Optimization of Temporal Coding of Tactile Information in Rat Thalamus by Locus Coeruleus Activation

The brainstem noradrenergic nucleus, the locus coeruleus (LC), exerts heavy influences on sensory processing, perception, and cognition through its diffuse projections throughout the brain. Previous studies have demonstrated that LC activation modulates the response and feature selectivity of thalamic relay neurons. However, the extent to which LC modulates the temporal coding of sensory information in the thalamus remains mostly unknown. Here, we found that LC stimulation significantly altered the temporal structure of the responses of the thalamic relay neurons to repeated whisker stimulation. A substantial portion of events (i.e., time points where the stimulus reliably evoked spikes as evidenced by dramatic elevations in the firing rate of the spike density function) were removed during LC stimulation, but many new events emerged. Interestingly, spikes within the emerged events have a higher feature selectivity, and therefore transmit more information about a tactile stimulus, than spikes within the removed events. This suggests that LC stimulation optimized the temporal coding of tactile information to improve information transmission. We further reconstructed the original whisker stimulus from a population of thalamic relay neurons' responses and corresponding feature selectivity. As expected, we found that reconstruction from thalamic responses was more accurate using spike trains of thalamic neurons recorded during LC stimulation than without LC stimulation, functionally confirming LC optimization of the thalamic temporal code. Together, our results demonstrated that activation of the LC-NE system optimizes temporal coding of sensory stimulus in the thalamus, presumably allowing for more accurate decoding of the stimulus in the downstream brain structures.

Sequential Nonlinear Filtering of Local Motion Cues by Global Motion Circuits

Many animals guide their movements using optic flow, the displacement of stationary objects across the retina caused by self-motion. How do animals selectively synthesize a global motion pattern from its local motion components? To what extent does this feature selectivity rely on circuit mechanisms versus dendritic processing? Here we used in vivo calcium imaging to identify pre- and postsynaptic mechanisms for processing local motion signals in global motion detection circuits in Drosophila. Lobula plate tangential cells (LPTCs) detect global motion by pooling input from local motion detectors, T4/T5 neurons. We show that T4/T5 neurons suppress responses to adjacent local motion signals whereas LPTC dendrites selectively amplify spatiotemporal sequences of local motion signals consistent with preferred global patterns. We propose that sequential nonlinear suppression and amplification operations allow optic flow circuitry to simultaneously prevent saturating responses to local signals while creating selectivity for global motion patterns critical to behavior.

Experience-Dependent Development of Feature-Selective Synchronization in the Primary Visual Cortex

Early visual experience is essential for the maturation of visual functions in which the primary visual cortex plays crucial roles. The extraction of visual features based on response selectivity of individual neurons, a fundamental process in the cortex, is basically established by eye opening in rodents, suggesting that visual experience is required for the development of neural functions other than feature extraction. Here, we show that synchronized firing, which is important for visual information processing, occurs selectively in adjacent neurons sharing similar orientation or spatial frequency preferences in layers 2-4 (upper layer) of rat visual cortex. This feature-selective spike synchrony was rudimentary when the eyes opened and became prominent during the first few weeks after eye opening only in the presence of pattern vision. In contrast, synchronization in layers 5-6 (lower layer) was almost independent of orientation similarity and more weakly dependent on spatial frequency similarity compared with upper layer synchrony. Lower layer synchronization was strengthened during development after eye opening independently of visual experience as a whole. However, the feature selectivity of synchronization was regulated by visual inputs, whereas the inputs without contours were sufficient for this regulation. Therefore, we speculate that feature-selective synchronization in the upper layer may convey detailed information on visual objects to the higher-order cortex, whereas weakly feature-selective synchronization in the lower layer may covey rather rough visual information to the subcortical areas or higher-order cortex. A major role of visual experience may be to establish the specific neural circuits underlying highly feature-selective synchronization.SIGNIFICANCE STATEMENT The neuronal mechanisms underlying experience-dependent improvement of visual functions still remain unresolved. In this study, we investigated whether early visual experience contributes to the development of synchronized neural firing in the primary visual cortex, which plays important roles in visual information processing. We found that synchronized firing depends more remarkably on the similarity of preferred visual stimuli in the upper than lower layer neurons. Pattern vision during development was required for the establishment of spike synchrony in the upper but not the lower layer. These findings provide a new view regarding the role of sensory experience in the functional development of the cortex and the differences in the modes of information processing in the upper and lower cortical layers.

Typology and Circuitry of Suppressed-by-Contrast Retinal Ganglion Cells

Retinal ganglion cells (RGCs) relay ~40 parallel and independent streams of visual information, each encoding a specific feature of a visual scene, to the brain for further processing. The polarity of a visual neuron’s response to a change in contrast is generally the first characteristic used for functional classification: ON cells increase their spike rate to positive contrast; OFF cells increase their spike rate for negative contrast; ON-OFF cells increase their spike rate for both contrast polarities. Suppressed-by-Contrast (SbC) neurons represent a less well-known fourth category; they decrease firing below a baseline rate for both positive and negative contrasts. SbC RGCs were discovered over 50 years ago, and SbC visual neurons have now been found in the thalamus and primary visual cortex of several mammalian species, including primates. Recent discoveries of SbC RGCs in mice have provided new opportunities for tracing upstream circuits in the retina responsible for the SbC computation and downstream targets in the brain where this information is used. We review and clarify recent work on the circuit mechanism of the SbC computation in these RGCs. Studies of mechanism rely on precisely defined cell types, and we argue that, like ON, OFF, and ON-OFF RGCs, SbC RGCs consist of more than one type. A new appreciation of the diversity of SbC RGCs will help guide future work on their targets in the brain and their roles in visual perception and behavior.

Linear Summation Underlies Direction Selectivity in Drosophila

While linear mechanisms lay the foundations of feature selectivity in many brain areas, direction selectivity in the elementary motion detector (EMD) of the fly has become a paradigm of nonlinear neuronal computation. We have bridged this divide by demonstrating that linear spatial summation can generate direction selectivity in the fruit fly Drosophila. Using linear systems analysis and two-photon imaging of a genetically encoded voltage indicator, we measure the emergence of direction-selective (DS) voltage signals in the Drosophila OFF pathway. Our study is a direct, quantitative investigation of the algorithm underlying directional signals, with the striking finding that linear spatial summation is sufficient for the emergence of direction selectivity. A linear stage of the fly EMD strongly resembles similar computations in vertebrate visual cortex, demands a reappraisal of the role of upstream nonlinearities, and implicates the voltage-to-calcium transformation in the refinement of feature selectivity in this system. VIDEO ABSTRACT.

Transformation of Feature Selectivity From Membrane Potential to Spikes in the Mouse Superior Colliculus

Neurons in the visual system display varying degrees of selectivity for stimulus features such as orientation and direction. Such feature selectivity is generated and processed by intricate circuit and synaptic mechanisms. A key factor in this process is the input-output transformation from membrane potential (V_m) to spikes in individual neurons. Here, we use in vivo whole-cell recording to study V_m-to-spike transformation of visual feature selectivity in the superficial neurons of the mouse superior colliculus (SC). As expected from the spike threshold effect, direction and orientation selectivity increase from V_m to spike responses. The degree of this increase is highly variable, and interestingly, it is correlated with the receptive field size of the recorded neurons. We find that the relationships between V_m and spike rate and between V_m dynamics and spike initiation are also correlated with receptive field size, which likely contribute to the observed input-output transformation of feature selectivity. Together, our findings provide useful information for understanding information processing and visual transformation in the mouse SC.

Inhibitory Control of Feature Selectivity in an Object Motion Sensitive Circuit of the Retina

Object motion sensitive (OMS) W3-retinal ganglion cells (W3-RGCs) in mice respond to local movements in a visual scene but remain silent during self-generated global image motion. The excitatory inputs that drive responses of W3-RGCs to local motion were recently characterized, but which inhibitory neurons suppress W3-RGCs' responses to global motion, how these neurons encode motion information, and how their connections are organized along the excitatory circuit axis remains unknown. Here, we find that a genetically identified amacrine cell (AC) type, TH2-AC, exhibits fast responses to global motion and slow responses to local motion. Optogenetic stimulation shows that TH2-ACs provide strong GABA_A receptor-mediated input to W3-RGCs but only weak input to upstream excitatory neurons. Cell-type-specific silencing reveals that temporally coded inhibition from TH2-ACs cancels W3-RGC spike responses to global but not local motion stimuli and, thus, controls the feature selectivity of OMS signals sent to the brain.

Three Small-Receptive-Field Ganglion Cells in the Mouse Retina Are Distinctly Tuned to Size, Speed, and Object Motion

Retinal ganglion cells (RGCs) are frequently divided into functional types by their ability to extract and relay specific features from a visual scene, such as the capacity to discern local or global motion, direction of motion, stimulus orientation, contrast or uniformity, or the presence of large or small objects. Here we introduce three previously uncharacterized, nondirection-selective ON-OFF RGC types that represent a distinct set of feature detectors in the mouse retina. The three high-definition (HD) RGCs possess small receptive-field centers and strong surround suppression. They respond selectively to objects of specific sizes, speeds, and types of motion. We present comprehensive morphological characterization of the HD RGCs and physiological recordings of their light responses, receptive-field size and structure, and synaptic mechanisms of surround suppression. We also explore the similarities and differences between the HD RGCs and a well characterized RGC with a comparably small receptive field, the local edge detector, in response to moving objects and textures. We model populations of each RGC type to study how they differ in their performance tracking a moving object. These results, besides introducing three new RGC types that together constitute a substantial fraction of mouse RGCs, provide insights into the role of different circuits in shaping RGC receptive fields and establish a foundation for continued study of the mechanisms of surround suppression and the neural basis of motion detection.

SIGNIFICANCE STATEMENT

The output cells of the retina, retinal ganglion cells (RGCs), are a diverse group of ∼40 distinct neuron types that are often assigned "feature detection" profiles based on the specific aspects of the visual scene to which they respond. Here we describe, for the first time, morphological and physiological characterization of three new RGC types in the mouse retina, substantially augmenting our understanding of feature selectivity. Experiments and modeling show that while these three "high-definition" RGCs share certain receptive-field properties, they also have distinct tuning to the size, speed, and type of motion on the retina, enabling them to occupy different niches in stimulus space.

Stimulus features coded by single neurons of a macaque body category selective patch

Body category-selective regions of the primate temporal cortex respond to images of bodies, but it is unclear which fragments of such images drive single neurons' responses in these regions. Here we applied the Bubbles technique to the responses of single macaque middle superior temporal sulcus (midSTS) body patch neurons to reveal the image fragments the neurons respond to. We found that local image fragments such as extremities (limbs), curved boundaries, and parts of the torso drove the large majority of neurons. Bubbles revealed the whole body in only a few neurons. Neurons coded the features in a manner that was tolerant to translation and scale changes. Most image fragments were excitatory but for a few neurons both inhibitory and excitatory fragments (opponent coding) were present in the same image. The fragments we reveal here in the body patch with Bubbles differ from those suggested in previous studies of face-selective neurons in face patches. Together, our data indicate that the majority of body patch neurons respond to local image fragments that occur frequently, but not exclusively, in bodies, with a coding that is tolerant to translation and scale. Overall, the data suggest that the body category selectivity of the midSTS body patch depends more on the feature statistics of bodies (e.g., extensions occur more frequently in bodies) than on semantics (bodies as an abstract category).

Linear and non-linear properties of feature selectivity in V4 neurons

Extrastriate area V4 is a critical component of visual form processing in both humans and non-human primates. Previous studies have shown that the tuning properties of V4 neurons demonstrate an intermediate level of complexity that lies between the narrow band orientation and spatial frequency tuning of neurons in primary visual cortex and the highly complex object selectivity seen in inferotemporal neurons. However, the nature of feature selectivity within this cortical area is not well understood, especially in the context of natural stimuli. Specifically, little is known about how the tuning properties of V4 neurons, measured in isolation, translate to feature selectivity within natural scenes. In this study, we assessed the degree to which preferences for natural image components can readily be inferred from classical orientation and spatial frequency tuning functions. Using a psychophysically-inspired method we isolated and identified the specific visual “driving features” occurring in natural scene photographs that reliably elicited spiking activity from single V4 neurons. We then compared the measured driving features to those predicted based on the spectral receptive field (SRF), estimated from responses to narrowband sinusoidal grating stimuli. This approach provided a quantitative framework for assessing the degree to which linear feature selectivity was preserved during natural vision. First, we found evidence of both spectrally and spatially tuned suppression within the receptive field, neither of which were present in the linear SRF. Second, we found driving features that were stable during translation of the image across the receptive field (due to small fixational eye movements). The degree of translation invariance fell along a continuum, with some cells showing nearly complete invariance across the receptive field and others exhibiting little to no position invariance. This form of limited translation invariance could indicate that a subset of V4 neurons are insensitive to small fixational eye movements, supporting perceptual stability during natural vision.

Thinking outside the box: rectilinear shapes selectively activate scene-selective cortex

Fifteen years ago, an intriguing area was found in human visual cortex. This area (the parahippocampal place area [PPA]) was initially interpreted as responding selectively to images of places. However, subsequent studies reported that PPA also responds strongly to a much wider range of image categories, including inanimate objects, tools, spatial context, landmarks, objectively large objects, indoor scenes, and/or isolated buildings. Here, we hypothesized that PPA responds selectively to a lower-level stimulus property (rectilinear features), which are common to many of the above higher-order categories. Using a novel wavelet image filter, we first demonstrated that rectangular features are common in these diverse stimulus categories. Then we tested whether PPA is selectively activated by rectangular features in six independent fMRI experiments using progressively simplified stimuli, from complex real-world images, through 3D/2D computer-generated shapes, through simple line stimuli. We found that PPA was consistently activated by rectilinear features, compared with curved and nonrectangular features. This rectilinear preference was (1) comparable in amplitude and selectivity, relative to the preference for category (scenes vs faces), (2) independent of known biases for specific orientations and spatial frequency, and (3) not predictable from V1 activity. Two additional scene-responsive areas were sensitive to a subset of rectilinear features. Thus, rectilinear selectivity may serve as a crucial building block for category-selective responses in PPA and functionally related areas.

Optimal attentional modulation of a neural population

Top-down attention has often been separately studied in the contexts of either optimal population coding or biasing of visual search. Yet, both are intimately linked, as they entail optimally modulating sensory variables in neural populations according to top-down goals. Designing experiments to probe top-down attentional modulation is difficult because non-linear population dynamics are hard to predict in the absence of a concise theoretical framework. Here, we describe a unified framework that encompasses both contexts. Our work sheds light onto the ongoing debate on whether attention modulates neural response gain, tuning width, and/or preferred feature. We evaluate the framework by conducting simulations for two tasks: (1) classification (discrimination) of two stimuli s a and s b and (2) searching for a target T among distractors D. Results demonstrate that all of gain, tuning, and preferred feature modulation happen to different extents, depending on stimulus conditions and task demands. The theoretical analysis shows that task difficulty (linked to difference Δ between s a and s b , or T, and D) is a crucial factor in optimal modulation, with different effects in discrimination vs. search. Further, our framework allows us to quantify the relative utility of neural parameters. In easy tasks (when Δ is large compared to the density of the neural population), modulating gains and preferred features is sufficient to yield nearly optimal performance; however, in difficult tasks (smaller Δ), modulating tuning width becomes necessary to improve performance. This suggests that the conflicting reports from different experimental studies may be due to differences in tasks and in their difficulties. We further propose future electrophysiology experiments to observe different types of attentional modulation in a same neuron.

Trade-off between curvature tuning and position invariance in visual area V4

Humans can rapidly recognize a multitude of objects despite differences in their appearance. The neural mechanisms that endow high-level sensory neurons with both selectivity to complex stimulus features and "tolerance" or invariance to identity-preserving transformations, such as spatial translation, remain poorly understood. Previous studies have demonstrated that both tolerance and selectivity to conjunctions of features are increased at successive stages of the ventral visual stream that mediates visual recognition. Within a given area, such as visual area V4 or the inferotemporal cortex, tolerance has been found to be inversely related to the sparseness of neural responses, which in turn was positively correlated with conjunction selectivity. However, the direct relationship between tolerance and conjunction selectivity has been difficult to establish, with different studies reporting either an inverse or no significant relationship. To resolve this, we measured V4 responses to natural scenes, and using recently developed statistical techniques, we estimated both the relevant stimulus features and the range of translation invariance for each neuron. Focusing the analysis on tuning to curvature, a tractable example of conjunction selectivity, we found that neurons that were tuned to more curved contours had smaller ranges of position invariance and produced sparser responses to natural stimuli. These trade-offs provide empirical support for recent theories of how the visual system estimates 3D shapes from shading and texture flows, as well as the tiling hypothesis of the visual space for different curvature values.

Feature selectivity of the gamma-band of the local field potential in primate primary visual cortex

Extracellular voltage fluctuations (local field potentials, LFPs) reflecting neural mass action are ubiquitous across species and brain regions. Numerous studies have characterized the properties of LFP signals in the cortex to study sensory and motor computations as well as cognitive processes like attention, perception and memory. In addition, its extracranial counterpart – the electroencephalogram – is widely used in clinical applications. However, the link between LFP signals and the underlying activity of local populations of neurons remains largely elusive. Here, we review recent work elucidating the relationship between spiking activity of local neural populations and LFP signals. We focus on oscillations in the gamma-band (30–90 Hz) of the LFP in the primary visual cortex (V1) of the macaque that dominate during visual stimulation. Given that in area V1 much is known about the properties of single neurons and the cortical architecture, it provides an excellent opportunity to study the mechanisms underlying the generation of the LFP.

Comparing the feature selectivity of the gamma-band of the local field potential and the underlying spiking activity in primate visual cortex

The local field potential (LFP), comprised of low-frequency extra-cellular voltage fluctuations, has been used extensively to study the mechanisms of brain function. In particular, oscillations in the gamma-band (30-90 Hz) are ubiquitous in the cortex of many species during various cognitive processes. Surprisingly little is known about the underlying biophysical processes generating this signal. Here, we examine the relationship of the local field potential to the activity of localized populations of neurons by simultaneously recording spiking activity and LFP from the primary visual cortex (V1) of awake, behaving macaques. The spatial organization of orientation tuning and ocular dominance in this area provides an excellent opportunity to study this question, because orientation tuning is organized at a scale around one order of magnitude finer than the size of ocular dominance columns. While we find a surprisingly weak correlation between the preferred orientation of multi-unit activity and gamma-band LFP recorded on the same tetrode, there is a strong correlation between the ocular preferences of both signals. Given the spatial arrangement of orientation tuning and ocular dominance, this leads us to conclude that the gamma-band of the LFP seems to sample an area considerably larger than orientation columns. Rather, its spatial resolution lies at the scale of ocular dominance columns.

Feature selectivity and interneuronal cooperation in the thalamocortical system

Action potentials are a universal currency for fast information transfer in the nervous system, yet few studies address how some spikes carry more information than others. We focused on the transformation of sensory representations in the lemniscal (high-fidelity) auditory thalamocortical network. While stimulating with a complex sound, we recorded simultaneously from functionally connected cell pairs in the ventral medial geniculate body and primary auditory cortex. Thalamic action potentials that immediately preceded or potentially caused a cortical spike were more selective than the average thalamic spike for spectrotemporal stimulus features. This net improvement of thalamic signaling indicates that for some thalamic cells, spikes are not propagated through cortex independently but interact with other inputs onto the same target cell. We then developed a method to identify the spectrotemporal nature of these interactions and found that they could be cooperative or antagonistic to the average receptive field of the thalamic cell. The degree of cooperativity with the thalamic cell determined the increase in feature selectivity for potentially causal thalamic spikes. We therefore show how some thalamic spikes carry more receptive field information than average and how other inputs cooperate to constrain the information communicated through a cortical cell.