Top-Down Attention and the Brain

2020 ◽  
pp. 212-213
Keyword(s):  
Top Down ◽  
2001 ◽  
Vol 39 (2-3) ◽  
pp. 137-150 ◽  
Author(s):  
S Karakaş ◽  
C Başar-Eroğlu ◽  
Ç Özesmi ◽  
H Kafadar ◽  
Ö.Ü Erzengin
Keyword(s):  
Top Down ◽  

2012 ◽  
Vol 24 (10) ◽  
pp. 2043-2056 ◽  
Author(s):  
Ayano Matsushima ◽  
Masaki Tanaka

Resistance to distraction is a key component of executive functions and is strongly linked to the prefrontal cortex. Recent evidence suggests that neural mechanisms exist for selective suppression of task-irrelevant information. However, neuronal signals related to selective suppression have not yet been identified, whereas nonselective surround suppression, which results from attentional enhancement for relevant stimuli, has been well documented. This study examined single neuron activities in the lateral PFC when monkeys covertly tracked one of randomly moving objects. Although many neurons responded to the target, we also found a group of neurons that exhibited a selective response to the distractor that was visually identical to the target. Because most neurons were insensitive to an additional distractor that explicitly differed in color from the target, the brain seemed to monitor the distractor only when necessary to maintain internal object segregation. Our results suggest that the lateral PFC might provide at least two top–down signals during covert object tracking: one for enhancement of visual processing for the target and the other for selective suppression of visual processing for the distractor. These signals might work together to discriminate objects, thereby regulating both the sensitivity and specificity of target choice during covert object tracking.


2006 ◽  
Vol 12 (2) ◽  
pp. 261-271 ◽  
Author(s):  
DONALD T. STUSS

The frontal lobes (FL), are they a general adaptive global capacity processor, or a series of fractionated processes? Our lesion studies focusing on attention have demonstrated impairments in distinct processes due to pathology in different frontal regions, implying fractionation of the “supervisory system.” However, when task demands are manipulated, it becomes evident that the frontal lobes are not just a series of independent processes. Increased complexity of task demands elicits greater involvement of frontal regions along a fixed network related to a general activation process. For some task demands, one or more anatomically distinct frontal processes may be recruited. In other conditions, there is a bottom-up nonfrontal/frontal network, with impairment noted maximally for the lesser task demands in the nonfrontal automatic processing regions, and then as task demands change, increased involvement of different frontal (more “strategic”) regions, until it appears all frontal regions are involved. With other measures, the network is top-down, with impairment in the measure first noted in the frontal region and then, with changing task demands, involving a posterior region. Adaptability is not just a property of FL, it is the fluid recruitment of different processes anywhere in the brain as required by the current task. (JINS, 2006,12, 261–271.)


2020 ◽  
Vol 30 (10) ◽  
pp. 5431-5448
Author(s):  
Yanfang Zuo ◽  
Yanwang Huang ◽  
Dingcheng Wu ◽  
Qingxiu Wang ◽  
Zuoren Wang

Abstract How does the brain selectively process signals from stimuli of different modalities? Coherent oscillations may function in coordinating communication between neuronal populations simultaneously involved in such cognitive behavior. Beta power (12–30 Hz) is implicated in top-down cognitive processes. Here we test the hypothesis that the brain increases encoding and behavioral influence of a target modality by shifting the relationship of neuronal spike phases relative to beta oscillations between primary sensory cortices and higher cortices. We simultaneously recorded neuronal spike and local field potentials in the posterior parietal cortex (PPC) and the primary auditory cortex (A1) when male rats made choices to either auditory or visual stimuli. Neuronal spikes exhibited modality-related phase locking to beta oscillations during stimulus sampling, and the phase shift between neuronal subpopulations demonstrated faster top-down signaling from PPC to A1 neurons when animals attended to auditory rather than visual stimuli. Importantly, complementary to spike timing, spike phase predicted rats’ attended-to target in single trials, which was related to the animals’ performance. Our findings support a candidate mechanism that cortices encode targets from different modalities by shifting neuronal spike phase. This work may extend our understanding of the importance of spike phase as a coding and readout mechanism.


2015 ◽  
Vol 7 (12) ◽  
pp. 1487-1517 ◽  
Author(s):  
G. Pezzulo ◽  
M. Levin

How do regenerating bodies know when to stop remodeling? Bioelectric signaling networks guide pattern formation and may implement a somatic memory system. Deep parallels may exist between information processing in the brain and morphogenetic control mechanisms.


Author(s):  
Martin V. Butz ◽  
Esther F. Kutter

While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key to understand how information integration must work computationally – at least in approximation – also in the brain. Bayesian networks in the form of graphical models allow the modularization of information and the factorization of interactions, which can strongly improve the efficiency of generative models. The resulting generative models essentially produce state estimations in the form of probability densities, which are very well-suited to integrate multiple sources of information, including top-down and bottom-up ones. A hierarchical neural visual processing architecture illustrates this point even further. Finally, some well-known visual illusions are shown and the perceptions are explained by means of generative, information integrating, perceptual processes, which in all cases combine top-down prior knowledge and expectations about objects and environments with the available, bottom-up visual information.


2019 ◽  
Vol 1124 ◽  
pp. 165-172
Author(s):  
Daniela Delfino ◽  
Diana Valeria Rossetti ◽  
Claudia Martelli ◽  
Ilaria Inserra ◽  
Federica Vincenzoni ◽  
...  

2013 ◽  
Vol 09 (02) ◽  
pp. 1350010 ◽  
Author(s):  
MATTEO CACCIOLA ◽  
GIANLUIGI OCCHIUTO ◽  
FRANCESCO CARLO MORABITO

Many computer vision problems consist of making a suitable content description of images usually aiming to extract the relevant information content. In case of images representing paintings or artworks, the information extracted is rather subject-dependent, thus escaping any universal quantification. However, we proposed a measure of complexity of such kinds of oeuvres which is related to brain processing. The artistic complexity measures the brain inability to categorize complex nonsense forms represented in modern art, in a dynamic process of acquisition that most involves top-down mechanisms. Here, we compare the quantitative results of our analysis on a wide set of paintings of various artists to the cues extracted from a standard bottom-up approach based on visual saliency concept. In every painting inspection, the brain searches for more informative areas at different scales, then connecting them in an attempt to capture the full impact of information content. Artistic complexity is able to quantify information which might have been individually lost in the fruition of a human observer thus identifying the artistic hand. Visual saliency highlights the most salient areas of the paintings standing out from their neighbours and grabbing our attention. Nevertheless, we will show that a comparison on the ways the two algorithms act, may manifest some interesting links, finally indicating an interplay between bottom-up and top-down modalities.


2016 ◽  
Vol 116 (6) ◽  
pp. 2497-2512 ◽  
Author(s):  
Anne Kösem ◽  
Anahita Basirat ◽  
Leila Azizi ◽  
Virginie van Wassenhove

During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept.


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