Beneath the cortex is the subcortex, divided into the forebrain, midbrain, and hindbrain, which covers many regions although our discussion will largely touch on the superior colliculus and the thalamus , two areas that play an important role in visual processing. A salient phenomenon is neural signaling through action potentials or spikes. For a sensory neuron, the spikes it generates are tied to its receptive field. For example, in a visual neuron, its receptive field is understood in spatial terms and corresponds to that area of external space where an appropriate stimulus triggers the neuron to spike.

Given this correlation between stimulus and spikes, the latter carries information about the former. Information processing in sensory systems involves processing of information regarding stimuli within receptive fields.

Which electrical property provides the most fruitful explanatory basis for understanding consciousness remains an open question. For example, when looking at a single neuron, neuroscientists are not interested in spikes per se but the spike rate generated by a neuron per unit time.

Yet spike rate is one among many potentially relevant neural properties. Consider the blood oxygen level dependent signal BOLD measure in functional magnetic resonance imaging fMRI.

The BOLD signal is a measure of changes in blood flow in the brain when neural tissue is active and is postulated to be a function of electrical properties at a different part of a neuron than that part tied to spikes. Specifically, given a synapse which is the connection between two neurons to form a basic circuit motif, spikes are tied to the pre synaptic side while the BOLD signal is thought to be a function of electrical changes on the post synaptic side signal flow is from pre to post.

The number of neural properties potentially relevant to explaining mental phenomena is dizzying. How precisely to understand neural representation is itself a vexed question Cao , ; Shea , but we will deploy a simple assumption with respect to spikes which can be reconfigured for other properties: where a sensory neuron generates spikes when a stimulus is placed in its receptive field, the spikes carry information about the stimulus strictly speaking, about a random variable.

An important distinction separates access consciousness from phenomenal consciousness Block For example, one understands what it is like to see red only if one has visual experiences of the relevant type Jackson As noted earlier, introspection is the first source of evidence about consciousness.

Introspective reports bridge the subjective and objective. Introspective reports demonstrate that the subject can access the targeted conscious state. That is, the state is access -conscious: it is accessible for use in reasoning, report, and the control of action.

Talk of access-consciousness must keep track of the distinction between actual access versus accessibility. Thus, access consciousness provides much of the evidence for empirical theories of consciousness.

Still, it seems plausible that a state can be conscious even if one does not access it in report so long as that state is accessible. One can report it.

Access-consciousness is usually defined in terms of this dispositional notion of accessibility. Rational access contrasts with a broader conception of intentional access that takes a mental state to be access-conscious if it can inform goal-directed or intentional behavior including behavior that is not rational or done for a reason.

This broader notion allows for additional measurable behaviors as relevant in assessing phenomenal consciousness especially in non-linguistic animals. So, if access provides us with evidence for phenomenal consciousness, this can be a through introspective reports; b through rational behavior, c through intentional behavior including nonrational behavior.

Indeed, in certain contexts, reflexive behavior provides measures of consciousness section 2. Explanations answer specific questions. Two questions regarding phenomenal consciousness frame this entry: Generic and Specific. Call this property generic consciousness , a property shared by specific conscious states such as seeing a red rose, feeling a touch, or being angry.

If there is such an N , then the presence of N entails that an associated mental state M is conscious and or its absence entails that M is unconscious. This yields a question about specific contents of consciousness such as experiencing the motion of an object see section 5. Expanding a bit, perceptual states have intentional content and specifying that content is one way of describing what that state is like. In introspectively accessing her conscious states, a subject reports what her experience is like by reporting what she experiences.

Thus, the subject can report seeing an object moving, changing color, or being of a certain kind e. Discussion of specific consciousness will focus on perceptual states described as consciously perceiving X where X can be a particular such as a face, a property such as the frequency of a vibration or a proposition, say seeing that an object moves in a certain direction. Many philosophers take perceiving X to be perceptually representing X.

Intentional content on this reading is a semantic notion, and this suggests a linking principle tying conscious content to the brain: Perceptually representing X is based on neural representations of X. The principle explains specific consciousness by appeal to neural representational content. Posing a clear question involves grasping its possible answers and in science, this is informed by identifying experiments that can provide evidence for such answers.

The emphasis on necessary and sufficient conditions in our two questions indicates how to empirically test specific proposals. To test sufficiency, one would aim to produce or modulate a certain neural state and then demonstrate that consciousness of a certain form arises.

To test necessity, one would eliminate a certain neural state and demonstrate that consciousness is abolished. Notice that such tests go beyond mere correlation between neural states and conscious states see section 1. In many experimental contexts, the underlying idea is causal necessity and sufficiency. Whichever option holds for S , the first step is to find N , a neural correlate of consciousness section 1.

In what follows, to explain generic consciousness, various global properties of neural systems will be considered section 3 as well as specific anatomical regions that are tied to conscious versus unconscious vision as a case study section 4. For specific consciousness, fine-grained manipulations of neural representations will be examined that plausibly shift and modulate the contents of perceptual experience section 5. It is undeniable that some organisms are subjects of experience.

But the question of how it is that these systems are subjects of experience is perplexing. Why is it that when our cognitive systems engage in visual and auditory information-processing, we have visual or auditory experience: the quality of deep blue, the sensation of middle C?

How can we explain why there is something it is like to entertain a mental image, or to experience an emotion? It is widely agreed that experience arises from a physical basis, but we have no good explanation of why and how it so arises. Why should physical processing give rise to a rich inner life at all? It seems objectively unreasonable that it should, and yet it does. If any problem qualifies as the problem of consciousness, it is this one.

Chalmers The Hard Problem can be specified in terms of generic and specific consciousness Chalmers In both cases, Chalmers argues that there is an inherent limitation to empirical explanations of phenomenal consciousness in that empirical explanations will be fundamentally either structural or functional, yet phenomenal consciousness is not reducible to either. This means that there will be something that is left out in empirical explanations of consciousness, a missing ingredient see also the explanatory gap [Levine ].

There are different responses to the hard problem. One response is to sharpen the explanatory targets of neuroscience by focusing on what Chalmers calls structural features of phenomenal consciousness, such as the spatial structure of visual experience, or on the contents of phenomenal consciousness. When we assess explanations of specific contents of consciousness, these focus on the neural representations that fix conscious contents. These explanations leave open exactly what the secret ingredient is that shifts a state with that content from unconsciousness to consciousness.

On ingredients explaining generic consciousness, a variety of options have been proposed see section 3 , but it is unclear whether these answer the Hard Problem, especially if any answer to that the Problem has a necessary condition that the explanation must conceptually close off certain possibilities, say the possibility that the ingredient could be added yet consciousness not ignite as in a zombie, a creature without phenomenal consciousness see the entry on zombies.

Indeed, some philosophers deny the hard problem see Dennett for a recent statement. Perhaps the most common attitude for neuroscientists is to set the hard problem aside.

Instead of explaining the existence of consciousness in the biological world, they set themselves to explaining generic consciousness by identifying neural properties that can turn consciousness on and off and explaining specific consciousness by identifying the neural representational basis of conscious contents. Identifying correlates is an important first step in understanding consciousness, but it is an early step.

After all, correlates are not necessarily explanatory in the sense of answering specific questions posed by neuroscience. That one does not want a mere correlate was recognized by Chalmers who defined an NCC as follows:. An NCC is a minimal neural system N such that there is a mapping from states of N to states of consciousness, where a given state of N is sufficient under conditions C , for the corresponding state of consciousness. One wants a minimal neural system since, crudely put, the brain is sufficient for consciousness but to point this out is hardly to explain consciousness even if it provides an answer to questions about sufficiency.

The emphasis on sufficiency goes beyond mere correlation, as neuroscientists aim to answer more than the question: What is a neural correlate for conscious phenomenon C? Perhaps more specifically: What neural phenomenon is causally sufficient for consciousness? After all, assume that the NCC is type identical to a conscious state.

Thus, some correlated effects will not be explanatory. For example, citing the effects of consciousness will not provide causally sufficient conditions for consciousness.

In other contexts, neuroscientists speak of the neural basis of a phenomenon where the basis does not simply correlate with the phenomenon but also explains and possibly grounds it. However, talk of correlates is entrenched in the neuroscience of consciousness, so one must remember that the goal is to find the subset of neural correlates that are explanatory, in answering concrete questions. Reference to neural correlates in this entry will always mean neural explanatory correlate of consciousness on occasion, I will speak of these as the neural basis of consciousness.

That is, our two questions about specific and generic consciousness focus the discussion on neuroscientific theories and data that contribute to explaining them. This project allows that there are limits to neural explanations of consciousness, precisely because of the explanatory gap Levine Since studying consciousness requires that scientists track its presence, it will be important to examine various methods used in neuroscience to isolate and probe conscious states. Scientists primarily study phenomenal consciousness through subjective reports.

We can treat reports in neuroscience as conceptual in that they express how the subject recognizes things to be, whether regarding what they perceive perceptual or observational reports, as in psychophysics or regarding what mental states they are in introspective reports.

Subjective reports of conscious states draw on distinctively first-personal access to that state. The subject introspects. Introspection raises questions that science has only recently begun to address systematically in large part because of longstanding suspicion regarding introspective methods. Introspection was judged to be an unreliable method for addressing questions about mental processing.

This makes it difficult to address long-standing worries about introspective reliability regarding consciousness. In science, questions raised about the reliability of a method are answered by calibrating and testing the method. This calibration has not been done with respect to the type of introspection commonly practiced by philosophers.

A scientist might worry that philosophical introspection merely recycles rejected methods of a century ago, indeed without the stringent controls or training imposed by earlier psychologists. How can we ascertain and ensure the reliability of introspection in the empirical study of consciousness? One way to address the issue is to connect introspection to attention. Philosophical conceptions of introspective attention construe it as capable of directly focusing on phenomenal properties and experiences.

As this idea is fleshed out, however, it is clearly not a form of attention studied by cognitive science, for the posited direct introspective attention is neither perceptual attention nor what psychologists call internal attention e.

Calibrating introspection as it is used in the science of consciousness would benefit from concrete models of introspection, models we lack see Spener , for a general form of calibration. One philosophical tradition links introspection to perceptual attention, and this allows construction of concrete models informed by science. Look at a tree and try to turn your attention to intrinsic features of your visual experience.

Harman This is related to a proposal inspired by Gareth Evans : in introspecting perceptual states, say judging that one sees an object, one draws on the same perceptual capacities used to answer the question whether the object is present. Further, the advantage of this proposal is that questions of reliability come down to questions of the reliability of psychological capacities that can be empirically assessed, say perceptual, attentional and conceptual reliability.

Introspection can be reliable. Successful clinical practice relies on accurate introspection as when dealing with pain or correcting blurry vision in optometry. The success of medical interventions suggests that patient reports of these phenomenal states are reliable.

Further, in many of the examples to be discussed, the perceptual attention-based account provides a plausible cognitive model of introspection. Subjects report on what they perceptually experience by attending to the object of their experience, and where perception and attention are reliable, a plausible hypothesis is that their introspective judgments will be reliable as well.

Accordingly, I assume the reliability of introspection in the empirical studies to be discussed. Still, given that no scientist should assert the reliability of a method without calibration, introspection must be subject to the same standards. There is more work to be done. Introspection illustrates a type of cognitive access, for a state that is introspected is access conscious. This raises a question that has epistemic implications: is access consciousness necessary for phenomenal consciousness?

If it is not, then there can be phenomenal states that are not access conscious, so are in principle not reportable. That is, phenomenal consciousness can overflow access consciousness Block Access is tied to attention. For example, the Global Workspace theory of consciousness understands consciousness in terms of access section 3.

So, the necessity of attention for phenomenal consciousness is entailed by the necessity of access for phenomenal consciousness. Many scientists of consciousness take there to be evidence for no phenomenal consciousness without access and little if no evidence of phenomenal consciousness outside of access.

An important set of studies focuses on the thesis that attention is a necessary gate for phenomenal consciousness, where attention is tied to access. Call this the gatekeeping thesis. To assess that evidence, we must ask: what is attention? An uncontroversial conception of attention is that it is subject selection of a target to inform task performance Wu b. The experimental studies thought to support the necessity of attention for consciousness draw on this conception.

This approach tests necessity by ensuring through task performance that the subject is not attending to S. One then measures whether the subject is aware of S by observing whether the subject reports it. If the subject does not report S , then the hypothesis is that failure of attention to S explains the failure of conscious awareness of S and hence the failure of report. During the task, a person in a gorilla costume walks across the scene.

Half of the subjects fail to notice and report the gorilla, this being construed as evidence for the absence of visual awareness of the gorilla. Hence, failure to attend to the gorilla is said to render subjects phenomenally blind to it.

The gatekeeping thesis holds that attention is necessary for consciousness, so that removing it from a target eliminates consciousness of it. Yet there is a flaw in the methodology. To report a stimulus, one must attend to it, i. The experimental logic requires eliminating attention to a stimulus S to test if attention is a necessary condition for consciousness e. Yet even if the subject were conscious of S , when attention to S is eliminated, one can predict that the subject will fail to act report on S since attention is necessary for report.

The observed results are actually consistent with the subject being conscious of S without attending to it, and thus are neutral between overflow and gatekeeping. Instead, the experiments concern parameters for the capture of attention and not consciousness.

While those antagonistic to overflow have argued that it is not empirically testable M. After all, to test the necessity of attention for consciousness, we must eliminate attention to a target while gathering evidence for the absence of consciousness.

How then can we gather the required evidence to assess competing theories? For example, Frässle et al. They presented subjects either with stimuli moving in opposite directions or stimuli of different luminance values, one stimulus in each pair presented separately to each eye.

This induces binocular rivalry, an alternation in which of the two stimuli is visually experienced see section 5. Where the stimuli involved motion, subjects demonstrated optokinetic nystagmus where the eye slowly moves in the direction of the stimulus and then makes a fast, corrective saccade ballistic eye movement in the opposite direction.

Frässle et al. observed that optokinetic nystagmus tracked the perceived direction of the stimulus as reported by the subject. Similarly, for stimuli of different luminance, the pupils would dilate, being wider for dimmer stimuli, and narrower for brighter stimuli, again correlating with subjective reports of the intensity of the stimulus.

They seem to provide a way to track phenomenal consciousness even when access is eliminated. Once it is validated, monitoring this reflex can provide a way to substitute for subjective reports within that paradigm. One cannot, however, simply extend the use of no-report paradigms outside the behavioral contexts within which the method is validated. With each new experimental context, we must revalidate the measure with introspective report.

Can we use no report paradigms to address whether access is necessary for phenomenal consciousness? A likely experiment would be one that validates no-report correlates for some conscious phenomenon P in a concrete experimental context C. With this validation in hand, one then eliminates accessibility and attention with respect to P in C. If the no-report correlate remains, would this clearly support overflow?

Perhaps, though gatekeeping theorists likely will respond that the result does not rule out the possibility that phenomenal consciousness disappears with access consciousness despite the no-report correlate remaining. For example, the reflexive response and phenomenal consciousness might have a common cause that remains even if phenomenal consciousness is selectively eliminated by removing access.

A standard approach is to have subjects perform a task, say perceptual discrimination of a stimulus, and then indicate how confident they are that their perceptual judgment was accurate. How is metacognitive assessment of performance tied to consciousness? The metacognitive judgment reflects introspective assessment of the quality of perceptual states and can provide information about the presence of consciousness. If subjects accurately respond to the stimulus but showed no difference in metacognitive confidence in respect of the quality of perception of the target versus of the blank, this would provide evidence of the absence of consciousness in vision effectively, blindsight in normal subjects; section 4.

Interestingly, Peters and Lau found no evidence for unconscious vision in their specific paradigm. One concern with metacognitive approaches is that they also rely on introspection Rosenthal ; see also Sandberg et al.

If metacognition relies on introspection, does it not accrue all the disadvantages of the latter? One advantage of metacognition is that it allows for psychophysical analysis.

There has also been work done on metacognition and its neural basis. Alternatively, information about confidence might be read out by other structures, say prefrontal cortex see section 3. Metacognitive and introspective judgments result from intentional action, so why not look at intentional action, broadly construed, for evidence of consciousness? Often, when subjects perform perception guided actions, we infer that they are relevantly conscious. It would be odd if a person cooks dinner and then denies having seen any of the ingredients.

That they did something intentionally provides evidence that they were consciously aware of what they acted on. An emphasis on intentional action embraces a broader evidential basis for consciousness. Consider the Intentional Action Inference to phenomenal consciousness:. If some subject acts intentionally, where her action is guided by a perceptual state, then the perceptual state is phenomenally conscious.

An epistemic version takes the action to provide good evidence that the state is conscious. Notice that introspection is typically an intentional action so it is covered by the inference. In this way, the Inference effectively levels the evidential playing field: introspective reports are simply one form among many types of intentional actions that provide evidence for consciousness.

Those reports are not privileged. The intentional action inference and no-report paradigms highlight the fact the science of consciousness has largely restricted its behavioral data to one type of intentional action, introspection. What is the basis of privileging one intentional action over others? Consider the calibration issue. For many types of intentional action deployed in experiments, scientists can calibrate performance by objective measures such as accuracy.

This has not been done for introspection of consciousness, so scientists have privileged an uncalibrated measure over a calibrated one. This seems empirically ill-advised. On the flip side, one worry about the intentional action inference is that it ignores guidance by unconscious perceptual states see sections 4 and 5. The Intentional Action Inference is operative when subjective reports are not available. A patient in the vegetative state appears at times to be wakeful, with cycles of eye closure and eye opening resembling those of sleep and waking.

As a rule, the patient can breathe spontaneously and has a stable circulation. The state may be a transient stage in the recovery from coma or it may persist until death.

Working Party RCP Unlike vegetative state patients, minimally conscious state patients seemingly perform intentional actions. Recent work suggests that some patients diagnosed as in the vegetative state are conscious.

Owen et al. The commands were presented at the beginning of a thirty-second period, alternating between imagination and relax commands. The patient demonstrated similar activity when matched to control subjects performing the same task: sustained activation of the supplementary motor area SMA was observed during the motor imagery task while sustained activation of the parahippocampal gyrus including the parahippocampal place area PPA was observed during the spatial imagery task.

Note that these tasks probe specific contents of consciousness by monitoring neural correlates of conscious imagery. In normal subjects, reading action words is known to activate sensorimotor areas Pulvermüller draw on a neural correlate of imagination, a mental action. Of note, experiments stimulating the parahippocampal place area induces seeming hallucinations of places Mégevand et al. Deciding whether there is phenomenality in a mental representation implies putting a boundary—drawing a line—between different types of representations…We have to start from the intuition that consciousness in the phenomenal sense exists, and is a mental function in its own right.

That intuition immediately implies that there is also un conscious information processing. Lamme It is uncontroversial that there is unconscious information processing, say processing occurring in a computer.

What Lamme means is that there are conscious and unconscious mental states representations. For example, there might be visual states of seeing X that are conscious or not section 4.

To provide a gloss on the hypotheses: For the Global Neuronal Workspace, entry into the neural workspace is necessary and sufficient for a state or content to be consciousness. For Recurrent Processing Theory, a type of recurrent processing in sensory areas is necessary and sufficient for perceptual consciousness, so entry into the Workspace is not necessary.

For Higher-Order Theories, the presence of a higher-order state tied to prefrontal areas is necessary and sufficient for phenomenal experience, so recurrent processing in sensory areas is not necessary nor is entry into the workspace. For Information Integration Theories, a type of integration of information is necessary and sufficient for a state to be conscious. One explanation of generic consciousness invokes the global neuronal workspace.

Notice that the previous characterization does not commit to whether it is phenomenal or access consciousness that is being defined. The accessibility of information is then defined as its potential access by other systems. Dehaene Dehaene et al. Hence, only states in 3 are conscious. Figure Legend: The top figure provides a neural architecture for the workspace, indicating the systems that can be involved. The lower figure sets the architecture within the six layers of the cortex spanning frontal and sensory areas, with emphasis on neurons in layers 2 and 3.

Figure reproduced from Dehaene, Kerszberg, and Changeux Copyright National Academy of Sciences. The global neuronal workspace theory ties access to brain architecture. It postulates a cortical structure that involves workspace neurons with long-range connections linking systems: perceptual, mnemonic, attentional, evaluational and motoric.

What is the global workspace in neural terms? Long-range workspace neurons within different systems can constitute the workspace, but they should not necessarily be identified with the workspace. A subset of workspace neurons becomes the workspace when they exemplify certain neural properties. The workspace then is not a rigid neural structure but a rapidly changing neural network, typically only a proper subset of all workspace neurons.

Consider then a neural population that carries content p and is constituted by workspace neurons. In virtue of being workspace neurons, the content p is accessible to other systems, but it does not yet follow that the neurons then constitute the global workspace.

A further requirement is that workspace neurons are 1 put into an active state that must be sustained so that 2 the activation generates a recurrent activity between workspace systems. Only when these systems are recurrently activated are they, along with the units that access the information they carry, constituents of the workspace.

This activity accounts for the idea of global broadcast in that workspace contents are accessible to further systems. The global neuronal workspace theory provides an account of access consciousness but what of phenomenal consciousness? There is, however, a potential confound. We track phenomenal consciousness by access in introspective report, so widespread activity during reports of conscious experience correlates with both access and phenomenal consciousness.

Correlation cannot tell us whether the observed activity is the basis of phenomenal consciousness or of access consciousness in report Block This remains a live question for as discussed in section 2.

To eliminate the confound, experimenters ensure that performance does not differ between conditions where consciousness is present and where it is not. Still, the absence of observed activity by an imaging technique does not imply the absence of actual activity for the activity might be beyond the limits of detection of that technique.

A different explanation ties perceptual consciousness to processing independent of the workspace, with focus on recurrent activity in sensory areas. This approach emphasizes properties of first-order neural representation as explaining consciousness. Victor Lamme , argues that recurrent processing is necessary and sufficient for consciousness. Recurrent processing occurs where sensory systems are highly interconnected and involve feedforward and feedback connections. For example, forward connections from primary visual area V1, the first cortical visual area, carry information to higher-level processing areas, and the initial registration of visual information involves a forward sweep of processing.

Lamme holds that recurrent processing in Stage 3 is necessary and sufficient for consciousness. Thus, what it is for a visual state to be conscious is for a certain recurrent processing state to hold of the relevant visual circuitry. This identifies the crucial difference between the global neuronal workspace and recurrent processing theory: the former holds that recurrent processing at Stage 4 is necessary for consciousness while the latter holds that recurrent processing at Stage 3 is sufficient.

Thus, recurrent processing theory affirms phenomenal consciousness without access by the global neuronal workspace. In that sense, it is an overflow theory see section 2. Why think that Stage 3 processing is sufficient for consciousness? Given that Stage 3 processing is not accessible to introspective report, we lack introspective evidence for sufficiency. Lamme appeals to experiments with brief presentation of stimuli such as letters where subjects are said to report seeing more than they can identify in report Lamme It is not clear that this is strong motivation for recurrent processing, since the very fact that subjects can report seeing more letters shows that they have some access to them, just not access to letter identity.

Lamme also presents what he calls neuroscience arguments. This strategy compares two neural networks, one taken to be sufficient for consciousness, say the processing at Stage 4 as per Global Workspace theories, and one where sufficiency is in dispute, say recurrent activity in Stage 3.

Lamme argues that certain features found in Stage 4 are also found in Stage 3 and given this similarity, it is reasonable to hold that Stage 3 processing suffices for consciousness.

For example, both stages exhibit recurrent processing. Global neuronal workspace theorists can allow that recurrent processing in stage 3 is correlated, even necessary, but deny that this activity is explanatory in the relevant sense of identifying sufficient conditions for consciousness.

It is worth reemphasizing the empirical challenge in testing whether access is necessary for phenomenal consciousness sections 2. The two theories return different answers, one requiring access, the other denying it. As we saw, the methodological challenge in testing for the presence of phenomenal consciousness independently of access remains a hurdle for both theories.

A long-standing approach to conscious states holds that one is in a conscious state if and only if one relevantly represents oneself as being in such a state. For example, one is in a conscious visual state of seeing a moving object if and only if one suitably represents oneself being in that visual state.

The intuitive rationale for such theories is that if one were in a visual state but in no way aware of that state, then the visual state would not be conscious. Thus, to be in a conscious state, one must be aware of it, i. Higher-order theories merge with empirical work by tying high-order representations with activity in prefrontal cortex which is taken to be the neural substrate of the required higher-order representations. On certain higher-order theories, one can be in a conscious visual state even if there is no visual system activity, so long as one represents oneself as being in that state.

For example, on the higher-order theory, lesions to prefrontal cortex should affect consciousness Kozuch , testing the necessity of prefrontal cortex for consciousness. Against higher-order theories, some reports claim that patients with prefrontal cortex surgically removed maintain preserved perceptual consciousness Boly et al. This would lend support to recurrent processing theories that hold that prefrontal cortical activity is not necessary for consciousness.

Bilateral suppression of prefrontal activity using transcranial magnetic stimulation also seems to selectively impair visibility as evidenced by metacognitive report Rounis et al. Information Integration Theory of Consciousness IIT draws on the notion of integrated information , symbolized by Φ, as a way to explain generic consciousness Tononi , IIT defines integrated information in terms of the effective information carried by the parts of the system in light of its causal profile. For example, we can focus on a part of the whole circuit, say two connected nodes, and compute the effective information that can be carried by this microcircuit.

The system carries integrated information if the effective informational content of the whole is greater than the sum of the informational content of the parts.

If there is no partitioning where the summed informational content of the parts equals the whole, then the system as a whole carries integrated information and it has a positive value for Φ. Intuitively, the interaction of the parts adds more to the system than the parts do alone. IIT holds that a non-zero value for Φ implies that a neural system is conscious, with more consciousness going with greater values for Φ.

For example, Tononi has argued that the human cerebellum has a low value for Φ despite there being four to five times the number of neurons in the cerebellum versus in human cortex. On IIT, what matters is the presence of appropriate connections and not the number of neurons. A potential problem for IIT is that it treats many things to be conscious which are prima facie not in Other Internet Resources , see Aaronson a; for striking counterexamples and Aaronson b with a response from Tononi.

For certain higher-order thought theories, having a higher-order state, supported by prefrontal cortex, without corresponding sensory states can suffice for conscious states. In this case, the front of the brain would be sufficient for consciousness. Finally, the global neuronal workspace, drawing on workspace neurons that are present across brain areas to form the workspace, might be taken to straddle the difference, depending on the type of conscious state involved.

They require entry into the global workspace such that neither sensory activity nor a higher order thought on its own is sufficient, i. What is clear is that once theories make concrete predictions of brain areas involved in generic consciousness, neuroscience can test them. Work on unconscious vision provides an informative example. In the past decades, scientists have argued for unconscious seeing and investigated its brain basis especially in neuropsychology , the study of subjects with brain damage.

Interestingly, if there is unconscious seeing, then the intentional action inference must be restricted in scope since some intentional behaviors might be guided by unconscious perception section 2.

That is, the existence of unconscious perception blocks a direct inference from perceptually guided intentional behavior to perceptual consciousness. The case study of unconscious vision promises to illuminate more specific studies of generic consciousness along with having repercussions for how we attribute conscious states.

Since the groundbreaking work of Leslie Ungerleider and Mortimer Mishkin , scientists divide primate cortical vision into two streams: dorsal and ventral for further dissection, see Kravitz et al.

The dorsal stream projects into the parietal lobe while the ventral stream projects into the temporal lobe see Figure 1. Controversy surrounds the functions of the streams. Ungerleider and Mishkin originally argued that the streams were functionally divided in terms of what and where : the ventral stream for categorical perception and the dorsal stream for spatial perception.

There continues to be debate surrounding the Milner and Goodale account Schenk and McIntosh but it has strongly influenced philosophers of mind. Lesions to the dorsal stream do not seem to affect conscious vision in that subjects are able to provide accurate reports of what they see but see Wu a. Rather, dorsal lesions can affect visual-guidance of action with optic ataxia being a common result.

Optic ataxic subjects perform inaccurate motor actions. Lesions in the ventral stream disrupt normal conscious vision, yielding visual agnosia, an inability to see visual form or to visually categorize objects Farah Dorsal stream processing is said to be unconscious.

If the dorsal stream is critical in the visual guidance of many motor actions such as reaching and grasping, then those actions would be guided by unconscious visual states. The visual agnosic patient DF provides critical support for this claim. Like other visual agnosics with similar lesions, DF is at chance in reporting aspects of form, say the orientation of a line or the shape of objects.

Nevertheless, she retains color and texture vision. Strikingly, DF can generate accurate visually guided action, say the manipulation of objects along specific parameters: putting an object through a slot or reaching for and grasping round stones in a way sensitive to their center of mass.

Simultaneously, DF denies seeing the relevant features and, if asked to verbally report them, she is at chance. What is uncontroversial is that there is a division in explanatory neural correlates of visually guided behavior with the dorsal stream weighted towards the visual guidance of motor movements and the ventral stream weighted towards the visual guidance of conceptual behavior such as report and reasoning see section 5. A substantial further inference is that consciousness is segregated away from the dorsal stream to the ventral stream.

How strong is this inference? Recall the intentional action inference. In performing the slot task, DF is doing something intentionally and in a visually guided way.

For control subjects performing the task, we conclude that this visually guided behavior is guided by conscious vision. Indeed, a folk-psychological assumption might be that consciousness informs mundane action Clark ; for a different perspective see Wallhagen Since DF shows similar performance on the same task, why not conclude that she is also visually conscious? DF denies seeing features she is visually sensitive to in action.

Should introspection then trump intentional action in attributing consciousness? Two issues are worth considering. The first is that introspective reports involve a specific type of intentional action guided by the experience at issue. One type of intentional behavior is being prioritized over another in adjudicating whether a subject is conscious. What is the empirical justification for this prioritization? The second issue is that DF is possibly unique among visual agnosics.

It is a substantial inference to move from DF to a general claim about the dorsal stream being unconscious in neurotypical individuals see Mole for arguments that consciousness does not divide between the streams and Wu for an argument for unconscious visually guided action in normal subjects.

What this shows is that the methodological decisions that we make regarding how we track consciousness are substantial in theorizing about the neural bases of conscious and unconscious vision. A second neuropsychological phenomenon also highlighting putative unconscious vision is blindsight which results from lesions in primary visual cortex V1 typically leading to blindness over the part of visual space contralateral to the sight of the lesion Weiskrantz For example, left hemisphere V1 deals with right visual space, so lesions in left V1 lead to deficits in seeing the right side of space.

Subjects then report that they cannot see a visual stimulus in the affected visual space. For example, a blindsight patient with bilateral damage to V1 i.

Blindsight patients see in the sense of visually discriminating the stimulus to act on it yet deny that they see it. Like DF, blindsighters show a dissociation between certain actions and report, but unlike DF, they do not spontaneously respond to relevant features but must be encouraged to generate behaviors towards them.

The neuroanatomical basis of blindsight capacities remains unclear. Certainly, the loss of V1 deprives later cortical visual areas of a normal source of visual information. Still, there are other ways that information from the eye bypasses V1 to provide inputs to later visual areas. Alternative pathways include the superior colliculus SC , the lateral geniculate nucleus LGN in the thalamus, and the pulvinar as likely sources. Figure Legend: The front of the head is to the left, the back of the head is to the right.

One should imagine that the blue-linked regions are above the orange-linked regions, cortex above subcortex. V4 is assigned to the base of the ventral stream; V5, called area MT in nonhuman primates, is assigned to the base of the dorsal stream. The latter two have direct extrastriate projections projections to visual areas in the occipital lobe outside of V1 while the superior colliculus synapses onto neurons in the LGN and pulvinar which then connect to extrastriate areas Figure 3.

Which of these provide for the basis for blindsight remains an open question though all pathways might play some role Cowey ; Leopold If blindsight involves nonphenomenal, unconscious vision, then these pathways would be a substrate for it, and a functioning V1 might be necessary for normal conscious vision. Campion et al. In their reports, blindsight subjects feel like they are guessing about stimuli they can objectively discriminate. drew on signal detection theory , which emphasizes two determinants of detection behavior: perceptual sensitivity and response criterion.

Consider trying to detect something moving in the brush at twilight versus at noon. In the latter, the signal will be greatly separated from noise the object will be easier to detect while in the former, the signal will not be the object will be harder to detect. Yet in either case, one might operate with a conservative response criterion, say because one is afraid to be wrong. hypothesized that blindsight patients are conscious in that they are aware of visual signal where discriminability is low cf.

the twilight condition. Further, blindsight patients are more conservative in their response so will be apt to report the absence of a signal by saying that they do not see the relevant stimulus even though the signal is there, and they can detect it, as verified by their above chance visually guided behavior. This possibility was explicitly tested by Azzopardi and Cowey with the well-studied blindsight patient, GY.

They compared blindsight performance with normal subjects at threshold vision using signal detection measures and found that with respect to motion stimuli, the difference between discrimination and detection used to argue for blindsight can be explained by changes in response criterion, as Campion et al.

That is, GYs claim that he does not see the stimulus is due to a conservative criterion and not to a detection incapacity. In introspecting, what concepts are available to subjects will determine their sensitivity in report. In many studies with blindsight, subjects are given a binary option: do you see the stimulus or do you not see it? This presents a tremendous opportunity that innovation in fintech can solve by speeding up money movement, increasing access to capital, and making it easier to manage business operations in a central place.

Fintech offers innovative products and services where outdated practices and processes offer limited options. For example, fintech is enabling increased access to capital for business owners from diverse and varying backgrounds by leveraging alternative data to evaluate creditworthiness and risk models. This can positively impact all types of business owners, but especially those underserved by traditional financial service models.

When we look across the Intuit QuickBooks platform and the overall fintech ecosystem, we see a variety of innovations fueled by AI and data science that are helping small businesses succeed. By efficiently embedding and connecting financial services like banking, payments, and lending to help small businesses, we can reinvent how SMBs get paid and enable greater access to the vital funds they need at critical points in their journey.

Overall, we see fintech as empowering people who have been left behind by antiquated financial systems, giving them real-time insights, tips, and tools they need to turn their financial dreams into a reality. Innovations in payments and financial technologies have helped transform daily life for millions of people. People who are unbanked often rely on more expensive alternative financial products AFPs such as payday loans, money orders, and other expensive credit facilities that typically charge higher fees and interest rates, making it more likely that people have to dip into their savings to stay afloat.

A few examples include:. Mobile wallets - The unbanked may not have traditional bank accounts but can have verified mobile wallet accounts for shopping and bill payments.

Their mobile wallet identity can be used to open a virtual bank account for secure and convenient online banking. Minimal to no-fee banking services - Fintech companies typically have much lower acquisition and operating costs than traditional financial institutions.

They are then able to pass on these savings in the form of no-fee or no-minimum-balance products to their customers. This enables immigrants and other populations that may be underbanked to move up the credit lifecycle to get additional forms of credit such as auto, home and education loans, etc.

Entrepreneurs from every background, in every part of the world, should be empowered to start and scale global businesses. Most businesses still face daunting challenges with very basic matters. These are still very manually intensive processes, and they are barriers to entrepreneurship in the form of paperwork, PDFs, faxes, and forms.

Stripe is working to solve these rather mundane and boring challenges, almost always with an application programming interface that simplifies complex processes into a few clicks. Stripe powers nearly half a million businesses in rural America.

The internet economy is just beginning to make a real difference for businesses of all sizes in all kinds of places. We are excited about this future. The way we make decisions on credit should be fair and inclusive and done in a way that takes into account a greater picture of a person.

Lenders can better serve their borrowers with more data and better math. Zest AI has successfully built a compliant, consistent, and equitable AI-automated underwriting technology that lenders can utilize to help make their credit decisions. While artificial intelligence AI systems have been a tool historically used by sophisticated investors to maximize their returns, newer and more advanced AI systems will be the key innovation to democratize access to financial systems in the future.

D espite privacy, ethics, and bias issues that remain to be resolved with AI systems, the good news is that as large r datasets become progressively easier to interconnect, AI and related natural language processing NLP technology innovations are increasingly able to equalize access. T he even better news is that this democratization is taking multiple forms. AI can be used to provide risk assessments necessary to bank those under-served or denied access. AI systems can also retrieve troves of data not used in traditional credit reports, including personal cash flow, payment applications usage, on-time utility payments, and other data buried within large datasets, to create fair and more accurate risk assessments essential to obtain credit and other financial services.

By expanding credit availability to historically underserved communities, AI enables them to gain credit and build wealth. Additionally, personalized portfolio management will become available to more people with the implementation and advancement of AI.

Sophisticated financial advice and routine oversight, typically reserved for traditional investors, will allow individuals, including marginalized and low-income people, to maximize the value of their financial portfolios.

Moreover, when coupled with NLP technologies, even greater democratization can result as inexperienced investors can interact with AI systems in plain English, while providing an easier interface to financial markets than existing execution tools. Open finance technology enables millions of people to use the apps and services that they rely on to manage their financial lives — from overdraft protection, to money management, investing for retirement, or building credit.

More than 8 in 10 Americans are now using digital finance tools powered by open finance. This is because consumers see something they like or want — a new choice, more options, or lower costs. What is open finance? At its core, it is about putting consumers in control of their own data and allowing them to use it to get a better deal. When people can easily switch to another company and bring their financial history with them, that presents real competition to legacy services and forces everyone to improve, with positive results for consumers.

For example, we see the impact this is having on large players being forced to drop overdraft fees or to compete to deliver products consumers want. We see the benefits of open finance first hand at Plaid, as we support thousands of companies, from the biggest fintechs, to startups, to large and small banks. All are building products that depend on one thing - consumers' ability to securely share their data to use different services.

Open finance has supported more inclusive, competitive financial systems for consumers and small businesses in the U. and across the globe — and there is room to do much more. As an example, the National Consumer Law Consumer recently put out a new report that looked at consumers providing access to their bank account data so their rent payments could inform their mortgage underwriting and help build credit.

This is part of the promise of open finance. At Plaid, we believe a consumer should have a right to their own data, and agency over that data, no matter where it sits. This will be essential to securing benefits of open finance for consumers for many years to come.

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times. Donna Goodison dgoodison is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers.

She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

Both prongs of that are important. But cost-cutting is a reality for many customers given the worldwide economic turmoil, and AWS has seen an increase in customers looking to control their cloud spending. By the way, they should be doing that all the time. The motivation's just a little bit higher in the current economic situation. This interview has been edited and condensed for clarity. Besides the sheer growth of AWS, what do you think has changed the most while you were at Tableau? Were you surprised by anything?

The number of customers who are now deeply deployed on AWS, deployed in the cloud, in a way that's fundamental to their business and fundamental to their success surprised me. There was a time years ago where there were not that many enterprise CEOs who were well-versed in the cloud. It's not just about deploying technology. The conversation that I most end up having with CEOs is about organizational transformation.

It is about how they can put data at the center of their decision-making in a way that most organizations have never actually done in their history. And it's about using the cloud to innovate more quickly and to drive speed into their organizations. Those are cultural characteristics, not technology characteristics, and those have organizational implications about how they organize and what teams they need to have.

It turns out that while the technology is sophisticated, deploying the technology is arguably the lesser challenge compared with how do you mold and shape the organization to best take advantage of all the benefits that the cloud is providing. How has your experience at Tableau affected AWS and how you think about putting your stamp on AWS?

I, personally, have just spent almost five years deeply immersed in the world of data and analytics and business intelligence, and hopefully I learned something during that time about those topics. I'm able to bring back a real insider's view, if you will, about where that world is heading — data, analytics, databases, machine learning, and how all those things come together, and how you really need to view what's happening with data as an end-to-end story.

It's not about having a point solution for a database or an analytic service, it's really about understanding the flow of data from when it comes into your organization all the way through the other end, where people are collaborating and sharing and making decisions based on that data. AWS has tremendous resources devoted in all these areas. Can you talk about the intersection of data and machine learning and how you see that playing out in the next couple of years?

What we're seeing is three areas really coming together: You've got databases, analytics capabilities, and machine learning, and it's sort of like a Venn diagram with a partial overlap of those three circles. There are areas of each which are arguably still independent from each other, but there's a very large and a very powerful intersection of the three — to the point where we've actually organized inside of AWS around that and have a single leader for all of those areas to really help bring those together.

There's so much data in the world, and the amount of it continues to explode. We were saying that five years ago, and it's even more true today. The rate of growth is only accelerating.

It's a huge opportunity and a huge problem. A lot of people are drowning in their data and don't know how to use it to make decisions. Other organizations have figured out how to use these very powerful technologies to really gain insights rapidly from their data. What we're really trying to do is to look at that end-to-end journey of data and to build really compelling, powerful capabilities and services at each stop in that data journey and then…knit all that together with strong concepts like governance.

By putting good governance in place about who has access to what data and where you want to be careful within those guardrails that you set up, you can then set people free to be creative and to explore all the data that's available to them. AWS has more than services now. Have you hit the peak for that or can you sustain that growth? We're not done building yet, and I don't know when we ever will be.

We continue to both release new services because customers need them and they ask us for them and, at the same time, we've put tremendous effort into adding new capabilities inside of the existing services that we've already built. We don't just build a service and move on. Inside of each of our services — you can pick any example — we're just adding new capabilities all the time. One of our focuses now is to make sure that we're really helping customers to connect and integrate between our different services.

So those kinds of capabilities — both building new services, deepening our feature set within existing services, and integrating across our services — are all really important areas that we'll continue to invest in.

Do customers still want those fundamental building blocks and to piece them together themselves, or do they just want AWS to take care of all that? There's no one-size-fits-all solution to what customers want. It is interesting, and I will say somewhat surprising to me, how much basic capabilities, such as price performance of compute, are still absolutely vital to our customers. But it's absolutely vital.

Part of that is because of the size of datasets and because of the machine learning capabilities which are now being created. They require vast amounts of compute, but nobody will be able to do that compute unless we keep dramatically improving the price performance. We also absolutely have more and more customers who want to interact with AWS at a higher level of abstraction…more at the application layer or broader solutions, and we're putting a lot of energy, a lot of resources, into a number of higher-level solutions.

One of the biggest of those … is Amazon Connect, which is our contact center solution. In minutes or hours or days, you can be up and running with a contact center in the cloud. At the beginning of the pandemic, Barclays … sent all their agents home. In something like 10 days, they got 6, agents up and running on Amazon Connect so they could continue servicing their end customers with customer service.

We've built a lot of sophisticated capabilities that are machine learning-based inside of Connect. We can do call transcription, so that supervisors can help with training agents and services that extract meaning and themes out of those calls.

We don't talk about the primitive capabilities that power that, we just talk about the capabilities to transcribe calls and to extract meaning from the calls. It's really important that we provide solutions for customers at all levels of the stack. Given the economic challenges that customers are facing, how is AWS ensuring that enterprises are getting better returns on their cloud investments?

Now's the time to lean into the cloud more than ever, precisely because of the uncertainty. We saw it during the pandemic in early , and we're seeing it again now, which is, the benefits of the cloud only magnify in times of uncertainty. For example, the one thing which many companies do in challenging economic times is to cut capital expense.

For most companies, the cloud represents operating expense, not capital expense. You're not buying servers, you're basically paying per unit of time or unit of storage. That provides tremendous flexibility for many companies who just don't have the CapEx in their budgets to still be able to get important, innovation-driving projects done.

Another huge benefit of the cloud is the flexibility that it provides — the elasticity, the ability to dramatically raise or dramatically shrink the amount of resources that are consumed.

You can only imagine if a company was in their own data centers, how hard that would have been to grow that quickly. The ability to dramatically grow or dramatically shrink your IT spend essentially is a unique feature of the cloud. These kinds of challenging times are exactly when you want to prepare yourself to be the innovators … to reinvigorate and reinvest and drive growth forward again.

We've seen so many customers who have prepared themselves, are using AWS, and then when a challenge hits, are actually able to accelerate because they've got competitors who are not as prepared, or there's a new opportunity that they spot. We see a lot of customers actually leaning into their cloud journeys during these uncertain economic times. Do you still push multi-year contracts, and when there's times like this, do customers have the ability to renegotiate?

Many are rapidly accelerating their journey to the cloud. Some customers are doing some belt-tightening. What we see a lot of is folks just being really focused on optimizing their resources, making sure that they're shutting down resources which they're not consuming. You do see some discretionary projects which are being not canceled, but pushed out.

Every customer is free to make that choice. But of course, many of our larger customers want to make longer-term commitments, want to have a deeper relationship with us, want the economics that come with that commitment.

We're signing more long-term commitments than ever these days. We provide incredible value for our customers, which is what they care about.

That kind of analysis would not be feasible, you wouldn't even be able to do that for most companies, on their own premises. So some of these workloads just become better, become very powerful cost-savings mechanisms, really only possible with advanced analytics that you can run in the cloud.

In other cases, just the fact that we have things like our Graviton processors and … run such large capabilities across multiple customers, our use of resources is so much more efficient than others. We are of significant enough scale that we, of course, have good purchasing economics of things like bandwidth and energy and so forth. So, in general, there's significant cost savings by running on AWS, and that's what our customers are focused on. The margins of our business are going to … fluctuate up and down quarter to quarter.

It will depend on what capital projects we've spent on that quarter. Obviously, energy prices are high at the moment, and so there are some quarters that are puts, other quarters there are takes. The important thing for our customers is the value we provide them compared to what they're used to. And those benefits have been dramatic for years, as evidenced by the customers' adoption of AWS and the fact that we're still growing at the rate we are given the size business that we are.

That adoption speaks louder than any other voice. Do you anticipate a higher percentage of customer workloads moving back on premises than you maybe would have three years ago? Absolutely not. We're a big enough business, if you asked me have you ever seen X, I could probably find one of anything, but the absolute dominant trend is customers dramatically accelerating their move to the cloud.

Moving internal enterprise IT workloads like SAP to the cloud, that's a big trend. Creating new analytics capabilities that many times didn't even exist before and running those in the cloud.

More startups than ever are building innovative new businesses in AWS. Our public-sector business continues to grow, serving both federal as well as state and local and educational institutions around the world. It really is still day one. The opportunity is still very much in front of us, very much in front of our customers, and they continue to see that opportunity and to move rapidly to the cloud.

In general, when we look across our worldwide customer base, we see time after time that the most innovation and the most efficient cost structure happens when customers choose one provider, when they're running predominantly on AWS. A lot of benefits of scale for our customers, including the expertise that they develop on learning one stack and really getting expert, rather than dividing up their expertise and having to go back to basics on the next parallel stack.

That being said, many customers are in a hybrid state, where they run IT in different environments. In some cases, that's by choice; in other cases, it's due to acquisitions, like buying companies and inherited technology.

We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS.

Some may have resources that run in other clouds. We want to make that entire hybrid environment as easy and as powerful for customers as possible, so we've actually invested and continue to invest very heavily in these hybrid capabilities. A lot of customers are using containerized workloads now, and one of the big container technologies is Kubernetes. We have a managed Kubernetes service, Elastic Kubernetes Service, and we have a … distribution of Kubernetes Amazon EKS Distro that customers can take and run on their own premises and even use to boot up resources in another public cloud and have all that be done in a consistent fashion and be able to observe and manage across all those environments.

So we're very committed to providing hybrid capabilities, including running on premises, including running in other clouds, and making the world as easy and as cost-efficient as possible for customers. Can you talk about why you brought Dilip Kumar, who was Amazon's vice president of physical retail and tech, into AWS as vice president applications and how that will play out? He's a longtime, tenured Amazonian with many, many different roles — important roles — in the company over a many-year period.

Dilip has come over to AWS to report directly to me, running an applications group. We do have more and more customers who want to interact with the cloud at a higher level — higher up the stack or more on the application layer. We talked about Connect, our contact center solution, and we've also built services specifically for the healthcare industry like a data lake for healthcare records called Amazon HealthLake.

We've built a lot of industrial services like IoT services for industrial settings, for example, to monitor industrial equipment to understand when it needs preventive maintenance. We have a lot of capabilities we're building that are either for … horizontal use cases like Amazon Connect or industry verticals like automotive, healthcare, financial services.

We see more and more demand for those, and Dilip has come in to really coalesce a lot of teams' capabilities, who will be focusing on those areas. You can expect to see us invest significantly in those areas and to come out with some really exciting innovations. Would that include going into CRM or ERP or other higher-level, run-your-business applications?

I don't think we have immediate plans in those particular areas, but as we've always said, we're going to be completely guided by our customers, and we'll go where our customers tell us it's most important to go next. It's always been our north star. Correction: This story was updated Nov.

Bennett Richardson bennettrich is the president of Protocol. Prior to joining Protocol in , Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company.

Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB.

Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University. Prior to joining Protocol in , he worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter. He has previously worked at MIT Technology Review, Gizmodo, and New Scientist, and has held lectureships at the University of Oxford and Imperial College London.

He also holds a doctorate in engineering from the University of Oxford. We launched Protocol in February to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication. As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent.

Source Code will be published and sent for the next few weeks, but it will also close down in December.

Below is list of command-line options recognized by the ImageMagick command-line tools. If you want a description of a particular option, click on the option name in the navigation bar above and you will go right to it. Unless otherwise noted, each option is recognized by the commands: convert and mogrify. A Gaussian operator of the given radius and standard deviation sigma is used. If sigma is not given it defaults to 1.

The sigma value is the important argument, and determines the actual amount of blurring that will take place. The radius is only used to determine the size of the array which holds the calculated Gaussian distribution. It should be an integer. If not given, or set to zero, IM will calculate the largest possible radius that will provide meaningful results for the Gaussian distribution.

See Image Geometry for complete details about the geometry argument. The -adaptive-resize option defaults to data-dependent triangulation. Use the -filter to choose a different resampling algorithm. Offsets, if present in the geometry string, are ignored, and the -gravity option has no effect.

This option is enabled by default. An attempt is made to save all images of an image sequence into the given output file. However, some formats, such as JPEG and PNG, do not support more than one image per file, and in that case ImageMagick is forced to write each image as a separate file. As such, if more than one image needs to be written, the filename given is modified by adding a -scene number before the suffix, in order to make distinct names for each image. As an example, the command. will create a sequence of 17 images the two given plus 15 more created by -morph , named: my00morph.

jpg, my01morph. jpg, my02morph. In summary, ImageMagick tries to write all images to one file, but will save to multiple files, if any of the following conditions exist Set the drawing transformation matrix for combined rotating and scaling. This option sets a transformation matrix, for use by subsequent -draw or -transform options.

The matrix entries are entered as comma-separated numeric values either in quotes or without spaces. Internally, the transformation matrix has 3x3 elements, but three of them are omitted from the input because they are constant.

The new transformed coordinates x' , y' of a pixel at position x , y in the original image are calculated using the following matrix equation. The size of the resulting image is that of the smallest rectangle that contains the transformed source image.

The parameters t x and t y subsequently shift the image pixels so that those that are moved out of the image area are cut off. The transformation matrix complies with the left-handed pixel coordinate system: positive x and y directions are rightward and downward, resp. If the translation coefficients t x and t y are omitted they default to 0,0. Therefore, four parameters suffice for rotation and scaling without translation. Scaling by the factors s x and s y in the x and y directions, respectively, is accomplished with the following.

See -transform , and the -distort method ' Affineprojection for more information. Translation by a displacement t x , t y is accomplished like so:. The cumulative effect of a sequence of -affine transformations can be accomplished by instead by a single -affine operation using the matrix equal to the product of the matrices of the individual transformations.

An attempt is made to detect near-singular transformation matrices. If the matrix determinant has a sufficiently small absolute value it is rejected. Used to set a flag on an image indicating whether or not to use existing alpha channel data, to create an alpha channel, or to perform other operations on the alpha channel. Choose the argument type from the list below. This is a convenience for annotating an image with text. For more precise control over text annotations, use -draw.

The values Xdegrees and Ydegrees control the shears applied to the text, while t x and t y are offsets that give the location of the text relative any -gravity setting and defaults to the upper left corner of the image.

Using -annotate degrees or -annotate degrees x degrees produces an unsheared rotation of the text. The direction of the rotation is positive, which means a clockwise rotation if degrees is positive.

This conforms to the usual mathematical convention once it is realized that the positive y —direction is conventionally considered to be downward for images. The new transformed coordinates x' , y' of a pixel at position x , y in the image are calculated using the following matrix equation. If t x and t y are omitted, they default to 0. This makes the bottom-left of the text becomes the upper-left corner of the image, which is probably undesirable.

Adding a -gravity option in this case leads to nice results. Text is any UTF-8 encoded character sequence. If text is of the form ' mytext. txt', the text is read from the file mytext. Text in a file is taken literally; no embedded formatting characters are recognized.

By default, objects e. text, lines, polygons, etc. are antialiased when drawn. This will then reduce the number of colors added to an image to just the colors being directly drawn. That is, no mixed colors are added when drawing such objects.

This option creates a single longer image, by joining all the current images in sequence top-to-bottom. If they are not of the same width, narrower images are padded with the current -background color setting, and their position relative to each other can be controlled by the current -gravity setting. For more flexible options, including the ability to add space between images, use -smush. Use this option to supply a password for decrypting a PDF that has been encrypted using Microsoft Crypto API MSC API.

The encrypting using the MSC API is not supported. For a different encryption method, see -encipher and -decipher.

This works well for real-life images with little or no extreme dark and light areas, but tend to fail for images with large amounts of bright sky or dark shadows. It also does not work well for diagrams or cartoon like images. It uses the -channel setting, including the ' sync ' flag for channel synchronization , to determine which color values is used and modified. As the default -channel setting is ' RGB,sync ', channels are modified together by the same gamma value, preserving colors.

This is a 'perfect' image normalization operator. It finds the exact minimum and maximum color values in the image and then applies a -level operator to stretch the values to the full range of values. On the other hand it is the right operator to use for color stretching gradient images being used to generate Color lookup tables, distortion maps, or other 'mathematically' defined images.

The operator is very similar to the -normalize , -contrast-stretch , and -linear-stretch operators, but without 'histogram binning' or 'clipping' problems that these operators may have. That is -auto-level is the perfect or ideal version these operators.

It uses the -channel setting, including the special ' sync ' flag for channel synchronization , to determine which color values are used and modified.

Adjusts an image so that its orientation is suitable for viewing i. top-left orientation. This operator reads and resets the EXIF image profile setting 'Orientation' and then performs the appropriate 90 degree rotation on the image to orient the image, for correct viewing.

This EXIF profile setting is usually set using a gravity sensor in digital camera, however photos taken directly downward or upward may not have an appropriate value. Also images that have been orientation 'corrected' without reseting this setting, may be 'corrected' again resulting in a incorrect result. If the EXIF profile was previously stripped, the -auto-orient operator will do nothing.

The computed threshold is returned as the auto-threshold:verbose image property. This backdrop covers the entire workstation screen and is useful for hiding other X window activity while viewing the image. The color of the backdrop is specified as the background color. The color is specified using the format described under the -fill option. The default background color if none is specified or found in the image is white.

Repeat the entire command for the given number of iterations and report the user-time and elapsed time. For instance, consider the following command and its output. Modify the benchmark with the -duration to run the benchmark for a fixed number of seconds and -concurrent to run the benchmark in parallel requires the OpenMP feature.

In this example, 5 iterations were completed at 2. This option shifts the output of -convolve so that positive and negative results are relative to the specified bias value. This is important for non-HDRI compilations of ImageMagick when dealing with convolutions that contain negative as well as positive values.

This is especially the case with convolutions involving high pass filters or edge detection. Without an output bias, the negative values are clipped at zero. See the discussion on HDRI implementations of ImageMagick on the page High Dynamic-Range Images.

For more about HDRI go the ImageMagick Usage pages or this Wikipedia entry. A non-linear, edge-preserving, and noise-reducing smoothing filter for images. It replaces the intensity of each pixel with a weighted average of intensity values from nearby pixels. This weight is based on a Gaussian distribution.

It transforms an image from the normal spatial domain to the frequency domain. To determine the cooresponding size in pixels at 72DPI, use this command for example:. Unfortunately, while there are many studies presenting their own distinct way to build features and applying them to some problem in materials science, fewer studies 96 , , actually present quantitative comparisons between descriptors. This operator is especially suited to replacing a grayscale image with a specific color gradient from the CLUT image. The merged translations are run through tools::checkPofile to check that C-style formats are used correctly: if not the mismatches are reported and the broken translations are not installed. In any case, name conflicts of headers and directories under package include directories should be avoided, both between packages and between a package and system and third-party software. However, if the filename extension matches a supported format, the extension is replaced with the image format type specified with -format.

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