integration rules

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integration rules

Příspěvekod ATA » sob, 29. čer 2013, 00:18

A Normalization Model of Multisensory Integration
http://europepmc.org/articles/PMC310277 ... ZcAlqLcO.8

*“principle of inverse effectiveness”, which states that multisensory enhancement is large for weak multimodal stimuli and decreases with stimulus intensity

*For low stimulus intensities, the bimodal response (solid black) exceeds the sum of the unimodal responses (dashed black), indicating super-additivity (Fig. 2B). However, as stimulus intensity increases, the bimodal response becomes sub-additive, demonstrating inverse effectiveness.


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(Input1, ‘+’ symbol) is presented in the center of the RF, while the other input (Input2, ‘×’ symbol) is spatially offset from the RF center by different amounts (Fig. 3A). When both inputs are centered on the RF (Fig. 3B, left-most column), the combined response exceeds the unimodal responses for all stimulus intensities (as in Fig. 2B). As Input2 is offset from the RF center, the bimodal response decreases relative to that of the more effective Input1. Importantly, when the stimulus offset substantially exceeds one standard deviation of the Gaussian RF profile (two right-most columns of Fig. 3B), the combined response becomes suppressed below the unimodal response to Input1. Hence, the model neuron exhibits the spatial principle. The intuition for this result is simple: the less effective (i.e., offset) input contributes little to the underlying linear response of the neuron, but contributes strongly to the normalization signal because the normalization pool includes neurons with RFs that span a larger region of space. Note that the model neuron exhibits inverse effectiveness for all of these stimulus conditions (Fig. 3C), although super-additivity declines as the spatial offset increases.
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Re: integration rules

Příspěvekod ATA » sob, 29. čer 2013, 17:39

http://www.frontiersin.org/Neural_Circu ... 00022/full


Vyžší oblasti vizuálního kortexu lze snadněji modulovat pomocí vědomí (pozornosti)
Vizualizace věcí odpovídající pozdějším úrovním zpracování ve vizuálním kortexu muže mít větší učinek
Areas higher in the cortical hierarchy, such as middle superior temporal cortex (MST) or ventral intraparietal cortex (VIP), show more attentional modulation than lower areas, such as primary visual cortex (V1) or middle temporal cortex (MT; Figure 1). However, it has recently been suggested that top-down attentional modulation, however small, can already be observed in areas as synaptically close to the retina as the lateral geniculate nucleus (LGN;
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Učinek pozornosti na neurony v oblasti V2
When the two stimuli were presented simultaneously and attention was directed away from the stimuli, the recorded neuronal response magnitude was in-between the responses to either stimulus alone. However, when attention was directed toward one of the two simultaneously presented stimuli, the neuronal response closely resembled the response that was evoked by the attended stimulus in isolation (Figure 2)

Responses of one neuron in area V2 are plotted as a function of time (ms) after stimulus onset. The solid lines show the neuron’s response to either stimulus alone when attention is directed away (Att Away), with the black line representing the neuron’s response to the probe (horizontally oriented, non-preferred stimulus) and the green line representing the response to the reference (vertically oriented, preferred stimulus). When both stimuli are presented simultaneously (dotted lines), the neuron’s response magnitude is intermediate. Directing attention (indicated by the cone symbol) to the reference stimulus (Att Ref, in red) shifts the neuron’s response toward to reference-only response (green) compared to when attention is directed away (blue).

found that the rate increase due to attention would raise the signal-to-noise ratio (SNR) by 10%, while the attention-driven decrease in correlation increased the SNR by 39%.

research in the last decade has revealed that top-down attention is also highly correlated with an increased power of neuronal oscillations in the gamma frequency band
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This bottom-up activation (Stimulus Drive) is depicted along the two stimulus properties, with each pixel representing a single neuron and brightness representing the strength of activation. Paying attention to a certain spatial location (corresponding to the red circle in the left panel) creates an Attention Field that is selective for the RF center dimension, but not for the orientation preference dimension. Multiplying the Attention Field point-by-point with the Stimulus Drive yields an Excitatory Drive, which is then convolved with a Suppressive Field (a Gaussian representing the lateral inhibition) to produce the Suppressive Drive, or surround-inhibition. Finally, dividing the Excitatory Drive by the Suppressive Drive yields a normalized Population Response, with the attended stimulus having a larger output than the unattended stimulus. Figure adapted from Reynolds and Heeger (2009).

When the attention field is large compared to the stimulus size, the modulation is predominantly a contrast-gain enhancement. If, however, the attention field is small compared to the stimulus size, the effect seems to be predominantly response gain. These specific predictions have recently been confirmed with a paradigm that used the spatial certainty of visual stimuli to modulate the size of the attention field (Herrmann et al., 2010).

The concept of an attention field is reminiscent of previously proposed theoretical constructs like a saliency map (Itti and Koch, 2001) or a priority map (Bisley and Goldberg, 2010) and their neurophysiological representations in parietal and prefrontal cortex (Gottlieb et al., 1998; Bisley and Goldberg, 2010; Bisley, 2011). A saliency map represents the relative strength of bottom-up stimulus features that are used to guide attention (Koch and Ullman, 1985; Itti and Koch, 2001). A priority map, on the other hand, combines the bottom-up saliency map with top-down endogenous factors for the selection of objects for eye movements or attention (Serences and Yantis, 2006; Bisley and Goldberg, 2010). The abstract concept of an attention field in the normalization model can perhaps best be seen as the collection of these top-down influences in the priority map. As such it more or less constitutes a top-down counterpart to the bottom-up saliency map. Since their initial reception, the concepts of saliency and priority maps have become common practice in guided visual search models (Itti and Koch, 2001; Bisley and Goldberg, 2010; Bisley, 2011). Enhanced salience of certain objects prioritizes these objects in serial search tasks so that the object that is most likely to be the target will be attended first. In a similar way, an attention field can enhance the firing rate of neurons corresponding to certain object features (orientation) and cause an early bias in neuronal activation in favor of stimuli that correspond to the template represented in the attention field.

Strong correlations have been found between attention and enhanced gamma-band synchronization (Fell et al., 2003; Bichot et al., 2005; Womelsdorf and Fries, 2007). Gamma-band synchronizations are also known to be modulated by oscillations in other frequency ranges, such as the theta-cycle oscillations that are implicated in the shifting of attention (Fries, 2009), and delta-wave oscillations (Lakatos et al., 2008).

--
Consequently, the extent of an excitatory neuron’s depolarizing drive is converted into the moment of spiking relative to the phase of the cycle period. This means that as the excitatory drive of a neuron increases, so does its ability to overcome inhibition earlier in the cycle (Fries et al., 2007).

Moreover, the gamma cycle might provide a way in which pyramidal cells engage in winner-take-all processes (Olufsen et al., 2003; Börgers et al., 2005). Whenever a pyramidal cell fires, it activates local interneurons that send inhibitory signals back to the whole population of excitatory neurons. Because of this process, when the first few pyramidal cells have started firing action potentials, inhibition of all excitatory cells will start to increase. This makes it harder for pyramidal cells that have not yet fired to produce any spikes at all.

Consequently, the phase position of spikes relative to their cycle period is an important indication of the amount of information they carry. In fact, it has been shown that the first 1–5% of the spikes that encode a stimulus contain most information and that the other 95% provide relatively little additional information

In this framework, attention could then control the extent with which rate-codes are transformed into time codes. Since the gamma cycle can convert a neuron’s depolarizing drive into the moment of spiking relative to the phase of the cycle period, an increase of the amplitude of oscillations (as is observed during directed attention) could increase the extent to which rate-coded information is transformed to temporally coded information.

Another possible function of neural oscillations is formulated in the communication-through-coherence (CTC) hypothesis (Fries, 2005). This hypothesis states that neuronal communication between populations is only efficient if these populations are oscillating in synchrony and prevented if their oscillatory cycles are asynchronous. This hypothesis is based on two observations. First, as we have seen in the preceding paragraph neuronal populations have the intrinsic property to produce oscillatory activity (Kopell et al., 2000; Tiesinga et al., 2001). Second, as a neuronal population goes through an oscillatory cycle, its excitability changes drastically. While small excitatory inputs might be enough to activate a neuron when its corresponding interneurons are silent, the same neuron may require an extremely large amount of excitatory input when it is receiving large hyperpolarizing currents from the interneuron population. Accordingly, every oscillation period has a limited temporal window for effective communication that opens and closes with the phases of the oscillatory cycle. This means that only phase-locked neuronal populations are able to influence each other’s firing patterns effectively; a hypothesis that has been verified with neural network modeling (Kremkow et al., 2010).

Furthermore, the modulation strength of a TMS pulse has been shown to depend on the beta oscillation phase of the stimulated neural tissue, which suggests that beta band synchronization (and possibly also gamma-band synchronization) entails a rhythmic gain modulation of neuronal input (Van Elswijk et al., 2010). Such a process could very well be the underlying mechanism of winner-takes-all mechanisms that have recently been found in posterior

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This illustration shows three neuronal populations (red, green, and blue). There are two populations (red and green) that each connect to the third (blue), but only one (red) is synchronized to it via neuronal oscillations (middle right), while the other (green) is out-of-phase. Spikes from the synchronized population (red) arrive at their target population (blue) within the peak of excitability, while signals from the out-of-phase population (green) have no effect. Such phase-locking process could explain why higher cortical areas show larger attention effects. When two stimuli are simultaneously presented, the corresponding retinotopic regions in lower level visual cortex (e.g., V1) will overlap less than in higher level visual cortex (e.g., V4). Neurons in subsequent cortical areas that can in principle respond to either stimulus can only be phase-locked to input from one of the stimuli, leading to competitive interactions in the region of overla
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Re: integration rules

Příspěvekod ATA » ned, 30. čer 2013, 00:23

- přesnost
-- přesnost senzoru
-- šum
-- kumulace šumu
-- zvýšení šumu při relaxaci

- integrace signálů na zvýšení přesnosti odhadu

Humans integrate visual and haptic information in a statistically optimal fashion
http://www.cns.nyu.edu/~david/courses/p ... re2002.pdf
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On the other hand: Dummy hands and peripersonal space

Příspěvekod ATA » úte, 02. črc 2013, 02:08

On the other hand: Dummy hands and peripersonal space
http://www0.cs.ucl.ac.uk/research/vr/Pr ... w-2008.pdf

* aligned in an anatomically plausible position.
= pozice ruky(částí těla) musí byt anatomicky možná , pokud je jiná tak záleži na intenzite pri hodne velké intenzitě se muže dokoce vytvořit tělo kolem/z ruky , zaleži take na intenzitě ostaních vstupua vzájemé integraci.

* responses to visual and auditory stimuli only when they are presented near to the body,typically approaching or receding from the relevant body part
=vizualizovat u ruky ne někde predsebou v prostoru nebo pokud už je to v prostoru tak vždy kombinaci ruka+obejekt blizko sebe idelane primo interakci

* integrace v RF neuronu (možna by řešilo otazku vzdálenosti)
=každej neuron ma oblast ketrou spracova integruje jen data z oblasti

* crossmodal congruency effect (CCE) stronger in peripersonal space
= efekt vizualizace bude větší poblíž ruky

*fMRI showed significantly stronger activation to a visual stimulus when it was approaching the subject’s hand, as compared to a similar stimulus moving far from their hands
= to co se približuje je hrozba/msíme reagova to ce približuje ma vetši efekt než to co se vzdaluje

? prumerují se signály pouze v pripadě že vysledek je presnější ?

*RHI F drift 15–30%
*RHI 4-6,11s

*the occurrence of the RHI is limited by the distance between the dummy hand and the subject’s real hand
Lloyd found a significant decrease in illusion strength (compared to the minimal separation) for separations greater than 27.5cm.

exponential decay of illusion strength with distance

when the dummy hand is placed outside the initial(i.e.,un-shifted)peri-hand space, the visual stimulus near the dummy hand is not represented by peri-hand multisensory mechanisms, and therefore no referred
tactile sensation to the dummy hand can be elicited
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http://www.sciencedirect.com/science/ar ... 2606002119
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Re: integration rules

Příspěvekod ATA » úte, 02. črc 2013, 03:49

Spatial limits on the nonvisual self-touch illusion and the visual rubber hand illusion: Subjective experience of the illusion and proprioceptive drift
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Re: integration rules

Příspěvekod ATA » úte, 02. črc 2013, 04:10

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Fig. 3. Mean (circles) and standard deviation (error bars) of the perceived size of the thumb (filled circles) and index finger (open circles) during control, after full anaesthesia of the thumb induced by local anaesthestic injection into the digital nerves of the thumb, after innocuous stimulation of the intact thumb, and after painful cooling of the thumb. Asterisk denotes significantly different to control.

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Re: integration rules

Příspěvekod ATA » úte, 02. črc 2013, 05:36

Multisensory brain mechanisms of bodily self-consciousness
http://infoscience.epfl.ch/record/18012 ... e_2012.pdf
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Re: integration rules

Příspěvekod ATA » úte, 02. črc 2013, 23:37

Hands only illusion: multisensory integration elicits sense of ownership for body parts but not for non-corporeal objects
http://www.pc.rhul.ac.uk/sites/lab/wp-c ... R-2010.pdf
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Re: integration rules

Příspěvekod ATA » čtv, 04. črc 2013, 01:05

peripersonal space
can be divided into two parts: a near sector, constituted of the space immediately surrounding body (about 5 cm), where visuotactile integration is strongest; and a far sector (at approximately 35 cm from the body), where visuotactile interactions are weaker.
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Re: integration rules

Příspěvekod ATA » stř, 16. bře 2016, 18:54

Help! I'm a multidimensional being trapped in a linear time-space continuum!

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Re: integration rules

Příspěvekod ATA » stř, 16. bře 2016, 21:10

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