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Spiking neural network (SNN) distinguish themselves from artificial neural network (ANN) because of their inherent temporal processing and spike-based computations, enabling a power-efficient implementation in neuromorphic hardware. In this study, we demonstrate that data processing with spiking neurons can be enhanced by co-learning the synaptic weights with two other biologically inspired neuronal features: (1) a set of parameters describing neuronal adaptation processes and (2) synaptic propagation delays. The former allows a spiking neuron to learn how to specifically react to incoming spikes based on its past. The trained adaptation parameters result in neuronal heterogeneity, which leads to a greater variety in available spike patterns and is also found in the brain. The latter enables to learn to explicitly correlate spike trains that are temporally distanced. Synaptic delays reflect the time an action potential requires to travel from one neuron to another. We show that each of the co-learned features separately leads to an improvement over the baseline SNN and that the combination of both leads to state-of-the-art SNN results on all speech recognition datasets investigated with a simple 2-hidden layer feed-forward network. Our SNN outperforms the benchmark ANN on the neuromorphic datasets (Spiking Heidelberg Digits and Spiking Speech Commands), even with fewer trainable parameters. On the 35-class Google Speech Commands dataset, our SNN also outperforms a GRU of similar size. Our study presents brain-inspired improvements in SNN that enable them to excel over an equivalent ANN of similar size on tasks with rich temporal dynamics. [ABSTRACT FROM AUTHOR]

Spiking neural network (SNN) distinguish themselves from artificial neural network (ANN) because of their inherent temporal processing and spike-based computations, enabling a power-efficient implementation in neuromorphic hardware. In this study, we demonstrate that data processing with spiking neurons can be enhanced by co-learning the synaptic weights with two other biologically inspired neuronal features: (1) a set of parameters describing neuronal adaptation processes and (2) synaptic propagation delays. The former allows a spiking neuron to learn how to specifically react to incoming spikes based on its past. The trained adaptation parameters result in neuronal heterogeneity, which leads to a greater variety in available spike patterns and is also found in the brain. The latter enables to learn to explicitly correlate spike trains that are temporally distanced. Synaptic delays reflect the time an action potential requires to travel from one neuron to another. We show that each of the co-learned features separately leads to an improvement over the baseline SNN and that the combination of both leads to state-of-the-art SNN results on all speech recognition datasets investigated with a simple 2-hidden layer feed-forward network. Our SNN outperforms the benchmark ANN on the neuromorphic datasets (Spiking Heidelberg Digits and Spiking Speech Commands), even with fewer trainable parameters. On the 35-class Google Speech Commands dataset, our SNN also outperforms a GRU of similar size. Our study presents brain-inspired improvements in SNN that enable them to excel over an equivalent ANN of similar size on tasks with rich temporal dynamics.

A model based on inhibitory coupling has been proposed to explain perceptual oscillations. This 'adapting reciprocal inhibition' model postulates that it is the strength of inhibitory coupling that determines the fate of competition between percepts. Here, we used an fMRI-based adaptation technique to reveal the influence of neighboring neuronal populations, such as reciprocal inhibition, in motion-selective hMT+/V5. If reciprocal inhibition exists in this region, the following predictions should hold: 1. stimulus-driven response would not simply decrease, as predicted by simple repetition-suppression of neuronal populations, but instead, increase due to the activity from adjacent populations; 2. perceptual decision involving competing representations, should reflect decreased reciprocal inhibition by adaptation; 3. neural activity for the competing percept should also later on increase upon adaptation. Our results confirm these three predictions, showing that a model of perceptual decision based on adapting reciprocal inhibition holds true. Finally, they also show that the net effect of the well-known repetition suppression phenomenon can be reversed by this mechanism.

Since humans still outperform artificial neural networks on many tasks, drawing inspiration from the brain may help to improve current machine learning algorithms. Contrastive Hebbian learning (CHL) and equilibrium propagation (EP) are biologically plausible algorithms that update weights using only local information (without explicitly calculating gradients) and still achieve performance comparable to conventional backpropagation. In this study, we augmented CHL and EP with Adjusted Adaptation, inspired by the adaptation effect observed in neurons, in which a neuron's response to a given stimulus is adjusted after a short time. We add this adaptation feature to multilayer perceptrons and convolutional neural networks trained on MNIST and CIFAR- 10. Surprisingly, adaptation improved the performance of these networks. We discuss the biological inspiration for this idea and investigate why Neuronal Adaptation could be an important brain mechanism to improve the stability and accuracy of learning. [ABSTRACT FROM AUTHOR]

Abstract Atopic dermatitis (AD) is highly comorbid with negative emotions such as anxiety and depression. Although acupuncture has demonstrated efficacy in AD, its influence on comorbid anxiety and depression remains unclear. We sought to explore the impact and mechanisms of action of acupuncture on comorbid anxiety and depression of AD. AD-like skin lesions were induced by the topical application of MC903 to the mouse cheek. Acupuncture was performed at Gok-Ji (LI11) acupoints. AD-like phenotypes were quantified by lesion scores, scratching behavior, and histopathological changes. The effects of acupuncture on comorbid anxiety and depression-like behaviors were assessed using the elevated plus-maze (EPM), open-field tests (OFT), and tail-suspension test (TST). In addition, biochemical changes in the brain reward regions were investigated by immunoblotting for the expression of tyrosine hydroxylase (TH), dopamine D1 receptor (D1R), phospho-dopamine and cAMP-regulated phosphoprotein-32 kDa (pDARPP-32), phospho-cAMP response element binding protein (pCREB), ΔFosB, and brain-derived neurotrophic factor (BDNF) in the nucleus accumbens, dorsolateral striatum, and ventral tegmental area. Acupuncture effectively improved the chronic itching and robust AD-like skin lesions with epidermal thickening. Additionally, it considerably reduced comorbid anxiety- and depression-like symptoms, as indicated by more time spent in the open arms of the EPM and in the center of the open field and less time spent immobile in the TST. Higher pCREB, ΔFosB, BDNF, and pDARPP-32 levels, and reduced TH and D1R protein expression in the brain reward regions of AD mice were reversed by acupuncture treatment. The beneficial effects of acupuncture on clinical symptoms (scratching behavior) and comorbid psychological distress in AD strongly correlated with dorsal striatal ΔFosB levels. Collectively, these data indicate that acupuncture had a significant, positive impact on comorbid anxiety- and depression-like behaviors by modulating neuroadaptation in the brain reward circuit in mice with AD, providing a novel perspective for the non-pharmacological management of psychiatric comorbidities of AD.

Atopic dermatitis (AD) is highly comorbid with negative emotions such as anxiety and depression. Although acupuncture has demonstrated efficacy in AD, its influence on comorbid anxiety and depression remains unclear. We sought to explore the impact and mechanisms of action of acupuncture on comorbid anxiety and depression of AD. AD-like skin lesions were induced by the topical application of MC903 to the mouse cheek. Acupuncture was performed at Gok-Ji (LI11) acupoints. AD-like phenotypes were quantified by lesion scores, scratching behavior, and histopathological changes. The effects of acupuncture on comorbid anxiety and depression-like behaviors were assessed using the elevated plus-maze (EPM), open-field tests (OFT), and tail-suspension test (TST). In addition, biochemical changes in the brain reward regions were investigated by immunoblotting for the expression of tyrosine hydroxylase (TH), dopamine D1 receptor (D1R), phospho-dopamine and cAMP-regulated phosphoprotein-32 kDa (pDARPP-32), phospho-cAMP response element binding protein (pCREB), ΔFosB, and brain-derived neurotrophic factor (BDNF) in the nucleus accumbens, dorsolateral striatum, and ventral tegmental area. Acupuncture effectively improved the chronic itching and robust AD-like skin lesions with epidermal thickening. Additionally, it considerably reduced comorbid anxiety- and depression-like symptoms, as indicated by more time spent in the open arms of the EPM and in the center of the open field and less time spent immobile in the TST. Higher pCREB, ΔFosB, BDNF, and pDARPP-32 levels, and reduced TH and D1R protein expression in the brain reward regions of AD mice were reversed by acupuncture treatment. The beneficial effects of acupuncture on clinical symptoms (scratching behavior) and comorbid psychological distress in AD strongly correlated with dorsal striatal ΔFosB levels. Collectively, these data indicate that acupuncture had a significant, positive impact on comorbid anxiety- and depression-like behaviors by modulating neuroadaptation in the brain reward circuit in mice with AD, providing a novel perspective for the non-pharmacological management of psychiatric comorbidities of AD. [ABSTRACT FROM AUTHOR]

Being able to correctly predict the future and to adjust own actions accordingly can offer a great survival advantage. In fact, this could be the main reason why brains evolved. Consciousness, the most mysterious feature of brain activity, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Similarly at a single neuron level, predicting future activity and adapting synaptic inputs accordingly was shown to be the best strategy to maximize the metabolic energy for a neuron. Following on these ideas, here we examined if surprise minimization by single neurons could be a basis for consciousness. First, we showed in simulations that as a neural network learns a new task, then the surprise within neurons (defined as the difference between actual and expected activity) changes similarly to the consciousness of skills in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of milliseconds) resulted in improved network performance. This improvement is likely because adapting activity based on the internal predictive model allows each neuron to make a more "educated" response to stimuli. Based on those results, we propose that the neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. Such adaptation allows neurons to exchange information about own predictions and thus to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this can allow testing directly our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational, and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness. [ABSTRACT FROM AUTHOR]

Being able to correctly predict the future and to adjust own actions accordingly can offer a great survival advantage. In fact, this could be the main reason why brains evolved. Consciousness, the most mysterious feature of brain activity, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Similarly at a single neuron level, predicting future activity and adapting synaptic inputs accordingly was shown to be the best strategy to maximize the metabolic energy for a neuron. Following on these ideas, here we examined if surprise minimization by single neurons could be a basis for consciousness. First, we showed in simulations that as a neural network learns a new task, then the surprise within neurons (defined as the difference between actual and expected activity) changes similarly to the consciousness of skills in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of milliseconds) resulted in improved network performance. This improvement is likely because adapting activity based on the internal predictive model allows each neuron to make a more “educated” response to stimuli. Based on those results, we propose that the neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. Such adaptation allows neurons to exchange information about own predictions and thus to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this can allow testing directly our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational, and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.

Purpose: To understand the mechanisms for the effects of resistance training on functional parameters, and to assess the injury risk of the involved tissues, it is necessary to examine the underlying morphological and structural changes of the respective tissues. Methods: The presented information on physiological adaptations have been deduced from cross-sectional studies comparing youth athletes with controls and children with adults as well as from longitudinal studies examining the effects of resistance training in untrained children and adolescents and in youth athletes. Results: The evidence indicates, that training induced changes in motor performance rely partly on enhanced neuromuscular control, and partly on morphological adaptation of muscles and tendons, such as changes in muscle, muscle fiber and tendon cross-sectional area, muscle composition, and tendon material properties, with the bone also adapting by increasing bone mineral content and cortical area. Conclusion: Although the training induced adaptations of the investigated tissues follows similar principles in children as in adults, the magnitude of the adaptive response appears to be more subtle. As studies investigating physiological adaptation in youth athletes are sparse, more research in this area is warranted to elucidate the specific physiological stimulus-response relationship necessary for effective training programs and injury prevention. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Central coordination of cardiovascular function is accomplished, in part, by the baroreceptor reflex, a multi-input multi-output physiological control system that regulates the activity of the parasympathetic and sympathetic nervous systems via interactions among multiple brainstem nuclei. Recent single-cell analyses within the brain revealed that individual neurons within and across brain nuclei exhibit distinct transcriptional states contributing to neuronal function. Such transcriptional heterogeneity complicates the task of understanding how neurons within and across brain nuclei organize and function to process multiple inputs and coordinate cardiovascular functions within the larger context of the baroreceptor reflex. However, prior analysis of brainstem neurons revealed that single-neuron transcriptional heterogeneity reflects an adaptive response to synaptic inputs and that neurons organize into distinct subtypes with respect to synaptic inputs received. Based on these results, we hypothesize that adaptation of neuronal subtypes support robust biological function through graded cellular responses. We test this hypothesis by examining the functional impact of neuronal adaptation on parasympathetic activity within the context of short-term baroreceptor reflex regulation. In this work, we extend existing quantitative closed-loop models of the baroreceptor reflex by incorporating into the model distinct input-driven neuronal subtypes and neuroanatomical groups that modulate parasympathetic activity. We then use this extended model to investigate, via simulation, the functional role of neuronal adaptation under conditions of health and systolic heart failure. Simulation results suggest that parasympathetic activity can be modulated appropriately by the coordination of distinct neuronal subtypes to maintain normal cardiovascular functions under systolic heart failure conditions. Moreover, differing degrees of adaptation of these neuronal subtypes contribute to cardiovascular behaviors corresponding to distinct clinical phenotypes of heart failure, such as exercise intolerance. Further, our results suggest that an imbalance between sympathetic and parasympathetic activity regulating ventricular contractility contributes to exercise intolerance in systolic heart failure patients, and restoring this balance can improve the short-term cardiovascular performance of these patients.

Foreground stimuli and task engagement enhance neuronal adaptation to background noise in the inferior colliculus of macaques. J Neurophysiol 124: 1315-1326, 2020. First published September 16, 2020; doi:10.1152/jn.00153.2020.--Auditory neuronal responses are modified by background noise. Inferior colliculus (IC) neuronal responses adapt to the most frequent sound level within an acoustic scene (adaptation to stimulus statistics), a mechanism that may preserve neuronal and behavioral thresholds for signal detection. However, it is still unclear whether the presence of foreground stimuli and/or task involvement can modify neuronal adaptation. To investigate how task engagement interacts with this mechanism, we compared the response of IC neurons to background noise, which caused adaptation to stimulus statistics, while macaque monkeys performed a masked tone detection task (taskdriven condition) with responses recorded when the same background noise was presented alone (passive listening condition). In the task-dependent condition, monkeys performed a Go/No-Go task while 50-ms tones were embedded within an adaptation-inducing continuous background noise whose levels changed every 50 ms and were drawn from a probability distribution. The adaptation to noise stimulus statistics in IC neuronal responses was significantly enhanced in the task-driven condition compared with the passive listening condition, showing that foreground stimuli and/or taskengagement can modify IC neuronal responses. Additionally, the response of IC neurons to noise was significantly affected by the preceding sensory information (history effect) regardless of task involvement. These studies show that dynamic range adaptation in IC preserves behavioral and neurometric thresholds irrespective of noise type and a dependence of neuronal activity on task-related factors at subcortical levels of processing. [ABSTRACT FROM AUTHOR]

Central coordination of cardiovascular function is accomplished, in part, by the baroreceptor reflex, a multi-input multi-output physiological control system that regulates the activity of the parasympathetic and sympathetic nervous systems via interactions among multiple brainstem nuclei. Recent single-cell analyses within the brain revealed that individual neurons within and across brain nuclei exhibit distinct transcriptional states contributing to neuronal function. Such transcriptional heterogeneity complicates the task of understanding how neurons within and across brain nuclei organize and function to process multiple inputs and coordinate cardiovascular functions within the larger context of the baroreceptor reflex. However, prior analysis of brainstem neurons revealed that single-neuron transcriptional heterogeneity reflects an adaptive response to synaptic inputs and that neurons organize into distinct subtypes with respect to synaptic inputs received. Based on these results, we hypothesize that adaptation of neuronal subtypes support robust biological function through graded cellular responses. We test this hypothesis by examining the functional impact of neuronal adaptation on parasympathetic activity within the context of short-term baroreceptor reflex regulation. In this work, we extend existing quantitative closed-loop models of the baroreceptor reflex by incorporating into the model distinct input-driven neuronal subtypes and neuroanatomical groups that modulate parasympathetic activity. We then use this extended model to investigate, via simulation, the functional role of neuronal adaptation under conditions of health and systolic heart failure. Simulation results suggest that parasympathetic activity can be modulated appropriately by the coordination of distinct neuronal subtypes to maintain normal cardiovascular functions under systolic heart failure conditions. Moreover, differing degrees of adaptation of these neuronal subtypes contribute to cardiovascular behaviors corresponding to distinct clinical phenotypes of heart failure, such as exercise intolerance. Further, our results suggest that an imbalance between sympathetic and parasympathetic activity regulating ventricular contractility contributes to exercise intolerance in systolic heart failure patients, and restoring this balance can improve the short-term cardiovascular performance of these patients. [ABSTRACT FROM AUTHOR]

The etiology of idiopathic pain conditions, such as Provoked vulvodynia (PV), is multifactorial. The efficiency of venlafaxine, serotonin-noradrenaline reuptake inhibitor (SNRIs) in modulating vulvar pain led to the hypothesis that PV might involve central mechanisms. Here, we investigate whether vulvar pain is associated with gene-expression changes in mood, stress and pain systems, including amygdala (Amg), medial prefrontal cortex (mPFC), and periaqueductal gray matter (PAG). Additionally, we examined the analgesic and anxiolytic effects of venlafaxine. We found that the development of chronic vulvar pain in an animal model of PV is associated by overexpression of genes related to neuronal-activity and neuroinflammation in the Amg, mPFC, and PAG. Additionally, changes in the expression of GABA and serotonin synthesis, and reuptake were noted in the Amg and mPFC. Unsurprisingly, anxiety-like behavior and emotional-disorder were observed in rats with chronic vulvar pain. Nevertheless, treatment with venlafaxine (37.5 mg/kg) for one month significantly improves the vulvar hypersensitivity, as well as reduces the anxiety level. More critically, the long-term gene expression adaptation in serotonin receptor and synthesis, GABA synthesis, neuroplasticity, and neuroinflammation in the Amg, mPFC, and PAG, were modulated by venlafaxine in rats with vulvar pain. Our findings suggest that vulvar hypersensitivity induced by inflammation might associated with gene expression changes in brain areas that are involved in mood, stress and pain regulation. These changes probably play a role in central sensitization, and anxiety. Strikingly, enhancing the activity of serotonin and noradrenaline via venlafaxine treatment in rats with vulvar pain induces analgesic and anxiolytic effects. • Provoked vulvodynia is an idiopathic pain condition characterized by vulvar pain. • Chronic vulvar pain (CVP) causes anxiety-like behavior and emotional-disorder in rats. • CVP associate with neuroinflammation in the mPFC, amygdala and PAG. • Venlafaxine (VLX) alleviates vulvar pain and anxiety in rats with CVP. • Gene-expression changes in 5HT, GABA synthesis and neuroinflammation modulated by VLX. [ABSTRACT FROM AUTHOR]

• fMRI-based adaptation, which has been developed as a tool to identify functional selectivity in the human brain, can also reveal the influence of neighboring neuronal populations. • Our data reveals neural evidence for a disinhibition effect as a result of the adaptation of adjacent populations, which is in line with the adapting reciprocal inhibition model. • Reciprocal inhibition can, thus, be tracked in the human brain using fMRI, adding to the understanding of human multistable perception and the neural coding of visual information. • Our results also provide a mechanism for reversal of repetition suppression effects. A model based on inhibitory coupling has been proposed to explain perceptual oscillations. This 'adapting reciprocal inhibition' model postulates that it is the strength of inhibitory coupling that determines the fate of competition between percepts. Here, we used an fMRI-based adaptation technique to reveal the influence of neighboring neuronal populations, such as reciprocal inhibition, in motion-selective hMT+/V5. If reciprocal inhibition exists in this region, the following predictions should hold: 1. stimulus-driven response would not simply decrease, as predicted by simple repetition-suppression of neuronal populations, but instead, increase due to the activity from adjacent populations; 2. perceptual decision involving competing representations, should reflect decreased reciprocal inhibition by adaptation; 3. neural activity for the competing percept should also later on increase upon adaptation. Our results confirm these three predictions, showing that a model of perceptual decision based on adapting reciprocal inhibition holds true. Finally, they also show that the net effect of the well-known repetition suppression phenomenon can be reversed by this mechanism. [ABSTRACT FROM AUTHOR]

Context, aftereffect, neuronal adaptation, neural network, salience detection, face adaptation, perceptual adaptation, sensory system Motion after-effects in cat striate cortex elicited by moving gratings. Quiroga et al., taking a computational approach, predicted that recurrent connections in a population of orientation selective neurons can give rise, over short time scales of a few hundred ms, to attractive perceptual aftereffects instead of commonly reported repulsive aftereffects. Keywords: context; neuronal adaptation; neural network; salience detection; aftereffect; perceptual adaptation; sensory system; face adaptation EN context neuronal adaptation neural network salience detection aftereffect perceptual adaptation sensory system face adaptation 1 3 3 12/13/21 20211208 NES 211208 In the natural word, organisms are constantly exposed to continuous streams of sensory input. [Extracted from the article]

Background: Impairments in working memory (WM) have been well documented in people with schizophrenia (PSZ). However, these quantitative WM impairments can often be explained by nonspecific factors, such as impaired goal maintenance. Here, we used a spatial orientation delayed response task to explore a qualitative difference in WM dynamics between PSZ and healthy control participants (HCs). More specifically, we took advantage of the discovery that WM representations may drift either toward or away from previous trial targets (serial dependence). We tested the hypothesis that WM representations would drift toward the previous trial target in HCs but away from the previous trial target in PSZ., Methods: We assessed serial dependence in PSZ (n = 31) and HCs (n = 25) using orientation as the to-be-remembered feature and memory delays lasting from 0 to 8 seconds. Participants were asked to remember the orientation of a teardrop-shaped object and reproduce the orientation after a delay period of varying length., Results: Consistent with prior studies, we found that current trial memory representations were less precise in PSZ than in HCs. We also found that WM for the current trial orientation drifted toward the previous trial orientation in HCs (representational attraction) but drifted away from the previous trial orientation in PSZ (representational repulsion)., Conclusions: These results demonstrate a qualitative difference in WM dynamics between PSZ and HCs that cannot be easily explained by nuisance factors such as reduced effort. Most computational neuroscience models also fail to explain these results because they maintain information solely by means of sustained neural firing, which does not extend across trials. The results suggest a fundamental difference between PSZ and HCs in longer-term memory mechanisms that persist across trials, such as short-term potentiation and neuronal adaptation., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The detectability of target sounds embedded within noisy backgrounds is affected by the regularities that summarize acoustic sceneries. Previous studies suggested that the dynamic range of neurons in the inferior colliculus (IC) of anesthetized guinea pigs shifts toward the mean sound pressure level in irregular acoustic environments. Yet, it is unclear how this neuronal adaptation processes may influence the effectiveness of sounds as a masker, both behaviorally and in terms of neuronal encoding. To answer this question, we measured the neural response of IC neurons while macaque monkeys performed a Go/No-Go tone detection task. Macaques detected a 50-ms tone that was either simultaneously gated with a burst of noise or embedded within a continuous noise background, whose levels were randomly sampled (every 50 ms) from a probability distribution. The mean of the distribution matched the level of the gated burst of noise. Psychometric and IC neurometric thresholds to tones did not differ between the two masking conditions. However, the neuronal firing rate versus level function was significantly affected by the temporal characteristics of the noise masker. Simultaneously gated noise caused higher baseline responses and greater dynamic range compression compared with noise distribution. The slopes of psychometric and neurometric functions were significantly shallower for higher variance distributions, suggesting that neuronal sensitivity might change with the variability of the sound. Our results suggest that the adaptive response of IC neurons to sound regularities does not affect the effectiveness of the noise-masking signal, which remains invariant to surrounding noise amplitudes. NEW & NOTEWORTHY Auditory neurons adapt to the statistics of sound levels in the acoustic scene. However, it is still unclear to what extent such adaptation influences the effectiveness of the stimulus as a masker. Our study represents the first attempt to investigate how the adaptation to the statistics of masking stimuli may be related to the effectiveness of masking, and to the single-unit encoding of the midbrain auditory neurons in behaving animals. [ABSTRACT FROM AUTHOR]

Hemodynamic responses, in general, and the blood oxygenation level-dependent (BOLD) fMRI signal, in particular, provide an indirect measure of neuronal activity. There is strong evidence that the BOLD response correlates well with post-synaptic changes, induced by changes in the excitatory and inhibitory (E-I) balance between active neuronal populations. Typical BOLD responses exhibit transients, such as the early-overshoot and post-stimulus undershoot, that can be linked to transients in neuronal activity, but they can also result from vascular uncoupling between cerebral blood flow (CBF) and venous cerebral blood volume (venous CBV). Recently, we have proposed a novel generative hemodynamic model of the BOLD signal within the dynamic causal modeling framework, inspired by physiological observations, called P-DCM (Havlicek et al., 2015). We demonstrated the generative model's ability to more accurately model commonly observed neuronal and vascular transients in single regions but also effective connectivity between multiple brain areas (Havlicek et al., 2017b). In this paper, we additionally demonstrate the versatility of the generative model to jointly explain dynamic relationships between neuronal and hemodynamic physiological variables underlying the BOLD signal using multi-modal data. For this purpose, we utilized three distinct data-sets of experimentally induced responses in the primary visual areas measured in human, cat, and monkey brain, respectively: (1) CBF and BOLD responses; (2) CBF, total CBV, and BOLD responses (Jin and Kim, 2008); and (3) positive and negative neuronal and BOLD responses (Shmuel et al., 2006). By fitting the generative model to the three multi-modal experimental data-sets, we showed that the presence or absence of dynamic features in the BOLD signal is not an unambiguous indication of presence or absence of those features on the neuronal level. Nevertheless, the generative model that takes into account the dynamics of the physiological mechanisms underlying the BOLD response allowed dissociating neuronal from vascular transients and deducing excitatory and inhibitory neuronal activity time-courses from BOLD data alone and from multi-modal data.

Hemodynamic responses, in general, and the blood oxygenation level-dependent (BOLD) fMRI signal, in particular, provide an indirect measure of neuronal activity. There is strong evidence that the BOLD response correlates well with post-synaptic changes, induced by changes in the excitatory and inhibitory (E-I) balance between active neuronal populations. Typical BOLD responses exhibit transients, such as the early-overshoot and post-stimulus undershoot, that can be linked to transients in neuronal activity, but they can also result from vascular uncoupling between cerebral blood flow (CBF) and venous cerebral blood volume (venous CBV). Recently, we have proposed a novel generative hemodynamic model of the BOLD signal within the dynamic causal modeling framework, inspired by physiological observations, called P-DCM (Havlicek et al., 2015). We demonstrated the generative model's ability to more accurately model commonly observed neuronal and vascular transients in single regions but also effective connectivity between multiple brain areas (Havlicek et al., 2017b). In this paper, we additionally demonstrate the versatility of the generative model to jointly explain dynamic relationships between neuronal and hemodynamic physiological variables underlying the BOLD signal using multi-modal data. For this purpose, we utilized three distinct data-sets of experimentally induced responses in the primary visual areas measured in human, cat, and monkey brain, respectively: (1) CBF and BOLD responses; (2) CBF, total CBV, and BOLD responses (Jin and Kim, 2008); and (3) positive and negative neuronal and BOLD responses (Shmuel et al., 2006). By fitting the generative model to the three multi-modal experimental data-sets, we showed that the presence or absence of dynamic features in the BOLD signal is not an unambiguous indication of presence or absence of those features on the neuronal level. Nevertheless, the generativemodel that takes into account the dynamics of the physiological mechanisms underlying the BOLD response allowed dissociating neuronal from vascular transients and deducing excitatory and inhibitory neuronal activity time-courses from BOLD data alone and from multi-modal data. [ABSTRACT FROM AUTHOR]

The question of why males of many species produce elaborate mating displays has now been largely resolved: females prefer to mate with males that produce such displays. However, the question of why females prefer such displays has been controversial, with an emerging consensus that such displays often provide information to females about the direct fitness benefits that males provide to females and/or the indirect fitness benefits provided to offspring. Alternative explanations, such as production of arbitrarily attractive sons or innate pre-existing female sensory or perceptual bias, have also received support in certain taxa. Here, we describe multivariate female preference functions for male acoustic traits in two chirping species of field crickets with slow pulse rates; our data reveal cryptic female preferences for long trills that have not previously been observed in other chirping species. The trill preferences are evolutionarily pre-existing in the sense that males have not (yet?) exploited them, and they coexist with chirp preferences as alternative stable states within female song preference space. We discuss escape from neuronal adaptation as a possible mechanism underlying such latent preferences. [ABSTRACT FROM AUTHOR]

Over the last two decades, functional magnetic resonance imaging (fMRI) has become a powerful research method to investigate cortical visual plasticity. Abnormal fMRI response patterns have been occasionally detected in the visually deprived cortex of patients with bilateral retinal diseases. Controversy remains whether these observations indicate structural reorganization of the visual cortex or unmasking of previously silent cortico-cortical connections. In optic nerve diseases, there is weak evidence showing that early visual cortex seems to lack reorganization, while higher-order visual areas undergo plastic changes which may contribute to optimise visual function. There is however accumulating imaging evidence demonstrating trans-synaptic degeneration of the visual cortex in patients with disease of the anterior visual pathways. This may preclude the use of restorative treatments in these patients. Here, we review and update the body of fMRI evidence on visual cortical plasticity. [ABSTRACT FROM AUTHOR]

Since humans still outperform artificial neural networks on many tasks, drawing inspiration from the brain may help to improve current machine learning algorithms. Contrastive Hebbian learning (CHL) and equilibrium propagation (EP) are biologically plausible algorithms that update weights using only local information (without explicitly calculating gradients) and still achieve performance comparable to conventional backpropagation. In this study, we augmented CHL and EP with Adjusted Adaptation , inspired by the adaptation effect observed in neurons, in which a neuron's response to a given stimulus is adjusted after a short time. We add this adaptation feature to multilayer perceptrons and convolutional neural networks trained on MNIST and CIFAR-10. Surprisingly, adaptation improved the performance of these networks. We discuss the biological inspiration for this idea and investigate why Neuronal Adaptation could be an important brain mechanism to improve the stability and accuracy of learning., Competing Interests: No potential conflict of interest was reported by the authors., (© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)

Voltage-gated K+ channels of the Shaw family (also known as the KCNC or Kv3 family) play pivotal roles in mammalian brains, and genetic or pharmacological disruption of their activities in mice results in a spectrum of behavioral defects. We have used the model system of Caenorhabditis elegans to elucidate conserved molecular mechanisms that regulate these channels. We have now found that the C. elegans Shaw channel KHT-1, and its mammalian homologue, murine Kv3.1b, are both modulated by acid phosphatases. Thus, the C. elegans phosphatase ACP-2 is stably associated with KHT-1, while its mammalian homolog, prostatic acid phosphatase (PAP; also known as ACPP-201) stably associates with murine Kv3.1b K+ channels in vitro and in vivo. In biochemical experiments both phosphatases were able to reverse phosphorylation of their associated channel. The effect of phosphorylation on both channels is to produce a decrease in current amplitude and electrophysiological analyses demonstrated that dephosphorylation reversed the effects of phosphorylation on the magnitude of the macroscopic currents. ACP-2 and KHT-1 were colocalized in the nervous system of C. elegans and, in the mouse nervous system, PAP and Kv3.1b were colocalized in subsets of neurons, including in the brain stem and the ventricular zone. Taken together, this body of evidence suggests that acid phosphatases are general regulatory partners of Shaw-like K+ channels. [ABSTRACT FROM AUTHOR]

Locomotor activity like walking or flying has recently been shown to alter visual processing in several species. In insects, the neuromodulator octopamine is thought to play an important role in mediating state changes during locomotion of the animal [K.D. Longden & H.G. Krapp (2009) J. Neurophysiol., 102, 3606-3618; (2010) Front. Syst. Neurosci., 4, 153; S.N. Jung et al. (2011) J. Neurosci., 31, 9231-9237]. Here, we used the octopamine agonist chlordimeform (CDM) to mimic effects of behavioural state changes on visual motion processing. We recorded from identified motion-sensitive visual interneurons in the lobula plate of the blowfly Calliphora vicina. In these neurons, which are thought to be involved in visual guidance of locomotion, motion adaptation leads to a prominent attenuation of contrast sensitivity. Following CDM application, the neurons maintained high contrast sensitivity in the adapted state. This modulation of contrast gain adaptation was independent of the activity of the recorded neurons, because it was also present after stimulation with visual motion that did not result in deviations from the neurons' resting activity. We conclude that CDM affects presynaptic inputs of the recorded neurons. Accordingly, the effect of CDM was weak when adapting and test stimuli were presented in different parts of the receptive field, stimulating separate populations of local presynaptic neurons. In the peripheral visual system adaptation depends on the temporal frequency of the stimulus pattern and is therefore related to pattern velocity. Contrast gain adaptation could therefore be the basis for a shift in the velocity tuning that was previously suggested to contribute to state-dependent processing of visual motion information in the lobula plate interneurons. [ABSTRACT FROM AUTHOR]

Neuronal mechanisms of auditory distance perception are poorly understood, largely because contributions of intensity and distance processing are difficult to differentiate. Typically, the received intensity increases when sound sources approach us. However, we can also distinguish between soft-but-nearby and loud-but-distant sounds, indicating that distance processing can also be based on intensity-independent cues. Here, we combined behavioral experiments, fMRI measurements, and computational analyses to identify the neural representation of distance independent of intensity. In a virtual reverberant environment, we simulated sound sources at varying distances (15-100 cm) along the right-side interaural axis. Our acoustic analysis suggested that, of the individual intensity-independent depth cues available for these stimuli, direct-to-reverberant ratio (D/R) is more reliable and robust than interaural level difference (ILD). However, on the basis of our behavioral results, subjects' discrimination performance was more consistent with complex intensity-independent distance representations, combining both available cues, than with representations on the basis of either D/R or ILD individually. fMRI activations to sounds varying in distance (containing all cues, including intensity), compared with activations to sounds varying in intensity only, were significantly increased in the planum temporale and posterior superior temporal gyrus contralateral to the direction of stimulation. This fMRI result suggests that neurons in posterior nonprimary auditory cortices, in or near the areas processing other auditory spatial features, are sensitive to intensity-independent sound properties relevant for auditory distance perception. [ABSTRACT FROM AUTHOR]

Adaptation changes in the corticospinal mechanisms of muscle contraction control in athletes were investigated. Using the transcranial magnetic stimulation method, the parameters of motor evoked potentials of skeletal muscles of the lower limbs during voluntary static loads of various intensities and durations were measured. Athletes, as compared to the reference group, exhibited a greater increase in the maximal amplitude of the motor evoked potentials of the skeletal muscles of the lower limbs, a smaller decrease in the central motor conduction time of nerve pulses and the peripheral period in electromyograms, and a smaller increase in the cortical and segmental silent periods with increasing intensity and duration of isometric muscle contractions. The mechanisms of adaptation of corticospinal regulation of human muscle contraction to specific conditions of extreme motor activities are discussed. [ABSTRACT FROM AUTHOR]

Here, we characterize a new K+ channel–kinase complex that operates in the metazoan Caenorhabditis elegans to control learning behaviour. This channel is composed of a pore-forming subunit, dubbed KHT-1 (73% homology to human Kv3.1), and the accessory subunit MPS-1, which shows kinase activity. Genetic, biochemical and electrophysiological evidence show that KHT-1 and MPS-1 form a complex in vitro and in native mechanosensory PLM neurons, and that KHT-1 is a substrate for the kinase activity of MPS-1. Behavioural analysis further shows that the kinase activity of MPS-1 is specifically required for habituation to repetitive mechanical stimulation. Thus, worms bearing an inactive MPS-1 variant (D178N) respond normally to touch on the body but do not habituate to repetitive mechanical stimulation such as tapping on the side of the Petri dish. Hence, the phosphorylation status of KHT-1–MPS-1 seems to be linked to distinct behavioural responses. In the non-phosphorylated state the channel is necessary for the normal function of the touch neurons. In the auto-phosphorylated state the channel acts to induce neuronal adaptation to mechanical stimulation. Taken together, these data establish a new mechanism of dynamic regulation of electrical signalling in the nervous system. [ABSTRACT FROM AUTHOR]

Sensory neurons adapt to changes in the natural statistics of their environments through processes such as gain control and firing threshold adjustment. It has been argued that neurons early in sensory pathways adapt according to information-theoretic criteria, perhaps maximising their coding efficiency or information rate. Here, we draw a distinction between how a neuron's preferred operating point is determined and how its preferred operating point is maintained through adaptation. We propose that a neuron's preferred operating point can be characterised by the probability density function (PDF) of its output spike rate, and that adaptation maintains an invariant output PDF, regardless of how this output PDF is initially set. Considering a sigmoidal transfer function for simplicity, we derive simple adaptation rules for a neuron with one sensory input that permit adaptation to the lower-order statistics of the input, independent of how the preferred operating point of the neuron is set. Thus, if the preferred operating point is, in fact, set according to information-theoretic criteria, then these rules nonetheless maintain a neuron at that point. Our approach generalises from the unimodal case to the multimodal case, for a neuron with inputs from distinct sensory channels, and we briefly consider this case too. [ABSTRACT FROM AUTHOR]

Abstract: The response of the rat visual system to flashes of blue light has been studied by blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI). The BOLD temporal response is dependent on the number of flashes presented and demonstrates a refractory period that depends on flash frequency. Activated brain regions included the primary and secondary visual cortex, superior colliculus (SC), dorsal lateral geniculate (DLG), and lateral posterior nucleus (LP), which were found to exhibit differing temporal responses. To explain these differences, the BOLD neurovascular response function was modeled. A second-order differential equation was developed and solved numerically to arrive at region-specific response functions. Included in the model are the light input from the diode (duty cycle), a refractory period, a transient response following onset and cessation of stimulus, and a slow adjustment to changes in the average level of the signal. Constants in the differential equation were evaluated for each region by fitting the model to the experimental BOLD response from a single flash, and the equation was then solved for multiple flashes. The simulation mimics the major features of the data; however, remaining differences in the frequency dependence of the response between the cortical and subcortical regions were unexplained. We hypothesized that these discrepancies were due to regional-specific differences in neuronal response to flash frequency. To test this hypothesis, cortical visual evoked potentials (VEPs) were recorded using the same stimulation protocol as the fMRI. Cortical VEPs were more suppressed than subcortical VEPs as flash frequency increased, supporting our hypothesis. This is the first report that regional differences in neuronal activation to the same stimulus lead to differential BOLD activation. [Copyright &y& Elsevier]

Abstract: The occurrence of perceived reversed motion while observers view a continuous, periodically moving stimulus (a bistable phenomenon coined the “continuous Wagon Wheel Illusion” or “c-WWI”) has been taken as evidence that some aspects of motion perception rely on discrete sampling of visual information. Alternative accounts rely on the possibility of a motion aftereffect that may become visible even while the adapting stimulus is present. Here I show that motion adaptation might be necessary, but is not sufficient to explain the illusion. When local adaptation is prevented by slowly drifting the moving wheel across the retina, the c-WWI illusion tends to decrease, as do other bistable percepts (e.g. binocular rivalry). However, the strength of the c-WWI and that of adaptation (as measured by either the static or flicker motion aftereffects) are not directly related: although the c-WWI decreases with increasing eccentricity, the aftereffects actually intensify concurrently. A similar dissociation can be induced by manipulating stimulus contrast. This indicates that the c-WWI may be enabled by, but is not equivalent to, local motion adaptation – and that other factors such as discrete sampling may be involved in its generation. [Copyright &y& Elsevier]

A biophysical model of a neocortical microcircuit system is formulated and employed in studies of neuromodulatory control of dynamics and function. The model is based on recent observations of reciprocal connections between pyramidal cells and inhibitory interneurons and incorporates a new type of activity-dependent short-term depression of synaptic couplings recently observed. The model neurons are of a low-dimensional type also accounting for neuronal adaptation, i.e. the coupling between neuronal activity and excitability, which can be regulated by various neuromodulators in the brain. The results obtained demonstrate a capacity for neuromodulatory control of dynamical mode linked to functional mode. The functional aspects considered refer to the observed resolution of multiple objects in working memory as well as the binding of different features for the perception of an object. The effects of neuromodulators displayed by the model are in accordance with many observations on neuromodulatory influence on cognitive functions and brain disorders. [ABSTRACT FROM AUTHOR]

Anterior piriform cortex (aPCX) neurons rapidly filter repetitive odor stimuli despite relatively maintained input from mitral cells. This cortical adaptation is correlated with short-term depression of afferent synapses, in vivo. The purpose of this study was to elucidate mechanisms underlying this nonassociative neural plasticity using in vivo and in vitro preparations and to determine its role in cortical odor adaptation. Lateral olfactory tract (LOT)-evoked responses were recorded in rat aPCX coronal slices. Extracellular and intracellular potentials were recorded before and after simulated odor stimulation of the LOT. Results were compared with in vivo intracellular recordings from aPCX layer II/III neurons and field recordings in urethane-anesthetized rats stimulated with odorants. The onset, time course, and extent of LOT synaptic depression during both in vitro electrical and in vivo odorant stimulation methods were similar. Similar to the odor specificity of cortical odor adaptation in vivo, there was no evidence of heterosynaptic depression between independent inputs in vitro. In vitro evidence suggests at least two mechanisms contribute to this activity-dependent synaptic depression: a rapidly recovering presynaptic depression during the initial 10-20 sec of the post-train recovery period and a longer lasting (∼120 sec) depression that can be blocked by the metabotropic glutamate receptor (mGluR) II/III antagonist (RS)-α-cyclopropyl-4-phosphonophenylglycine (CPPG) and by the β-adrenergic receptor agonist isoproterenol. Importantly, in line with the in vitro findings, both adaptation of odor responses in the β (15-35 Hz) spectral range and the associated synaptic depression can also be blocked by intracortical infusion of CPPG in vivo. [ABSTRACT FROM AUTHOR]

Adult neurons possess the ability to adapt to a changing environment. Loss of target-derived neurotrophic factors due to axotomy or isolation by culturing is known to induce changes in neuropeptide expression in several types of peripheral neurons. The aim of the present study was to investigate changes in the expression of vasoactive intestinal polypeptide (VIP) and nitric oxide synthase (NOS) in cultured myenteric ganglia and dissociated neurons. Myenteric ganglia and neurons from rat small intestine were dissociated and cultured for up to 21 days. Immunocytochemistry was used to determine the total number of neurons and the proportions of subpopulations containing VIP or NOS or both in preparations of whole mounts (controls used to determine the conditions in vivo), myenteric ganglion culture and dissociated myenteric neuronal culture. In situ hybridization was used to determine changes in the expressions of NOS and VIP mRNA. The relative number of VIP-expressing neurons increased significantly during culturing. The percentage of all neurons expressing VIP was 3.6±0.3% in whole mounts, 22–24% in cultured myenteric ganglia, and up to 35% in cultured dissociated neurons. NOS-expressing neurons constituted approximately 30–40% of all neurons in whole mounts as well as in cultured ganglia or dissociated neurons. A dramatic increase in NOS/VIP-containing neurons were detected in cultured neurons irrespective of whether they were arranged in ganglia or dissociated, as compared to whole mount preparations. This suggests that the NOS-containing neurons are the ones that increase their VIP expression. The induced expression of VIP in cultured adult myenteric neurons indicates that VIP is important for neuronal adaptation, maintenance and survival. [Copyright &y& Elsevier]