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.

scholarly journals Distinct neural mechanisms construct classical versus extraclassical inhibitory surrounds in an inhibitory nucleus in the midbrain attention network

2020 ◽  
Author(s):  
Hannah M. Schryver ◽  
Jing Xuan Lim ◽  
Shreesh P. Mysore
Keyword(s):  
Spatial Attention ◽  
Optic Tectum ◽  
Receptive Fields ◽  
Neural Mechanisms ◽  
Competitive Interactions ◽  
Inhibitory Neurons ◽  
Stimulus Selection ◽  
Critical Importance ◽  
Attention Network ◽  
Fundamental Units

ABSTRACTInhibitory neurons in the midbrain spatial attention network, called isthmi pars magnocellularis (Imc), control stimulus selection by the sensorimotor and attentional hub, the optic tectum (OT). Here, we investigate in the barn owl how classical as well as extraclassical (global) inhibitory surrounds of Imc receptive fields (RFs), fundamental units of Imc computational function, are constructed. We find that focal, reversible blockade of GABAergic input onto Imc neurons disconnects their extraclassical inhibitory surrounds, but, surprisingly, leaves intact their classical surrounds. Subsequently, with paired recordings and iontophoresis, first at spatially aligned site-pairs in Imc and OT, and then, at mutually distant site-pairs within Imc, we demonstrate that classical inhibitory surrounds of Imc RFs are inherited from OT, but their extraclassical inhibitory surrounds are constructed within Imc. These results reveal key design principles of the midbrain spatial attention circuit, and attest to the critical importance of competitive interactions within Imc for its operation.

A Model of the Neural Mechanisms Underlying Multisensory Integration in the Superior Colliculus

Perception ◽  
10.1068/p5842 ◽  
2007 ◽  
Vol 36 (10) ◽  
pp. 1431-1443 ◽  
Author(s):  
Benjamin A Rowland ◽  
Terrence R Stanford ◽  
Barry E Stein
Keyword(s):  
Superior Colliculus ◽  
Computational Model ◽  
Multisensory Integration ◽  
Neural Mechanisms ◽  
Specific Component ◽  
Algebraic Form ◽  
Sensory Inputs ◽  
Midbrain Structure ◽  
Cat Superior Colliculus

Much of the information about multisensory integration is derived from studies of the cat superior colliculus (SC), a midbrain structure involved in orientation behaviors. This integration is apparent in the enhanced responses of SC neurons to cross-modal stimuli, responses that exceed those to any of the modality-specific component stimuli. The simplest model of multisensory integration is one in which the SC neuron simply sums its various sensory inputs. However, a number of empirical findings reveal the inadequacy of such a model; for example, the finding that deactivation of cortico-collicular inputs eliminates the enhanced response to a cross-modal stimulus without eliminating responses to the modality-specific component stimuli. These and other empirical findings inform a computational model that accounts for all of the most fundamental aspects of SC multisensory integration. The model is presented in two forms: an algebraic form that conveys the essential insights, and a compartmental form that represents the neuronal computations in a more biologically realistic way.

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.

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 Cortical networks for face perception in two-month-old infants

2014 ◽  
Vol 281 (1793) ◽  
pp. 20141468 ◽  
Author(s):  
Tamami Nakano ◽  
Kazuko Nakatani
Keyword(s):  
Face Processing ◽  
Behavioural Change ◽  
Visual Pathway ◽  
Recovery Phase ◽  
Neural Mechanisms ◽  
Human Face ◽  
Functional Development ◽  
Functional Pathways ◽  
Preference Behaviour ◽  
Functional Deterioration

Newborns have an innate system for preferentially looking at an upright human face. This face preference behaviour disappears at approximately one month of age and reappears a few months later. However, the neural mechanisms underlying this U-shaped behavioural change remain unclear. Here, we isolate the functional development of the cortical visual pathway for face processing using S-cone-isolating stimulation, which blinds the subcortical visual pathway. Using luminance stimuli, which are conveyed by both the subcortical and cortical visual pathways, the preference for upright faces was not observed in two-month-old infants, but it was observed in four- and six-month-old infants, confirming the recovery phase of the U-shaped development. By contrast, using S-cone stimuli, two-month-old infants already showed a preference for upright faces, as did four- and six-month-old infants, demonstrating that the cortical visual pathway for face processing is already functioning at the bottom of the U-shape at two months of age. The present results suggest that the transient functional deterioration stems from a conflict between the subcortical and cortical functional pathways, and that the recovery thereafter involves establishing a level of coordination between the two pathways.

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.

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