Tuned Normalization Explains the Size of Attention Modulations

Ni, Amy M.; Ray, Supratim; Maunsell, John H. R.

doi:10.1016/j.neuron.2012.01.006

Cited by 103 publications

(177 citation statements)

References 63 publications

(110 reference statements)

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“…22,23]. Here, each neuron is normalized not only by its suppressive surround, but also by its own net-excitatory input.…”

Section: Resultsmentioning

confidence: 99%

“…Such a mechanism was previously shown to be a vital component in a model capturing the response properties of direction-selective neurons in extrastriate cortex [22]. The tuned normalization in another recent report [23] is also conceptually similar: here, the authors showed that MT neuronal responses to a pair of stimuli within the receptive field (one moving in the preferred direction and the other in the anti-preferred direction) were well explained by direction-tuned divisive normalization. The majority of neurons in their data showed a greater normalizing influence of the preferred stimulus.…”

Section: Discussionmentioning

confidence: 99%

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An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

2016

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Paying attention to a sensory feature improves its perception and impairs that of others. Recent work has shown that a Normalization Model of Attention (NMoA) can account for a wide range of physiological findings and the influence of different attentional manipulations on visual performance. A key prediction of the NMoA is that attention to a visual feature like an orientation or a motion direction will increase the response of neurons preferring the attended feature (response gain) rather than increase the sensory input strength of the attended stimulus (input gain). This effect of feature-based attention on neuronal responses should translate to similar patterns of improvement in behavioral performance, with psychometric functions showing response gain rather than input gain when attention is directed to the task-relevant feature. In contrast, we report here that when human subjects are cued to attend to one of two motion directions in a transparent motion display, attentional effects manifest as a combination of input and response gain. Further, the impact on input gain is greater when attention is directed towards a narrow range of motion directions than when it is directed towards a broad range. These results are captured by an extended NMoA, which either includes a stimulus-independent attentional contribution to normalization or utilizes direction-tuned normalization. The proposed extensions are consistent with the feature-similarity gain model of attention and the attentional modulation in extrastriate area MT, where neuronal responses are enhanced and suppressed by attention to preferred and non-preferred motion directions respectively.

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“…22,23]. Here, each neuron is normalized not only by its suppressive surround, but also by its own net-excitatory input.…”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

2016

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“…Such studies have investigated “sensory” conditions, i.e., when none of the stimuli were behaviorally relevant (Snowden et al, 1991; Recanzone et al, 1997; Britten and Heuer, 1999; Treue et al, 2000; Majaj et al, 2007), as well as “attentional” conditions, i.e., task designs where one of the stimuli were behaviorally relevant (Seidemann and Newsome, 1999; Treue and Trujillo, 1999; Patzwahl and Treue, 2009; Niebergall et al, 2011a,b; Ni et al, 2012). All of these studies implicitly or explicitly assume that neurons always respond to multiple stimuli in their receptive field with a single response state that represents an integration (averaging with or without scaling or gain control) of the individual stimulus responses.…”

Section: Discussionmentioning

confidence: 99%

Neurons in Primate Visual Cortex Alternate between Responses to Multiple Stimuli in Their Receptive Field

Kozyrev

Kyllingsbæk

et al. 2016

Front. Comput. Neurosci.

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A fundamental question concerning representation of the visual world in our brain is how a cortical cell responds when presented with more than a single stimulus. We find supportive evidence that most cells presented with a pair of stimuli respond predominantly to one stimulus at a time, rather than a weighted average response. Traditionally, the firing rate is assumed to be a weighted average of the firing rates to the individual stimuli (response-averaging model) (Bundesen et al., 2005). Here, we also evaluate a probability-mixing model (Bundesen et al., 2005), where neurons temporally multiplex the responses to the individual stimuli. This provides a mechanism by which the representational identity of multiple stimuli in complex visual scenes can be maintained despite the large receptive fields in higher extrastriate visual cortex in primates. We compare the two models through analysis of data from single cells in the middle temporal visual area (MT) of rhesus monkeys when presented with two separate stimuli inside their receptive field with attention directed to one of the two stimuli or outside the receptive field. The spike trains were modeled by stochastic point processes, including memory effects of past spikes and attentional effects, and statistical model selection between the two models was performed by information theoretic measures as well as the predictive accuracy of the models. As an auxiliary measure, we also tested for uni- or multimodality in interspike interval distributions, and performed a correlation analysis of simultaneously recorded pairs of neurons, to evaluate population behavior.

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“…For example, normalization is a computational process that explains the well-known observation that presenting two stimuli in a sensory cortical neuron’s response field results in neuronal activity that is approximately the average of the responses of the neuron to the presentation of each stimulus alone, rather than the sum. Normalization provides a description of how neurons integrate their multiple sources of excitatory and inhibitory inputs and is a key computation thought to underlie attention (Boynton 2009, Carandini & Heeger 2012, Lee & Maunsell 2009, Maunsell 2015, Ni et al 2012, Reynolds & Heeger 2009). In vivo, collicular neurons show properties of normalization similar to those seen in the visual cortex.…”

Section: Microcircuits Of the Superior Colliculusmentioning

confidence: 99%

Circuits for Action and Cognition: A View from the Superior Colliculus

Basso¹,

May

2017

Annu. Rev. Vis. Sci.

305

245

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The superior colliculus is one of the most well-studied structures in the brain, and with each new report, its proposed role in behavior seems to increase in complexity. Forty years of evidence show that the colliculus is critical for reorienting an organism toward objects of interest. In monkeys, this involves saccadic eye movements. Recent work in the monkey colliculus and in the homologous optic tectum of the bird extends our understanding of the role of the colliculus in higher mental functions, such as attention and decision making. In this review, we highlight some of these recent results, as well as those capitalizing on circuit-based methodologies using transgenic mice models, to understand the contribution of the colliculus to attention and decision making. The wealth of information we have about the colliculus, together with new tools, provides a unique opportunity to obtain a detailed accounting of the neurons, circuits, and computations that underlie complex behavior.

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Tuned Normalization Explains the Size of Attention Modulations

Cited by 103 publications

References 63 publications

An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

Neurons in Primate Visual Cortex Alternate between Responses to Multiple Stimuli in Their Receptive Field

Circuits for Action and Cognition: A View from the Superior Colliculus

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