, whereby excitatory and inhibitory neurons preferentially synapse onto neurons respectively with correlated and anticorrelated receptive fields. A recent intracellular study questions this push-pull hypothesis, failing to find spatial anticorrelation patterns between excitation and inhibition across the receptive field. We present here a spiking model of V1 that integrates relevant anatomic and physiological constraints and shows that a more versatile motif of correlation-based connectivity with selectively tuned excitation and broadened inhibition is sufficient to account for the diversity of functional descriptions obtained for different classes of stimuli.

Analysis of extracellular spike waveforms and associated receptive fields of neurons in cat primary visual cortex.

Extracellular spikes recorded in the visual cortex (Area 17/18, V1) are commonly classified into either regular-spiking (RS) or fast-spiking (FS). Using multi-electrode arrays positioned in cat V1 and a broadband stimulus, we show that there is also a distinct class with positive-spiking (PS) waveforms. PS units were associated mainly with non-oriented receptive fields while RS and FS units had orientation-selective receptive fields. We suggest that PS units are recordings of axons originating from the thalamus. This conclusion was reinforced by our finding that we could record PS units after cortical silencing, but not record RS and FS units. The importance of our findings is that we were able to correlate spike shapes with receptive field characteristics with high precision using multi-electrode extracellular recording techniques. This allows considerable increases in the amount of information that can be extracted from future cortical experiments. Extracellular spike waveforms from recordings in the visual cortex have been classified into either regular-spiking (RS) or fast-spiking (FS) units. While both these types of spike waveforms are negative-dominant, we show that there are also distinct classes of spike waveforms in visual Area 17/18 (V1) of anaesthetised cats with positive-dominant waveforms, which are not regularly reported. The spatial receptive fields (RFs) of these different spike waveform types were estimated, which objectively revealed the existence of oriented and non-oriented RFs. We found that units with positive-dominant spikes, which have been associated with recordings from axons in the literature, had mostly non-oriented RFs (84%), which are similar to the centre-surround RFs observed in the dorsal lateral geniculate nucleus (dLGN). Thus, we hypothesise that these positive-dominant waveforms may be recordings from dLGN afferents. We recorded from V1 before and after the application of muscimol (a cortical silencer) and found that the positive-dominant spikes (PS) remained while the RS and FS cells did not. We also noted that the PS units had spiking characteristics normally associated with dLGN units (i.e. higher response spike rates, lower response latencies and higher proportion of burst spikes). Our findings show quantitatively that it is possible to correlate the RF properties of cortical neurons with particular spike waveforms. This has implications for how extracellular recordings should be interpreted and complex experiments can now be contemplated that would have been very challenging previously, such as assessing the feedforward connectivity between brain areas in the same location of cortical tissue.

Influence of rhythmic light stimulation on orientation signal within visual cortex columns in the cat

The present study used optical imaging to investigate the development of the optical signal within orientational columns in primary visual cortex of cats reared under conditions of rhythmic light stimulation. Results showed that, although inter-columnar spacing was unchanged, a 3-5-fold decrement in optical signal from orientation columns and a drastic decline in contrast sensitivity was observed in both areas 18 and 17. These data suggest the modification of cortical columnar functioning under artificially correlated synchronization of retinal input.

TMS-induced neuronal plasticity enables targeted remodeling of visual cortical maps

Transcranial magnetic stimulation (TMS) has become a popular clinical method to modify cortical processing. The events underlying TMS-induced functional changes remain, however, largely unknown because current noninvasive recording methods lack spatiotemporal resolution or are incompatible with the strong TMS-associated electrical field. In particular, an answer to the question of how the relatively unspecific nature of TMS stimulation leads to specific neuronal reorganization, as well as a detailed picture of TMS-triggered reorganization of functional brain modules, is missing. Here we used real-time optical imaging in an animal experimental setting to track, at submillimeter range, TMS-induced functional changes in visual feature maps over several square millimeters of the brain's surface. We show that high-frequency TMS creates a transient cortical state with increased excitability and increased response variability, which opens a time window for enhanced plasticity. Visual stimulation (i.e., 30 min of passive exposure) with a single orientation applied during this TMS-induced permissive period led to enlarged imprinting of the chosen orientation on the visual map across visual cortex. This reorganization was stable for hours and was characterized by a systematic shift in orientation preference toward the trained orientation. Thus, TMS can noninvasively trigger a targeted large-scale remodeling of fundamentally mature functional architecture in early sensory cortex.

Describing complex cells in primary visual cortex: a comparison of context and multifilter LN models.

Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multifilter linear-nonlinear (LN) models and context models. Models are, however, never correct, and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: 1) we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions, and 2) we evaluate context models and multifilter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multifilter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multifilter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior.NEW & NOTEWORTHY We used data from complex cells in primary visual cortex to estimate a wide variety of receptive field models from two frameworks that have previously not been compared with each other. The models included traditionally used multifilter linear-nonlinear models and novel variants of context models. Using mutual information and correlation coefficients as performance measures, we showed that context models are superior for describing complex cells and that the novel context models performed the best.

Relationship between the Dynamics of Orientation Tuning and Spatiotemporal Receptive Field Structures of Cat LGN Neurons

Simple cells in the cat primary visual cortex usually have elongated receptive fields (RFs), and their orientation selectivity can be largely predicted by their RFs. As to the relay cells in cats’ lateral geniculate nucleus (LGN), they also have weak but significant orientation bias (OB). It is thus of interest to investigate the fine spatiotemporal receptive field (STRF) properties in LGN, compare them with the dynamics of orientation tuning, and examine the dynamic relationship between STRF and orientation sensitivity in LGN. We mapped the STRFs of the LGN neurons in cats with white noise and characterized the dynamics of the orientation tuning by flashing gratings. We found that most of the LGN neurons showed elongated RFs and that the elongation axes were consistent with the preferred orientations. STRFs and the dynamics of orientation tuning were closely correlated temporally: the elongation of RFs and OB emerged, peaked and decayed at the same pace, with unchanged elongation axis of RF and preferred orientation but consistently changing aspect ratio of RF and OB strength across time. Importantly, the above consistency between RF and orientation tuning was not influenced by the ablation of the primary visual cortex. Furthermore, biased orientation tuning emerged 20–30 ms earlier than those in the primary visual cortex. These data demonstrated that similar to the primary visual cortex, the orientation sensitivity was closely reflected by the RF properties in LGN. However, the elongated RF and OB in LGN did not originate from the primary visual cortex feedback.

Motion contrast in primary visual cortex: a direct comparison of single neuron and population encoding.

Features from outside the classical receptive field (CRF) can modulate the stimulus-driven activity of single cells in the primary visual cortex. This modulation, mediated by horizontal and feedback networks, has been extensively described as a variation of firing rate and is considered the basis of processing features as, for example, motion contrast. However, surround influences have also been identified in pairwise spiking or local field coherence. Yet, evidence about co-existence and integration of different neural signatures remains elusive. To compare multiple signatures, we recorded spiking and LFP activity evoked by stimuli exhibiting a motion contrast in the CRFs surround in anesthetized cat primary visual cortex. We chose natural-like scenes over gratings to avoid predominance of simple visual features, which could be easily represented by a rate code. We analyzed firing rates and phase-locking to low-gamma frequency in single cells and neuronal assemblies. Motion contrast was reflected in all measures but in semi-independent populations. Whereas activation of assemblies accompanied single neuron rates, their phase relations were modulated differently. Interestingly, only assembly phase relations mirrored the direction of movement of the surround and were selectively affected by thermal deactivation of visual interhemispheric connections. We argue that motion contrast can be reflected in complementary and superimposed neuronal signatures that can represent different surround features in independent neuronal populations.

GABAB receptor-dependent bidirectional regulation of critical period ocular dominance plasticity in cats.

Gama amino butyric acid (GABA) inhibition plays an important role in the onset and offset of the critical period for ocular dominance (OD) plasticity in the primary visual cortex. Previous studies have focused on the involvement of GABAA receptors, while the potential contribution of GABAB receptors to OD plasticity has been neglected. In this study, the GABAB receptor antagonist SCH50911 or agonist baclofen was infused into the primary visual cortex of cats concurrently with a period of monocular deprivation (MD). Using single-unit recordings we found that the OD shift induced by four days of MD during the critical period was impaired by infusion of the antagonist SCH50911, but enhanced by infusion of the agonist baclofen. In contrast, seven days of MD in adult cats did not induce any significant OD shift, even when combined with the infusion of SCH50911 or baclofen. Together, these findings indicate that an endogenous GABAB receptor-mediated inhibition contributes to juvenile, but not adult, OD plasticity.

Front Cover: Vascular tree extraction for photoacoustic microscopy and imaging of cat primary visual cortex (J. Biophotonics 6‐7/2017)

Front Cover: Vascular tree extraction for photoacoustic microscopy and imaging of cat primary visual cortex (J. Biophotonics 6‐7/2017)

A biological blueprint for the axons of superficial layer pyramidal cells in cat primary visual cortex

Pyramidal cells in the superficial layers of neocortex of higher mammals form a lateral network of axon clusters known as the ‘daisy’ network. The role of these axon clusters remains speculative and we still lack a comprehensive quantitative description of the single neurons forming the daisy or their heterogeneity. We filled intracellularly 50 superficial layer pyramidal neurons in the cat primary visual cortex and reconstructed the axonal tree and their synaptic boutons in 3D. Individual bouton clusters were identified using an objective mean-shift algorithm. By parameterizing the morphology of these 50 axonal trees and the 217 bouton clusters they formed, we were able to extract one set of relatively constant parameters and another set of variable parameters. Both sets combined allowed us to outline a comprehensive biological blueprint of superficial layer pyramidal neurons. Overall, our detailed analysis supports the hypothesis that pyramidal neurons use their lateral clusters to combine differential contextual cues, required for context-dependent processing of natural scenes.

The hemodynamic signal as a first-order low-pass temporal filter: Evidence and implications for neuroimaging studies

Neuronal activation triggers local changes in blood flow and hemoglobin oxygenation. These hemodynamic signals can be recorded through functional magnetic resonance imaging or intrinsic optical imaging, and allows inferring neural activity in response to stimuli. These techniques are widely used to uncover functional brain architectures. However, their accuracy suffers from distortions inherent to hemodynamic responses and noise. The analysis of these signals currently relies on models of impulse hemodynamic responses to brief stimuli. Here, in order to infer precise functional architectures, we focused on integrated signals associated to the dynamic response of functional maps. To this end, we recorded orientation and direction maps in cat primary visual cortex and compared two protocols: the conventional episodic stimulation technique and a continuous, periodic stimulation paradigm. Conventional methods show that the dynamics of activation and deactivation of the functional maps follows a linear first-order differential equation representing a low-pass filter. Comparison with the periodic stimulation methods confirmed this observation: the phase shifts and magnitude attenuations extracted at various frequencies were consistent with a low-pass filter with a 5s time constant. This dynamics presumably reflects the variations in deoxyhemoglobin mediated by arterial dilations. This dynamics open new avenues in the analysis of neuroimaging data that differs from common methods based on the hemodynamic response function. In particular, we demonstrate that inverting this first-order low-pass filter minimized the distortions of the signal and enabled a much faster and accurate reconstruction of functional maps.

Vascular tree extraction for photoacoustic microscopy and imaging of cat primary visual cortex.

A vascular tree extraction algorithm is proposed to automatically extract independent and complete vascular trees from both background and other crossed vascular trees for photoacoustic microscopy (PAM) imaging. Extracted parameters include vascular tree centerline, diameters, boundaries and three-dimensional (3-D) direction along the tree. Based on the concept of blood vessel tracking, the proposed algorithm extracts complete vascular trees by utilizing a ray casting framework to realize functions which includes vessel direction estimation, vessel branching detection and vessel crossover point detection. An optical-resolution PAM (OR-PAM) system is set up and the acquired images of cat primary visual cortex are used to demonstrate the effectiveness of the proposed algorithm. The proposed algorithm successfully extracts a complete and complex arteriole tree composed of multiple loop structures. Most branches and vessel crossovers in the arteriole tree are accurately extracted. Accuray of the algorithm is further tested on phantom images and real OR-PAM vascular tree images. As the extracted parameters are directly related with monitoring hemodynamic responses at the level of vascular trees, the proposed algorithm may facilitate the application of PAM on studies of neurovascular coupling and related brain functions and diseases. OR-PAM maximum intensity projection image of cat primary visual cortex.

Absolute Depth Sensitivity in Cat Primary Visual Cortex under Natural Viewing Conditions.

Mechanisms of 3D perception, investigated in many laboratories, have defined depth either relative to the fixation plane or to other objects in the visual scene. It is obvious that for efficient perception of the 3D world, additional mechanisms of depth constancy could operate in the visual system to provide information about absolute distance. Neurons with properties reflecting some features of depth constancy have been described in the parietal and extrastriate occipital cortical areas. It has also been shown that, for some neurons in the visual area V1, responses to stimuli of constant angular size differ at close and remote distances. The present study was designed to investigate whether, in natural free gaze viewing conditions, neurons tuned to absolute depths can be found in the primary visual cortex (area V1). Single-unit extracellular activity was recorded from the visual cortex of waking cats sitting on a trolley in front of a large screen. The trolley was slowly approaching the visual scene, which consisted of stationary sinusoidal gratings of optimal orientation rear-projected over the whole surface of the screen. Each neuron was tested with two gratings, with spatial frequency of one grating being twice as high as that of the other. Assuming that a cell is tuned to a spatial frequency, its maximum response to the grating with a spatial frequency twice as high should be shifted to a distance half way closer to the screen in order to attain the same size of retinal projection. For hypothetical neurons selective to absolute depth, location of the maximum response should remain at the same distance irrespective of the type of stimulus. It was found that about 20% of neurons in our experimental paradigm demonstrated sensitivity to particular distances independently of the spatial frequencies of the gratings. We interpret these findings as an indication of the use of absolute depth information in the primary visual cortex.

Orientation Selectivity in the Retina: ON Cell Types and Mechanisms.

Orientation selectivity was first described in cat primary visual cortex by [Hubel and Wiesel (1962)][1] as the selectivity of neuronal firing for elongated visual stimuli oriented along a specific axis. Shortly afterward, [Levick (1967)][2] identified orientation-selective ganglion cells (OSGCs) in