This type of attention involves being able to be suddenly drawn to a specific visual, auditory, or tactile stimuli such as a loud noise or a flash of light. It is a way of responding rapidly to external stimuli, which can be particularly important in situations where something in the environment requires immediate attention and quick action. Limited attention, or divided attention, is a form of attention that also involves multitasking.
In this case, however, attention is divided between multiple tasks. Rather than shifting focus, people attend to these stimuli at the same time and may respond simultaneously to multiple demands. The illusion that attention is limitless has led many people to practice multitasking.
Research published in has pointed out how multitasking seldom works well because our attention is, in reality, limited. For the most part, our ability to focus our attention on one thing while blocking out competing distractors seems automatic. Yet the ability of people to selectively focus their attention on a specific subject while dismissing others is very complex.
But even people without attention problems can benefit from using strategies designed to improve attention and focus. Some things you can try include:. New ways of improving attention may also be on the horizon.
This may be helpful for treating attentional problems that are the result of some conditions. Achieving a greater understanding of this process holds promise for better treatments for those coping with this condition down the line. Ever wonder what your personality type means? Sign up to find out more in our Healthy Mind newsletter. Classics in the History of Psychology. The Principles of Psychology, William James Sustained attention across the life span in a sample of 10, Dissociating ability and strategy.
Psychol Sci. Sleep and attention in Alzheimer's Disease. Yale J Biol Med. Stevens C, Bavelier D. The role of selective attention on academic foundations: A cognitive neuroscience perspective.
Dev Cogn Neurosci. While a small neural network is the most prominent approach, over the years there have been many different ideas to compute that score. The last one worth mentioning can be found in Graves A. Ways to compute attention. The approach that stood the test of time, however, is the last one proposed by Bahdanau et al. And obviously, we can extend that to use more layers. This effectively means that attention is now a set of trainable weights that can be tuned using our standard backpropagation algorithm.
The decoder decides parts of the source sentence to pay attention to. By letting the decoder have an attention mechanism, we relieve the encoder from the burden of having to encode all information in the source sentence into a fixed-length vector. With this new approach, the information can be spread throughout the sequence of annotations, which can be selectively retrieved by the decoder accordingly.
We sacrificed computational complexity. Until now we assumed that attention is computed over the entire input sequence global attention. Despite its simplicity, it can be computationally expensive and sometimes unnecessary. As a result, there are papers that suggest local attention as a solution. Evidently, this can sometimes be better for very long sequences. Local attention can also be merely seen as hard attention since we need to take a hard decision first, to exclude some input units.
The colors in the attention indicate that these weights are constantly changing while in convolution and fully connected layers they are slowly changing by gradient descent. We can also define the attention of the same sequence, called self-attention.
Personally, I like to think of self-attention as a graph. Actually, it can be regarded as a k-vertex connected undirected weighted graph. Undirected indicates that the matrix is symmetric. The self-attention can be computed in any mentioned trainable way. The end goal is to create a meaningful representation of the sequence before transforming to another. Admittedly, attention has a lot of reasons to be effective apart from tackling the bottleneck problem. First, it usually eliminates the vanishing gradient problem , as they provide direct connections between the encoder states and the decoder.
Conceptually, they act similarly as skip connections in convolutional neural networks. By inspecting the distribution of attention weights, we can gain insights into the behavior of the model, as well as to understand its limitations. Think, for example, the English-to-French heatmap we showed before. I had an aha moment when I saw the swap of words in translation.
While transformers are definitely used for machine translation, they are often considered as general-purpose NLP models that are also effective on tasks like text generation, chatbots, text classification, etc.
But we can also go beyond NLP. We briefly saw attention being used in image classification models, where we look at different parts of an image to solve a specific task. In fact, visual attention models recently outperformed the state of the art Imagenet model [3]. We also have seen examples in healthcare , recommender systems, and even on graph neural networks. To summarize everything said so far in a nutshell, I would say: Attention is much more than transformers and transformers are more than NLP approaches.
For a more holistic approach on NLP approaches with attention models we recommend the Coursera course. So if you aim to understand transformers, now you are ready to go! Sustained Attention : The ability to attend to a stimulus or activity over a long period of time.
Selective Attention : The ability to attend to a specific stimulus or activity in the presence of other distracting stimuli. Alternating Attention : The ability to change focus attention between two or more stimuli. Divided Attention : The ability to attend different stimuli or attention at the same time. According to the neuroanatomical model from Posner and Petersen , there are three different attentional systems.
It is closely related to the reticular formation and some of its connections, like the frontal areas, limbic systems, the thalamus, and the basal ganglia. The brain areas related to this system are the posterior parietal cortex, the lateral pulvinar nucleus of the thalamus, and the superior colliculus.
It's closely related to the prefrontal dorsolateral cortex, the orbitofrontal cortex, the anterior cingulate cortex, the supplementary motor area, and with the neostriatum striate nucleus.
Attention is necessary for the proper functioning of our other cognitive skills, which is why an alteration in any of the attentional processes may make any daily activity more difficult to complete. However, it's important to remember that it's completely normal for attention levels to vary throughout the day, and having trouble paying attention mid-afternoon does not necessarily mean that there is any presence of an alteration.
Some factors that may affect attention levels are tiredness, fatigue, high temperatures, consuming drugs or other substances, as well as a number of others.
Excessive attentional states typical of delirious states are known as hyperprosexia. The contrary is known as hypoprosexia or inattention. ADHD is characterized by a difficulty controlling and directing attention to a stimulus and controlling behavior in general. The brains of people with ADHD have been shown to have a series of anatomical differences in the nucleus accumbens, the striate nucleus, the putamen, the amygdala, the hippocampus, prefrontal areas, and the thalamus.
These neuroanatomical differences and symptoms may be the consequence of late brain maturation. Altered states of consciousness, like coma or aprosexia , a vegetative state , and a state of minimal conscinsiousness all have alterations in Arousal or in focused attention and more complex attentional sub-processes.
These disorders are caused by brain damage like stroke or chronic traumatic encephalopathy CTE. Brain damage may also cause other attentional problems like distractibility or excessive fatigue, or other more specific problems like heminegligence , dementias like Alzheimer's Disease. On the other hand, anxiety disorders or depressive disorders tend to have an increased attentional level, specifically toward negative or anxiety-producing stimuli. Evaluating attention can be helpful to understand attention in a number of different areas.
Academic Areas to know if a student will have trouble studying or if they'll need extra breaks. Clinical or Medical Areas to know if a patient is able to carry out their daily tasks independently and safely. Professional Areas to know if a worker is able to perform well in certain positions, or if they will be able to stay focused and work well throughout their entire shift. With the help of a complete neuropsychological assessment , it is possible to easily and effectively evaluate a number of different cognitive skills, like focused attention.
This test helps to evaluate other behavioral alterations, response time, visual perception, shifting, inhibition, updating, spatial perception, processing speed, visual scanning, and hand-eye coordination. Every cognitive skill, including attention, can be trained and improved.
CogniFit may help you with its training programs. Brain plasticity is the basis of attention rehabilitation and other cognitive skills. The brain and its neural connections can be strengthened by challenging and working them, so by frequently training these skills, the brain structures related to attention become stronger. CogniFit was created by a team of professionals specialized in the area of neurogenesis and synaptic plasticity, which is how we were able to create a personalized cognitive stimulation program that would be tailored to the needs of each user.
The conscious experience of space is primarily based on bodily movements Berthoz, ; Morris, However, bodily movements, albeit necessary, are not sufficient Marchetti, b.
The conscious experience of space also requires that: a attention is internally applied to prorioceptors and the vestibular system in order to isolate and bring to consciousness the single perceptions entailed by movement.
External attention is also required to build some conscious experiences of space Berthoz, ; b working memory assemblies these single perceptions, by keeping them present in an incremental way. For example, move your index finger slowly. Now, look at the tip of the finger while the finger moves, and consider it as a moving object. Next, repeat the movement and consider the path or line drawn by the tip of the finger. You will notice that in the former case you will simply follow the tip of the finger, maybe anticipating its direction, but without keeping track of the positions previously occupied by it; on the contrary, in the latter case you will follow the tip of the finger by constantly keeping track of the positions it occupied, moment after moment, since it started moving.
Language allows us to variously and, theoretically, endlessly combine meanings. This combinatorial power is made possible by relational units such as conjunctions and prepositions: Sapir, ; Ceccato, ; Ceccato and Zonta, ; Benedetti, , , , which, tying together two or more semantic elements simple words, other relational units, complex thoughts, etc.
These two forms of memory, albeit necessary, are not sufficient. Theoretically, correlational networks can be infinite.
However, the well-known limits of working memory constrain this possibility. In fact, sentences have a limited length and are separated by semicolons, full stops, pauses, etc. At full stops, working memory stops being loaded, and what has been present in it up to that moment, must be in some way stored in a summarized form in a short-term memory.
Pronouns have the function of reloading into working memory what has been stored in short-term memory. It should be noted that, compared and contrary to the experiences of time and space, language does not specifically require that working memory cumulates attentional states. In language, working memory has the primary and most general function of supporting relational units in variously combining semantic elements. Moreover, language specifically needs the involvement of semantic memory, which is only rarely, or indirectly, involved when constructing temporal and spatial experiences.
Additionally, language deeply requires other forms of attention, such as shared attention Tomasello, , ; Oakley, Language and the kind of thought it entails linguistic or correlational thought: Ceccato and Zonta, ; Benedetti, can be considered a specific subset of conscious thinking Marchetti, In many cases, we have dynamic and evolving visuo-spatial thought such as when we think, for example, about a flower that opens , or forms of thoughts involving other senses.
Generally speaking, conscious thinking requires operators other than just the relational units involved by language: these operators should allow, for example, for the transformation of the object of thought, or the production of new conscious experiences from earlier ones, or the comparison of elements.
Therefore, conscious thinking, compared to language, sometimes requires a deeper involvement of working memory such as when evolving representations are produced , and the presence of dedicated and usually unconscious frames, representational and operational systems that are not strictly required by language such as those that allow one to draw inferences, or make decisions.
A final consideration should be made about the empirical verification of the analyses I have put forward here and elsewhere Marchetti, , Generally speaking, it should be noted that these analyses are particularly suited to be verified by an empirical approach centered on the notion of operation and its combinatorial power.
In fact, my analyses describe in a sufficiently detailed way what operations that is, how basic elements are assembled and combined must be performed in order to obtain certain forms of consciousness. As already shown in another paper Benedetti et al. OA does not put forward specific analyses in operational terms of phenomenological contents and forms.
However, because of the hierarchical organization implied by its theoretical framework, OA is very suited to verify precisely this kind of analysis. This article is an attempt to demonstrate that some of the most important forms of consciousness — episodic memory, episodic future thought, perception, language and conscious thinking — are based on an active constructive process.
Despite the fact that we experience the world surrounding us as a continuous, seamless flow of information, many psychological and neurophysiological observations reveal that information is actually extracted and processed in distinct moments, similar to the snapshots of a camera. For most of the forms of consciousness to occur, a construction combining the various moments or snapshots is required.
The main plausible mechanisms implied in this construction process are attention and working memory. Attention allows for the selection of the basic elements to be assembled. Empirical evidence shows that attention works on a period basis around 7 Hz : it samples information even when only a single location has to be monitored.
Working memory represents the mechanism that allows for the assembly of the basic elements selected by attention, by establishing and holding temporary bindings between contents and contexts. Both the selection of basic elements and their assembly can be performed in various ways, thus allowing various construction processes to be performed, thereby obtaining various forms of consciousness. Temporal experience is based on a specific kind of working of attention and combination of attentional moments.
Namely, the duration of a given event is determined by the cumulative quantity of labor performed by the portion of our attention A t that is kept focused on the conscious experience of the event.
The experience of duration provides the basis for the construction of the conscious experiences of past, present and future. By adding the temporal dimensions of past and future to an event, it is possible to subjectively experience that event as remembered or occurring in the future. The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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