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59
The Normalization Model of Attention
- NEURON REVIEW
, 2009
"... Attention has been found to have a wide variety of effects on the responses of neurons in visual cortex. We describe a model of attention that exhibits each of these different forms of attentional modulation, depending on the stimulus conditions and the spread (or selectivity) of the attention field ..."
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Cited by 110 (5 self)
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Attention has been found to have a wide variety of effects on the responses of neurons in visual cortex. We describe a model of attention that exhibits each of these different forms of attentional modulation, depending on the stimulus conditions and the spread (or selectivity) of the attention field in the model. The model helps reconcile proposals that have been taken to represent alternative theories of attention. We argue that the variety and complexity of the results reported in the literature emerge from the variety of empirical protocols that were used, such that the results observed in any one experiment depended on the stimulus conditions and the subject’s attentional strategy, a notion that we define precisely in terms of the attention field in the model, but that has not typically been completely under experimental control.
Attention, short-term memory, and action selection: A unifying theory
, 2005
"... Cognitive behaviour requires complex context-dependent processing of information that emerges from the links between attentional perceptual processes, working memory and reward-based evaluation of the performed actions. We describe a computational neuroscience theoretical framework which shows how a ..."
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Cited by 58 (13 self)
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Cognitive behaviour requires complex context-dependent processing of information that emerges from the links between attentional perceptual processes, working memory and reward-based evaluation of the performed actions. We describe a computational neuroscience theoretical framework which shows how an attentional state held in a short term memory in the prefrontal cortex can by top-down processing influence ventral and dorsal stream cortical areas using biased competition to account for many aspects of visual attention. We also show how within the prefrontal cortex an attentional bias can influence the mapping of sensory inputs to motor outputs, and thus play an important role in decision making. We also show how the absence of expected rewards can switch an attentional bias signal, and thus rapidly and flexibly alter cognitive performance. This theoretical framework incorporates spiking and synaptic dynamics which enable single neuron responses, fMRI activations, psychophysical results, the effects of pharmacological agents, and the effects of damage to parts of the system to be explicitly simulated and predicted. This computational neuroscience framework provides an approach for integrating different levels of investigation of brain function, and for understanding the relations between them. The models also directly address how bottom-up and top-down processes interact in visual cognition,
Selective attention to affective value alters how the brain processes olfactory stimuli
- J. Cogn
, 2008
"... & How does selective attention to affect influence sensory processing? In a functional magnetic resonance imaging investigation, when subjects were instructed to remember and rate the pleasantness of a jasmin odor, activations were greater in the medial orbitofrontal and pregenual cingulate cort ..."
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Cited by 34 (14 self)
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& How does selective attention to affect influence sensory processing? In a functional magnetic resonance imaging investigation, when subjects were instructed to remember and rate the pleasantness of a jasmin odor, activations were greater in the medial orbitofrontal and pregenual cingulate cortex than when subjects were instructed to remember and rate the intensity of the odor. When the subjects were instructed to remember and rate the intensity, activations were greater in the inferior frontal gyrus. These top–down effects occurred not only during odor delivery but started in a preparation period after the instruction before odor delivery, and continued after termination of the odor in a short-term memory period. Thus, depending on the context in which odors are presented and whether affect is relevant, the brain prepares itself, responds to, and remembers an odor differently. These findings show that when attention is paid to affective value, the brain systems engaged to prepare for, represent, and remember a sensory stimulus are different from those engaged when attention is directed to the physical properties of a stimulus such as its intensity. This differential biasing of brain regions engaged in processing a sensory stimulus depending on whether the cognitive demand is for affect-related versus more sensory-related processing may be an important aspect of cognition and attention. This has many implications for understanding the effects not only of olfactory but also of other sensory stimuli. &
Decision-making and Weber’s Law: a neurophysiological model
- European Journal of Neuroscience
, 2006
"... We describe an integrate-and-fire attractor model of the decision-related activity of ventral premotor cortex (VPC) neurons during a vibrotactile frequency comparison task [Romo et al. (2004) Neuron, 41, 165–173]. Populations of neurons for each decision in a biased competition attractor network rec ..."
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Cited by 28 (9 self)
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We describe an integrate-and-fire attractor model of the decision-related activity of ventral premotor cortex (VPC) neurons during a vibrotactile frequency comparison task [Romo et al. (2004) Neuron, 41, 165–173]. Populations of neurons for each decision in a biased competition attractor network receive a bias input that depends on the firing rates of VPC neurons that code for the two vibrotactile frequencies. The firing rate of the neurons in whichever attractor wins, reflects the sign of the difference in the frequencies (Df) being compared but not the absolute frequencies. However, the transition from the initial spontaneous firing state to one of the two possible attractor states depends probabilistically on the difference of the vibrotactile frequencies scaled by the base frequency. This is due to finite size noise effects related to the spiking activity in the network, and the divisive feedback inhibition implemented through inhibitory interneurons. Thus the neurophysiological basis for a psychophysical effect, Weber’s Law, can be related to statistical fluctuations and divisive inhibition in an attractor decision-making network.
Invariant visual object recognition: A model, with lighting invariance
- Journal of Physiology - Paris
, 2006
"... How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. T ..."
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Cited by 21 (6 self)
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How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate topdown feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.
Weber’s law in decision making: integrating behavioral data in humans with a neurophysiological model,
- The Journal of Neuroscience : The Official Journal of the Society for Neuroscience
, 2007
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Invariant global motion recognition in the dorsal visual system: a unifying theory
- Neural Computation
, 2006
"... The motion of an object (such as a wheel rotating) is seen as con-sistent independently of its position and size on the retina. Neu-rons in higher cortical visual areas respond to these global motion stimuli invariantly, but neurons in early cortical areas with small receptive fields cannot represen ..."
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Cited by 13 (3 self)
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The motion of an object (such as a wheel rotating) is seen as con-sistent independently of its position and size on the retina. Neu-rons in higher cortical visual areas respond to these global motion stimuli invariantly, but neurons in early cortical areas with small receptive fields cannot represent this motion, not only because of the aperture problem, but also because they do not have invariant representations. In a unifying hypothesis with the design of the ventral cortical visual system, we propose that the dorsal visual sys-tem uses a hierarchical feedforward network architecture (V1, V2, MT, MSTd, parietal cortex) with training of the connections with a short term memory trace associative synaptic modification rule to capture what is invariant at each stage. Simulations show that the proposal is computationally feasible, in that invariant representa-tions of the motion flow fields produced by objects self-organize in the later layers of the architecture. The model produces invariant representations of the motion flow fields produced by global in-plane motion of an object, in-plane rotational motion, looming vs reced-ing of the object, and object-based rotation about a principal axis. Thus the dorsal and ventral visual systems may share some similar computational principles.
Activity Recognition by Integrating the Physics of Motion with a Neuromorphic Model of Perception ∗
"... In this paper, we propose a computational framework for integrating the physics of motion with the neurobiological basis of perception in order to model and recognize human actions and object activities. The essence, or gist, of an action is intrinsically related to the motion of the scene’s objects ..."
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Cited by 9 (6 self)
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In this paper, we propose a computational framework for integrating the physics of motion with the neurobiological basis of perception in order to model and recognize human actions and object activities. The essence, or gist, of an action is intrinsically related to the motion of the scene’s objects. We define the Hamiltonian Energy Signature (HES) and derive the S-Metric to yield a global representation of the motion of the scene’s objects in order to capture the gist of the activity. The HES is a scalar time-series that represents the motion of an object over the course of an activity and the S-Metric is a distance metric which characterizes the global motion of the object, or the entire scene, with a single, scalar value. The neurobiological aspect of activity recognition is handled by casting our analysis within a framework inspired by Neuromorphic Computing (NMC), in which we integrate a Motion Energy model with a Form/Shape model. We employ different Form/Shape representations depending on the video resolution but use our HES and S-Metric for the Motion Energy approach in either case. As the core of our Integration mechanism, we utilize variants of the latest neurobiological models of feature integration and biased competition, which we implement within a Multiple Hypothesis Testing (MHT) framework. Experimental validation of the theory is provided on standard datasets capturing a variety of problem settings: single agent actions (KTH), multi-agent actions, and aerial sequences (VIVID). 1.
