scholarly journals Increase in Mutual Information During Interaction with the Environment Contributes to Perception

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 365 ◽  
Author(s):  
Daya Gupta ◽  
Andreas Bahmer
Keyword(s):  
Mutual Information ◽  
Neural Circuits ◽  
Probability Distributions ◽  
Sensory Information ◽  
Hierarchical Level ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Action And Perception ◽  
Temporal Coupling ◽  
Motor Interaction

Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with the physical environment are partly accounted for by a reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level, but belonging to different networks. The increase in mutual information is partly accounted for by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta (Front. Neurosci. 2018). We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs’ and neural circuits’ connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. The increase in mutual information, given the knowledge about environmental sensory stimuli and the type of motor response produced, is responsible for the coupling between action and perception. In addition, the processing of sensory inputs within neural circuits, with no prior knowledge of the occurrence of a sensory stimulus, increases Shannon information. Consequently, the increase in surprise serves to increase the evidence of the sensory model of physical surroundings

scholarly journals Increase in Mutual Information During Interaction of the Brain with Environment Contributes to Perception

2019 ◽  
Author(s):  
Daya Gupta ◽  
Andreas Bahmer
Keyword(s):  
Mutual Information ◽  
Sensory Input ◽  
Neural Circuits ◽  
Probability Distributions ◽  
Sensory Information ◽  
Hierarchical Level ◽  
Temporal Coupling ◽  
The Given ◽  
The Brain ◽  
Motor Interaction

Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with physical environment are accounted partly by the reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information among them, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level but belonging to different networks. The increase in mutual information is partly accounted by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta [1]. We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs and neural circuits connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. It is also argued that perception from a sensory input is the result of networking of many circuits to a common circuit that primarily processes the given sensory input.

scholarly journals Nucleus Basalis links sensory stimuli with delayed reinforcement to support learning

2019 ◽  
Author(s):  
W. Guo ◽  
D.B. Polley
Keyword(s):  
Basal Forebrain ◽  
Neural Circuits ◽  
Cortical Plasticity ◽  
Cholinergic Neurons ◽  
Nucleus Basalis ◽  
Fear Learning ◽  
Delayed Reinforcement ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Cholinergic Basal Forebrain

SummaryLinking stimuli with delayed reinforcement requires neural circuits that can bridge extended temporal gaps. Auditory cortex (ACx) circuits reorganize to support auditory fear learning, but only when afferent sensory inputs temporally overlap with cholinergic reinforcement signals. Here we show that mouse ACx neurons rapidly reorganize to support learning, even when sensory and reinforcement cues are separated by a long gap. We found that cholinergic basal forebrain neurons bypass the temporal delay through multiplexed, short-latency encoding of sensory and reinforcement cues. At the initiation of learning, cholinergic neurons in Nucleus Basalis increase responses to conditioned sound frequencies and increase functional connectivity with ACx. By rapidly scaling up responses to sounds that predict reinforcement, cholinergic inputs jump the gap to align with bottom-up sensory traces and support associative cortical plasticity.

scholarly journals Rotational Dynamics Reduce Interference Between Sensory and Memory Representations

2019 ◽  
Author(s):  
Alexandra Libby ◽  
Timothy J. Buschman
Keyword(s):  
Sensory Information ◽  
Primary Auditory Cortex ◽  
Cell Types ◽  
Neural Population ◽  
Memory Representation ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Continuous Stream ◽  
Statistical Regularities ◽  
The Brain

AbstractSensory stimuli arrive in a continuous stream. By learning statistical regularities in the sequence of stimuli, the brain can predict future stimuli (Xu et al. 2012; Gavornik and Bear 2014; Maniscalco et al. 2018; J. Fiser and Aslin 2002). Such learning requires associating immediate sensory information with the memory of recently encountered stimuli (Ostojic and Fusi 2013; Kiyonaga et al. 2017). However, new sensory information can also interfere with short-term memories (Parthasarathy et al. 2017). How the brain prevents such interference is unknown. Here, we show that sensory representations rotate in neural space over time, to form an independent memory representation, thus reducing interference with future sensory inputs. We used an implicit learning paradigm in mice to study how statistical regularities in a sequence of stimuli are learned and represented in primary auditory cortex. Mice experienced both common sequences of stimuli (e.g. ABCD) and uncommon sequences (e.g. XYCD). Over four days of learning, the neural population representation of commonly associated stimuli (e.g. A and C) converged. This facilitated the prediction of upcoming stimuli, but also led unexpected sensory inputs to overwrite the sensory representation of previous stimuli (postdiction). Surprisingly, we found the memory of previous stimuli persisted in a second, orthogonal dimension. Unsupervised clustering of functional cell types revealed that the emergence of this second memory dimension is supported by two separate types of neurons; a ‘stable’ population that maintained its selectivity throughout the sequence and a ‘switching’ population that dynamically inverted its selectivity. This combination of sustained and dynamic representations produces a rotation of the encoding dimension in the neural population. This rotational dynamic may be a general principle, by which the cortex protects memories of prior events from interference by incoming stimuli.

scholarly journals Corticostriatal control of defense behavior in mice induced by auditory looming cues

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhong Li ◽  
Jin-Xing Wei ◽  
Guang-Wei Zhang ◽  
Junxiang J. Huang ◽  
Brian Zingg ◽  
...  
Keyword(s):  
Essential Role ◽  
Neural Circuits ◽  
Temporal Dynamics ◽  
Defense Behavior ◽  
Innate Defense ◽  
Sensory Inputs ◽  
Corticostriatal Projections ◽  
Behavioral Transition ◽  
Auditory Looming

AbstractAnimals exhibit innate defense behaviors in response to approaching threats cued by the dynamics of sensory inputs of various modalities. The underlying neural circuits have been mostly studied in the visual system, but remain unclear for other modalities. Here, by utilizing sounds with increasing (vs. decreasing) loudness to mimic looming (vs. receding) objects, we find that looming sounds elicit stereotypical sequential defensive reactions: freezing followed by flight. Both behaviors require the activity of auditory cortex, in particular the sustained type of responses, but are differentially mediated by corticostriatal projections primarily innervating D2 neurons in the tail of the striatum and corticocollicular projections to the superior colliculus, respectively. The behavioral transition from freezing to flight can be attributed to the differential temporal dynamics of the striatal and collicular neurons in their responses to looming sound stimuli. Our results reveal an essential role of the striatum in the innate defense control.

scholarly journals Sensory over-responsivity is related to GABAergic inhibition in thalamocortical circuits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily T. Wood ◽  
Kaitlin K. Cummings ◽  
Jiwon Jung ◽  
Genevieve Patterson ◽  
Nana Okada ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Sensory Information ◽  
Network Connectivity ◽  
Sensory Stimulation ◽  
Autism Spectrum ◽  
Future Research ◽  
Resonance Spectroscopy ◽  
Gamma Aminobutyric Acid ◽  
Sensory Stimuli ◽  
Brain Responses

AbstractSensory over-responsivity (SOR), extreme sensitivity to or avoidance of sensory stimuli (e.g., scratchy fabrics, loud sounds), is a highly prevalent and impairing feature of neurodevelopmental disorders such as autism spectrum disorders (ASD), anxiety, and ADHD. Previous studies have found overactive brain responses and reduced modulation of thalamocortical connectivity in response to mildly aversive sensory stimulation in ASD. These findings suggest altered thalamic sensory gating which could be associated with an excitatory/inhibitory neurochemical imbalance, but such thalamic neurochemistry has never been examined in relation to SOR. Here we utilized magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to examine the relationship between thalamic and somatosensory cortex inhibitory (gamma-aminobutyric acid, GABA) and excitatory (glutamate) neurochemicals with the intrinsic functional connectivity of those regions in 35 ASD and 35 typically developing pediatric subjects. Although there were no diagnostic group differences in neurochemical concentrations in either region, within the ASD group, SOR severity correlated negatively with thalamic GABA (r = −0.48, p < 0.05) and positively with somatosensory glutamate (r = 0.68, p < 0.01). Further, in the ASD group, thalamic GABA concentration predicted altered connectivity with regions previously implicated in SOR. These variations in GABA and associated network connectivity in the ASD group highlight the potential role of GABA as a mechanism underlying individual differences in SOR, a major source of phenotypic heterogeneity in ASD. In ASD, abnormalities of the thalamic neurochemical balance could interfere with the thalamic role in integrating, relaying, and inhibiting attention to sensory information. These results have implications for future research and GABA-modulating pharmacologic interventions.

scholarly journals The emulation theory of representation: Motor control, imagery, and perception

2004 ◽  
Vol 27 (3) ◽  
pp. 377-396 ◽  
Author(s):  
Rick Grush
Keyword(s):  
Motor Control ◽  
Sensory Feedback ◽  
Sensory Input ◽  
Neural Circuits ◽  
Sensory Information ◽  
The Body ◽  
Feedback Delay ◽  
Run Off ◽  
Effects Of Feedback ◽  
The Brain

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.

FosGFP expression does not capture a sensory learning-related engram in superficial layers of mouse barrel cortex

2021 ◽  
Vol 118 (52) ◽  
pp. e2112212118
Author(s):  
Jiseok Lee ◽  
Joanna Urban-Ciecko ◽  
Eunsol Park ◽  
Mo Zhu ◽  
Stephanie E. Myal ◽  
...  
Keyword(s):  
Pyramidal Neurons ◽  
Barrel Cortex ◽  
Sensory Information ◽  
Learning Task ◽  
Early Gene ◽  
Sensory Stimuli ◽  
Association Learning ◽  
Neural Ensembles ◽  
Dependent Learning

Immediate-early gene (IEG) expression has been used to identify small neural ensembles linked to a particular experience, based on the principle that a selective subset of activated neurons will encode specific memories or behavioral responses. The majority of these studies have focused on “engrams” in higher-order brain areas where more abstract or convergent sensory information is represented, such as the hippocampus, prefrontal cortex, or amygdala. In primary sensory cortex, IEG expression can label neurons that are responsive to specific sensory stimuli, but experience-dependent shaping of neural ensembles marked by IEG expression has not been demonstrated. Here, we use a fosGFP transgenic mouse to longitudinally monitor in vivo expression of the activity-dependent gene c-fos in superficial layers (L2/3) of primary somatosensory cortex (S1) during a whisker-dependent learning task. We find that sensory association training does not detectably alter fosGFP expression in L2/3 neurons. Although training broadly enhances thalamocortical synaptic strength in pyramidal neurons, we find that synapses onto fosGFP+ neurons are not selectively increased by training; rather, synaptic strengthening is concentrated in fosGFP− neurons. Taken together, these data indicate that expression of the IEG reporter fosGFP does not facilitate identification of a learning-specific engram in L2/3 in barrel cortex during whisker-dependent sensory association learning.

scholarly journals Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective

2019 ◽  
Author(s):  
Samantha Hughes ◽  
Tansu Celikel
Keyword(s):  
Motor Neurons ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Sensory Information ◽  
Circuit Complexity ◽  
Inhibitory Circuits ◽  
Invertebrate Species ◽  
Gating Mechanism ◽  
Motor Actions ◽  
Sensorimotor Representations

From single-cell organisms to complex neural networks, all evolved to provide control solutions to generate context and goal-specific actions. Neural circuits performing sensorimotor computation to drive navigation employ inhibitory control as a gating mechanism, as they hierarchically transform (multi)sensory information into motor actions. Here, we focus on this literature to critically discuss the proposition that prominent inhibitory projections form sensorimotor circuits. After reviewing the neural circuits of navigation across various invertebrate species, we argue that with increased neural circuit complexity and the emergence of parallel computations inhibitory circuits acquire new functions. The contribution of inhibitory neurotransmission for navigation goes beyond shaping the communication that drives motor neurons, instead, include encoding of emergent sensorimotor representations. A mechanistic understanding of the neural circuits performing sensorimotor computations in invertebrates will unravel the minimum circuit requirements driving adaptive navigation.

The Synergistic Organization of Muscle Recruitment Constrains Visuomotor Adaptation

2009 ◽  
Vol 101 (5) ◽  
pp. 2263-2269 ◽  
Author(s):  
Aymar de Rugy ◽  
Mark R. Hinder ◽  
Daniel G. Woolley ◽  
Richard G. Carson
Keyword(s):  
Time Course ◽  
Neural Circuits ◽  
Visual Target ◽  
Sensory Information ◽  
Visuomotor Adaptation ◽  
Visuomotor Rotation ◽  
Joint Torques ◽  
Flexion Extension ◽  
Isometric Torque ◽  
The Individual

Reaching to visual targets engages the nervous system in a series of transformations between sensory information and motor commands. That which remains to be determined is the extent to which the processes that mediate sensorimotor adaptation to novel environments engage neural circuits that represent the required movement in joint-based or muscle-based coordinate systems. We sought to establish the contribution of these alternative representations to the process of visuomotor adaptation. To do so we applied a visuomotor rotation during a center-out isometric torque production task that involved flexion/extension and supination/pronation at the elbow-joint complex. In separate sessions, distinct half-quadrant rotations (i.e., 45°) were applied such that adaptation could be achieved either by only rescaling the individual joint torques (i.e., the visual target and torque target remained in the same quadrant) or by additionally requiring torque reversal at a contributing joint (i.e., the visual target and torque target were in different quadrants). Analysis of the time course of directional errors revealed that the degree of adaptation was lower (by ∼20%) when reversals in the direction of joint torques were required. It has been established previously that in this task space, a transition between supination and pronation requires the engagement of a different set of muscle synergists, whereas in a transition between flexion and extension no such change is required. The additional observation that the initial level of adaptation was lower and the subsequent aftereffects were smaller, for trials that involved a pronation–supination transition than for those that involved a flexion–extension transition, supports the conclusion that the process of adaptation engaged, at least in part, neural circuits that represent the required motor output in a muscle-based coordinate system.

The Neural Basis of Escape Behavior in Vertebrates

2020 ◽  
Vol 43 (1) ◽  
pp. 417-439 ◽  
Author(s):  
Tiago Branco ◽  
Peter Redgrave
Keyword(s):  
Neural Circuits ◽  
Escape Behavior ◽  
Building Blocks ◽  
Normative Theory ◽  
Neural Systems ◽  
Adaptive Behaviors ◽  
Neural Basis ◽  
Sensory Stimuli ◽  
Evolutionarily Conserved ◽  
Escape Behaviors

Escape is one of the most studied animal behaviors, and there is a rich normative theory that links threat properties to evasive actions and their timing. The behavioral principles of escape are evolutionarily conserved and rely on elementary computational steps such as classifying sensory stimuli and executing appropriate movements. These are common building blocks of general adaptive behaviors. Here we consider the computational challenges required for escape behaviors to be implemented, discuss possible algorithmic solutions, and review some of the underlying neural circuits and mechanisms. We outline shared neural principles that can be implemented by evolutionarily ancient neural systems to generate escape behavior, to which cortical encephalization has been added to allow for increased sophistication and flexibility in responding to threat.

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