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Hallucinations and perceptual abnormalities in psychosis are thought to arise from imbalanced integration of prior information and sensory inputs. We combined psychophysics, Bayesian modeling, and electroencephalography (EEG) to investigate potential changes in perceptual and causal inference in response to audiovisual flash-beep sequences in medicated individuals with schizophrenia who exhibited limited psychotic symptoms. Seventeen participants with schizophrenia and 23 healthy controls reported either the number of flashes or the number of beeps of audiovisual sequences that varied in their audiovisual numeric disparity across trials. Both groups balanced sensory integration and segregation in line with Bayesian causal inference rather than resorting to simpler heuristics. Both also showed comparable weighting of prior information regarding the signals' causal structure, although the schizophrenia group slightly overweighted prior information about the number of flashes or beeps. At the neural level, both groups computed Bayesian causal inference through dynamic encoding of independent estimates of the flash and beep counts, followed by estimates that flexibly combine audiovisual inputs. Our results demonstrate that the core neurocomputational mechanisms for audiovisual perceptual and causal inference in number estimation tasks are largely preserved in our limited sample of medicated post-acute individuals with schizophrenia. Future research should explore whether these findings generalize to unmedicated patients with acute psychotic symptoms. Hallucinations and perceptual abnormalities in psychosis are thought to arise from imbalanced integration of prior information and sensory inputs. This study shows that the neurocomputational mechanisms of multisensory perceptual and causal inference remain remarkably intact in schizophrenia. [ABSTRACT FROM AUTHOR]

Trunk control involves integration of sensorimotor information in the brain. Individuals with chronic low back pain (cLBP) have impaired trunk control and show differences in brain structure and function in sensorimotor areas compared with healthy controls (HC). However, the relationship between brain structure and trunk control in this group is not well understood. This cross-sectional study aimed to compare seated trunk control and sensorimotor white matter (WM) structure in people with cLBP and HC and explore relationships between WM properties and trunk control in each group. Thirty-two people with cLBP and 35 HC were tested sitting on an unstable chair to isolate trunk control; performance was measured using the 95% confidence ellipse area (CEA95) of center-of-pressure tracing. A WM network between cortical sensorimotor regions of interest was derived using probabilistic tractography. WM microstructure and anatomical connectivity between cortical sensorimotor regions were assessed. A mixed-model ANOVA showed that people with cLBP had worse trunk control than HC (F = 12.96; p <.001; ηp2 =.091). There were no differences in WM microstructure or anatomical connectivity between groups (p = 0.564 to 0.940). In the cLBP group, WM microstructure was moderately correlated (|r| =.456 to.565; p ≤.009) with trunk control. Additionally, the cLBP group demonstrated stronger relationships between anatomical connectivity and trunk control (|r| =.377 to.618 p <.034) compared to the HC group. Unique to the cLBP group, WM connectivity between right somatosensory and left motor areas highlights the importance of interhemispheric information exchange for trunk control. Parietal areas associated with attention and spatial reference frames were also relevant to trunk control. These findings suggest that people with cLBP adopt a more cortically driven sensorimotor integration strategy for trunk control. Future research should replicate these findings and identify interventions to effectively modulate this strategy. [ABSTRACT FROM AUTHOR]

Inhibitory circuits in the mammalian olfactory bulb (OB) dynamically reformat olfactory information as it propagates from peripheral receptors to downstream cortex. To gain mechanistic insight into how specific OB interneuron types support this sensory processing, we examine unitary synaptic interactions between excitatory mitral and tufted cells (MTCs), the OB projection neurons, and a conserved population of anaxonic external plexiform layer interneurons (EPL-INs) using pair and quartet whole-cell recordings in acute mouse brain slices. Physiological, morphological, neurochemical, and synaptic analyses divide EPL-INs into distinct subtypes and reveal that parvalbumin-expressing fast-spiking EPL-INs (FSIs) perisomatically innervate MTCs with release-competent dendrites and synaptically detonate to mediate fast, short-latency recurrent and lateral inhibition. Sparse MTC synchronization supralinearly increases this high-fidelity inhibition, while sensory afferent activation combined with single-cell silencing reveals that individual FSIs account for a substantial fraction of total network-driven MTC lateral inhibition. OB output is thus powerfully shaped by detonation-driven high-fidelity perisomatic inhibition. Inhibitory circuits in the mammalian olfactory bulb shape information as it propagates from peripheral receptors to the downstream cortex. This study reveals that fast-spiking interneurons perisomatically inhibit projection neurons in the mammalian olfactory bulb via synaptic detonation. [ABSTRACT FROM AUTHOR]

Standing up from a chair is a key daily life activity that is sensitive to functional limitations as we age and associated with falls, frailty, and institutional living. Predictive neuromusculoskeletal models can potentially shed light on the interconnectivity and interdependency of age-related changes in neuromuscular capacity, reinforcement schemes, sensory integration, and adaptation strategies during stand-up. Most stand-up movements transfer directly into walking (sit-to-walk). The aim of this study was to develop and validate a neuromusculoskeletal model with reflex-based muscle control that enables simulation of the sit-to-walk movement under various conditions (seat height, foot placement). We developed a planar sit-to-walk musculoskeletal model (11 degrees-of-freedom, 20 muscles) and neuromuscular controller, consisting of a two-phase stand-up controller and a reflex-based gait controller. The stand-up controller contains generic neural pathways of delayed proprioceptive feedback from muscle length, force, velocity, and upper-body orientation (vestibular feedback) and includes both monosynaptic an antagonistic feedback pathways. The control parameters where optimized using a shooting-based optimization method, based on a high-level optimization criterium. Simulations were compared to recorded kinematics, ground reaction forces, and muscle activation. The simulated kinematics resemble the measured kinematics and muscle activations. The adaptation strategies that resulted from alterations in seat height, are comparable to those observed in adults. The simulation framework and model are publicly available and allow to study age-related compensation strategies, including reduced muscular capacity, reduced neural capacity, external perturbations, and altered movement objectives. [ABSTRACT FROM AUTHOR]

The processing of sensory information, even at early stages, is influenced by the internal state of the animal. Internal states, such as arousal, are often characterized by relating neural activity to a single "level" of arousal, defined by a behavioral indicator such as pupil size. In this study, we expand the understanding of arousal-related modulations in sensory systems by uncovering multiple timescales of pupil dynamics and their relationship to neural activity. Specifically, we observed a robust coupling between spiking activity in the mouse dorsolateral geniculate nucleus (dLGN) of the thalamus and pupil dynamics across timescales spanning a few seconds to several minutes. Throughout all these timescales, 2 distinct spiking modes—individual tonic spikes and tightly clustered bursts of spikes—preferred opposite phases of pupil dynamics. This multi-scale coupling reveals modulations distinct from those captured by pupil size per se, locomotion, and eye movements. Furthermore, coupling persisted even during viewing of a naturalistic movie, where it contributed to differences in the encoding of visual information. We conclude that dLGN spiking activity is under the simultaneous influence of multiple arousal-related processes associated with pupil dynamics occurring over a broad range of timescales. Pupil size can be used as an indicator of arousal, but how it relates to spontaneous and stimulus driven neural activity is not well understood. This study uncovers multiple timescales of pupil dynamics and characterizes their relationship to neural activity in mice. [ABSTRACT FROM AUTHOR]

Introduction: Developmental coordination disorder (DCD) is one of the most prevalent pediatric chronic conditions. Without proper intervention, significant delays in motor skill performance and learning may persist until adulthood. Moderate-to-vigorous physical exercise has been proven to improve motor learning (adaptation and consolidation) in children with or without disorders. However, the effect of a short bout of physical exercise on motor adaptation and consolidation in children with DCD has not been examined. Furthermore, the role of perceptual-motor integration and attention as mediators of learning has not been examined via neuroimaging in this population. Objectives: Therefore, the primary aims of this project will be to compare children with and without DCD to (a) examine the effect of acute exercise on motor learning (adaptation and consolidation) while performing a rotational visuo-motor adaptation task (rVMA), and (b) explore cortical activation in the dorsolateral- and ventrolateral-prefrontal cortex areas while learning the rVMA task under rest or post-exercise conditions. Methods: One hundred twenty children will be recruited (60 DCD, 60 controls) and within-cohort randomly assigned to either exercise (13-minute shuttle run task) or rest prior to performing the rVMA task. Adaptation and consolidation will be evaluated via two error variables and three retention tests (1h, 24h and 7 days post adaptation). Cortical activation will be registered via functional near-infrared spectroscopy (fNIRS) during the baseline, adaptation, and consolidation. Discussion: We expect to find exercise benefits on motor learning and attention so that children with DCD profiles will be closer to those of children with typical development. The results of this project will provide further evidence to: (a) better characterize children with DCD for the design of educational materials, and (b) establish acute exercise as a potential intervention to improve motor learning and attention. [ABSTRACT FROM AUTHOR]

In an ever-changing visual world, animals' survival depends on their ability to perceive and respond to rapidly changing motion cues. The primary visual cortex (V1) is at the forefront of this sensory processing, orchestrating neural responses to perturbations in visual flow. However, the underlying neural mechanisms that lead to distinct cortical responses to such perturbations remain enigmatic. In this study, our objective was to uncover the neural dynamics that govern V1 neurons' responses to visual flow perturbations using a biologically realistic computational model. By subjecting the model to sudden changes in visual input, we observed opposing cortical responses in excitatory layer 2/3 (L2/3) neurons, namely, depolarizing and hyperpolarizing responses. We found that this segregation was primarily driven by the competition between external visual input and recurrent inhibition, particularly within L2/3 and L4. This division was not observed in excitatory L5/6 neurons, suggesting a more prominent role for inhibitory mechanisms in the visual processing of the upper cortical layers. Our findings share similarities with recent experimental studies focusing on the opposing influence of top-down and bottom-up inputs in the mouse primary visual cortex during visual flow perturbations. Author summary: This study aims to shed light on the intricate dynamics of neural responses within the mouse primary visual cortex (V1) subjected to visual flow perturbations, unraveling the emergence of distinct functional classes of excitatory L2/3 neurons, namely depolarizing (dVf) and hyperpolarizing (hVf) neurons. Through the implementation of a biologically realistic computational model, the investigation highlights the profound impact of synaptic connectivity, inhibitory circuits, and dynamic inputs on shaping these responses. The identified competition by common inhibition mechanism between dVf and hVf neurons, driven not only by long-range thalamic inputs but also by local connectivity, provides new insights into the underlying neural circuitry. This study opens avenues for further exploration into the role of locomotion-related inputs in modulating neural responses, offering a comprehensive framework for future investigations into sensory perception and neural coding. [ABSTRACT FROM AUTHOR]

Associating values to environmental cues is a critical aspect of learning from experiences, allowing animals to predict and maximise future rewards. Value-related signals in the brain were once considered a property of higher sensory regions, but their wide distribution across many brain regions is increasingly recognised. Here, we investigate how reward-related signals begin to be incorporated, mechanistically, at the earliest stage of olfactory processing, namely, in the olfactory bulb. In head-fixed mice performing Go/No-Go discrimination of closely related olfactory mixtures, rewarded odours evoke widespread inhibition in one class of output neurons, that is, in mitral cells but not tufted cells. The temporal characteristics of this reward-related inhibition suggest it is odour-driven, but it is also context-dependent since it is absent during pseudo-conditioning and pharmacological silencing of the piriform cortex. Further, the reward-related modulation is present in the somata but not in the apical dendritic tuft of mitral cells, suggesting an involvement of circuit components located deep in the olfactory bulb. Depth-resolved imaging from granule cell dendritic gemmules suggests that granule cells that target mitral cells receive a reward-related extrinsic drive. Thus, our study supports the notion that value-related modulation of olfactory signals is a characteristic of olfactory processing in the primary olfactory area and narrows down the possible underlying mechanisms to deeper circuit components that contact mitral cells perisomatically. Reward-driven learning begins in the very early stages of sensory processing. This study reinforces the idea that value-related modulation of olfactory signals is a key aspect of primary olfactory processing, and identifies potential mechanisms by characterizing deeper circuit components that interact with the soma of mitral cells. [ABSTRACT FROM AUTHOR]

New memories are labile and consolidate over time. Contemporary findings demonstrate that, like sleep, awake quiescence supports consolidation: people remember more new memories if they experience a brief period of post-encoding quiet rest than sensory processing. Furthermore, it was recently demonstrated that the quality of new memories can also be enhanced significantly by awake quiescence. This phenomenon offers great applied potential, for example, in education and eyewitness testimony settings. However, the translation of rest-related gains from the laboratory to everyday life remains poorly characterised and findings are mixed. Here, we report follow-on evidence demonstrating that rest-related gains in visual detail memory may be more challenging to achieve in naturalistic than laboratory-based settings. In contrast to established laboratory findings, using an online version of an established consolidation paradigm, we observed no memory benefit of post-encoding quiescence, relative to an engaging perceptual task, in the retention of detailed visual memories as measured through a lure discrimination task. This null finding could not be explained by intentional rehearsal in those who rested or between-group differences in participants' demographics or mental state, including fatigue and mood. Crucially, post-experimental reports indicated that those in the rest group experienced challenges in initiating and maintaining a state of quiescence, which may account for our null finding. Based on these findings, we propose three areas of focus for future work should rest-related gains in memory be translated from the lab to field: (1) to establish the specific environmental and individual conditions that are conducive and detrimental to awake consolidation, (2) to understand the barriers to initiating and maintaining a state of quiescence in naturalistic settings, and (3) to examine how knowledge of quiescence and its cognitive benefits can encourage the initiation and maintenance of states that are conductive to awake consolidation. [ABSTRACT FROM AUTHOR]

Perception is known to cycle through periods of enhanced and reduced sensitivity to external information. Here, we asked whether such slow fluctuations arise as a noise-related epiphenomenon of limited processing capacity or, alternatively, represent a structured mechanism of perceptual inference. Using 2 large-scale datasets, we found that humans and mice alternate between externally and internally oriented modes of sensory analysis. During external mode, perception aligns more closely with the external sensory information, whereas internal mode is characterized by enhanced biases toward perceptual history. Computational modeling indicated that dynamic changes in mode are enabled by 2 interlinked factors: (i) the integration of subsequent inputs over time and (ii) slow antiphase oscillations in the perceptual impact of external sensory information versus internal predictions that are provided by perceptual history. We propose that between-mode fluctuations generate unambiguous error signals that enable optimal inference in volatile environments. Perception is known to cycle through periods of enhanced and reduced sensitivity to external information, but what is the significance of such slow fluctuations? This study shows that humans and mice fluctuate between external and internal modes of sensory processing, and that this generates unambiguous error signals that enable optimal inference in volatile environments. [ABSTRACT FROM AUTHOR]

The question of how our sensory perception abilities develop has been an active area of research, establishing trajectories of development from infancy that last well into late childhood and even adolescence. In this context, several studies have established changes in sensory processing of vision and touch around the age of 8 to 9 years. In this experiment, we explored the visual and haptic perceptual development of elementary school children of ages 6–11 in similarity-rating tasks of unfamiliar objects and compared their performance to adults. The participants were presented with parametrically-defined objects to be explored haptically and visually in separate groups for both children and adults. Our results showed that the raw similarity ratings of the children had more variability compared to adults. A detailed multidimensional scaling analysis revealed that the reconstructed perceptual space of the adult haptic group was significantly closer to the parameter space compared to the children group, whereas both groups' visual perceptual space was similarly well reconstructed. Beyond this, however, we found no clear evidence for an age effect in either modality within the children group. These results suggest that haptic processing of unfamiliar, abstract shapes may continue to develop beyond the age of 11 years later into adolescence. [ABSTRACT FROM AUTHOR]

Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD. Author summary: Our brains are constantly processing sensory information, but they must also be able to detect when something unexpected happens. This ability, known as deviance detection, is critical for filtering out irrelevant information and focusing on new or important stimuli. The precise mechanisms underpinning deviance detection remain unknown. While previous research and modeling studies have focused on synaptic changes as the mechanism for deviance detection, we hypothesized that firing rate adaptation, which is a non-synaptic plasticity mechanism that reduces a neuron's response to repeated stimulation, is also involved. Using spiking neural network simulations, we found that adaptation alone is sufficient to produce deviance detection. Additionally, we found that when neuronal adaptation was combined with synaptic short-term depression, the two mechanisms worked together to improve deviance detection. Our findings suggest that the brain may encode predictable information by rapidly adapting both neurons and synapses to frequent stimuli, allowing for heightened sensitivity to unexpected events. An improved understanding of how the brain detects unexpected events could lead to the development of new treatments for disorders such as autism, schizophrenia, or ADHD, which are associated with sensory processing difficulties. [ABSTRACT FROM AUTHOR]

Animals must integrate sensory cues with their current behavioral context to generate a suitable response. How this integration occurs is poorly understood. Previously, we developed high-throughput methods to probe neural activity in populations of Caenorhabditis elegans and discovered that the animal's mechanosensory processing is rapidly modulated by the animal's locomotion. Specifically, we found that when the worm turns it suppresses its mechanosensory-evoked reversal response. Here, we report that C. elegans use inhibitory feedback from turning-associated neurons to provide this rapid modulation of mechanosensory processing. By performing high-throughput optogenetic perturbations triggered on behavior, we show that turning-associated neurons SAA, RIV, and/or SMB suppress mechanosensory-evoked reversals during turns. We find that activation of the gentle-touch mechanosensory neurons or of any of the interneurons AIZ, RIM, AIB, and AVE during a turn is less likely to evoke a reversal than activation during forward movement. Inhibiting neurons SAA, RIV, and SMB during a turn restores the likelihood with which mechanosensory activation evokes reversals. Separately, activation of premotor interneuron AVA evokes reversals regardless of whether the animal is turning or moving forward. We therefore propose that inhibitory signals from SAA, RIV, and/or SMB gate mechanosensory signals upstream of neuron AVA. We conclude that C. elegans rely on inhibitory feedback from the motor circuit to modulate its response to sensory stimuli on fast timescales. This need for motor signals in sensory processing may explain the ubiquity in many organisms of motor-related neural activity patterns seen across the brain, including in sensory processing areas. Animals consider their current actions when responding to their environment, but how does the brain accomplish this? This study uses high-throughput optogenetic perturbations to reveal how motor-related signals influence a nematode's response to touch sensation. [ABSTRACT FROM AUTHOR]

Background: Autism is a normal part of cognitive diversity, resulting in communication and sensory processing differences, which can become disabling in a neurotypical world. Autistic people have an increased likelihood of physical and mental co-occurring conditions and die earlier than neurotypical peers. Inaccessible healthcare may contribute to this. Autism Health Passports (AHPs) are paper-based or digital tools which can be used to describe healthcare accessibility needs; they are recommended in UK clinical guidance. However, questions remained as to the theoretical underpinnings and effectiveness of AHPs. Methods: We undertook a systematic literature search identifying studies focused on AHPs for adults (aged over 16 years) from five databases. Included literature was subjected to realist evaluation. Data were extracted using a standardised form, developed by the research team, which considered research design, study quality for realist review and the Context, Mechanisms and Outcomes (CMOs) associated with each AHP tool. Findings: 162 unique records were identified, and 13 items were included in the review. Only one item was considered high quality. Contextual factors focused on the inaccessibility of healthcare to Autistic patients and staff lack of confidence and training in supporting Autistic needs. Interventions were heterogeneous, with most sources reporting few details as to how they had been developed. The most frequently included contents were communication preferences. Mechanisms were often not stated or were inferred by the reviewers and lacked specificity. Outcomes were included in four studies and were primarily focused on AHP uptake, rather than Outcomes which measured impact. Conclusion: There is insufficient evidence to conclude that AHPs reduce the health inequalities experienced by Autistic people. Using an AHP tool alone in a healthcare Context that does not meet Autistic needs, without the inclusion of the local Autistic community developing the tool, and a wider intervention to reduce known barriers to health inequality, may mean that AHPs do not trigger any Mechanisms, and thus cannot affect Outcomes. [ABSTRACT FROM AUTHOR]

Although recent technological developments in the field of bionic upper limb prostheses, their rejection rate remains excessively high. The reasons are diverse (e.g. lack of functionality, control complexity, and comfortability) and most of these are reported only through self-rated questionnaires. Indeed, there is no quantitative evaluation of the extent to which a novel prosthetic solution can effectively address users' needs compared to other technologies. This manuscript discusses the challenges and limitations of current upper limb prosthetic devices and evaluates their functionality through a standard functional assessment, the Assessment of Capacity for Myoelectric Control (ACMC). To include a good representation of technologies, the authors collect information from participants in the Cybathlon Powered Arm Prostheses Race 2016 and 2020. The article analyzes 7 hour and 41 min of video footage to evaluate the performance of different prosthetic devices in various tasks inspired by activities of daily living (ADL). The results show that commercially-available rigid hands perform well in dexterous grasping, while body-powered solutions are more reliable and convenient for competitive environments. The article also highlights the importance of wrist design and control modality for successful execution of ADL. Moreover, we discuss the limitations of the evaluation methodology and suggest improvements for future assessments. With regard to future development, this work highlights the need for research in intuitive control of multiple degrees of freedom, adaptive solutions, and the integration of sensory feedback. [ABSTRACT FROM AUTHOR]

Adaptive rewiring provides a basic principle of self-organizing connectivity in evolving neural network topology. By selectively adding connections to regions with intense signal flow and deleting underutilized connections, adaptive rewiring generates optimized brain-like, i.e. modular, small-world, and rich club connectivity structures. Besides topology, neural self-organization also follows spatial optimization principles, such as minimizing the neural wiring distance and topographic alignment of neural pathways. We simulated the interplay of these spatial principles and adaptive rewiring in evolving neural networks with weighted and directed connections. The neural traffic flow within the network is represented by the equivalent of diffusion dynamics for directed edges: consensus and advection. We observe a constructive synergy between adaptive and spatial rewiring, which contributes to network connectedness. In particular, wiring distance minimization facilitates adaptive rewiring in creating convergent-divergent units. These units support the flow of neural information and enable context-sensitive information processing in the sensory cortex and elsewhere. Convergent-divergent units consist of convergent hub nodes, which collect inputs from pools of nodes and project these signals via a densely interconnected set of intermediate nodes onto divergent hub nodes, which broadcast their output back to the network. Convergent-divergent units vary in the degree to which their intermediate nodes are isolated from the rest of the network. This degree, and hence the context-sensitivity of the network's processing style, is parametrically determined in the evolving network model by the relative prominence of spatial versus adaptive rewiring. Author summary: Context-sensitivity plays an important role in neural signal processing. A type of network structure supporting context-sensitive processing is known as a convergent-divergent unit. Convergent-divergent units can give rise to sensory neurons that respond to local features but are also modulated, in their activities, by long-range contextual information. These units can arise through self-organization in neural networks according to adaptive rewiring, a principle used to optimize network structure for information processing. Two spatial rewiring principles, distance minimization and topographic alignment, are also considered important in shaping network connectivity structure, but their role in the formation of context sensitivity is unknown. We asked whether these spatial rewiring principles can facilitate adaptive rewiring in the formation of convergent-divergent units. Using weighted digraphs, we found that the proportion of rewiring based on distance minimization improves context-sensitivity, as shown by the increased robustness of the convergent-divergent units, while the subtler effects of the alignment principle depend on the shape of the topographic map that network connections align with. [ABSTRACT FROM AUTHOR]

Sensorimotor decision-making is believed to involve a process of accumulating sensory evidence over time. While current theories posit a single accumulation process prior to planning an overt motor response, here, we propose an active role of motor processes in decision formation via a secondary leaky motor accumulation stage. The motor leak adapts the "memory" with which this secondary accumulator reintegrates the primary accumulated sensory evidence, thus adjusting the temporal smoothing in the motor evidence and, correspondingly, the lag between the primary and motor accumulators. We compare this framework against different single accumulator variants using formal model comparison, fitting choice, and response times in a task where human observers made categorical decisions about a noisy sequence of images, under different speed–accuracy trade-off instructions. We show that, rather than boundary adjustments (controlling the amount of evidence accumulated for decision commitment), adjustment of the leak in the secondary motor accumulator provides the better description of behavior across conditions. Importantly, we derive neural correlates of these 2 integration processes from electroencephalography data recorded during the same task and show that these neural correlates adhere to the neural response profiles predicted by the model. This framework thus provides a neurobiologically plausible description of sensorimotor decision-making that captures emerging evidence of the active role of motor processes in choice behavior. Sensorimotor decision-making is believed to involve a process of accumulating sensory evidence over time. This study reveals that two concurrent but temporally lagged evidence accumulation signals in human EEG are associated with a double-integration framework in which a secondary motor accumulation process dictates choice behavior while controlling for the urgency in making a decision. [ABSTRACT FROM AUTHOR]

The mechanisms that enable humans to evaluate their confidence across a range of different decisions remain poorly understood. To bridge this gap in understanding, we used computational modelling to investigate the processes that underlie confidence judgements for perceptual decisions and the extent to which these computations are the same in the visual and auditory modalities. Participants completed two versions of a categorisation task with visual or auditory stimuli and made confidence judgements about their category decisions. In each modality, we varied both evidence strength, (i.e., the strength of the evidence for a particular category) and sensory uncertainty (i.e., the intensity of the sensory signal). We evaluated several classes of computational models which formalise the mapping of evidence strength and sensory uncertainty to confidence in different ways: 1) unscaled evidence strength models, 2) scaled evidence strength models, and 3) Bayesian models. Our model comparison results showed that across tasks and modalities, participants take evidence strength and sensory uncertainty into account in a way that is consistent with the scaled evidence strength class. Notably, the Bayesian class provided a relatively poor account of the data across modalities, particularly in the more complex categorisation task. Our findings suggest that a common process is used for evaluating confidence in perceptual decisions across domains, but that the parameter settings governing the process are tuned differently in each modality. Overall, our results highlight the impact of sensory uncertainty on confidence and the unity of metacognitive processing across sensory modalities. Author summary: In this study, we investigated the computational processes that describe how people derive a sense of confidence in their decisions. In particular, we used computational models to describe how decision confidence is generated from different stimulus features, specifically evidence strength and sensory uncertainty, and determined whether the same computations generalise to both visual and auditory decisions. We tested a range of different computational models from three distinct theoretical classes, where each class of models instantiated different algorithmic hypotheses about the computations that are used to generate confidence. We found that a single class of models, in which confidence is derived from a subjective assessment of the strength of the evidence for a particular choice scaled by an estimate of sensory uncertainty, provided the best account of confidence for both visual and auditory decisions. Our findings suggest that the same type of algorithm is used for evaluating confidence across sensory modalities but that the 'settings' (or parameters) of this process are fine-tuned within each modality. [ABSTRACT FROM AUTHOR]

In natural environments objects comprise multiple features from the same or different sensory modalities but it is not known how perception of an object is affected by the value associations of its constituent parts. The present study compares intra- and cross-modal value-driven effects on behavioral and electrophysiological correlates of perception. Human participants first learned the reward associations of visual and auditory cues. Subsequently, they performed a visual discrimination task in the presence of previously rewarded, task-irrelevant visual or auditory cues (intra- and cross-modal cues, respectively). During the conditioning phase, when reward associations were learned and reward cues were the target of the task, high value stimuli of both modalities enhanced the electrophysiological correlates of sensory processing in posterior electrodes. During the post-conditioning phase, when reward delivery was halted and previously rewarded stimuli were task-irrelevant, cross-modal value significantly enhanced the behavioral measures of visual sensitivity, whereas intra-modal value produced only an insignificant decrement. Analysis of the simultaneously recorded event-related potentials (ERPs) of posterior electrodes revealed similar findings. We found an early (90–120 ms) suppression of ERPs evoked by high-value, intra-modal stimuli. Cross-modal stimuli led to a later value-driven modulation, with an enhancement of response positivity for high- compared to low-value stimuli starting at the N1 window (180–250 ms) and extending to the P3 (300–600 ms) responses. These results indicate that sensory processing of a compound stimulus comprising a visual target and task-irrelevant visual or auditory cues is modulated by the reward value of both sensory modalities, but such modulations rely on distinct underlying mechanisms. [ABSTRACT FROM AUTHOR]

The superior colliculus (SC), a conserved midbrain node with extensive long-range connectivity throughout the brain, is a key structure for innate behaviors. Descending cortical pathways are increasingly recognized as central control points for SC-mediated behaviors, but how cortico-collicular pathways coordinate SC activity at the cellular level is poorly understood. Moreover, despite the known role of the SC as a multisensory integrator, the involvement of the SC in the somatosensory system is largely unexplored in comparison to its involvement in the visual and auditory systems. Here, we mapped the connectivity of the whisker-sensitive region of the SC in mice with trans-synaptic and intersectional tracing tools and in vivo electrophysiology. The results reveal a novel trans-collicular connectivity motif in which neurons in motor- and somatosensory cortices impinge onto the brainstem-SC-brainstem sensory-motor arc and onto SC-midbrain output pathways via only one synapse in the SC. Intersectional approaches and optogenetically assisted connectivity quantifications in vivo reveal convergence of motor and somatosensory cortical input on individual SC neurons, providing a new framework for sensory-motor integration in the SC. More than a third of the cortical recipient neurons in the whisker SC are GABAergic neurons, which include a hitherto unknown population of GABAergic projection neurons targeting thalamic nuclei and the zona incerta. These results pinpoint a whisker region in the SC of mice as a node for the integration of somatosensory and motor cortical signals via parallel excitatory and inhibitory trans-collicular pathways, which link cortical and subcortical whisker circuits for somato-motor integration. The superior colliculus, a conserved midbrain node with extensive long-range connectivity throughout the brain, is a key structure for innate behaviors. This study uses trans-synaptic tracing and functional analysis to reveal novel pathways via the superior colliculus for the transformation of cortical signals into long-range output signals in the mouse whisker system. [ABSTRACT FROM AUTHOR]

Throughout the last decades, understanding the neural mechanisms of sensory processing has been a key objective for neuroscientists. Many studies focused on uncovering the microcircuit-level architecture of somatosensation using the rodent whisker system as a model. Although these studies have significantly advanced our understanding of tactile processing, the question remains to what extent the whisker system can provide results translatable to the human somatosensory system. To address this, we developed a restrained vibrotactile detection task involving the limb system in mice. A vibrotactile stimulus was delivered to the hindlimb of head-fixed mice, who were trained to perform a Go/No-go detection task. Mice were able to learn this task with satisfactory performance and with reasonably short training times. In addition, the task we developed is versatile, as it can be combined with diverse neuroscience methods. Thus, this study introduces a novel task to study the neuron-level mechanisms of tactile processing in a system other than the more commonly studied whisker system. [ABSTRACT FROM AUTHOR]

The caudate nucleus has been thought to be involved in the control of motor commands by the cerebrum, and recent studies suggest that it may play a role in the control of attachment behavior, cognition, emotion, and mental functions. Implied by the basal ganglia's involvement in the execution, planning and control of movement, the caudate nucleus functions in a situation-dependent manner where processing of external stimuli is important on the basis of learning and memory. Sensory processing, which determines the response to external stimuli, has been shown to be related to various brain regions but it remains unknown how sensory processing is associated with the structure of the caudate nucleus and white matter microstructures of the caudate. Using four diffusion parameters derived from diffusion tensor imaging (DTI) (i.e., fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), and radial diffusivity (RD)) and the Adolescent/Adult Sensory Profile (AASP) questionnaire of 99 healthy subjects [42 males and 57 females; mean age:26.9 years, standard deviation 6.9], we investigated the relationship between white matter structure in the caudate nucleus and sensory processing. In consistent with what had been suggested by the results of previous studies, we found significant correlations between AD, MD and tactile sensation. Furthermore, we found a significant correlation between AD, MD and tactile sensory avoidance, the AASP sub-scores regarding the tactile senses. To the best of our knowledge, this is the first study to show that DTI diffusion parameters correlate with AASP scores in specific brain regions. [ABSTRACT FROM AUTHOR]

The construct of "sensory processing sensitivity" has become an extremely popular concept outside the scientific literature under the term "high sensitivity" (HS), reflected in a variety of self-help guides and media reports. Therefore, the present study aimed to investigate this phenomenon by examining in-depth individuals who consider the label HS essential to their self-definition. In semi-structured interviews, 38 individuals described their understanding of HS and its perceived manifestations and impact on their lives (among other topics). Subsequently, the data were content-analytically evaluated, i.e., categorized and quantified. One key finding was that HS individuals feel relief following self-attribution or self-diagnosis. Moreover, this self-attribution replaced the feeling of being somehow different from the others, which almost all interviewees mentioned, with positive attributes. The main negative features of HS mentioned were feeling overwhelmed by sensory and emotional stimuli. The results are discussed with regard to the significance of the label HS for this group on the one hand, and with regard to alternative approaches for future research on the other hand. [ABSTRACT FROM AUTHOR]

Objectives: The study aims to better understand the rhythmic abilities of people who stutter and to identify which processes potentially are impaired in this population: (1) beat perception and reproduction; (2) the execution of movements, in particular their initiation; (3) sensorimotor integration. Material and method: Finger tapping behavior of 16 adults who stutter (PWS) was compared with that of 16 matching controls (PNS) in five rhythmic tasks of various complexity: three synchronization tasks ― a simple 1:1 isochronous pattern, a complex non-isochronous pattern, and a 4 tap:1 beat isochronous pattern ―, a reaction task to an aperiodic and unpredictable pattern, and a reproduction task of an isochronous pattern after passively listening. Results: PWS were able to reproduce an isochronous pattern on their own, without external auditory stimuli, with similar accuracy as PNS, but with increased variability. This group difference in variability was observed immediately after passive listening, without prior motor engagement, and was not enhanced or reduced after several seconds of tapping. Although PWS showed increased tapping variability in the reproduction task as well as in synchronization tasks, this timing variability did not correlate significantly with the variability in reaction times or tapping force. Compared to PNS, PWS exhibited larger negative mean asynchronies, and increased synchronization variability in synchronization tasks. These group differences were not affected by beat hierarchy (i.e., "strong" vs. "weak" beats), pattern complexity (non-isochronous vs. isochronous) or presence versus absence of external auditory stimulus (1:1 vs. 1:4 isochronous pattern). Differences between PWS and PNS were not enhanced or reduced with sensorimotor learning, over the first taps of a synchronization task. Conclusion: Our observations support the hypothesis of a deficit in neuronal oscillators coupling in production, but not in perception, of rhythmic patterns, and a larger delay in multi-modal feedback processing for PWS. [ABSTRACT FROM AUTHOR]

The physical boundaries of our body do not define what we perceive as self. This malleable representation arises from the neural integration of sensory information coming from the environment. Manipulating the visual and haptic cues produces changes in body perception, inducing the Full Body Illusion (FBI), a vastly used approach to exploring humans' perception. After pioneering FBI demonstrations, issues arose regarding its setup, using experimenter-based touch and pre-recorded videos. Moreover, its outcome measures are based mainly on subjective reports, leading to biased results, or on heterogeneous objective ones giving poor consensus on their validity. To address these limitations, we developed and tested a multisensory platform allowing highly controlled experimental conditions, thanks to the leveraged use of innovative technologies: Virtual Reality (VR) and Transcutaneous Electrical Nerve Stimulation (TENS). This enabled a high spatial and temporal precision of the visual and haptic cues, efficiently eliciting FBI. While it matched the classic approach in subjective measures, our setup resulted also in significant results for all objective measurements. Importantly, FBI was elicited when all 4 limbs were multimodally stimulated but also in a single limb condition. Our results behoove the adoption of a comprehensive set of measures, introducing a new neuroscientific platform to investigate body representations. [ABSTRACT FROM AUTHOR]

The acquisition of sensory information about the world is a dynamic and interactive experience, yet the majority of sensory research focuses on perception without action and is conducted with participants who are passive observers with very limited control over their environment. This approach allows for highly controlled, repeatable experiments and has led to major advances in our understanding of basic sensory processing. Typical human perceptual experiences, however, are far more complex than conventional action-perception experiments and often involve bi-directional interactions between perception and action. Innovations in virtual reality (VR) technology offer an approach to close this notable disconnect between perceptual experiences and experiments. VR experiments can be conducted with a high level of empirical control while also allowing for movement and agency as well as controlled naturalistic environments. New VR technology also permits tracking of fine hand movements, allowing for seamless empirical integration of perception and action. Here, we used VR to assess how multisensory information and cognitive demands affect hand movements while reaching for virtual targets. First, we manipulated the visibility of the reaching hand to uncouple vision and proprioception in a task measuring accuracy while reaching toward a virtual target (n = 20, healthy young adults). The results, which as expected revealed multisensory facilitation, provided a rapid and a highly sensitive measure of isolated proprioceptive accuracy. In the second experiment, we presented the virtual target only briefly and showed that VR can be used as an efficient and robust measurement of spatial memory (n = 18, healthy young adults). Finally, to assess the feasibility of using VR to study perception and action in populations with physical disabilities, we showed that the results from the visual-proprioceptive task generalize to two patients with recent cerebellar stroke. Overall, we show that VR coupled with hand-tracking offers an efficient and adaptable way to study human perception and action. [ABSTRACT FROM AUTHOR]

The research described herein is based on the assumptions of the sensory processing sensitivity concept and the meta framework for the concept of environmental sensitivity. The adopted theoretical framework shows that individuals differ in their sensitivity to the environment, with some being more sensitive than others. From the evolutionary perspective, it has also been assumed that sensory processing sensitivity follows a normal distribution in the population, with a minority being exceptionally or highly sensitive to environmental stimuli. We explored data from a sample of 928 young adolescents in two studies. The tool used to evaluate their sensitivity was the Highly Sensitive Child Scale, which in studies 1 and 2 had a three-factor structure. Latent class analysis was used for the interpretation of the data of the studied groups. The obtained results indicate the existence of three groups which differ significantly from each other according to the HSC result. Based on the obtained results, it may be assumed that young adolescents are divided into three groups characterized by different sensitivities and their percentage distribution is not in agreement with the research conducted to date. The acquired information has both a theoretical value and a practical applicability, prompting reflection about the different aspects of the study, such as cultural differences, changes related to the development stage and the characteristics of the evaluation tool itself. From the perspective of possible applications, the obtained results may provide important information (1) to decision-makers who plan support or intervention programs at various levels of prevention, (2) for practitioners to provide them with the means with which to consider sensitivity as an important factor in coping with difficulties through diversified and adequate support (3) that is broadly applicable in the face of an environmental crisis (pandemic, the changing structure of class groups which is related to the number of refugees). [ABSTRACT FROM AUTHOR]

Human experience of time exhibits systematic, context-dependent deviations from clock time; for example, time is experienced differently at work than on holiday. Here we test the proposal that differences from clock time in subjective experience of time arise because time estimates are constructed by accumulating the same quantity that guides perception: salient events. Healthy human participants watched naturalistic, silent videos of up to 24 seconds in duration and estimated their duration while fMRI was acquired. We were able to reconstruct trial-by-trial biases in participants' duration reports, which reflect subjective experience of duration, purely from salient events in their visual cortex BOLD activity. By contrast, salient events in neither of two control regions – auditory and somatosensory cortex–were predictive of duration biases. These results held despite being able to (trivially) predict clock time from all three brain areas. Our results reveal that the information arising during perceptual processing of a dynamic environment provides a sufficient basis for reconstructing human subjective time duration. Author summary: Our perception of time isn't like a clock; it varies depending on other aspects of experience, such as what we see and hear in that moment. Previous studies have shown that differences in simple features, such as an image being larger or smaller, or brighter or dimmer, can change how we perceive time for those experiences. But in everyday life, the properties of these simple features can change frequently, presenting a challenge to understanding real-world time perception based on simple lab experiments. To overcome this problem, we developed a computational model of human time perception based on tracking changes in neural activity across brain regions involved in sensory processing (using non-invasive brain imaging). By measuring changes in brain activity patterns across these regions, our approach accommodates the different and changing feature combinations present in natural scenarios, such as walking on a busy street. Our model reproduces people's duration reports for natural videos (up to almost half a minute long) and, most importantly, predicts whether a person reports a scene as relatively shorter or longer–the biases in time perception that reflect how natural experience of time deviates from clock time. [ABSTRACT FROM AUTHOR]

Modern living and working environments are more and more interspersed with the concurrent execution of locomotion and sensory processing, most often in the visual domain. Many job profiles involve the presentation of visual information while walking, for example in warehouse logistics work, where a worker has to manage walking to the correct aisle to pick up a package while being presented with visual information over data-glasses concerning the next order. Similar use-cases can be found in manufacturing jobs, for example in car montage assembly lines where next steps are presented via augmented reality headsets while walking at a slow pace. Considering the overall scarcity of cognitive resources available to be deployed to either the cognitive or motor processes, task performance decrements were found when increasing load in either domain. Interestingly, the walking motion also had beneficial effects on peripheral contrast detection and the inhibition of visual stream information. Taking these findings into account, we conducted a study that comprised the detection of single visual targets (Landolt Cs) within a broad range of the visual field (-40° to +40° visual angle) while either standing, walking, or walking with concurrent perturbations. We used questionnaire (NASA-TLX), behavioral (response times and accuracy), and neurophysiological data (ERPs and ERSPs) to quantify the effects of cognitive-motor interference. The study was conducted in a Gait Real-time Analysis Interactive Laboratory (GRAIL), using a 180° projection screen and a swayable and tiltable dual-belt treadmill. Questionnaire and behavioral measures showed common patterns. We found increasing subjective physical workload and behavioral decrements with increasing stimulus eccentricity and motor complexity. Electrophysiological results also indicated decrements in stimulus processing with higher stimulus eccentricity and movement complexity (P3, Theta), but highlighted a beneficial role when walking without perturbations and processing more peripheral stimuli regarding earlier sensory components (N1pc/N2pc, N2). These findings suggest that walking without impediments can enhance the visual processing of peripheral information and therefore help with perceiving non-foveal sensory content. Also, our results could help with re-evaluating previous findings in the context of cognitive-motor interference, as increased motor complexity might not always impede cognitive processing and performance. [ABSTRACT FROM AUTHOR]

Arousal levels strongly affect task performance. Yet, what arousal level is optimal for a task depends on its difficulty. Easy task performance peaks at higher arousal levels, whereas performance on difficult tasks displays an inverted U-shape relationship with arousal, peaking at medium arousal levels, an observation first made by Yerkes and Dodson in 1908. It is commonly proposed that the noradrenergic locus coeruleus system regulates these effects on performance through a widespread release of noradrenaline resulting in changes of cortical gain. This account, however, does not explain why performance decays with high arousal levels only in difficult, but not in simple tasks. Here, we present a mechanistic model that revisits the Yerkes-Dodson effect from a sensory perspective: a deep convolutional neural network augmented with a global gain mechanism reproduced the same interaction between arousal state and task difficulty in its performance. Investigating this model revealed that global gain states differentially modulated sensory information encoding across the processing hierarchy, which explained their differential effects on performance on simple versus difficult tasks. These findings offer a novel hierarchical sensory processing account of how, and why, arousal state affects task performance. Author summary: Over a hundred years ago, it was first observed that the effect of arousal on performance depends on task difficulty: the Yerkes-Dodson effect. Difficult tasks are best solved at intermediate arousal levels, whereas easy tasks benefit from a high arousal state. Current theories on how arousal affects neural processing cannot explain this effect of task difficulty. Here, we implement a key effect of arousal on cortical processing, a change in neuronal gain, in a computational model of visual processing capable of object recognition. Across a series of experiments, we find that our model can reproduce the Yerkes-Dodson effect behaviorally and that this effect can be explained by where in the processing hierarchy different arousal states optimize sensory information encoding. [ABSTRACT FROM AUTHOR]

Animals are constantly bombarded with stimuli, which presents a fundamental problem of sorting among pervasive uninformative stimuli and novel, possibly meaningful stimuli. We evaluated novelty detection behaviorally in honey bees as they position their antennae differentially in an air stream carrying familiar or novel odors. We then characterized neuronal responses to familiar and novel odors in the first synaptic integration center in the brain–the antennal lobes. We found that the neurons that exhibited stronger initial responses to the odor that was to be familiarized are the same units that later distinguish familiar and novel odors, independently of chemical identities. These units, including both tentative projection neurons and local neurons, showed a decreased response to the familiar odor but an increased response to the novel odor. Our results suggest that the antennal lobe may represent familiarity or novelty to an odor stimulus in addition to its chemical identity code. Therefore, the mechanisms for novelty detection may be present in early sensory processing, either as a result of local synaptic interaction or via feedback from higher brain centers. [ABSTRACT FROM AUTHOR]

The general stress response (GSR) in Listeria monocytogenes plays a critical role in the survival of this pathogen in the host gastrointestinal tract. The GSR is regulated by the alternative sigma factor B (σB), whose role in protection against acid stress is well established. Here, we investigated the involvement of the stressosome, a sensory hub, in transducing low pH signals to induce the GSR. Mild acid shock (15 min at pH 5.0) activated σB and conferred protection against a subsequent lethal pH challenge. A mutant strain where the stressosome subunit RsbR1 was solely present retained the ability to induce σB activity at pH 5.0. The role of stressosome phosphorylation in signal transduction was investigated by mutating the putative phosphorylation sites in the core stressosome proteins RsbR1 (rsbR1-T175A, -T209A, -T241A) and RsbS (rsbS-S56A), or the stressosome kinase RsbT (rsbT-N49A). The rsbS S56A and rsbT N49A mutations abolished the response to low pH. The rsbR1-T209A and rsbR1-T241A mutants displayed constitutive σB activity. Mild acid shock upregulates invasion genes inlAB and stimulates epithelial cell invasion, effects that were abolished in mutants with an inactive or overactive stressosome. Overall, the results show that the stressosome is required for acid-induced activation of σB in L. monocytogenes. Furthermore, they show that RsbR1 can function independently of its paralogues and signal transduction requires RsbT-mediated phosphorylation of RsbS on S56 and RsbR1 on T209 but not T175. These insights shed light on the mechanisms of signal transduction that activate the GSR in L. monocytogenes in response to acidic environments, and highlight the role this sensory process in the early stages of the infectious cycle. Author summary: The stress sensing hub known as the stressosome, found in many bacterial and archaeal lineages, plays a crucial role in both stress tolerance and virulence in the food-borne pathogen Listeria monocytogenes. However, the mechanisms that lead to its activation and the subsequent activation of the general stress response have remained elusive. In this study, we examined the signal transduction mechanisms that operate in the stressosome in response to acid stress. We found that only one of the five putative sensory proteins present in L. monocytogenes, RsbR1, was required for effective transduction of acid tress signals. We further found that phosphorylation of RsbS and RsbR1, mediated by the RsbT kinase, is essential for signal transduction. Failure to phosphorylate RsbS on Serine 56 completely abolished acid sensing by the stressosome, which prevented the development of adaptive acid tolerance. The acid-induced activation of internalin gene expression was also abolished in mutants with defective stressosome signalling, suggesting a role for the stressosome in the invasion of host cells. Together the data provide new insights into the mechanisms that activate the stressosome in response to acid stress and highlight the role this sensory hub plays in virulence. [ABSTRACT FROM AUTHOR]

Perception is often characterized computationally as an inference process in which uncertain or ambiguous sensory inputs are combined with prior expectations. Although behavioral studies have shown that observers can change their prior expectations in the context of a task, robust neural signatures of task-specific priors have been elusive. Here, we analytically derive such signatures under the general assumption that the responses of sensory neurons encode posterior beliefs that combine sensory inputs with task-specific expectations. Specifically, we derive predictions for the task-dependence of correlated neural variability and decision-related signals in sensory neurons. The qualitative aspects of our results are parameter-free and specific to the statistics of each task. The predictions for correlated variability also differ from predictions of classic feedforward models of sensory processing and are therefore a strong test of theories of hierarchical Bayesian inference in the brain. Importantly, we find that Bayesian learning predicts an increase in so-called "differential correlations" as the observer's internal model learns the stimulus distribution, and the observer's behavioral performance improves. This stands in contrast to classic feedforward encoding/decoding models of sensory processing, since such correlations are fundamentally information-limiting. We find support for our predictions in data from existing neurophysiological studies across a variety of tasks and brain areas. Finally, we show in simulation how measurements of sensory neural responses can reveal information about a subject's internal beliefs about the task. Taken together, our results reinterpret task-dependent sources of neural covariability as signatures of Bayesian inference and provide new insights into their cause and their function. Author summary: Perceptual decision-making has classically been studied in the context of feedforward encoding/ decoding models. Here, we derive predictions for the responses of sensory neurons under the assumption that the brain performs hierarchical Bayesian inference, including feedback signals that communicate task-specific prior expectations. Interestingly, those predictions stand in contrast to some of the conclusions drawn in the classic framework. In particular, we find that Bayesian learning predicts the increase of a type of correlated variability called "differential correlations" over the course of learning. Differential correlations limit information, and hence are seen as harmful in feedforward models. Since our results are also specific to the statistics of a given task, and since they hold under a wide class of theories about how Bayesian probabilities may be represented by neural responses, they constitute a strong test of the Bayesian Brain hypothesis. Our results can explain the task-dependence of correlated variability in prior studies and suggest a reason why these kinds of correlations are surprisingly common in empirical data. Interpreted in a probabilistic framework, correlated variability provides a window into an observer's task-related beliefs. [ABSTRACT FROM AUTHOR]

Sensory processing is hard because the variables of interest are encoded in spike trains in a relatively complex way. A major goal in studies of sensory processing is to understand how the brain extracts those variables. Here we revisit a common encoding model in which variables are encoded linearly. Although there are typically more variables than neurons, this problem is still solvable because only a small number of variables appear at any one time (sparse prior). However, previous solutions require all-to-all connectivity, inconsistent with the sparse connectivity seen in the brain. Here we propose an algorithm that provably reaches the MAP (maximum a posteriori) inference solution, but does so using sparse connectivity. Our algorithm is inspired by the circuit of the mouse olfactory bulb, but our approach is general enough to apply to other modalities. In addition, it should be possible to extend it to nonlinear encoding models. Author summary: Sensory systems must infer latent variables from noisy and ambiguous input. MAP inference—choosing the most likely value for the latent variables given the sensory input—is one of the simplest methods for doing that, but its neural implementation often requires all-to-all connectivity between the neurons involved. In common sensory contexts this can require a single neuron to connect to hundreds of thousands of others, which is biologically implausible. In this work we take inspiration from the 'sister' mitral cells of the olfactory system—groups of neurons associated with the same input channel—to derive a method for performing MAP inference using sparse connectivity. We do so by assigning sister cells to random subsets of the latent variables and using additional cells to ensure that sisters correctly share information. We then derive the circuitry and dynamics required for the sister cells to compute the original MAP inference solution. Our work yields a biologically plausible circuit that provably solves the MAP inference problem and provides experimentally testable predictions. While inspired by the olfactory system, our method is quite general, and is likely to apply to other sensory modalities. [ABSTRACT FROM AUTHOR]

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. Author summary: Integrating visual and auditory stimuli that occur at the same location and time improves our ability to identify and respond to external events. This type of sensory integration is an important brain function, and its deficits are known symptoms of patients with autism and schizophrenia. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual and auditory inputs 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 their 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 found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. 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. These results open the door to further studies using mice that are designed to determine the circuitry underlying multisensory integration, and the mechanisms used for its development. [ABSTRACT FROM AUTHOR]

We show how anomalous time reversal of stimuli and their associated responses can exist in very small connectionist models. These networks are built from dynamical toy model neurons which adhere to a minimal set of biologically plausible properties. The appearance of a "ghost" response, temporally and spatially located in between responses caused by actual stimuli, as in the phi phenomenon, is demonstrated in a similar small network, where it is caused by priming and long-distance feedforward paths. We then demonstrate that the color phi phenomenon can be present in an echo state network, a recurrent neural network, without explicitly training for the presence of the effect, such that it emerges as an artifact of the dynamical processing. Our results suggest that the color phi phenomenon might simply be a feature of the inherent dynamical and nonlinear sensory processing in the brain and in and of itself is not related to consciousness. Author summary: Well known visual illusions are used to investigate how objective physical stimuli translate to subjective conscious experiences and are therefore believed to offer clues at how human consciousness works. One such illusion, the color phi phenomenon is marked by an anomalous time reversal of what is shown to test subjects and what they report to have seen. The color phi phenomenon has been a prime example to illustrate that conscious experience, instead of being merely a recording of the facts as they happen, involves both pre- and post-constructive processes resulting in a coherent narrative. We provide an alternative interpretation by showing that all aspects of this phenomenon can be adequately modeled in small neural networks. These networks are composed of simple leaky integrator neurons, emphasizing the importance of taking into account dynamical behavior. We illustrate how anomalous temporally-reversed perception of stimuli can appear based exclusively on bottom-up dynamics. Since the color phi phenomenon emerges as a feature of dynamical processing in our model, we conclude that it may explain less about human consciousness than previously thought and that it could be nothing more than a feature of dynamical processing in the brain. [ABSTRACT FROM AUTHOR]

Self-reporting of pain can be difficult in populations with communication challenges or atypical sensory processing, such as children with autism spectrum disorder (ASD). Consequently, pain can go untreated. An objective method to identify discomfort would be valuable to individuals unable to express or recognize their own bodily distress. Near-infrared spectroscopy (NIRS) is a brain-imaging modality that is suited for this application. We evaluated the potential of detecting a cortical response to discomfort in the ASD population using NIRS. Using a continuous-wave spectrometer, prefrontal and parietal measures were collected from 15 males with ASD and 7 typically developing (TD) males 10–15 years of age. Participants were exposed to a noxious cold stimulus by immersing their hands in cold water and tepid water as a baseline task. Across all participants, the magnitude and timing of the cold and tepid water-induced brain responses were significantly different (p < 0.001). The effect of the task on the brain response depended on the study group (group x task: p < 0.001), with the ASD group exhibiting a blunted response to the cold stimulus. Findings suggest that NIRS may serve as a tool for objective pain assessment and atypical sensory processing. [ABSTRACT FROM AUTHOR]

The purpose of current study is to reveal spatiotemporal features of oscillatory EEG activities in response to emotional arousal induced by emotional video stimuli, and to find the characteristics of cortical activities showing significant difference according to arousal levels. The EEGs recorded during watching affective video clips were transformed to cortical current density time-series, and then, cluster-based permutation test was applied to determine the spatiotemporal origins of alpha- and beta-band activities showing significant difference between high and low arousal levels. We found stronger desynchronization of alpha-band activities due to higher arousal in visual areas, which may be due to stronger activation for sensory information processing for the highly arousing video stimuli. In precentral and superior parietal regions, the stronger desynchronization in alpha-and low beta-bands was observed for the high arousal stimuli. This is expected to reflect enhanced mirror neuron system activities, which is involved in understanding the intention of other's action. Similar changes according to arousal level were found also in inter-regional phase synchronization in alpha- and beta-bands. [ABSTRACT FROM AUTHOR]

Divisive normalization (DN) is a prominent computational building block in the brain that has been proposed as a canonical cortical operation. Numerous experimental studies have verified its importance for capturing nonlinear neural response properties to simple, artificial stimuli, and computational studies suggest that DN is also an important component for processing natural stimuli. However, we lack quantitative models of DN that are directly informed by measurements of spiking responses in the brain and applicable to arbitrary stimuli. Here, we propose a DN model that is applicable to arbitrary input images. We test its ability to predict how neurons in macaque primary visual cortex (V1) respond to natural images, with a focus on nonlinear response properties within the classical receptive field. Our model consists of one layer of subunits followed by learned orientation-specific DN. It outperforms linear-nonlinear and wavelet-based feature representations and makes a significant step towards the performance of state-of-the-art convolutional neural network (CNN) models. Unlike deep CNNs, our compact DN model offers a direct interpretation of the nature of normalization. By inspecting the learned normalization pool of our model, we gained insights into a long-standing question about the tuning properties of DN that update the current textbook description: we found that within the receptive field oriented features were normalized preferentially by features with similar orientation rather than non-specifically as currently assumed. Author summary: Divisive normalization (DN) is a computational building block throughout sensory processing in the brain. We currently lack an understanding of what role this normalization mechanism plays when processing complex stimuli like natural images. Here, we use modern machine learning methods to build a general DN model that is directly informed by data from primary visual cortex (V1). Contrary to high-predictive deep learning models, our DN-based model's parameters offer a straightforward interpretation of the nature of normalization. Within the receptive field, we found that neurons responding strongly to a specific orientation are preferentially normalized by other neurons that are highly active for similar orientations, rather than being normalized by all neurons as it is currently assumed by textbook models. [ABSTRACT FROM AUTHOR]

The goal of this study was to test for long-term benefits three years after the completion of a cognitive training intervention (Project: EVO™) in a subset of children with Sensory Processing Dysfunction (SPD). Our initial findings revealed that children with SPD who also met research criteria for Attention Deficit Hyperactivity Disorder (SPD+IA) showed a significant decrease in parent-observed inattentive behaviors, which remained stable in a nine-month follow-up assessment. Forty nine caregivers of participants who completed the Project: EVO™ training were contacted to be included in this follow up study. Each was emailed an invitation to complete the Vanderbilt ADHD Diagnostic Parent Rating Scale, which yielded a completion rate of 39/49 (80%). A Generalized Estimating Equations analysis was used to assess changes in symptoms over time, specifically to determine whether the initial improvements were retained. The SPD+IA cohort continued to show sustained benefits on their parent-reported scores of inattention, with 54% of SPD+IA individuals no longer meeting criteria for ADHD three years following intervention. These findings provide initial insights into the potential long-term benefits of a digital health intervention for children with attention-based issues. [ABSTRACT FROM AUTHOR]

The connection between stimulus perception and time perception remains unknown. The present study combines human and rat psychophysics with sensory cortical neuronal firing to construct a computational model for the percept of elapsed time embedded within sense of touch. When subjects judged the duration of a vibration applied to the fingertip (human) or whiskers (rat), increasing stimulus intensity led to increasing perceived duration. Symmetrically, increasing vibration duration led to increasing perceived intensity. We modeled real spike trains recorded from vibrissal somatosensory cortex as input to dual leaky integrators–an intensity integrator with short time constant and a duration integrator with long time constant–generating neurometric functions that replicated the actual psychophysical functions of rats. Returning to human psychophysics, we then confirmed specific predictions of the dual leaky integrator model. This study offers a framework, based on sensory coding and subsequent accumulation of sensory drive, to account for how a feeling of the passage of time accompanies the tactile sensory experience. Author summary: The challenge to neuroscience posed by the sense of time lies, first and foremost, in the fact there do not exist dedicated receptors–the passage of time is a sensory experience constructed without sensors. In the present study, we have found that the perceived duration of a vibration applied to the skin increases not only in relation to actual elapsed time but also in relation to the intensity of the vibration. Our data uncover this robust relationship–"stronger is judged as longer"–in the psychophysical results both of human subjects and rats, indicating a general mechanism linking stimulus features to perceived time. We propose a computational model where the experience of the elapsed time accompanying a stimulus is generated when the activity of the sensory cortical neuronal populations encoding that stimulus is integrated by a downstream accumulator. We test the plausibility of the model by simulating the time percept that would emerge through integration of the neuronal firing of real spike trains recorded from the sensory cortex of rats receiving the vibratory stimulus. The close match of the model's prediction of perceived time to actual perceived time for the same stimuli supports the proposed sensory integration account for time perception. [ABSTRACT FROM AUTHOR]

Chapatti (unleavened flatbread) is a staple food in northern India and neighboring countries but the genetics behind its processing quality are poorly understood. To understand the genes determining chapatti quality, differentially expressed genes were selected from microarray data of contrasting chapatti cultivars. From the gene and trait association studies, a null allele of granule bound starch synthase (GBSS; Wx-B1) was found to be associated with low amylose content and good chapatti quality. For validation, near-isogenic lines (NILs) of this allele were created by marker assisted backcross (MAB) breeding. Background screening indicated 88.2 to 96.7% background recovery in 16 selected BC3F5 NILs. Processing quality and sensory evaluation of selected NILs indicated improvement in chapatti making quality. Traits that showed improvement were mouthfeel, tearing strength and softness indicating that the Wx-B1 may be one of the major genes controlling chapatti softness. [ABSTRACT FROM AUTHOR]

Information in working memory (WM) can guide visual attention towards matched features. While recent work has suggested that cognitive control can act upon WM guidance of visual attention, little is known about how the state of memorized items retaining in WM contribute to its influence over attention. Here, we disentangle the role of inhibition and maintenance on WM-guided attention with a novel delayed match-to-sample dual-task. The results showed that active inhibition facilitated searching by diminishing sensory processing and deterring attentional guidance, indexed by an attenuated P1 amplitude and unaffected N2pc amplitude, respectively. By contrast, active maintenance impaired searching by attentional guidance while sensory processing remained unimpaired, indexed by an enhanced N2pc amplitude and unchanged P1 amplitude, respectively. Furthermore, multivariate pattern analyses could sucessfully decode maintenance and inhibition, suggesting that two states differed in modulating visual attention. We propose that remembered contents may play an anchoring role for attentional guidance, and the state of those contents retaining in WM may directly influence the shifting of attention. The maintenance could guide attention by accessing input information, while the inhibition could deter the shifting of attention by suppressing sensory processing. These findings provide a possible reinterpretation of the influence of WM on attention. [ABSTRACT FROM AUTHOR]

This study investigated the efficacy of a culturally modified resilience education program on Japanese adolescents' well-being from a differential susceptibility perspective. First, a culturally modified resilience education intervention was developed by employing the SPARK resilience program and implemented with 407 Japanese high school students in Tokyo (age = 15–16, M = 192, F = 215). To test intervention efficacy, students' level of resilience, self-esteem, self-efficacy, and depression were measured pre-, post-, and three months after intervention. Additionally, sensory processing sensitivity, using the Japanese version of the Highly Sensitive Child Scale for Adolescence, was measured as an index of individual sensitivity. Analysis of variance was used to examine the baseline differences and interaction effects of students' gender and level of sensory processing sensitivity. Latent growth curve models were used to assess the overall effects of the intervention and change over time. Results indicated that the intervention was effective in enhancing students' overall self-efficacy; and that highly sensitive students, who scored significantly lower in well-being than their counterparts at baseline, responded more positively to the intervention, and had a greater reduction in depression and promotion of self-esteem. These findings provided unique evidence in line with the differential susceptibility perspective and useful implications to develop personalized treatment interventions for adolescents in different cultural contexts. [ABSTRACT FROM AUTHOR]

The mammalian sensory cortex is composed of multiple types of inhibitory and excitatory neurons, which form sophisticated microcircuits for processing and transmitting sensory information. Despite rapid progress in understanding the function of distinct neuronal populations, the parameters of connectivity that are required for the function of these microcircuits remain unknown. Recent studies found that two most common inhibitory interneurons, parvalbumin- (PV) and somatostatin-(SST) positive interneurons control sound-evoked responses, temporal adaptation and network dynamics in the auditory cortex (AC). These studies can inform our understanding of parameters for the connectivity of excitatory-inhibitory cortical circuits. Specifically, we asked whether a common microcircuit can account for the disparate effects found in studies by different groups. By starting with a cortical rate model, we find that a simple current-compensating mechanism accounts for the experimental findings from multiple groups. They key mechanisms are two-fold. First, PVs compensate for reduced SST activity when thalamic inputs are strong with less compensation when thalamic inputs are weak. Second, SSTs are generally disinhibited by reduced PV activity regardless of thalamic input strength. These roles are augmented by plastic synapses. These differential roles reproduce the differential effects of PVs and SSTs in stimulus-specific adaptation, forward suppression and tuning-curve adaptation, as well as the influence of PVs on feedforward functional connectivity in the circuit. This circuit exhibits a balance of inhibitory and excitatory currents that persists on stimulation. This approach brings together multiple findings from different laboratories and identifies a circuit that can be used in future studies of upstream and downstream sensory processing. Author summary: The mammalian auditory cortex is composed of multiple types of inhibitory and excitatory neurons, which form sophisticated microcircuits for processing and transmitting sensory information. Distinct inhibitory neuron subtypes play distinct functions in auditory processing, but it remains unknown what simple set of underlying mechanisms is responsible for inhibitory cortical function. Here, we built minimal rate and spiking models and identified a specific set of synaptic mechanisms that could best reproduce the broad set of experimental results in the auditory cortex. The simplicity of our model provides an understanding of inhibitory cortical processing at the circuit level, which explains results from different laboratories, and provides for a novel computational framework for future studies of cortical function. [ABSTRACT FROM AUTHOR]

When people judge the weight of two objects of equal mass but different size, they perceive the smaller one as being heavier. Up to date, there is no consensus about the mechanisms which give rise to this size-weight illusion. We recently suggested a model that describes heaviness perception as a weighted average of two sensory heaviness estimates with correlated noise: one estimate derived from mass, the other one derived from density. The density estimate is first derived from mass and size, but at the final perceptual level, perceived heaviness is biased by an object's density, not by its size. Here, we tested the models' prediction that weight discrimination of equal-size objects is better in lifting conditions which are prone to the size-weight illusion as compared to conditions lacking (the essentially uninformative) size information. This is predicted because in these objects density covaries with mass, and according to the model density serves as an additional sensory cue. Participants performed a two-interval forced-choice weight discrimination task. We manipulated the quality of either haptic (Experiment 1) or visual (Experiment 2) size information and measured just-noticeable differences (JNDs). Both for the haptic and the visual illusion, JNDs were lower in lifting conditions in which size information was available. Thus, when heaviness perception can be influenced by an object's density, it is more reliable. This discrimination benefit under conditions that provide the additional information that objects are of equal size is further support for the role of density and the integration of sensory estimates in the size-weight illusion. [ABSTRACT FROM AUTHOR]

Subtle abnormalities in sensory integration, motor coordination and sequencing of complex motor acts or neurological soft signs (NSS) are characteristic phenomena in patients with schizophrenia at any stage of the illness. Previous MRI studies in schizophrenia found NSS to be associated with cortical, thalamic and cerebellar changes. Since these studies mainly focused on first-episode or recent onset schizophrenia, the cerebral correlates of NSS in chronic schizophrenia remained rather unclear. 49 middle-aged patients with chronic schizophrenia with a mean duration of illness of 20.3 ± 14.0 years and 29 healthy subjects matched for age and sex were included. NSS were examined on the Heidelberg Scale and correlated to grey matter (GM) by using whole brain high resolution magnetic resonance imaging (3 Tesla) with SPM12/CAT12 analyses. As expected, NSS in patients were significantly (p≤0.001) elevated in contrast to healthy controls, a finding, which not only applied to NSS total score, but also to the respective subscales "motor coordination", "sensory integration", "complex motor tasks", "right/left and spatial orientation" and "hard signs". Within the patient group NSS total scores were significantly correlated to reduced GM in right lingual gyrus, left parahippocampal gyrus, left superior temporal gyrus, left thalamus (medial dorsal nucleus) and left posterior lobe of the cerebellum (declive). Respective negative associations could also be revealed for the subscales "motor coordination", "complex motor tasks" and "right/left and spatial orientation". These findings remained significant after FWE-correction for multiple comparisons and were confirmed when years of education, chlorpromazine-equivalents or variables indicating the severity of psychopathology were introduced as additional covariates. According to our results lingual, parahippocampal, superior temporal, inferior and middle frontal gyri, thalamus and cerebellum have to be considered as important sites of NSS in chronic schizophrenia. That these findings only applied for patients but not healthy controls may indicate a different pathogenesis of NSS. [ABSTRACT FROM AUTHOR]

The number of elements in two stereo-surfaces parallelly overlapped in depth is overestimated compared to that in a single flat surface, even when both have the same number of elements. Using stereoscopic pairs of elements, we evaluated two hypotheses on the overestimation: one that a higher-order process, forming a background surface, increases the number of perceived elements, and the other that the number of elements potentially occluded by the elements on a front surface is taken accounted for. The data from four experiments showed that (a) when binocular disparity between (or among) stereoscopic elements was small, the overestimation occurred for the stimuli we used—a two-surface-overlapping stimulus, where the likelihood for the process to operate was manipulated by changing the averaged luminance of each surface, a volumetric stimulus, where the likelihood for the background surface to be formed would decrease, and a two-non-overlapping-surface stimulus, where the surfaces in depth were not overlapped—, and (b) when binocular disparity was large, the overestimation occurred for the two-surfaces-overlapping stimulus, when the averaged luminance of the two surfaces were the same, and for the volumetric stimulus, but diminished for the surface-overlapping stimulus, when the averaged luminance differed between the surfaces and for the surfaces-non-overlapping stimulus. These results cannot be explained either hypothesis only. We explain the results by postulating that the sensory system processing disparities of elements interferes with that estimating the number of elements, resulting in an overestimation of the elements in a stereo-stimulus, and the disparity range within which the interference occurs may depend on the stimulus depth structure. [ABSTRACT FROM AUTHOR]

Cortical interneurons expressing vasoactive intestinal polypeptide (VIP) and choline acetyltransferase (ChAT) are sparsely distributed throughout the neocortex, constituting only 0.5% of its neuronal population. The co-expression of VIP and ChAT suggests that these VIP/ChAT interneurons (VChIs) can release both γ-aminobutyric acid (GABA) and acetylcholine (ACh). In vitro physiological studies quantified the response properties and local connectivity patterns of the VChIs; however, the function of VChIs has not been explored in vivo. To study the role of VChIs in cortical network dynamics and their long-range connectivity pattern, we used in vivo electrophysiology and rabies virus tracing in the barrel cortex of mice. We found that VChIs have a low spontaneous spiking rate (approximately 1 spike/s) in the barrel cortex of anesthetized mice; nevertheless, they responded with higher fidelity to whisker stimulation than the neighboring layer 2/3 pyramidal neurons (Pyrs). Analysis of long-range inputs to VChIs with monosynaptic rabies virus tracing revealed that direct thalamic projections are a significant input source to these cells. Optogenetic activation of VChIs in the barrel cortex of awake mice suppresses the sensory responses of excitatory neurons in intermediate amplitudes of whisker deflections while increasing the evoked spike latency. The effect of VChI activation on the response was similar for both high-whisking (HW) and low-whisking (LW) conditions. Our findings demonstrate that, despite their sparsity, VChIs can effectively modulate sensory processing in the cortical microcircuit. This study shows that despite their sparsity (about 0.5% of neurons), a population of interneurons in the mouse barrel cortex that express genes associated with both cholinergic and GABAergic signalling can effectively modulate sensory processing in the cortical microcircuit. [ABSTRACT FROM AUTHOR]

The striatum is involved in the completion and optimization of sensorimotor tasks. In rodents, its dorsolateral part receives converging glutamatergic corticostriatal (CS) inputs from whisker-related primary somatosensory (S1) and motor (M1) cortical areas, which are interconnected at the cortical level. Although it has been demonstrated that the medium-spiny neurons (MSNs) from the dorsolateral striatum process sensory information from the whiskers via the S1 CS pathway, the functional impact of the corresponding M1 CS inputs onto the same striatal neurons remained unknown. Here, by combining in vivo S1 electrocorticogram with intracellular recordings from somatosensory MSNs in the rat, we first confirmed the heterogeneity of striatal responsiveness to whisker stimuli, encompassing MSNs responding exclusively by subthreshold synaptic depolarizations, MSNs exhibiting sub- and suprathreshold responses over successive stimulations, and non-responding cells. All recorded MSNs also exhibited clear-cut monosynaptic depolarizing potentials in response to electrical stimulations of the corresponding ipsilateral M1 cortex, which were efficient to fire striatal cells. Since M1-evoked responses in MSNs could result from the intra-cortical recruitment of S1 CS neurons, we performed intracellular recordings of S1 pyramidal neurons and compared their firing latency following M1 stimuli to the latency of striatal synaptic responses. We found that the onset of M1-evoked synaptic responses in MSNs significantly preceded the firing of S1 neurons, demonstrating a direct synaptic excitation of MSNs by M1. However, the firing of MSNs seemed to require the combined excitatory effects of S1 and M1 CS inputs. This study directly demonstrates that the same somatosensory MSNs can process excitatory synaptic inputs from two functionally-related sensory and motor cortical regions converging into the same striatal sector. The effectiveness of these convergent cortical inputs in eliciting action potentials in MSNs may represent a key mechanism of striatum-related sensorimotor behaviors. [ABSTRACT FROM AUTHOR]