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Anil K Seth

Publications and source records attributed to Anil K Seth.

10 recordsLinked to original sources
PubMed2006

Theories and measures of consciousness: an extended framework.

A recent theoretical emphasis on complex interactions within neural systems underlying consciousness has been accompanied by proposals for the quantitative characterization of these interactions. In this article, we distinguish key aspects of consciousness that are amenable to quantitative measurement from those that are not. We carry out a formal analysis of the strengths and limitations of three quantitative measures of dynamical complexity in the neural systems underlying consciousness: neural complexity, information integration, and causal density. We find that no single measure fully captures the multidimensional complexity of these systems, and all of these measures have practical limitations. Our analysis suggests guidelines for the specification of alternative measures which, in combination, may improve the quantitative characterization of conscious neural systems. Given that some aspects of consciousness are likely to resist quantification altogether, we conclude that a satisfactory theory is likely to be one that combines both qualitative and quantitative elements.

Animals↗
PubMed2006

Single-trial discrimination of truthful from deceptive responses during a game of financial risk using alpha-band MEG signals.

We studied whether magnetoencephalography (MEG) could detect deceptive responses on a single-subject, trial-by-trial basis. To elicit spontaneous, ecologically valid deception, we developed a paradigm in which subjects in a simulated customs setting were presented with a series of pictures of items which might be in their baggage, and for each item, they decided whether to "declare" (tell the truth) or "smuggle" (lie). Telling the truth involved a small but certain monetary penalty, whereas lying involved both greater monetary risk and greater potential reward. Most subjects showed decreased signal power in the 8-12 Hz (alpha) range during deceptive responses as compared to truthful responses. In a cross-validation analysis, we were able to use alpha power to classify truthful and deceptive responses on a trial-by-trial basis, with significantly greater predictive accuracy than that achieved using simultaneously recorded skin conductance signals. Average predictive accuracy for spontaneous deception was greater than 78%, and for some subjects, predictive accuracy exceeded 90%. Our results raise the possibility that alpha power modulation during deception may reflect risk management and/or cognitive control.

Adult↗
PubMed2005

Criteria for consciousness in humans and other mammals.

The standard behavioral index for human consciousness is the ability to report events with accuracy. While this method is routinely used for scientific and medical applications in humans, it is not easy to generalize to other species. Brain evidence may lend itself more easily to comparative testing. Human consciousness involves widespread, relatively fast low-amplitude interactions in the thalamocortical core of the brain, driven by current tasks and conditions. These features have also been found in other mammals, which suggests that consciousness is a major biological adaptation in mammals. We suggest more than a dozen additional properties of human consciousness that may be used to test comparative predictions. Such homologies are necessarily more remote in non-mammals, which do not share the thalamocortical complex. However, as we learn more we may be able to make "deeper" predictions that apply to some birds, reptiles, large-brained invertebrates, and perhaps other species.

Adaptation, Physiological↗
PubMed2005

Neural Darwinism and consciousness.

Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

Biological Evolution↗
PubMed2005

Identifying hallmarks of consciousness in non-mammalian species.

Most early studies of consciousness have focused on human subjects. This is understandable, given that humans are capable of reporting accurately the events they experience through language or by way of other kinds of voluntary response. As researchers turn their attention to other animals, "accurate report" methodologies become increasingly difficult to apply. Alternative strategies for amassing evidence for consciousness in non-human species include searching for evolutionary homologies in anatomical substrates and measurement of physiological correlates of conscious states. In addition, creative means must be developed for eliciting behaviors consistent with consciousness. In this paper, we explore whether necessary conditions for consciousness can be established for species as disparate as birds and cephalopods. We conclude that a strong case can be made for avian species and that the case for cephalopods remains open. Nonetheless, a consistent effort should yield new means for interpreting animal behavior.

Animals↗
PubMed2005

Causal connectivity of evolved neural networks during behavior.

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics.

Aging↗
PubMed2005

Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions.

We describe Darwin X, a physical device that interacts with a real environment, whose behavior is guided by a simulated nervous system incorporating aspects of the detailed anatomy and physiology of the hippocampus and its surrounding regions. This brain-based device integrates cues from its environment and solves a spatial memory task. The responses of simulated neuronal units in the hippocampal areas during its exploratory behavior are comparable to place cells in the rodent hippocampus and emerged by associating sensory cues during exploration. To identify different functional hippocampal pathways and their influence on behavior, we employed a time series analysis that distinguishes causal interactions within and between simulated hippocampal and neocortical regions while the device is engaged in a spatial memory task. Our analysis identified different functional pathways within the neural simulation and prompts novel predictions about the influence of the perforant path, the trisynaptic loop and hippocampal-cortical interactions on place cell activity and behavior during navigation. Moreover, this causal time series analysis may be useful in analyzing networks in general.

Animals↗
PubMed2004

Visual binding through reentrant connectivity and dynamic synchronization in a brain-based device.

Effective visual object recognition requires mechanisms to bind object features (e.g. color, shape and motion) while distinguishing distinct objects. Synchronously active neuronal circuits among reentrantly connected cortical areas may provide a basis for visual binding. To assess the potential of this mechanism, we have constructed a mobile brain-based device, Darwin VIII, which is guided by simulated analogues of cortical and sub-cortical areas required for visual processing, decision-making, reward and motor responses. These simulated areas are reentrantly connected and each area contains neuronal units representing both the mean activity level and the relative timing of the activity of groups of neurons. Darwin VIII learns to discriminate among multiple objects with shared visual features and associates 'target' objects with innately preferred auditory cues. We observed the co-activation of globally distributed neuronal circuits that corresponded to distinct objects in Darwin VIII's visual field. These circuits, which are constrained by a reentrant neuroanatomy and modulated by behavior and synaptic plasticity, are necessary for successful discrimination. By situating Darwin VIII in a rich real-world environment involving continual changes in the size and location of visual stimuli due to self-generated movement, and by recording its behavioral and neuronal responses in detail, we were able to show that reentrant connectivity and dynamic synchronization provide an effective mechanism for binding the features of visual objects.

Acoustic Stimulation↗
PubMed2003

The power of human brain magnetoencephalographic signals can be modulated up or down by changes in an attentive visual task.

This paper presents evidence indicating that the signals generated by neural responses to visual input can be either enhanced by increasing or suppressed by decreasing the area of the stimuli to which attention is directed. We used magnetoencephalography (MEG) to measure the frequency-tagged steady-state visual evoked responses of 11 subjects presented with two superimposed images flickering at different frequencies. Each image consisted of seven parallel bars of equal length; in any image, all bars were either red or green and either horizontal or vertical. At randomly chosen times during the experiments, any one of the three middle bars in either image transiently increased or decreased in width. Subjects were asked to attend to one image and ignore the other and to respond to changes in bar width in the attended image with a key press. In one condition, subject responses were required for changes in any of the three central bars of the attended image. We found that visual steady-state evoked responses to the attended image were enhanced relative to those evoked by the unattended image in this condition. In a second condition, subject responses were required for changes only in the middle bar. In this condition, the responses to the attended image were suppressed relative to those of the unattended image. These results may reflect relative differences in the synchronization and desynchronization of responding neuronal populations.

Adult↗