Visual working memory and visual attention are intimately related, such that working memory encoding and maintenance reflects actively sustained attention to a limited number of visual objects and ...events important for ongoing cognition and action. Although attention is typically considered to operate over perceptual input, a recent taxonomy proposes to additionally consider how attention can be directed to internal perceptual representations in the absence of sensory input, as well as other internal memories, choices, and thoughts (Chun, Golomb, & Turk-Browne, 2011). Such internal attention enables prolonged binding of features into integrated objects, along with enhancement of relevant sensory mechanisms. These processes are all limited in capacity, although different types of working memory and attention, such as spatial vs. object processing, operate independently with separate capacity. Overall, the success of maintenance depends on the ability to inhibit both external (perceptual) and internal (cognitive) distraction. Working memory is the interface by which attentional mechanisms select and actively maintain relevant perceptual information from the external world as internal representations within the mind.
Reinforcements and punishments facilitate adaptive behavior in diverse domains ranging from perception to social interactions. A conventional approach to understanding the corresponding neural ...substrates focuses on the basal ganglia and its dopaminergic projections. Here, we show that reinforcement and punishment signals are surprisingly ubiquitous in the gray matter of nearly every subdivision of the human brain. Humans played either matching-pennies or rock-paper-scissors games against computerized opponents while being scanned using fMRI. Multivoxel pattern analysis was used to decode previous choices and their outcomes, and to predict upcoming choices. Whereas choices were decodable from a confined set of brain structures, their outcomes were decodable from nearly all cortical and subcortical structures. In addition, signals related to both reinforcements and punishments were recovered reliably in many areas and displayed patterns not consistent with salience-based explanations. Thus, reinforcement and punishment might play global modulatory roles in the entire brain.
► Reinforcement and punishment signals are broadly distributed in the entire brain ► Ubiquitous reward signals are revealed by multi-voxel pattern analysis on fMRI data ► Sensory and choice signals are more narrowly distributed in the brain ► Ubiquitous reinforcement signals cannot be explained by strategy or salience
Attention and memory are typically studied as separate topics, but they are highly intertwined. Here we discuss the relation between memory and two fundamental types of attention: perceptual and ...reflective. Memory is the persisting consequence of cognitive activities initiated by and/or focused on external information from the environment (perceptual attention) and initiated by and/or focused on internal mental representations (reflective attention). We consider three key questions for advancing a cognitive neuroscience of attention and memory: To what extent do perception and reflection share representational areas? To what extent are the control processes that select, maintain, and manipulate perceptual and reflective information subserved by common areas and networks? During perception and reflection, to what extent are common areas responsible for binding features together to create complex, episodic memories and for reviving them later? Considering similarities and differences in perceptual and reflective attention helps integrate a broad range of findings and raises important unresolved issues.
Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual ...variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
Neuroimaging is a fast-developing research area in which anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), ...diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale data sets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: (i) feature selection, (ii) feature summarization, (iii) model building, and (iv) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a considerable amount of the variance in these measures. It has been demonstrated that the CPM protocol performs as well as or better than many of the existing approaches in brain-behavior prediction. As CPM focuses on linear modeling and a purely data-driven approach, neuroscientists with limited or no experience in machine learning or optimization will find it easy to implement these protocols. Depending on the volume of data to be processed, the protocol can take 10-100 min for model building, 1-48 h for permutation testing, and 10-20 min for visualization of results.
Although attention plays a ubiquitous role in perception and cognition, researchers lack a simple way to measure a person's overall attentional abilities. Because behavioral measures are diverse and ...difficult to standardize, we pursued a neuromarker of an important aspect of attention, sustained attention, using functional magnetic resonance imaging. To this end, we identified functional brain networks whose strength during a sustained attention task predicted individual differences in performance. Models based on these networks generalized to previously unseen individuals, even predicting performance from resting-state connectivity alone. Furthermore, these same models predicted a clinical measure of attention--symptoms of attention deficit hyperactivity disorder--from resting-state connectivity in an independent sample of children and adolescents. These results demonstrate that whole-brain functional network strength provides a broadly applicable neuromarker of sustained attention.
Attention is a core property of all perceptual and cognitive operations. Given limited capacity to process competing options, attentional mechanisms select, modulate, and sustain focus on information ...most relevant for behavior. A significant problem, however, is that attention is so ubiquitous that it is unwieldy to study. We propose a taxonomy based on the types of information that attention operates over--the targets of attention. At the broadest level, the taxonomy distinguishes between external attention and internal attention. External attention refers to the selection and modulation of sensory information. External attention selects locations in space, points in time, or modality-specific input. Such perceptual attention can also select features defined across any of these dimensions, or object representations that integrate over space, time, and modality. Internal attention refers to the selection, modulation, and maintenance of internally generated information, such as task rules, responses, long-term memory, or working memory. Working memory, in particular, lies closest to the intersection between external and internal attention. The taxonomy provides an organizing framework that recasts classic debates, raises new issues, and frames understanding of neural mechanisms.
To explain how multiple visual objects are attended and perceived, we propose that our visual system first selects a fixed number of about four objects from a crowded scene based on their spatial ...information (object individuation) and then encode their details (object identification). We describe the involvement of the inferior intra-parietal sulcus (IPS) in object individuation and the superior IPS and higher visual areas in object identification. Our neural object-file theory synthesizes and extends existing ideas in visual cognition and is supported by behavioral and neuroimaging results. It provides a better understanding of the role of the different parietal areas in encoding visual objects and can explain various forms of capacity-limited processing in visual cognition such as working memory.
The attentional requirements of consciousness Cohen, Michael A; Cavanagh, Patrick; Chun, Marvin M ...
Trends in cognitive sciences,
08/2012, Letnik:
16, Številka:
8
Journal Article
Recenzirano
It has been widely claimed that attention and awareness are doubly dissociable and that there is no causal relation between them. In support of this view are numerous claims of attention without ...awareness, and awareness without attention. Although there is evidence that attention can operate on or be drawn to unconscious stimuli, various recent findings demonstrate that there is no empirical support for awareness without attention. To properly test for awareness without attention, we propose that a stimulus be studied using a battery of tests based on diverse, mainstream paradigms from the current attention literature. When this type of analysis is performed, the evidence is fully consistent with a model in which attention is necessary, but not sufficient, for awareness.
Constructing a rich and continuous visual experience requires computing specific details across views as well as integrating similarities across views. In this paper, we report functional magnetic ...resonance imaging (fMRI) evidence that these distinct computations may occur in two scene-sensitive regions in the brain, the parahippocampal place area (PPA) and retrosplenial cortex (RSC). Participants saw different snapshot views from panoramic scenes, which represented clearly different views, but appeared to come from the same scene. Using fMRI adaptation, we tested whether the PPA and RSC treated these panoramic views as the same or different. In the panoramic condition, three different views from a single panoramic scene were presented. We did not find any attenuation for panoramic repeats in the PPA, showing viewpoint-specificity. In contrast, RSC showed significant attenuation for the panoramic condition, showing viewpoint-integration. However, when the panoramic views were not presented in a continuous way, both the specificity in the PPA and the integration in RSC were lost. These results demonstrate that the PPA and RSC compute different properties of scenes: the PPA focuses on selective discrimination of different views while RSC focuses on the integration of scenes under the same visual context. These complementary functions of the PPA and RSC enable both specific and integrative representations of scenes across several viewpoints.
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