Response Properties Of Neurons Research Articles

Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition

Deep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in early visual cortex, images were preprocessed with three different spatial frequency (SF) channels, before they were fed to a layer of spiking neurons whose synaptic weights were updated using spike-timing-dependent-plasticity. We investigate how the quality of the represented objects changes under different SF bands and WTA-I schemes. We demonstrate that a network of 200 spiking neurons tuned to three SFs can efficiently represent objects with as little as 15 spikes per neuron. Studying how core object recognition may be implemented using biologically plausible learning rules in SNNs may not only further our understanding of the brain, but also lead to novel and efficient artificial vision systems.

Surround suppression in mouse auditory cortex underlies auditory edge detection.

Surround suppression (SS) is a fundamental property of sensory processing throughout the brain. In the auditory system, the early processing stream encodes sounds using a one dimensional physical space-frequency. Previous studies in the auditory system have shown SS to manifest as bandwidth tuning around the preferred frequency. We asked whether bandwidth tuning can be found around frequencies away from the preferred frequency. We exploited the simplicity of spectral representation of sounds to study SS by manipulating both sound frequency and bandwidth. We recorded single unit spiking activity from the auditory cortex (ACx) of awake mice in response to an array of broadband stimuli with varying central frequencies and bandwidths. Our recordings revealed that a significant portion of neuronal response profiles had a preferred bandwidth that varied in a regular way with the sound's central frequency. To gain insight into the possible mechanism underlying these responses, we modelled neuronal activity using a variation of the "Mexican hat" function often used to model SS. The model accounted for response properties of single neurons with high accuracy. Our data and model show that these responses in ACx obey simple rules resulting from the presence of lateral inhibitory sidebands, mostly above the excitatory band of the neuron, that result in sensitivity to the location of top frequency edges, invariant to other spectral attributes. Our work offers a simple explanation for auditory edge detection and possibly other computations of spectral content in sounds.

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.

The prefrontal cortex of the Mexican free-tailed bat is more selective to communication calls than primary auditory cortex.

In this study, we examined the auditory responses of a prefrontal area, the frontal auditory field (FAF), of an echolocating bat (Tadarida brasiliensis) and presented a comparative analysis of the neuronal response properties between the FAF and the primary auditory cortex (A1). We compared single-unit responses from the A1 and the FAF elicited by pure tones, downward frequency-modulated sweeps (dFMs), and species-specific vocalizations. Unlike the A1, FAFs were not frequency tuned. However, progressive increases in dFM sweep rate elicited a systematic increase of response precision, a phenomenon that does not take place in the A1. Call selectivity was higher in the FAF versus A1. We calculated the neuronal spectrotemporal receptive fields (STRFs) and spike-triggered averages (STAs) to predict responses to the communication calls and provide an explanation for the differences in call selectivity between the FAF and A1. In the A1, we found a high correlation between predicted and evoked responses. However, we did not generate reasonable STRFs in the FAF, and the prediction based on the STAs showed lower correlation coefficient than that of the A1. This suggests nonlinear response properties in the FAF that are stronger than the linear response properties in the A1. Stimulating with a call sequence increased call selectivity in the A1, but it remained unchanged in the FAF. These data are consistent with a role for the FAF in assessing distinctive acoustic features downstream of A1, similar to the role proposed for primate ventrolateral prefrontal cortex.NEW & NOTEWORTHY In this study, we examined the neuronal responses of a frontal cortical area in an echolocating bat to behaviorally relevant acoustic stimuli and compared them with those in the primary auditory cortex (A1). In contrast to the A1, neurons in the bat frontal auditory field are not frequency tuned but showed a higher selectivity for social signals such as communication calls. The results presented here indicate that the frontal auditory field may represent an additional processing center for behaviorally relevant sounds.

Visual Responses to Moving and Flashed Stimuli of Neurons in Domestic Pigeon (Columba livia domestica) Optic Tectum.

Birds can rapidly and accurately detect moving objects for better survival in complex environments. This visual ability may be attributed to the response properties of neurons in the optic tectum. However, it is unknown how neurons in the optic tectum respond differently to moving objects compared to static ones. To address this question, neuronal activities were recorded from domestic pigeon (Columba livia domestica) optic tectum, responsible for orienting to moving objects, and the responses to moving and flashed stimuli were compared. An encoding model based on the Generalized Linear Model (GLM) framework was established to explain the difference in neuronal responses. The experimental results showed that the first spike latency to moving stimuli was smaller than that to flashed ones and firing rate was higher. The model further implied the faster and stronger response to a moving target result from spatiotemporal integration process, corresponding to the spatially sequential activation of tectal neurons and the accumulation of information in time. This study provides direct electrophysiological evidence about the different tectal neuron responses to moving objects and flashed ones. The findings of this investigation increase our understanding of the motion detection mechanism of tectal neurons.

Rapid Effects of Vagus Nerve Stimulation on Sensory Processing Through Activation of Neuromodulatory Systems.

After sensory information is encoded into neural signals at the periphery, it is processed through multiple brain regions before perception occurs (i.e., sensory processing). Recent work has begun to tease apart how neuromodulatory systems influence sensory processing. Vagus nerve stimulation (VNS) is well-known as an effective and safe method of activating neuromodulatory systems. There is a growing body of studies confirming VNS has immediate effects on sensory processing across multiple sensory modalities. These immediate effects of VNS on sensory processing are distinct from the more well-documented method of inducing lasting neuroplastic changes to the sensory pathways through repeatedly delivering a brief VNS burst paired with a sensory stimulus. Immediate effects occur upon VNS onset, often disappear upon VNS offset, and the modulation is present for all sensory stimuli. Conversely, the neuroplastic effect of pairing sub-second bursts of VNS with a sensory stimulus alters sensory processing only after multiple pairing sessions, this alteration remains after cessation of pairing sessions, and the alteration selectively affects the response properties of neurons encoding the specific paired sensory stimulus. Here, we call attention to the immediate effects VNS has on sensory processing. This review discusses existing studies on this topic, provides an overview of the underlying neuromodulatory systems that likely play a role, and briefly explores the potential translational applications of using VNS to rapidly regulate sensory processing.

Analysis of Neuronal Oscillations of Fractional-Order Morris-Lecar Model

Fractional calculus is a new approach for modeling biological and physical phenomena with memory effects. Fractional calculus uses differential and integral operators including non-integer orders to study the non-linear behavior of physical and biological systems with some degrees of fractionality or fractality. Since the long memory properties of neuronal responses can be better explained using fractional derivative, in this study we generalize the integer-order Morris-Lecar model in the fractional-order domain to better modeling of neuron dynamics. To investigate the complex spiking patterns of fractional-order Morris-Lecar neural system the fractional calculus has been applied to build this new mathematical model. We compare the results with integer-order Morris-Lecar model. The analytical solutions of these equations cannot explicitly be obtained. Therefore, to find the dynamical behaviors of solutions, we used approximation and numerical schemes. Depending on the different parameters values for 0<η≤1, the fractional-order Morris-Lecar reproduces quiescent, spiking and bursting activities the same as its original model but for higher input current. We numerically discover the hopf bifurcation, saddle node bifurcation of limit cycle and homoclinic bifurcation for this model for different input current and derivative orders. Taking the advantages of the fractional order derivative, for a variety of orders, we define different classes of this model which helps to better extract all the complicated dynamics of this single neuron model.

"Prefrontal" Neuronal Foundations of Visual Asymmetries in Pigeons.

This study was conducted in order to reveal the possibly lateralized processes in the avian nidopallium caudolaterale (NCL), a functional analogue to the mammalian prefrontal cortex, during a color discrimination task. Pigeons are known to be visually lateralized with a superiority of the left hemisphere/right eye for visual feature discriminations. While animals were working on a color discrimination task, we recorded single visuomotor neurons in left and right NCL. As expected, pigeons learned faster and responded more quickly when seeing the stimuli with their right eyes. Our electrophysiological recordings discovered several neuronal properties of NCL neurons that possibly contributed to this behavioral asymmetry. We found that the speed of stimulus encoding was identical between left and right NCL but action generation was different. Here, most left hemispheric NCL neurons reached their peak activities shortly before response execution. In contrast, the majority of right hemispheric neurons lagged behind and came too late to control the response. Thus, the left NCL dominated the animals’ behavior not by a higher efficacy of encoding, but by being faster in monopolizing the operant response. A further asymmetry concerned the hemisphere-specific integration of input from the contra- and ipsilateral eye. The left NCL was able to integrate and process visual input from the ipsilateral eye to a higher degree and thus achieved a more bilateral representation of two visual fields. We combine these novel findings with those from previous publications to come up with a working hypothesis that could explain how hemispheric asymmetries for visual feature discrimination in birds are realized by a sequential buildup of lateralized neuronal response properties in the avian forebrain.

Electrophysiological dataset from macaque visual cortical area MST in response to a novel motion stimulus

Establishing the cortical neural representation of visual stimuli is a central challenge of systems neuroscience. Publicly available data would allow a broad range of scientific analyses and hypothesis testing, but are rare and largely focused on the early visual system. To address the shortage of open data from higher visual areas, we provide a comprehensive dataset from a neurophysiology study in macaque monkey visual cortex that includes a complete record of extracellular action potential recordings from the extrastriate medial superior temporal (MST) area, behavioral data, and detailed stimulus records. It includes spiking activity of 172 single neurons recorded in 139 sessions from 4 hemispheres of 3 rhesus macaque monkeys. The data was collected across 3 experiments, designed to characterize the response properties of MST neurons to complex motion stimuli. This data can be used to elucidate visual information processing at the level of single neurons in a high-level area of primate visual cortex. Providing open access to this dataset also promotes the 3R-principle of responsible animal research.

Age-related changes in neuronal receptive fields of primary auditory cortex in frequency, amplitude, and temporal domains

Aging populations often experience difficulties hearing. This phenomenon, known as age-related hearing loss, is associated with decreases in hearing sensitivity and pathophysiological changes in the central auditory system, including the primary auditory cortex (AI). To better understand changes in the central auditory system, this study is designed to compare the receptive fields of AI neurons of young and old C57 mice in frequency, amplitude, and temporal domains by using random-delivery (various interval) of multi-frequency gamma-shaped tone pips and a novel data processing approach known as the intensity-stacked spectrotemporal receptive field (iSTRF). We show that the fundamental changes in the response properties of AI neurons in old mice were in line with the literature. Compared to young mice, AI neurons in old mice tuned to lower frequency and higher amplitude of tones with broader frequency tuning, shorter dB (dynamic) range, longer response duration, as well as a higher firing rate. We further compared the entire iSTRF and core iSTRF (above 50% maximal firing rate) between young and old mice; the core iSTRF represented the AI neuronal responses to sound that fall into the central frequency and amplitude ranges from the auditory periphery. It is remarkable that the difference was significant in the entire iSTRF while little difference was observed in the core iSTRFs between young and old mice. However, the lower best frequency and higher best amplitude were obvious in both iSTRFs that were mostly determined by the deficits in the inner ears of old mice. In the frequency domain, the tuning quality factor of entire iSTRFs was significantly greater in old mice, while that of core iSTRFs was not compared to young mice. In the amplitude domain, significantly shorter dB range in old mice were observed in the entire iSTRF, but not in the core iSTRF. In the temporal domain, the response duration of old AI neurons was significantly longer in entire iSTRFs, but not in core iSTRFs, when compared to young AI neurons. Furthermore, the average firing rate of old AI neurons was significantly higher in entire iSTRF, but not in core iSTRF. It is also interesting that the ratio of the firing rate to background firing rate (signal-noise ratio) were similar between young and old AI neurons. Our data suggests that age-related hearing loss has relatively less impact on auditory information processing when sounds fall into the optimal frequency and amplitude ranges of given AI neurons.

Processing of visual statistics of naturalistic videos in macaque visual areas V1 and V4

Natural scenes are characterized by diverse image statistics, including various parameters of the luminance histogram, outputs of Gabor-like filters, and pairwise correlations between the filter outputs of different positions, orientations, and scales (Portilla–Simoncelli statistics). Some of these statistics capture the response properties of visual neurons. However, it remains unclear to what extent such statistics can explain neural responses to natural scenes and how neurons that are tuned to these statistics are distributed across the cortex. Using two-photon calcium imaging and an encoding-model approach, we addressed these issues in macaque visual areas V1 and V4. For each imaged neuron, we constructed an encoding model to mimic its responses to naturalistic videos. By extracting Portilla–Simoncelli statistics through outputs of both filters and filter correlations, and by computing an optimally weighted sum of these outputs, the model successfully reproduced responses in a subpopulation of neurons. We evaluated the selectivities of these neurons by quantifying the contributions of each statistic to visual responses. Neurons whose responses were mainly determined by Gabor-like filter outputs (low-level statistics) were abundant at most imaging sites in V1. In V4, the relative contribution of higher order statistics, such as cross-scale correlation, was increased. Preferred image statistics varied markedly across V4 sites, and the response similarity of two neurons at individual imaging sites gradually declined with increasing cortical distance. The results indicate that natural scene analysis progresses from V1 to V4, and neurons sharing preferred image statistics are locally clustered in V4.

Impaired Subcortical Processing of Amplitude-Modulated Tones in Mice Deficient for Cacna2d3, a Risk Gene for Autism Spectrum Disorders in Humans.

Temporal processing of complex sounds is a fundamental and complex task in hearing and a prerequisite for processing and understanding vocalization, speech, and prosody. Here, we studied response properties of neurons in the inferior colliculus (IC) in mice lacking Cacna2d3, a risk gene for autism spectrum disorders (ASDs). The α2δ3 auxiliary Ca2+ channel subunit encoded by Cacna2d3 is essential for proper function of glutamatergic synapses in the auditory brainstem. Recent evidence has shown that much of auditory feature extraction is performed in the auditory brainstem and IC, including processing of amplitude modulation (AM). We determined both spectral and temporal properties of single- and multi-unit responses in the IC of anesthetized mice. IC units of α2δ3−/− mice showed normal tuning properties yet increased spontaneous rates compared with α2δ3+/+. When stimulated with AM tones, α2δ3−/− units exhibited less precise temporal coding and reduced evoked rates to higher modulation frequencies (fm). Whereas first spike latencies (FSLs) were increased for only few modulation frequencies, population peak latencies were increased for fm ranging from 20 to 100 Hz in α2δ3−/− IC units. The loss of precision of temporal coding with increasing fm from 70 to 160 Hz was characterized using a normalized offset-corrected (Pearson-like) correlation coefficient, which appeared more appropriate than the metrics of vector strength. The processing deficits of AM sounds analyzed at the level of the IC indicate that α2δ3−/− mice exhibit a subcortical auditory processing disorder (APD). Similar deficits may be present in other mouse models for ASDs.

Diverse processing underlying frequency integration in midbrain neurons of barn owls.

Emergent response properties of sensory neurons depend on circuit connectivity and somatodendritic processing. Neurons of the barn owl’s external nucleus of the inferior colliculus (ICx) display emergence of spatial selectivity. These neurons use interaural time difference (ITD) as a cue for the horizontal direction of sound sources. ITD is detected by upstream brainstem neurons with narrow frequency tuning, resulting in spatially ambiguous responses. This spatial ambiguity is resolved by ICx neurons integrating inputs over frequency, a relevant processing in sound localization across species. Previous models have predicted that ICx neurons function as point neurons that linearly integrate inputs across frequency. However, the complex dendritic trees and spines of ICx neurons raises the question of whether this prediction is accurate. Data from in vivo intracellular recordings of ICx neurons were used to address this question. Results revealed diverse frequency integration properties, where some ICx neurons showed responses consistent with the point neuron hypothesis and others with nonlinear dendritic integration. Modeling showed that varied connectivity patterns and forms of dendritic processing may underlie observed ICx neurons’ frequency integration processing. These results corroborate the ability of neurons with complex dendritic trees to implement diverse linear and nonlinear integration of synaptic inputs, of relevance for adaptive coding and learning, and supporting a fundamental mechanism in sound localization.

Nonlinear visuoauditory integration in the mouse superior colliculus.

Sensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.

Sensory Adaptation in the Whisker-Mediated Tactile System: Physiology, Theory, and Function.

In the natural environment, organisms are constantly exposed to a continuous stream of sensory input. The dynamics of sensory input changes with organism's behaviour and environmental context. The contextual variations may induce >100-fold change in the parameters of the stimulation that an animal experiences. Thus, it is vital for the organism to adapt to the new diet of stimulation. The response properties of neurons, in turn, dynamically adjust to the prevailing properties of sensory stimulation, a process known as “neuronal adaptation.” Neuronal adaptation is a ubiquitous phenomenon across all sensory modalities and occurs at different stages of processing from periphery to cortex. In spite of the wealth of research on contextual modulation and neuronal adaptation in visual and auditory systems, the neuronal and computational basis of sensory adaptation in somatosensory system is less understood. Here, we summarise the recent finding and views about the neuronal adaptation in the rodent whisker-mediated tactile system and further summarise the functional effect of neuronal adaptation on the response dynamics and encoding efficiency of neurons at single cell and population levels along the whisker-mediated touch system in rodents. Based on direct and indirect pieces of evidence presented here, we suggest sensory adaptation provides context-dependent functional mechanisms for noise reduction in sensory processing, salience processing and deviant stimulus detection, shift between integration and coincidence detection, band-pass frequency filtering, adjusting neuronal receptive fields, enhancing neural coding and improving discriminability around adapting stimuli, energy conservation, and disambiguating encoding of principal features of tactile stimuli.

Ketamine-xylazine anesthesia depth affects auditory neuronal responses in the lateral superior olive complex of the gerbil.

Studies of in vivo neuronal responses to auditory inputs in the superior olive complex (SOC) are usually done under anesthesia. However, little attention has been paid to the effect of anesthesia itself on response properties. Here, we assessed the effect of anesthesia depth under ketamine-xylazine anesthetics on auditory evoked response properties of lateral SOC neurons. Anesthesia depth was tracked by monitoring EEG spectral peak frequencies. An increase in anesthesia depth led to a decrease of spontaneous discharge activities and an elevated response threshold. The temporal responses to suprathreshold tones were also affected, with adapted responses reduced but peak responses unaffected. Deepening the anesthesia depth also increased first spike latency. However, spike jitter was not affected. Auditory brainstem responses to clicks confirmed that ketamine-xylazine anesthesia depth affects auditory neuronal activities and the effect on spike rate and spike timing persists through the auditory pathway. We concluded from those observations that ketamine-xylazine affects lateral SOC response properties depending on the anesthesia depth.NEW & NOTEWORTHY We studied how the depth of ketamine-xylazine anesthesia altered response properties of lateral superior olive complex neurons, and auditory brainstem evoked responses. Our results provide direct evidence that anesthesia depth affects auditory neuronal responses and reinforce the notion that both the anesthetics and the anesthesia depth should be considered when interpreting/comparing in vivo neuronal recordings.

Unilateral vestibular neurectomy induces a remodeling of somatosensory cortical maps.

Unilateral Vestibular Neurectomy (UVN) induces a postural syndrome whose compensation over time is underpinned by multimodal sensory substitution processes. However, at a chronic stage of compensation, UVN rats exhibit an enduring postural asymmetry expressed by an increase in the body weight on the ipsilesional paws. Given the anatomo-functional links between the vestibular nuclei and the primary somatosensory cortex (S1), we explored the interplay of vestibular and somatosensory cortical inputs following acute and chronic UVN. We determined whether the enduring imbalance in tactilo-plantar inputs impacts response properties of S1 cortical neurons and organizational features of somatotopic maps. We performed electrophysiological mapping of the hindpaw cutaneous representations in S1, immediately and one month after UVN. In parallel, we assessed the posturo-locomotor imbalance during the compensation process. UVN immediately induces an expansion of the cortical neuron cutaneous receptive fields (RFs) leading to a partial dedifferentiation of somatotopic maps. This effect was demonstrated for the ventral skin surface representations and was greater on the contralesional hindpaw for which the neuronal threshold to skin pressure strongly decreased. The RF enlargement was amplified for the representation of the ipsilesional hindpaw in relation to persistent postural asymmetries, but was transitory for the contralesional one. Our study shows, for the first time, that vestibular inputs exert a modulatory influence on S1 neuron's cutaneous responses. The lesion-induced cortical malleability highlights the influence of vestibular inputs on tactile processing related to postural control.

Predicting neuronal response properties from hemodynamic responses in the auditory cortex

Recent functional MRI (fMRI) studies have highlighted differences in responses to natural sounds along the rostral-caudal axis of the human superior temporal gyrus. However, due to the indirect nature of the fMRI signal, it has been challenging to relate these fMRI observations to actual neuronal response properties. To bridge this gap, we present a forward model of the fMRI responses to natural sounds combining a neuronal model of the auditory cortex with physiological modeling of the hemodynamic BOLD response. Neuronal responses are modeled with a dynamic recurrent firing rate model, reflecting the tonotopic, hierarchical processing in the auditory cortex along with the spectro-temporal tradeoff in the rostral-caudal axis of its belt areas. To link modeled neuronal response properties with human fMRI data in the auditory belt regions, we generated a space of neuronal models, which differed parametrically in spectral and temporal specificity of neuronal responses. Then, we obtained predictions of fMRI responses through a biophysical model of the hemodynamic BOLD response (P-DCM). Using Bayesian model comparison, our results showed that the hemodynamic BOLD responses of the caudal belt regions in the human auditory cortex were best explained by modeling faster temporal dynamics and broader spectral tuning of neuronal populations, while rostral belt regions were best explained through fine spectral tuning combined with slower temporal dynamics. These results support the hypotheses of complementary neural information processing along the rostral-caudal axis of the human superior temporal gyrus.

Corticothalamic Pathways in Auditory Processing: Recent Advances and Insights From Other Sensory Systems.

The corticothalamic (CT) pathways emanate from either Layer 5 (L5) or 6 (L6) of the neocortex and largely outnumber the ascending, thalamocortical pathways. The CT pathways provide the anatomical foundations for an intricate, bidirectional communication between thalamus and cortex. They act as dynamic circuits of information transfer with the ability to modulate or even drive the response properties of target neurons at each synaptic node of the circuit. L6 CT feedback pathways enable the cortex to shape the nature of its driving inputs, by directly modulating the sensory message arriving at the thalamus. L5 CT pathways can drive the postsynaptic neurons and initiate a transthalamic corticocortical circuit by which cortical areas communicate with each other. For this reason, L5 CT pathways place the thalamus at the heart of information transfer through the cortical hierarchy. Recent evidence goes even further to suggest that the thalamus via CT pathways regulates functional connectivity within and across cortical regions, and might be engaged in cognition, behavior, and perceptual inference. As descending pathways that enable reciprocal and context-dependent communication between thalamus and cortex, we venture that CT projections are particularly interesting in the context of hierarchical perceptual inference formulations such as those contemplated in predictive processing schemes, which so far heavily rely on cortical implementations. We discuss recent proposals suggesting that the thalamus, and particularly higher order thalamus via transthalamic pathways, could coordinate and contextualize hierarchical inference in cortical hierarchies. We will explore these ideas with a focus on the auditory system.

Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics.

Decades of neurobiological research have disclosed the diverse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysical properties of the neuron. However, changes in cognitive function do not arise directly from the modulation of individual neurons, but are mediated by population dynamics in mesoscopic neural ensembles. Understanding this multiscale mapping is an important but nontrivial issue. Here, we bridge these different levels of description by showing how computational models parametrically map classic neuromodulatory processes onto systems-level models of neural activity. The ensuing critical balance of systems-level activity supports perception and action, although our knowledge of this mapping remains incomplete. In this way, quantitative models that link microscale neuronal neuromodulation to systems-level brain function highlight gaps in knowledge and suggest new directions for integrating theoretical and experimental work.