Corticogeniculate feedback and visual processing in the primate

A mechanism for deviance detection and contextual routing in the thalamus: a review and theoretical proposal

Predictive processing theories conceptualize neocortical feedback as conveying expectations and contextual attention signals derived from internal cortical models, playing an essential role in the perception and interpretation of sensory information. However, few predictive processing frameworks outline concrete mechanistic roles for the corticothalamic (CT) feedback from layer 6 (L6), despite the fact that the number of CT axons is an order of magnitude greater than that of feedforward thalamocortical (TC) axons. Here we review the functional architecture of CT circuits and propose a mechanism through which L6 could regulate thalamic firing modes (burst, tonic) to detect unexpected inputs. Using simulations in a model of a TC cell, we show how the CT feedback could support prediction-based input discrimination in TC cells by promoting burst firing. This type of CT control can enable the thalamic circuit to implement spatial and context selective attention mechanisms. The proposed mechanism generates specific experimentally testable hypotheses. We suggest that the L6 CT feedback allows the thalamus to detect deviance from predictions of internal cortical models, thereby supporting contextual attention and routing operations, a far more powerful role than traditionally assumed.

Cortical depth profiles in primary visual cortex for illusory and imaginary experiences

Visual illusions and mental imagery are non-physical sensory experiences that involve cortical feedback processing in the primary visual cortex. Using laminar functional magnetic resonance imaging (fMRI) in two studies, we investigate if information about these internal experiences is visible in the activation patterns of different layers of primary visual cortex (V1). We find that imagery content is decodable mainly from deep layers of V1, whereas seemingly 'real' illusory content is decodable mainly from superficial layers. Furthermore, illusory content shares information with perceptual content, whilst imagery content does not generalise to illusory or perceptual information. Together, our results suggest that illusions and imagery, which differ immensely in their subjective experiences, also involve partially distinct early visual microcircuits. However, overlapping microcircuit recruitment might emerge based on the nuanced nature of subjective conscious experience.

Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction

Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS2/MoS2 hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS2/MoS2 phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems.

Recurrent Circuits Amplify Corticofugal Signals and Drive Feedforward Inhibition in the Inferior Colliculus

The inferior colliculus (IC) is a midbrain hub critical for perceiving complex sounds, such as speech. In addition to processing ascending inputs from most auditory brainstem nuclei, the IC receives descending inputs from auditory cortex that control IC neuron feature selectivity, plasticity, and certain forms of perceptual learning. Although corticofugal synapses primarily release the excitatory transmitter glutamate, many physiology studies show that auditory cortical activity has a net inhibitory effect on IC neuron spiking. Perplexingly, anatomy studies imply that corticofugal axons primarily target glutamatergic IC neurons while only sparsely innervating IC GABA neurons. Corticofugal inhibition of the IC may thus occur largely independently of feedforward activation of local GABA neurons. We shed light on this paradox using in vitro electrophysiology in acute IC slices from fluorescent reporter mice of either sex. Using optogenetic stimulation of corticofugal axons, we find that excitation evoked with single light flashes is indeed stronger in presumptive glutamatergic neurons compared with GABAergic neurons. However, many IC GABA neurons fire tonically at rest, such that sparse and weak excitation suffices to significantly increase their spike rates. Furthermore, a subset of glutamatergic IC neurons fire spikes during repetitive corticofugal activity, leading to polysynaptic excitation in IC GABA neurons owing to a dense intracollicular connectivity. Consequently, recurrent excitation amplifies corticofugal activity, drives spikes in IC GABA neurons, and generates substantial local inhibition in the IC. Thus, descending signals engage intracollicular inhibitory circuits despite apparent constraints of monosynaptic connectivity between auditory cortex and IC GABA neurons.SIGNIFICANCE STATEMENT Descending "corticofugal" projections are ubiquitous across mammalian sensory systems, and enable the neocortex to control subcortical activity in a predictive or feedback manner. Although corticofugal neurons are glutamatergic, neocortical activity often inhibits subcortical neuron spiking. How does an excitatory pathway generate inhibition? Here we study the corticofugal pathway from auditory cortex to inferior colliculus (IC), a midbrain hub important for complex sound perception. Surprisingly, cortico-collicular transmission was stronger onto IC glutamatergic compared with GABAergic neurons. However, corticofugal activity triggered spikes in IC glutamate neurons with local axons, thereby generating strong polysynaptic excitation and feedforward spiking of GABAergic neurons. Our results thus reveal a novel mechanism that recruits local inhibition despite limited monosynaptic convergence onto inhibitory networks.

Robust and efficient representations of dynamic stimuli in hierarchical neural networks via temporal smoothing

Introduction

Efficient coding that minimizes informational redundancy of neural representations is a widely accepted neural coding principle. Despite the benefit, maximizing efficiency in neural coding can make neural representation vulnerable to random noise. One way to achieve robustness against random noise is smoothening neural responses. However, it is not clear whether the smoothness of neural responses can hold robust neural representations when dynamic stimuli are processed through a hierarchical brain structure, in which not only random noise but also systematic error due to temporal lag can be induced.

Methods

In the present study, we showed that smoothness via spatio-temporally efficient coding can achieve both efficiency and robustness by effectively dealing with noise and neural delay in the visual hierarchy when processing dynamic visual stimuli.

Results

The simulation results demonstrated that a hierarchical neural network whose bidirectional synaptic connections were learned through spatio-temporally efficient coding with natural scenes could elicit neural responses to visual moving bars similar to those to static bars with the identical position and orientation, indicating robust neural responses against erroneous neural information. It implies that spatio-temporally efficient coding preserves the structure of visual environments locally in the neural responses of hierarchical structures.

Discussion

The present results suggest the importance of a balance between efficiency and robustness in neural coding for visual processing of dynamic stimuli across hierarchical brain structures.

Brain State-Dependent Modulation of Thalamic Visual Processing by Cortico-Thalamic Feedback

The behavioral state of a mammal impacts how the brain responds to visual stimuli as early as in the dorsolateral geniculate nucleus of the thalamus (dLGN), the primary relay of visual information to the cortex. A clear example of this is the markedly stronger response of dLGN neurons to higher temporal frequencies of the visual stimulus in alert as compared with quiescent animals. The dLGN receives strong feedback from the visual cortex, yet whether this feedback contributes to these state-dependent responses to visual stimuli is poorly understood. Here, we show that in male and female mice, silencing cortico-thalamic feedback profoundly reduces state-dependent differences in the response of dLGN neurons to visual stimuli. This holds true for dLGN responses to both temporal and spatial features of the visual stimulus. These results reveal that the state-dependent shift of the response to visual stimuli in an early stage of visual processing depends on cortico-thalamic feedback.SIGNIFICANCE STATEMENT Brain state affects even the earliest stages of sensory processing. A clear example of this phenomenon is the change in thalamic responses to visual stimuli depending on whether the animal's brain is in an alert or quiescent state. Despite the radical impact that brain state has on sensory processing, the underlying circuits are still poorly understood. Here, we show that both the temporal and spatial response properties of thalamic neurons to visual stimuli depend on the state of the animal and, crucially, that this state-dependent shift relies on the feedback projection from visual cortex to thalamus.

Functional interactions among neurons within single columns of macaque V1

Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.

Synaptic plasticity in self-powered artificial striate cortex for binocular orientation selectivity

Get in-depth understanding of each part of visual pathway yields insights to conquer the challenges that classic computer vision is facing. Here, we first report the bioinspired striate cortex with binocular and orientation selective receptive field based on the crossbar array of self-powered memristors which is solution-processed monolithic all-perovskite system with each cross-point containing one CsFAPbI₃ solar cell directly stacking on the CsPbBr₂I memristor. The plasticity of self-powered memristor can be modulated by optical stimuli following triplet-STDP rules. Furthermore, plasticity of 3 × 3 flexible crossbar array of self-powered memristors has been successfully modulated based on generalized BCM learning rule for optical-encoded pattern recognition. Finally, we implemented artificial striate cortex with binocularity and orientation selectivity based on two simulated 9 × 9 self-powered memristors networks. The emulation of striate cortex with binocular and orientation selectivity will facilitate the brisk edge and corner detection for machine vision in the future applications.

Designing efficient bio-inspired vision systems remains a challenge. Here, the authors report a bio-inspired striate visual cortex with binocular and orientation selective receptive field based on self-powered memristor to enable machine vision with brisk edge and corner detection in the future applications.

Short-term plasticity in the human visual thalamus

While there is evidence that the visual cortex retains a potential for plasticity in adulthood, less is known about the subcortical stages of visual processing. Here we asked whether short-term ocular dominance plasticity affects the human visual thalamus. We addressed this question in normally sighted adult humans, using ultra-high field (7T) magnetic resonance imaging combined with the paradigm of short-term monocular deprivation. With this approach, we previously demonstrated transient shifts of perceptual eye dominance and ocular dominance in visual cortex (Binda et al., 2018). Here we report evidence for short-term plasticity in the ventral division of the pulvinar (vPulv), where the deprived eye representation was enhanced over the non-deprived eye. This ventral-pulvinar plasticity was similar as previously seen in visual cortex and it was correlated with the ocular dominance shift measured behaviorally. In contrast, there was no effect of monocular deprivation in two adjacent thalamic regions: dorsal pulvinar (dPulv), and Lateral Geniculate Nucleus (LGN). We conclude that the visual thalamus retains potential for short-term plasticity in adulthood; the plasticity effect differs across thalamic subregions, possibly reflecting differences in their cortico-fugal connectivity.

Robust effects of corticothalamic feedback and behavioral state on movie responses in mouse dLGN

Neurons in the dorsolateral geniculate nucleus (dLGN) of the thalamus receive a substantial proportion of modulatory inputs from corticothalamic (CT) feedback and brain stem nuclei. Hypothesizing that these modulatory influences might be differentially engaged depending on the visual stimulus and behavioral state, we performed in vivo extracellular recordings from mouse dLGN while optogenetically suppressing CT feedback and monitoring behavioral state by locomotion and pupil dilation. For naturalistic movie clips, we found CT feedback to consistently increase dLGN response gain and promote tonic firing. In contrast, for gratings, CT feedback effects on firing rates were mixed. For both stimulus types, the neural signatures of CT feedback closely resembled those of behavioral state, yet effects of behavioral state on responses to movies persisted even when CT feedback was suppressed. We conclude that CT feedback modulates visual information on its way to cortex in a stimulus-dependent manner, but largely independently of behavioral state.

Loss and enhancement of layer-selective signals in geniculostriate and corticotectal pathways of adult human amblyopia

How abnormal visual experiences early in life influence human subcortical pathways is poorly understood. Using high-resolution fMRI and pathway-selective visual stimuli, we investigate the influence of amblyopia on response properties and the effective connectivity of subcortical visual pathways of the adult human brain. Compared to the normal and fellow eyes, stimuli presented to the amblyopic eye show selectively reduced response in the parvocellular layers of the lateral geniculate nucleus and weaker effective connectivity to V1. Compared to the normal eye, the response of the amblyopic eye to chromatic stimulus decreases in the superficial layers of the superior colliculus, while response of the fellow eye robustly increases in the deep SC with stronger connectivity from the visual cortex. Therefore, amblyopia leads to selective parvocellular alterations of the geniculostriate and corticotectal pathways. These findings provide the neural basis for amblyopic deficits in visual acuity, ocular motor control, and attention.

Effective connectivity in subcortical visual structures in de novo Patients with Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) manifests with the appearance of non-motor symptoms before motor symptoms onset. Among these, dysfunctioning visual structures have recently been reported to occur at early disease stages.

OBJECTIVE

This study addresses effective connectivity in the visual network of PD patients.

METHODS

Using functional MRI and dynamic causal modeling analysis, we evaluated the connectivity between the superior colliculus, the lateral geniculate nucleus and the primary visual area V1 in de novo untreated PD patients (n = 22). A subset of the PD patients (n = 8) was longitudinally assessed two times at two months and at six months after starting dopaminergic treatment. Results were compared to those of age-matched healthy controls (n = 22).

RESULTS

Our results indicate that the superior colliculus drives cerebral activity for luminance contrast processing both in healthy controls and untreated PD patients. The same effective connectivity was observed with neuromodulatory differences in terms of neuronal dynamic interactions. Our main findings were that the modulation induced by luminance contrast changes of the superior colliculus connectivity (self-connectivity and connectivity to the lateral geniculate nucleus) was inhibited in PD patients (effect of contrast: p = 0.79 and p = 0.77 respectively). The introduction of dopaminergic medication in a subset (n = 8) of the PD patients failed to restore the effective connectivity modulation observed in the healthy controls.

INTERPRETATION

The deficits in luminance contrast processing in PD was associated with a deficiency in connectivity adjustment from the superior colliculus to the lateral geniculate nucleus and to V1. No differences in cerebral blood flow were observed between controls and PD patients suggesting that the deficiency was at the neuronal level. Administration of a dopaminergic treatment over six months was not able to normalize the observed alterations in inter-regional coupling. These findings highlight the presence of early dysfunctions in primary visual areas, which might be used as early markers of the disease.

Bombesin-like peptide recruits disinhibitory cortical circuits and enhances fear memories

Disinhibitory neurons throughout the mammalian cortex are powerful enhancers of circuit excitability and plasticity. The differential expression of neuropeptide receptors in disinhibitory, inhibitory, and excitatory neurons suggests that each circuit motif may be controlled by distinct neuropeptidergic systems. Here, we reveal that a bombesin-like neuropeptide, gastrin-releasing peptide (GRP), recruits disinhibitory cortical microcircuits through selective targeting and activation of vasoactive intestinal peptide (VIP)-expressing cells. Using a genetically encoded GRP sensor, optogenetic anterograde stimulation, and trans-synaptic tracing, we reveal that GRP regulates VIP cells most likely via extrasynaptic diffusion from several local and long-range sources. In vivo photometry and CRISPR-Cas9-mediated knockout of the GRP receptor (GRPR) in auditory cortex indicate that VIP cells are strongly recruited by novel sounds and aversive shocks, and GRP-GRPR signaling enhances auditory fear memories. Our data establish peptidergic recruitment of selective disinhibitory cortical microcircuits as a mechanism to regulate fear memories.

A deep convolutional visual encoding model of neuronal responses in the LGN

The Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

NEUROTRANSMISSION IN VISUAL ANALYZER AND BIONIC EYE. A REVIEW

AIMS

The aim of the work is to point out the transmission of electrical voltage changes in the visual analyser and thus the efficiency of the bionic eye.

MATERIAL AND METHODS

The review deals with the question of the transmission of electrical changes in visual path voltage under physiological and pathological conditions. In particular, it points to feedback autoregulatory damage not only of primarily altered cellular structures, but of all other, both horizontally and vertically localized. Based on the results of functional magnetic resonance imaging and electrophysiological methods, it shows the pathology of the entire visual pathway in three eye diseases: retinitis pigmentosa, age-related macular degeneration and glaucoma.

RESULTS

The thesis also provides an overview of possible systems that are used to replace lost vision, from epiretinal, subretinal, suprachoroidal implants, through stimulation of the optic nerve, corpus geniculatum laterale to the visual cortex.

CONCLUSION

Due to the pathology of neurotransmission, bionic eye systems cannot be expected to be restored after stabilization of binocular functions.

Untangling the cortico-thalamo-cortical loop: cellular pieces of a knotty circuit puzzle

Functions of the neocortex depend on its bidirectional communication with the thalamus, via cortico-thalamo-cortical (CTC) loops. Recent work dissecting the synaptic connectivity in these loops is generating a clearer picture of their cellular organization. Here, we review findings across sensory, motor and cognitive areas, focusing on patterns of cell type-specific synaptic connections between the major types of cortical and thalamic neurons. We outline simple and complex CTC loops, and note features of these loops that appear to be general versus specialized. CTC loops are tightly interlinked with local cortical and corticocortical (CC) circuits, forming extended chains of loops that are probably critical for communication across hierarchically organized cerebral networks. Such CTC-CC loop chains appear to constitute a modular unit of organization, serving as scaffolding for area-specific structural and functional modifications. Inhibitory neurons and circuits are embedded throughout CTC loops, shaping the flow of excitation. We consider recent findings in the context of established CTC and CC circuit models, and highlight current efforts to pinpoint cell type-specific mechanisms in CTC loops involved in consciousness and perception. As pieces of the connectivity puzzle fall increasingly into place, this knowledge can guide further efforts to understand structure-function relationships in CTC loops.

Feedforward and feedback pathways of nociceptive and tactile processing in human somatosensory system: A study of dynamic causal modeling of fMRI data

Nociceptive and tactile information is processed in the somatosensory system via reciprocal (i.e., feedforward and feedback) projections between the thalamus, the primary (S1) and secondary (S2) somatosensory cortices. The exact hierarchy of nociceptive and tactile information processing within this 'thalamus-S1-S2' network and whether the processing hierarchy differs between the two somatosensory submodalities remains unclear. In particular, two questions related to the ascending and descending pathways have not been addressed. For the ascending pathways, whether tactile or nociceptive information is processed in parallel (i.e., 'thalamus-S1' and 'thalamus-S2') or in serial (i.e., 'thalamus-S1-S2') remains controversial. For the descending pathways, how corticothalamic feedback regulates nociceptive and tactile processing also remains elusive. Here, we aimed to investigate the hierarchical organization for the processing of nociceptive and tactile information in the 'thalamus-S1-S2' network using dynamic causal modeling (DCM) combined with high-temporal-resolution fMRI. We found that, for both nociceptive and tactile information processing, both S1 and S2 received inputs from thalamus, indicating a parallel structure of ascending pathways for nociceptive and tactile information processing. Furthermore, we observed distinct corticothalamic feedback regulations from S1 and S2, showing that S1 generally exerts inhibitory feedback regulation independent of external stimulation whereas S2 provides additional inhibition to the thalamic activity during nociceptive and tactile information processing in humans. These findings revealed that nociceptive and tactile information processing have similar hierarchical organization within the somatosensory system in the human brain.

An assistive computer vision tool to automatically detect changes in fish behavior in response to ambient odor

The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fish's environment warrant a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

Characterization of Feedback Neurons in the High-Level Visual Cortical Areas That Project Directly to the Primary Visual Cortex in the Cat

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat's high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II-III, IV, V, and VI, with a higher proportion in layer II-III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support "reverse hierarchy theory" or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.

Inhibitory stabilization and cortical computation

Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.

Variation of connectivity across exemplar sensory and associative thalamocortical loops in the mouse

The thalamus engages in sensation, action, and cognition, but the structure underlying these functions is poorly understood. Thalamic innervation of associative cortex targets several interneuron types, modulating dynamics and influencing plasticity. Is this structure-function relationship distinct from that of sensory thalamocortical systems? Here, we systematically compared function and structure across a sensory and an associative thalamocortical loop in the mouse. Enhancing excitability of mediodorsal thalamus, an associative structure, resulted in prefrontal activity dominated by inhibition. Equivalent enhancement of medial geniculate excitability robustly drove auditory cortical excitation. Structurally, geniculate axons innervated excitatory cortical targets in a preferential manner and with larger synaptic terminals, providing a putative explanation for functional divergence. The two thalamic circuits also had distinct input patterns, with mediodorsal thalamus receiving innervation from a diverse set of cortical areas. Altogether, our findings contribute to the emerging view of functional diversity across thalamic microcircuits and its structural basis.

Neuroprotection in glaucoma-electrophysiology

Hypertensive glaucoma is defined as a group of diseases with progressive loss of the neuroretinal margin of the optic disc that causes characteristic degenerative optic neuropathy. The present study provided an updated summary of the physiology and pathology of neurotransmission in the visual path, with the focus on glaucoma. The results of positron emission tomography, functional magnetic resonance imaging and mainly electrophysiological methods demonstrated pathogenesis of nerve cell damage in the visual pathway. Based on these conclusions, neuroprotection in glaucoma was proposed. This consists mainly of the reduction of the intraocular pressure. It is followed by a decrease of glutamate in the synaptic cleft and blockade of its binding to the NMDA receptors. The supply of energy substrates to altered nerve cells is also indispensable. Therapy should be systemic due to impairment of the complete visual path.

Thalamocortical Circuit Motifs: A General Framework

The role of the thalamus in cortical sensory transmission is well known, but its broader role in cognition is less appreciated. Recent studies have shown thalamic engagement in dynamic regulation of cortical activity in attention, executive control, and perceptual decision-making, but the circuit mechanisms underlying such functionality are unknown. Because the thalamus is composed of excitatory neurons that are devoid of local recurrent excitatory connectivity, delineating long-range, input-output connectivity patterns of single thalamic neurons is critical for building functional models. We discuss this need in relation to existing organizational schemes such as core versus matrix and first-order versus higher-order relay nuclei. We propose that a new classification is needed based on thalamocortical motifs, where structure naturally informs function. Overall, our synthesis puts understanding thalamic organization at the forefront of existing research in systems and computational neuroscience, with both basic and translational applications.

Resolving the Spatial Profile of Figure Enhancement in Human V1 through Population Receptive Field Modeling

The detection and segmentation of meaningful figures from their background is one of the primary functions of vision. While work in nonhuman primates has implicated early visual mechanisms in this figure-ground modulation, neuroimaging in humans has instead largely ascribed the processing of figures and objects to higher stages of the visual hierarchy. Here, we used high-field fMRI at 7 Tesla to measure BOLD responses to task-irrelevant orientation-defined figures in human early visual cortex (N = 6, four females). We used a novel population receptive field mapping-based approach to resolve the spatial profiles of two constituent mechanisms of figure-ground modulation: a local boundary response, and a further enhancement spanning the full extent of the figure region that is driven by global differences in features. Reconstructing the distinct spatial profiles of these effects reveals that figure enhancement modulates responses in human early visual cortex in a manner consistent with a mechanism of automatic, contextually driven feedback from higher visual areas.SIGNIFICANCE STATEMENT A core function of the visual system is to parse complex 2D input into meaningful figures. We do so constantly and seamlessly, both by processing information about visible edges and by analyzing large-scale differences between figure and background. While influential neurophysiology work has characterized an intriguing mechanism that enhances V1 responses to perceptual figures, we have a poor understanding of how the early visual system contributes to figure-ground processing in humans. Here, we use advanced computational analysis methods and high-field human fMRI data to resolve the distinct spatial profiles of local edge and global figure enhancement in the early visual system (V1 and LGN); the latter is distinct and consistent with a mechanism of automatic, stimulus-driven feedback from higher-level visual areas.

Substantiating synesthesia: a novel aid in a case of grapheme-colour synesthesia and concomitant dyscalculia

Here we present the case of SP, a 21-year-old female with life-long dyscalculia. SP was subsequently diagnosed with grapheme-color synesthesia, a diagnosis that serendipitously catalyzed our development of a novel aid:The digit-color calculator (DCC). The DCC substantiates SP's color concurrents, dramatically ameliorating her difficulties with basic calculations. We envisage the DCC and its analogues may assist others in educational settings, particularly if they experience difficulties with the acquisition of literacy and numeracy. Further devices that leverage synesthesia may also have the potential to improve the quality of life for others with trait synesthesia regardless of concomitant disorder.

Sensory Integration: Cross-Modal Communication Between the Olfactory and Visual Systems in Zebrafish

Cross-modal sensory communication is an innate biological process that refers to the combination and/or interpretation of different types of sensory input in the brain. Often, this process conjugates with neural modulation, by which the neural signals that convey sensory information are adjusted, such as intensity, frequency, complexity, and/or novelty. Although the anatomic pathways involved in cross-modal sensory integration have been previously described, the course of development and the physiological roles of multisensory signaling integration in brain functions remain to be elucidated. In this article, I review some of the recent findings in sensory integration from research using the zebrafish models. In zebrafish, cross-modal sensory integration occurs between the olfactory and visual systems. It is mediated by the olfacto-retinal centrifugal (ORC) pathway, which originates from the terminalis nerve (TN) in the olfactory bulb and terminates in the neural retina. In the retina, the TNs synapse with the inner nuclear layer dopaminergic interplexiform cells (DA-IPCs). Through the ORC pathway, stimulation of the olfactory neurons alters the cellular activity of TNs and DA-IPCs, which in turn modulates retinal neural function and increases behavioral visual sensitivity.

Neuroscience: Figured Out by Feedback to the Thalamus

The lateral geniculate nucleus of the thalamus (LGN) is a relay nucleus between the retina and the visual cortex. A new brain imaging study shows that LGN activity is modulated by figure-ground organization, even when the figure and ground are presented to different eyes: a hallmark of a cortical feedback effect.

Figure-Ground Modulation in the Human Lateral Geniculate Nucleus Is Distinguishable from Top-Down Attention

Nearly all of the information that reaches the primary visual cortex (V1) of the brain passes from the retina through the lateral geniculate nucleus (LGN) of the thalamus. Although the LGN's role in relaying feedforward signals from the retina to the cortex is well understood [1, 2], the functional role of the extensive feedback it receives from the cortex has remained elusive [3-6]. Here, we investigated whether corticothalamic feedback may contribute to perceptual processing in the LGN in a manner that is distinct from top-down effects of attention [7-10]. We used high-resolution fMRI at 7 Tesla to simultaneously measure responses to orientation-defined figures in the human LGN and V1. We found robust enhancement of perceptual figures throughout the early visual system, which could be distinguished from the effects of covert spatial attention [11-13]. In a second experiment, we demonstrated that figure enhancement occurred in the LGN even when the figure and surrounding background were presented dichoptically (i.e., to different eyes). As binocular integration primarily occurs in V1 [14, 15], these results implicate a mechanism of automatic, contextually sensitive feedback from binocular visual cortex underlying figure-ground modulation in the LGN. Our findings elucidate the functional mechanisms of this core function of the visual system [16-18], which allows people to segment and detect meaningful figures in complex visual environments. The involvement of the LGN in this rich, contextually informed visual processing-despite showing minimal feedforward selectivity for visual features [19, 20]-underscores the role of recurrent processing at the earliest stages of visual processing.

Locomotion modulates specific functional cell types in the mouse visual thalamus

The visual system is composed of diverse cell types that encode distinct aspects of the visual scene and may form separate processing channels. Here we present further evidence for that hypothesis whereby functional cell groups in the dorsal lateral geniculate nucleus (dLGN) are differentially modulated during behavior. Using simultaneous multi-electrode recordings in dLGN and primary visual cortex (V1) of behaving mice, we characterized the impact of locomotor activity on response amplitude, variability, correlation and spatiotemporal tuning. Locomotion strongly impacts the amplitudes of dLGN and V1 responses but the effects on variability and correlations are relatively minor. With regards to tunings, locomotion enhances dLGN responses to high temporal frequencies, preferentially affecting ON transient cells and neurons with nonlinear responses to high spatial frequencies. Channel specific modulations may serve to highlight particular visual inputs during active behaviors.

Locomotion is known to modulate neuronal firing in both the visual thalamus (LGN) and V1. Here, the authors characterize the LGN modulation in detail and report that neurons with transient ON responses for high spatial frequency stimuli show the strongest gain modulation.

Focal Gain Control of Thalamic Visual Receptive Fields by Layer 6 Corticothalamic Feedback

The projections between the thalamus and primary visual cortex (V1) are a key reciprocal neural circuit, relaying retinal signals to cortical layers 4 & 6 while being simultaneously regulated by massive layer 6 corticothalamic feedback. Effectively dissecting the influence of this corticothalamic feedback circuit in higher mammals remains a challenge for vision research. By pharmacologically increasing the focal gain of visually driven layer 6 responses of cat V1 in a controlled fashion, we examined the effects of such focal cortical changes on the response amplitudes and spatial structure of the receptive fields (RFs) of individual dorsal lateral geniculate nucleus (dLGN) cells. We found that enhancing visually driven cortical feedback could facilitate or suppress the overall responses of dLGN cells, and such an effect was linked to the orientation preference of the cortical neuron. Related to these selective retinotopic gain changes, enhanced feedback induced the RFs of dLGN cells to expand, contract or shift their spatial focus. Our results provide further evidence for a functional mechanism through which the cortex can selectively gate visual information flow from the thalamus back to the visual cortex.

Thalamocortical Circuits and Functional Architecture

The thalamocortical pathway is the main route of communication between the eye and the cerebral cortex. During embryonic development, thalamocortical afferents travel to L4 and are sorted by receptive field position, eye of origin, and contrast polarity (i.e., preference for light or dark stimuli). In primates and carnivores, this sorting involves numerous afferents, most of which sample a limited region of the binocular field. Devoting abundant thalamocortical resources to process a limited visual field has a clear advantage: It allows many stimulus combinations to be sampled at each spatial location. Moreover, the sampling efficiency can be further enhanced by organizing the afferents in a cortical grid for eye input and contrast polarity. We argue that thalamocortical interactions within this eye-polarity grid can be used to represent multiple stimulus combinations found in nature and to build an accurate cortical map for multidimensional stimulus space.

Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells

Visually evoked signals in the retina pass through the dorsal geniculate nucleus (dLGN) on the way to the visual cortex. This is however not a simple feedforward flow of information: there is a significant feedback from cortical cells back to both relay cells and interneurons in the dLGN. Despite four decades of experimental and theoretical studies, the functional role of this feedback is still debated. Here we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. For this model the responses are found by direct evaluation of two- or three-dimensional integrals allowing for fast and comprehensive studies of putative effects of different candidate organizations of the cortical feedback. Our analysis identifies a special mixed configuration of excitatory and inhibitory cortical feedback which seems to best account for available experimental data. This configuration consists of (i) a slow (long-delay) and spatially widespread inhibitory feedback, combined with (ii) a fast (short-delayed) and spatially narrow excitatory feedback, where (iii) the excitatory/inhibitory ON-ON connections are accompanied respectively by inhibitory/excitatory OFF-ON connections, i.e. following a phase-reversed arrangement. The recent development of optogenetic and pharmacogenetic methods has provided new tools for more precise manipulation and investigation of the thalamocortical circuit, in particular for mice. Such data will expectedly allow the eDOG model to be better constrained by data from specific animal model systems than has been possible until now for cat. We have therefore made the Python tool pyLGN which allows for easy adaptation of the eDOG model to new situations.

On route from the retina to primary visual cortex, visually evoked signals have to pass through the dorsal lateral geniculate nucleus (dLGN). However, this is not an exclusive feedforward flow of information as feedback exists from neurons in the cortex back to both relay cells and interneurons in the dLGN. The functional role of this feedback remains mostly unresolved. Here, we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. Our analysis indicates that a particular mix of excitatory and inhibitory cortical feedback agrees best with available experimental observations. In this configuration ON-center relay cells receive both excitatory and (indirect) inhibitory feedback from ON-center cortical cells (ON-ON feedback) where the excitatory feedback is fast and spatially narrow while the inhibitory feedback is slow and spatially widespread. In addition to the ON-ON feedback, the connections are accompanied by OFF-ON connections following a so-called phase-reversed (push-pull) arrangement. To facilitate further applications of the model, we have made the Python tool pyLGN which allows for easy modification and evaluation of the a priori quite general eDOG model to new situations.

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.

Reciprocal Connections Between Cortex and Thalamus Contribute to Retinal Axon Targeting to Dorsal Lateral Geniculate Nucleus

The dorsal Lateral Geniculate Nucleus (dLGN) is the primary image-forming target of the retina and shares a reciprocal connection with primary visual cortex (V1). Previous studies showed that corticothalamic input is essential for the development of thalamocortical projections, but less is known about the potential role of this reciprocal connection in the development of retinal projections. Here, we show a deficit of retinal innervation in the dLGN around E18.5 in Tra2β conditional knockout (cKO) "cortexless" mice, an age when apoptosis occurs along the thalamocortical tract and in some dLGN neurons. In vivo electrophysiology experiments in the dLGN further confirmed the loss of functional retinal input. Experiments with N-methyl-d-aspartic acid-induced V1 lesion as well as Fezf2 cKO mice confirmed that the disruption of connections between the dLGN and V1 lead to abnormal retinal projections to the dLGN. Interestingly, retinal projections to the ventral Lateral Geniculate Nucleus (vLGN) and Superior Colliculus (SC) were normal in all 3 mice models. Finally, we show that the cortexless mice had worse performance than control mice in a go-no go task with visual cues. Our results provide evidence that the wiring of visual circuit from the retina to the dLGN and V1 thereafter is coordinated at a surprisingly early stage of circuit development.

Suppression of V1 Feedback Produces a Shift in the Topographic Representation of Receptive Fields of LGN Cells by Unmasking Latent Retinal Drives

In awake monkeys, we used repetitive transcranial magnetic stimulation (rTMS) to focally inactivate visual cortex while measuring the responsiveness of parvocellular lateral geniculate nucleus (LGN) neurons. Effects were noted in 64/75 neurons, and could be divided into 2 main groups: (1) for 39 neurons, visual responsiveness decreased and visual latency increased without apparent shift in receptive field (RF) position and (2) a second group (n = 25, 33% of the recorded cells) whose excitability was not compromised, but whose RF position shifted an average of 4.5°. This change is related to the retinotopic correspondence observed between the recorded thalamic area and the affected cortical zone. The effect of inactivation for this group of neurons was compatible with silencing the original retinal drive and unmasking a second latent retinal drive onto the studied neuron. These results indicate novel and remarkable dynamics in thalamocortical circuitry that force us to reassess constraints on retinogeniculate transmission.

Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells

Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when feedback is present.

The functional role of the dorsal lateral geniculate nucleus (dLGN), placed on route from retina to primary visual cortex in the early visual pathway, is still poorly understood. A striking feature of the dLGN circuit is that dLGN cells not only receive feedforward input from the retina, but also a prominent feedback from cells in the visual cortex. It has been seen in experiments that cortical feedback modifies the spatial properties of dLGN cells in response to visual stimuli. In particular, it has been shown to increase the center-surround antagonism for flashing-spot and patch-grating visual stimuli, i.e., the suppression of responses to very large stimuli compared to smaller stimuli. Here we investigate the putative mechanisms behind this feature by means of a comprehensive network model of biophysically detailed neuron models for RCs and INs in the dLGN and orientation-selective cortical cells providing the feedback. Our results support that the experimentally observed feedback effects may be due to a phase-reversed (‘push-pull’) arrangement of the cortical feedback where ON-symmetry RCs receive (indirect) inhibitory feedback from ON-dominated cortical cell and excitation from OFF-dominated cortical cells, and vice versa for OFF-symmetry RCs.

Feature-Specific Organization of Feedback Pathways in Mouse Visual Cortex

Higher and lower cortical areas in the visual hierarchy are reciprocally connected [1]. Although much is known about how feedforward pathways shape receptive field properties of visual neurons, relatively little is known about the role of feedback pathways in visual processing. Feedback pathways are thought to carry top-down signals, including information about context (e.g., figure-ground segmentation and surround suppression) [2-5], and feedback has been demonstrated to sharpen orientation tuning of neurons in the primary visual cortex (V1) [6, 7]. However, the response characteristics of feedback neurons themselves and how feedback shapes V1 neurons' tuning for other features, such as spatial frequency (SF), remain largely unknown. Here, using a retrograde virus, targeted electrophysiological recordings, and optogenetic manipulations, we show that putatively feedback neurons in layer 5 (hereafter "L5 feedback") in higher visual areas, AL (anterolateral area) and PM (posteromedial area), display distinct visual properties in awake head-fixed mice. AL L5 feedback neurons prefer significantly lower SF (mean: 0.04 cycles per degree [cpd]) compared to PM L5 feedback neurons (0.15 cpd). Importantly, silencing AL L5 feedback reduced visual responses of V1 neurons preferring low SF (mean change in firing rate: -8.0%), whereas silencing PM L5 feedback suppressed responses of high-SF-preferring V1 neurons (-20.4%). These findings suggest that feedback connections from higher visual areas convey distinctly tuned visual inputs to V1 that serve to boost V1 neurons' responses to SF. Such like-to-like functional organization may represent an important feature of feedback pathways in sensory systems and in the nervous system in general.

A cross-species comparison of corticogeniculate structure and function

The corticogeniculate circuit is an evolutionarily conserved pathway linking the primary visual cortex with the visual thalamus in the feedback direction. While the corticogeniculate circuit is anatomically robust, the impact of corticogeniculate feedback on the visual response properties of visual thalamic neurons is subtle. Accordingly, discovering the function of corticogeniculate feedback in vision has been a particularly challenging task. In this review, the morphology, organization, physiology, and function of corticogeniculate feedback is compared across mammals commonly studied in visual neuroscience: primates, carnivores, rabbits, and rodents. Common structural and organizational motifs are present across species, including the organization of corticogeniculate feedback into parallel processing streams in highly visual mammals.

Corticogeniculate feedback sharpens the temporal precision and spatial resolution of visual signals in the ferret

The corticogeniculate (CG) pathway connects the visual cortex with the visual thalamus (LGN) in the feedback direction and enables the cortex to directly influence its own input. Despite numerous investigations, the role of this feedback circuit in visual perception remained elusive. To probe the function of CG feedback in a causal manner, we selectively and reversibly manipulated the activity of CG neurons in anesthetized ferrets in vivo using a combined viral-infection and optogenetics approach to drive expression of channelrhodopsin2 (ChR2) in CG neurons. We observed significant increases in temporal precision and spatial resolution of LGN neuronal responses to drifting grating and white noise stimuli when CG neurons expressing ChR2 were light activated. Enhancing CG feedback reduced visually evoked response latencies, increased spike-timing precision, and reduced classical receptive field size. Increased precision among LGN neurons led to increased spike-timing precision among granular layer V1 neurons as well. Together, our findings suggest that the function of CG feedback is to control the timing and precision of thalamic responses to incoming visual signals.

Neuronal degeneration in the dorsal lateral geniculate nucleus following lesions of primary visual cortex: comparison of young adult and geriatric marmoset monkeys

Neuronal loss in the lateral geniculate nucleus (LGN) is a consequence of lesions of the primary visual cortex (V1). Despite the importance of this phenomenon in understanding the residual capacities of the primate visual system following V1 damage, few quantitative studies are available, and the effect of age at the time of lesion remains unknown. We compared the volume, neuronal number, and neuronal density in the LGN, 6-21 months after unilateral V1 lesions in marmoset monkeys. Stereological sampling techniques and neuronal nuclei (NeuN) staining were used to assess the effects of similar-sized lesions in adult (2-4 years) and geriatric (10-14 years) animals. We found that lesions involving the opercular and caudal calcarine parts of V1 caused robust loss of neurons in topographically corresponding regions of the ipsilateral LGN (lesion projection zones), concomitant with a substantial reduction in the volume of this nucleus. Neuronal density was markedly reduced in the lesion projection zones, relative to the corresponding regions of the contralateral LGN, or the LGN in non-lesioned animals. Moreover, the percentage decrease in neuronal density within the lesion projection zones was significantly greater in the geriatric group, compared with the adult groups. The volume and neuronal density in the contralateral LGN of lesioned adult and geriatric marmosets were similar to those in non-lesioned animals. These results show that the primate LGN becomes more vulnerable to degeneration with advancing age. However, even in geriatric primates there is a population of LGN neurons which survives degeneration, and which could play a role in blindsight.

Cholinergic top-down influences on the auditory brainstem

Descending connections are present in many sensory systems and support adaptive information processing. This allows the sensory brain to code a wider range of inputs. A well characterized descending system is the olivo-cochlear cholinergic innervation of the inner ear, which mediates a reduction of the sensitivity of the inner ear upon perception of intense sounds. Because this inhibits the response to background noise, the olivo-cochlear system supports detection of transient sound events. Olivo-cochlear neurons also innervate the cochlear nucleus through axon collaterals. Here, acetylcholine increases the excitability of central neurons without reducing their temporal precision. Thus their target neurons in the superior olivary complex can more effectively process binaural temporal cues. We argue that the central effect of the olivo-cochlear system augments the peripheral effect. In addition, olivo-cochlear cholinergic neurons are under top-down control of cortical inputs, providing further adaptability of information processing on the level of the auditory brainstem.

Neural Elements for Predictive Coding

Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural engineering in the mouse. The exercise highlights a number of recurring themes, amongst them the consideration of interneuron diversity as a spur to theoretical development and the potential for specifying a pyramidal neuron’s function by its individual ‘connectome,’ combining its extrinsic projection (forward, backward or subcortical) with evaluation of its intrinsic network (e.g., unidirectional versus bidirectional connections with other pyramidal neurons).

To see or not to see; the ability of the magno- and parvocellular response to manifest itself in the VEP determines its appearance to a pattern reversing and pattern onset stimulus

INTRODUCTION

The relationship between stimulus property, brain activity, and the VEP is still a matter of uncertainty.

METHOD

We recorded the VEP of 43 volunteers when viewing a series of dartboard images presented as both a pattern reversing and pattern onset/offset stimulus. Across the dartboard images, the total stimulus area undergoing a luminance contrast change was varied in a graded manner.

RESULTS

We confirmed the presence of two independent neural processing stages. The amplitude of VEP components across our pattern reversing stimuli signaled a phasic neural response based on a temporal luminance contrast selective mechanism. The amplitude of VEP components across the pattern onset stimuli signaled both a phasic and a tonic neural response based on a temporal- and spatial luminance contrast selective mechanism respectively. Oscillation frequencies in the VEP suggested modulation of the phasic neural response by feedback from areas of the dorsal stream, while feedback from areas of the ventral stream modulated the tonic neural response. Each processing stage generated a sink and source phase in the VEP. Source localization indicated that during the sink phase electric current density was highest in V1, while during the source phase electric current density was highest in extra-striate cortex. Our model successfully predicted the appearance of the VEP to our images whether presented as a pattern reversing or a pattern onset/offset stimulus.

CONCLUSIONS

Focussing on the effects of a phasic and tonic response rather than contrast response function on the VEP, enabled us to develop a theory linking stimulus property, neural activity and the VEP.

Cortex dynamically modulates responses of thalamic relay neurons through prolonged circuit-level disinhibition in rat thalamus in vivo

Cortex actively modulates the responses of thalamic relay neurons through corticothalamic (CT) projections. Here we investigated the temporal precision of CT modulation on sensory responses of relay neurons in rat ventral posterior medial thalamus (VPM) to direction-specific whisker stimuli. CT feedback levels were either augmented by cortical electrical microstimulation or depressed by cortical application of muscimol, a potent agonist of γ-aminobutyric acid A-type (GABA_A) receptors. To evaluate the temporal specificity of CT influence, we compared the early (3-10 ms after stimulus onset) and late (10-100 ms) response components of VPM single units to whisker deflections in preferred or nonpreferred directions before and after altering CT feedback levels under urethane anesthesia. The data showed that cortical feedback most strongly affected the late responses of single VPM units to whisker stimulation. That is, cortical stimulation consistently increased the late responses of VPM units in the corresponding (homologous) barreloids to the stimulus direction preferred by neurons in the cortical locus stimulated. However, cortical stimulation could either increase or decrease the early response, depending on whether or not cortical and thalamic loci were tuned to the same direction. Such bidirectional regulation of the early and late VPM responses is consistent with a mechanism of circuit-level disinhibition in vivo. The results support the theory that CT feedback on thalamic sensory responses is mediated by a time-dependent shift of the excitation-inhibition balance in the thalamo-cortico-thalamic loop, such as would occur during sensory feature integration, plasticity, and learning in the awake state.