Perception and Imagery

Brain-Mind ◽  
2019 ◽  
pp. 50-71
Author(s):  
Paul Thagard
Keyword(s):  
Neural Mechanisms ◽  
Neural Representation ◽  
Sensory Inputs ◽  
General Account ◽  
Binding Competition ◽  
Mental Operations

This chapter provides a general account of imagery that applies to both external senses such as vision and internal senses such as pain. It identifies five mental operations that occur in all kinds of imagery: intensification, focusing, combination, juxtaposition, and decomposition. Each of these operations results from neural mechanisms that are part of the Semantic Pointer Architecture, including storage, retrieval, neural representation, binding, competition, and transformation. There is abundant psychological and neural evidence that imagery is real and that the brain’s computations employ special patterns of neural representation that develop from sensory inputs. This development requires binding into semantic pointers that are susceptible to symbol-like manipulation that exploits the different sensory characters of visual, auditory, and other sorts of representation.

scholarly journals Mice are not automatons; subjective experience in premotor circuits guides behavior

2021 ◽  
Author(s):  
Drew C. Schreiner ◽  
Christian Cazares ◽  
Rafael Renteria ◽  
Christina M Gremel
Keyword(s):  
Decision Making ◽  
Motor Cortex ◽  
Adaptive Behavior ◽  
Subjective Experience ◽  
Contextual Factors ◽  
Neural Mechanisms ◽  
Neural Representation ◽  
Recent Experience ◽  
Checking Behavior ◽  
Corticostriatal Circuits

Subjective experience is a powerful driver of decision-making and continuously accrues. However, most neurobiological studies constrain analyses to task-related variables and ignore how continuously and individually experienced internal, temporal, and contextual factors influence adaptive behavior during decision-making and the associated neural mechanisms. We show mice rely on learned information about recent and longer-term subjective experience of variables above and beyond prior actions and reward, including checking behavior and the passage of time, to guide self-initiated, self-paced, and self-generated actions. These experiential variables were represented in secondary motor cortex (M2) activity and its projections into dorsal medial striatum (DMS). M2 integrated this information to bias strategy-level decision-making, and DMS projections used specific aspects of this recent experience to plan upcoming actions. This suggests diverse aspects of experience drive decision-making and its neural representation, and shows premotor corticostriatal circuits are crucial for using selective aspects of experiential information to guide adaptive behavior.

scholarly journals A neural signature of pattern separation in the monkey hippocampus

2018 ◽  
Author(s):  
John J. Sakon ◽  
Wendy A. Suzuki
Keyword(s):  
Dentate Gyrus ◽  
Neural Mechanisms ◽  
Pattern Separation ◽  
Visual Pattern ◽  
Complex Behavior ◽  
Firing Rates ◽  
Sensory Inputs ◽  
Neural Signature

AbstractThe CA3 and dentate gyrus (DG) regions of the hippocampus are considered key for disambiguating sensory inputs from similar experiences in memory, a process termed pattern separation. The neural mechanisms underlying pattern separation, however, have been difficult to compare across species: rodents offer robust recording methods with less human-centric tasks while humans provide complex behavior with less recording potential. To overcome these limitations, we trained monkeys to perform a visual pattern separation task similar to those used in humans while recording activity from single CA3/DG neurons. We find that when animals discriminate recently seen novel images from similar (lure) images, behavior indicative of pattern separation, CA3/DG neurons respond to lure images more like novel than repeat images. Using a population of these neurons, we are able to classify novel, lure, and repeat images from each other using this pattern of firing rates. Notably, one subpopulation of these neurons is more responsible for distinguishing lures and repeats—the key discrimination indicative of pattern separation.

Mental Mechanisms

Mind-Society ◽  
2019 ◽  
pp. 22-47
Author(s):  
Paul Thagard
Keyword(s):  
Cognitive Appraisal ◽  
Mental Representations ◽  
Special Kind ◽  
Neural Mechanisms ◽  
Emotional Information ◽  
Sensory Inputs ◽  
The World ◽  
Sensory Motor ◽  
Human Thinking ◽  
High Level

Psychological explanations based on representations and procedures can be deepened by showing how they emerge from neural mechanisms. Neurons represent aspects of the world by collective patterns of firing. These patterns can be bound into more complicated patterns that can transcend the limitations of sensory inputs. Semantic pointers are a special kind of representation that operates by binding neural patterns encompassing sensory, motor, verbal, and emotional information. The semantic pointer theory applies not only to the ordinary operations of mental representations like concepts and rules but also to the most high-level kinds of human thinking, including language, creativity, and consciousness. Semantic pointers also encompass emotions, construed as bindings that combine cognitive appraisal with physiological perception.

scholarly journals Reading positional codes with fMRI: Problems and solutions

2016 ◽  
Author(s):  
Kristjan Kalm ◽  
Dennis Norris
Keyword(s):  
Memory Load ◽  
Large Body ◽  
Neural Mechanisms ◽  
Neural Representation ◽  
Sensory Adaptation ◽  
Neural Data ◽  
Problems And Solutions ◽  
Consistent Manner ◽  
Human Experiments ◽  
Human Neuroimaging

Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation, also change in a consistent manner as the sequence unfolds. In this paper we show that the problem of extracting neural data about the structure of a sequence is especially acute for fMRI, which is almost exclusively the modality used in human experiments. We show that such fMRI results must be treated with caution and in many cases the assumed neural representation might actually reflect unrelated processes.

Central Neural Mechanisms of Touch and Proprioception

1994 ◽  
Vol 72 (5) ◽  
pp. 542-545 ◽  
Author(s):  
John F. Kalaska
Keyword(s):  
Similar Case ◽  
Mechanical Stimulus ◽  
Muscle Contractions ◽  
Neural Mechanisms ◽  
Neural Representation ◽  
Perceptual Process ◽  
Active Muscle ◽  
Motivational State ◽  
Tactile Discrimination ◽  
Neuronal Mechanisms

The argument is made that somesthesia is not a strictly passive process, and its central neuronal mechanisms cannot be studied in all their complexity and subtlety by applying passive stimuli to uninterested or unconscious animals. The case is clear for kinesthesia. Peripheral proprioceptive signals are altered by active muscle contractions, and the central mechanisms of kinesthetic sensations should be studied during active movements. A similar case can be made for tactile discrimination. Ascending tactile afferents are subject to modulation during movement. Moreover, the generation of a central neural representation of the mechanical stimulus is only part of the tactile perceptual process. It is also influenced by the behavioral, attentive, and motivational state of the animal, whose effects can only be revealed in awake animals actively participating in discrimination tasks.Key words: tactile discrimination, proprioception, gating, attention, active touch.

scholarly journals Computational investigation of visually guided learning of spatially aligned auditory maps in the colliculus

2020 ◽  
Author(s):  
Timo Oess ◽  
Marc O. Ernst ◽  
Heiko Neumann
Keyword(s):  
Learning Algorithm ◽  
Neural Mechanisms ◽  
Visually Guided ◽  
Computational Investigation ◽  
Auditory Space ◽  
Sensory Inputs ◽  
Guided Learning ◽  
Spatial Registration ◽  
Eligibility Trace ◽  
Temporal And Spatial

The development of spatially registered auditory maps in the external nucleus of the inferior colliculus in young owls and their maintenance in adult animals is visually guided and evolves dynamically. To investigate the underlying neural mechanisms of this process, we developed a model of stabilized neoHebbian correlative learning which is augmented by an eligibility signal and a temporal trace of activations. This 3-component learning algorithm facilitates stable, yet flexible, formation of spatially registered auditory space maps composed of conductance-based topographically organized neu- ral units. Spatially aligned maps are learned for visual and auditory input stimuli that arrive in temporal and spatial registration. The reliability of visual sensory inputs can be used to regulate the learning rate in the form of an eligibility trace. We show that by shifting visual sensory inputs at the onset of learning the topography of auditory space maps is shifted accordingly. Simulation results explain why a shift of auditory maps in mature animals is possible only if corrections are induced in small steps. We conclude that learning spatially aligned auditory maps is flexibly controlled by reliable visual sensory neurons and can be formalized by a biological plausible unsupervised learning mechanism.

scholarly journals Speed invariance of tactile texture perception

2017 ◽  
Vol 118 (4) ◽  
pp. 2371-2377 ◽  
Author(s):  
Zoe M. Boundy-Singer ◽  
Hannes P. Saal ◽  
Sliman J. Bensmaia
Keyword(s):  
Activity Patterns ◽  
Strong Dependence ◽  
Scanning Speed ◽  
Nerve Fibers ◽  
Neural Mechanisms ◽  
Neural Representation ◽  
Perceptual Constancy ◽  
Texture Perception ◽  
Wide Range ◽  
Sense Of Touch

The nervous system achieves stable perceptual representations of objects despite large variations in the activity patterns of sensory receptors. Here, we explore perceptual constancy in the sense of touch. Specifically, we investigate the invariance of tactile texture perception across changes in scanning speed. Texture signals in the nerve have been shown to be highly dependent on speed: temporal spiking patterns in nerve fibers that encode fine textural features contract or dilate systematically with increases or decreases in scanning speed, respectively, resulting in concomitant changes in response rate. Nevertheless, texture perception has been shown, albeit with restricted stimulus sets and limited perceptual assays, to be independent of scanning speed. Indeed, previous studies investigated the effect of scanning speed on perceived roughness, only one aspect of texture, often with impoverished stimuli, namely gratings and embossed dot patterns. To fill this gap, we probe the perceptual constancy of a wide range of textures using two different paradigms: one that probes texture perception along well-established sensory dimensions independently and one that probes texture perception as a whole. We find that texture perception is highly stable across scanning speeds, irrespective of the texture or the perceptual assay. Any speed-related effects are dwarfed by differences in percepts evoked by different textures. This remarkable speed invariance of texture perception stands in stark contrast to the strong dependence of the texture responses of nerve fibers on scanning speed. Our results imply neural mechanisms that compensate for scanning speed to achieve stable representations of surface texture. NEW & NOTEWORTHY Our brain forms stable representations of objects regardless of viewpoint, a phenomenon known as invariance that has been described in several sensory modalities. Here, we explore invariance in the sense of touch and show that the tactile perception of texture does not depend on scanning speed. This perceptual constancy implies neural mechanisms that extract information about texture from the response of nerve fibers such that the resulting neural representation is stable across speeds.

Neurology Update: “Recent Developments in the Understanding of the Nervous System”

1980 ◽  
Vol 47 (2) ◽  
pp. 61-66
Author(s):  
M. Jean Gillespie
Keyword(s):  
Nervous System ◽  
Motor Response ◽  
Neural Mechanisms ◽  
Membrane Properties ◽  
Excitable Cells ◽  
Sensory Inputs ◽  
New Methods ◽  
Nucleus Plus ◽  
Recent Developments ◽  
The Central Nervous System

Neural Mechanisms of Sensori-Motor Integration New methods of investigation have enlarged understanding of the mechanisms underlying activity in the nervous system. Excitable cells transmit impulses by means of their special membrane properties and excitation is transmitted from cell to cell across specialized sites called synapses. In the nuclei of the central nervous system there are many small neurons that have no axon or only very short axons and dendrites. These are referred to as interneurons and the chemical transmitters they release may be excitatory or inhibitory to the cells with which they synapse. Cells with axons ending in a nucleus and cells with dendrites in the nucleus plus the interneurons which may intervene between the input of the message by an axon reaching the nucleus and its transmission onwards, form networks of cells that act as micro-circuits, affecting the nature of the neural signal. Control of transmission by these networks is the means by which sensory and motor impulses may be modified, enhanced, suppressed or facilitated. The integration of many sensory inputs, and the feedback during movement modulate and shape the motor response. An understanding of the mechanisms of inhibition and facilitation becomes increasingly important for therapists who use techniques based on “sensori-motor integration“.

scholarly journals How does the brain navigate knowledge of social relations? Testing for shared neural mechanisms for shifting attention in space and social knowledge

2020 ◽  
Author(s):  
Meng Du ◽  
Ruby Basyouni ◽  
Carolyn Parkinson
Keyword(s):  
Social Relations ◽  
Occipital Cortex ◽  
Neural Mechanisms ◽  
Social Knowledge ◽  
Response Patterns ◽  
Neural Basis ◽  
Abstract Knowledge ◽  
Attentional Shifts ◽  
Mental Operations ◽  
Shifting Attention

AbstractHow does the human brain support reasoning about social relations (e.g., social status, friendships)? Converging theories suggest that navigating knowledge of social relations may co-opt neural circuitry with evolutionarily older functions (e.g., shifting attention in space). Here, we analyzed multivoxel response patterns of fMRI data to examine the neural mechanisms for shifting attention in knowledge of a social hierarchy. The “directions” in which participants mentally navigated social knowledge were encoded in multivoxel patterns in superior parietal cortex, which also encoded directions of attentional shifts in space. Exploratory analyses implicated additional regions of posterior parietal and occipital cortex in encoding analogous mental operations in space and social knowledge. However, cross-domain analyses suggested that attentional shifts in space and social knowledge may be encoded in functionally independent response patterns. These results elucidate the neural basis for navigating abstract knowledge of social relations, and its connection to more basic mental operations.

scholarly journals Recurrent Antitopographic Inhibition Mediates Competitive Stimulus Selection in an Attention Network

2011 ◽  
Vol 105 (2) ◽  
pp. 793-805 ◽  
Author(s):  
Dihui Lai ◽  
Sebastian Brandt ◽  
Harald Luksch ◽  
Ralf Wessel
Keyword(s):  
Optic Tectum ◽  
Visual Pathway ◽  
Neural Mechanisms ◽  
Stimulus Selection ◽  
It Projects ◽  
Sensory Inputs ◽  
Surround Inhibition ◽  
Input Layer ◽  
Midbrain Structure ◽  
Constrained Model

Topographically organized neurons represent multiple stimuli within complex visual scenes and compete for subsequent processing in higher visual centers. The underlying neural mechanisms of this process have long been elusive. We investigate an experimentally constrained model of a midbrain structure: the optic tectum and the reciprocally connected nucleus isthmi. We show that a recurrent antitopographic inhibition mediates the competitive stimulus selection between distant sensory inputs in this visual pathway. This recurrent antitopographic inhibition is fundamentally different from surround inhibition in that it projects on all locations of its input layer, except to the locus from which it receives input. At a larger scale, the model shows how a focal top-down input from a forebrain region, the arcopallial gaze field, biases the competitive stimulus selection via the combined activation of a local excitation and the recurrent antitopographic inhibition. Our findings reveal circuit mechanisms of competitive stimulus selection and should motivate a search for anatomical implementations of these mechanisms in a range of vertebrate attentional systems.

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