scholarly journals Endogenous activity modulates stimulus and circuit-specific neural tuning and perception

2019 ◽  
Author(s):  
Yuanning Li ◽  
Michael J. Ward ◽  
R. Mark Richardson ◽  
Max G’Sell ◽  
Avniel Singh Ghuman
Keyword(s):  
Reaction Time ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Predictive Coding ◽  
Sensory Inputs ◽  
Specific Manner ◽  
Endogenous Activity ◽  
Intracranial Recordings ◽  
The Brain

AbstractPerception reflects not only input from the sensory periphery, but also the endogenous neural state when sensory inputs enter the brain. Whether endogenous neural states influence perception only through global mechanisms, such as arousal, or can also perception in a neural circuit and stimulus specific manner remains largely unknown. Intracranial recordings from 30 pre-surgical epilepsy patients showed that endogenous activity independently modulated the strength of trial-by-trial neural tuning of different visual category-selective neural circuits. Furthermore, the same aspect of the endogenous activity that influenced tuning in a particular neural circuit also correlated with reaction time only for trials with the category of image that circuit was selective for. These results suggest that endogenous activity may influence neural tuning and perception through circuit-specific predictive coding processes.

scholarly journals Multiple Functions of Draxin/Netrin-1 Signaling in the Development of Neural Circuits in the Spinal Cord and the Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Giasuddin Ahmed ◽  
Yohei Shinmyo
Keyword(s):  
Spinal Cord ◽  
Axon Guidance ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Deleted In Colorectal Cancer ◽  
Guidance Cue ◽  
Thalamocortical Projections ◽  
The Central Nervous System ◽  
Circuit Formation ◽  
The Brain

Axon guidance proteins play key roles in the formation of neural circuits during development. We previously identified an axon guidance cue, named draxin, that has no homology with other axon guidance proteins. Draxin is essential for the development of various neural circuits including the spinal cord commissure, corpus callosum, and thalamocortical projections. Draxin has been shown to not only control axon guidance through netrin-1 receptors, deleted in colorectal cancer (Dcc), and neogenin (Neo1) but also modulate netrin-1-mediated axon guidance and fasciculation. In this review, we summarize the multifaceted functions of draxin and netrin-1 signaling in neural circuit formation in the central nervous system. Furthermore, because recent studies suggest that the distributions and functions of axon guidance cues are highly regulated by glycoproteins such as Dystroglycan and Heparan sulfate proteoglycans, we discuss a possible function of glycoproteins in draxin/netrin-1-mediated axon guidance.

Dynamical Foundations of the Neural Circuit for Bayesian Decision Making

2009 ◽  
Vol 102 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Kenji Morita
Keyword(s):  
Decision Making ◽  
Bayesian Inference ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Bayesian Decision ◽  
Biophysical Modeling ◽  
Perceptual Decision Making ◽  
Basic Ideas ◽  
Bayesian Decision Making ◽  
The Brain

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

scholarly journals Predictive feedback to V1 dynamically updates with sensory input

2017 ◽  
Author(s):  
Grace Edwards ◽  
Petra Vetter ◽  
Fiona McGruer ◽  
Lucy S. Petro ◽  
Lars Muckli
Keyword(s):  
Eye Movements ◽  
Apparent Motion ◽  
Sensory Input ◽  
Predictive Coding ◽  
Functional Brain Imaging ◽  
Sensory Inputs ◽  
Amplification Process ◽  
Early Visual Cortex ◽  
Higher Visual Areas ◽  
The Brain

AbstractPredictive coding theories propose that the brain creates internal models of the environment to predict upcoming sensory input. Hierarchical predictive coding models of vision postulate that higher visual areas generate predictions of sensory inputs and feed them back to early visual cortex. In V1, sensory inputs that do not match the predictions lead to amplified brain activation, but does this amplification process dynamically update to new retinotopic locations with eye-movements? We investigated the effect of eye-movements in predictive feedback using functional brain imaging and eye-tracking whilst presenting an apparent motion illusion. Apparent motion induces an internal model of motion, during which sensory predictions of the illusory motion feed back to V1. We observed attenuated BOLD responses to predicted stimuli at the new post-saccadic location in V1. Therefore, pre-saccadic predictions update their retinotopic location in time for post-saccadic input, validating dynamic predictive coding theories in V1.

Central Neural Circuits Regulating Maternal Behavior in Nonhuman Mammals

2020 ◽  
pp. 99-163
Author(s):  
Michael Numan
Keyword(s):  
Maternal Behavior ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Virgin Female ◽  
Dopamine System ◽  
Mesolimbic Dopamine System ◽  
Brain Circuits ◽  
Maternal Motivation ◽  
Maternal Responses ◽  
The Brain

Chapter 5 reviews the brain circuits that regulate maternal behavior in nonhuman mammals. The medial preoptic area (MPOA) is essential for both the onset and maintenance of maternal behavior. Hormones and oxytocin act on the MPOA to stimulate the onset of maternal behavior. The neurotransmitters contained within MPOA neurons that may regulate maternal behavior are described, as are several neural inputs to the MPOA that regulate its output. A defensive neural circuit that inhibits maternal behavior in most virgin female mammals is described. MPOA output stimulates maternal behavior by depressing the defensive circuit while also activating neural circuits that underpin maternal motivation. MPOA output to the mesolimbic dopamine system is essential for appetitive maternal responses, while its output to the periaqueductal gray regulates consummatory responses. Synaptic plasticity within the MPOA-to-mesolimbic DA circuit is involved in the development of an enduring mother–infant bond.

Sensitive Periods in the Development of the Brain and Behavior

2004 ◽  
Vol 16 (8) ◽  
pp. 1412-1425 ◽  
Author(s):  
Eric I. Knudsen
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Critical Role ◽  
Sensitive Period ◽  
Critical Periods ◽  
Sensitive Periods ◽  
Brain And Behavior ◽  
The Individual ◽  
And Behavior ◽  
The Brain

Experience exerts a profound influence on the brain and, therefore, on behavior. When the effect of experience on the brain is particularly strong during a limited period in development, this period is referred to as a sensitive period. Such periods allow experience to instruct neural circuits to process or represent information in a way that is adaptive for the individual. When experience provides information that is essential for normal development and alters performance permanently, such sensitive periods are referred to as critical periods. Although sensitive periods are reflected in behavior, they are actually a property of neural circuits. Mechanisms of plasticity at the circuit level are discussed that have been shown to operate during sensitive periods. A hypothesis is proposed that experience during a sensitive period modifies the architecture of a circuit in fundamental ways, causing certain patterns of connectivity to become highly stable and, therefore, energetically preferred. Plasticity that occurs beyond the end of a sensitive period, which is substantial in many circuits, alters connectivity patterns within the architectural constraints established during the sensitive period. Preferences in a circuit that result from experience during sensitive periods are illustrated graphically as changes in a “stability landscape,” a metaphor that represents the relative contributions of genetic and experiential influences in shaping the information processing capabilities of a neural circuit. By understanding sensitive periods at the circuit level, as well as understanding the relationship between circuit properties and behavior, we gain a deeper insight into the critical role that experience plays in shaping the development of the brain and behavior.

scholarly journals Somatosensory evoked potentials, indexing lateral inhibition, are modulated according to the mode of perceptual processing: comparing or combining multi-digit tactile motion

2020 ◽  
Author(s):  
Irena Arslanova ◽  
Keying Wang ◽  
Hiroaki Gomi ◽  
Patrick Haggard
Keyword(s):  
Lateral Inhibition ◽  
Neural Circuit ◽  
Event Related Potential ◽  
Somatosensory Processing ◽  
Sensory Inputs ◽  
Motion Trajectories ◽  
The Right ◽  
Cortical Representations ◽  
The Brain ◽  
Combining Information

AbstractMany perceptual studies focus on the brain’s capacity to discriminate between stimuli. However, our normal experience of the world also involves integrating multiple stimuli into a single perceptual event. Neural circuit mechanisms such as lateral inhibition are believed to enhance local differences between sensory inputs from nearby regions of the receptor surface. However, this mechanism would seem dysfunctional when sensory inputs need to be combined rather than contrasted. Here, we investigated whether the brain can strategically regulate the strength of suppressive interactions that underlie lateral inhibition between finger representations in human somatosensory processing. To do this, we compared sensory processing between conditions that required either comparing or combining information. We delivered two simultaneous tactile motion trajectories to index and middle fingertips of the right hand. Participants had to either compare the directions of the two stimuli, or to combine them to form their average direction. To reveal preparatory tuning of somatosensory cortex, we used an established event-related potential design to measure the interaction between cortical representations evoked by digital nerve shocks immediately before each tactile stimulus. Consistent with previous studies, we found a clear suppressive interaction between cortical activations when participants were instructed to compare the tactile motion directions. Importantly, this suppressive interaction was significantly reduced when participants had to combine the same stimuli. These findings suggest that the brain can strategically switch between a comparative and a combinative mode of somatosensory processing, according to the perceptual goal, by preparatorily adjusting the strength of a process akin to lateral inhibition.

scholarly journals Neural Circuits Trained with Standard Reinforcement Learning Can Accumulate Probabilistic Information during Decision Making

2017 ◽  
Vol 29 (2) ◽  
pp. 368-393 ◽  
Author(s):  
Nils Kurzawa ◽  
Christopher Summerfield ◽  
Rafal Bogacz
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Neural Activity ◽  
Neural Circuits ◽  
Likelihood Ratios ◽  
Sensory Inputs ◽  
Probabilistic Information ◽  
Learning Rules ◽  
Log Likelihood ◽  
The Brain

Much experimental evidence suggests that during decision making, neural circuits accumulate evidence supporting alternative options. A computational model well describing this accumulation for choices between two options assumes that the brain integrates the log ratios of the likelihoods of the sensory inputs given the two options. Several models have been proposed for how neural circuits can learn these log-likelihood ratios from experience, but all of these models introduced novel and specially dedicated synaptic plasticity rules. Here we show that for a certain wide class of tasks, the log-likelihood ratios are approximately linearly proportional to the expected rewards for selecting actions. Therefore, a simple model based on standard reinforcement learning rules is able to estimate the log-likelihood ratios from experience and on each trial accumulate the log-likelihood ratios associated with presented stimuli while selecting an action. The simulations of the model replicate experimental data on both behavior and neural activity in tasks requiring accumulation of probabilistic cues. Our results suggest that there is no need for the brain to support dedicated plasticity rules, as the standard mechanisms proposed to describe reinforcement learning can enable the neural circuits to perform efficient probabilistic inference.

scholarly journals Processing of Degraded Speech in Brain Disorders

2021 ◽  
Vol 11 (3) ◽  
pp. 394
Author(s):  
Jessica Jiang ◽  
Elia Benhamou ◽  
Sheena Waters ◽  
Jeremy C. S. Johnson ◽  
Anna Volkmer ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Speech Processing ◽  
Neural Circuit ◽  
Predictive Coding ◽  
Brain Disorders ◽  
Healthy Individuals ◽  
Degraded Speech ◽  
The Brain ◽  
Sensitive Marker ◽  
Language Network

The speech we hear every day is typically “degraded” by competing sounds and the idiosyncratic vocal characteristics of individual speakers. While the comprehension of “degraded” speech is normally automatic, it depends on dynamic and adaptive processing across distributed neural networks. This presents the brain with an immense computational challenge, making degraded speech processing vulnerable to a range of brain disorders. Therefore, it is likely to be a sensitive marker of neural circuit dysfunction and an index of retained neural plasticity. Considering experimental methods for studying degraded speech and factors that affect its processing in healthy individuals, we review the evidence for altered degraded speech processing in major neurodegenerative diseases, traumatic brain injury and stroke. We develop a predictive coding framework for understanding deficits of degraded speech processing in these disorders, focussing on the “language-led dementias”—the primary progressive aphasias. We conclude by considering prospects for using degraded speech as a probe of language network pathophysiology, a diagnostic tool and a target for therapeutic intervention.

scholarly journals Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity

2018 ◽  
Author(s):  
Lu Shen ◽  
Biao Han ◽  
Lihan Chen ◽  
Qi Chen
Keyword(s):  
Time Window ◽  
Inference Process ◽  
Perceptual Inference ◽  
Band Frequency ◽  
Sensory Inputs ◽  
Alpha Frequency ◽  
Neural Representations ◽  
Intracranial Recordings ◽  
Time Information ◽  
The Brain

AbstractThe brain uses its intrinsic dynamics to actively predict observed sensory inputs, especially under perceptual ambiguity. However, it remains unclear how this inference process is neurally implemented in biasing perception of ambiguous inputs towards the predicted percepts. Using electroencephalography and intracranial recordings, we first show that the alpha-band frequency defines a unified time window for perceptual grouping across both space and time: information segments, either spatially or temporally segregated, will be integrated if they fall within the same alpha cycle. Moreover, predictions employ this prior knowledge on intrinsic alpha frequency to shift perceptual inference towards the most possibly observed percepts. Multivariate decoding analysis showed that perceptual inference, based on variance in prestimulus alpha frequency (PAF), biases post-stimulus neural representations by inducing preactivation of the predicted percepts. fMRI results additionally showed that prestimulus activity and intrinsic organization status in the frontoparietal attentional network predict perceptual outcomes, probably by modulating occipitoparietal PAFs.

scholarly journals A mechanism for synaptic copy between neural circuits

2018 ◽  
Author(s):  
Yuxiu Shao ◽  
Binxu Wang ◽  
Andrew T. Sornborger ◽  
Louis Tao
Keyword(s):  
Memory Consolidation ◽  
Information Transfer ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Neural Systems ◽  
Long Term Memory ◽  
Cortical Oscillations ◽  
The Brain ◽  
Putative Mechanism

The brain has a central, short-term learning module, the hippocampus, which transfers what it has learned to long-term memory in cortex during non-REM sleep. The putative mechanism responsible for this type of memory consolidation invokes hierarchically nested hippocampal ripples (100-250 Hz), thalamo-cortical spindles (7-15 Hz), and cortical slow oscillations (< 1 Hz) to enable transfer. Suppression of, for instance, thalamic spindles has been shown to impair hippocampus-dependent memory consolidation. Cortical oscillations are central to information transfer in neural systems. Significant evidence supports the idea that coincident spike input can allow the neural threshold to be overcome, and spikes to be propagated downstream in a circuit. Thus, an observation of oscillations in neural circuits would be an indication that repeated synchronous spiking is enabling information transfer. However, for memory transfer, in which synaptic weights must be being transferred from one neural circuit (region) to another, what is the mechanism? Here, we present a synaptic transfer mechanism whose structure provides some understanding of the phenomena that have been implicated in memory transfer, including the nested oscillations at various frequencies. The circuit is based on the principle of pulse-gated, graded information transfer between neural populations.PACS numbers: 87.18.Sn,87.19.lj,87.19.lm,87.19.lq

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