The integrated information theory of consciousness: Unmasked and identified.

In our response to a truly diverse set of commentaries, we first summarize the principal topical themes around which they cluster, then address two "outlier" positions (the problem of consciousness has been solved vs. is intractable). Next, we address ways in which commentaries by non-integrated information theory (IIT) authors engage with the specifics of our IIT critique, turning finally to the four commentaries by IIT authors.

Lesion network mapping demonstrates that mind-wandering is associated with the default mode network.

Functional neuroimaging research has consistently associated brain structures within the default mode network (DMN) and frontoparietal network (FPN) with mind-wandering. Targeted lesion research has documented impairments in mind-wandering after damage to the medial prefrontal cortex (mPFC) and hippocampal regions associated with the DMN. However, no lesion studies to date have applied lesion network mapping to identify common networks associated with deficits in mind-wandering. In lesion network mapping, resting-state functional connectivity data from healthy participants are used to infer which brain regions are functionally connected to each lesion location from a sample with brain injury. In the current study, we conducted a lesion network mapping analysis to test the hypothesis that lesions affecting the DMN and FPN would be associated with diminished mind-wandering. We assessed mind-wandering frequency on the Imaginal Processes Inventory (IPI) in participants with brain injury (n = 29) and healthy comparison participants without brain injury (n = 19). Lesion network mapping analyses showed the strongest association of reduced mind-wandering with the left inferior parietal lobule within the DMN. In addition, traditional lesion symptom mapping results revealed that reduced mind-wandering was associated with lesions of the dorsal, ventral, and anterior sectors of mPFC, parietal lobule, and inferior frontal gyrus in the DMN (p < 0.05 uncorrected). These findings provide novel lesion support for the role of the DMN in mind-wandering and contribute to a burgeoning literature on the neural correlates of spontaneous cognition.

The integrated information theory of consciousness: A case of mistaken identity.

Giulio Tononi's integrated information theory (IIT) proposes explaining consciousness by directly identifying it with integrated information. We examine the construct validity of IIT's measure of consciousness, phi (Φ), by analyzing its formal properties, its relation to key aspects of consciousness, and its co-variation with relevant empirical circumstances. Our analysis shows that IIT's identification of consciousness with the causal efficacy with which differentiated networks accomplish global information transfer (which is what Φ in fact measures) is mistaken. This misidentification has the consequence of requiring the attribution of consciousness to a range of natural systems and artifacts that include, but are not limited to, large-scale electrical power grids, gene-regulation networks, some electronic circuit boards, and social networks. Instead of treating this consequence of the theory as a disconfirmation, IIT embraces it. By regarding these systems as bearers of consciousness ex hypothesi, IIT is led toward the orbit of panpsychist ideation. This departure from science as we know it can be avoided by recognizing the functional misattribution at the heart of IIT's identity claim. We show, for example, what function is actually performed, at least in the human case, by the cortical combination of differentiation with integration that IIT identifies with consciousness. Finally, we examine what lessons may be drawn from IIT's failure to provide a credible account of consciousness for progress in the very active field of research concerned with exploring the phenomenon from formal and neural points of view.

The Moon illusion explained by the projective consciousness model.

Models of consciousness should account for the phenomenology of subjective experience, including perceptual illusions. The Moon Illusion is a paradigmatic example that has yet to be accounted for. The Moon often appears larger near the perceptual horizon and smaller high in the sky, though the visual angle subtended is invariant. We show how this illusion can result from the optimization of a 3D projective geometrical frame through free energy minimization, following the principles of the Projective Consciousness Model. The model accounts for all documented modulations of the illusion without anomalies (e.g., the "size-distance paradox"), surpasses other theories in explanatory power, makes sense of inter- and intra-subjective variability vis-à-vis the illusion, and yields new quantitative and qualitative predictions. Empirical data from a virtual reality experiment support the predictions of the model. We also discuss how the model suggests explanations for other relevant illusions, concerning objects both at far and nearer distances, including the sky dome illusion, illusions of perceived size observed in the context of crowding experiments, and the Ames Room illusion.

Probabilistic functional tractography of the human cortex revisited.

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.

Stimulation of subgenual cingulate area decreases limbic top-down effect on ventral visual stream: A DBS-EEG pilot study.

Deep brain stimulation (DBS) of the subgenual cingulate gyrus (area CG25) is beneficial in treatment resistant depression. Though the mechanisms of action of Cg25 DBS remain largely unknown, it is commonly believed that Cg25 DBS modulates limbic activity of large networks to achieve thymic regulation of patients. To investigate how emotional attention is influenced by Cg25 DBS, we assessed behavioral and electroencephalographic (EEG) responses to an emotional Stroop task in 5 patients during ON and OFF stimulation conditions. Using EEG source localization, we found that the main effect of DBS was a reduction of neuronal responses in limbic regions (temporal pole, medial prefrontal and posterior cingulate cortices) and in ventral visual areas involved in face processing. In the dynamic causal modeling (DCM) approach, the changes of the evoked response amplitudes are assumed to be due to changes of long range connectivity induced by Cg25 DBS. Here, using a simplified neural mass model that did not take explicitly into account the cytoarchitecture of the considered brain regions, we showed that the remote action of Cg25 DBS could be explained by a reduced top-down effective connectivity of the amygdalo-temporo-polar complex. Overall, our results thus indicate that Cg25 DBS during the emotional Stroop task causes a decrease of top-down limbic influence on the ventral visual stream itself, rather than a modulation of prefrontal cognitive processes only. Tuning down limbic excitability in relation to sensory processing might be one of the biological mechanisms through which Cg25 DBS produces positive clinical outcome in the treatment of resistant depression.

A mathematical model of embodied consciousness.

We introduce a mathematical model of embodied consciousness, the Projective Consciousness Model (PCM), which is based on the hypothesis that the spatial field of consciousness (FoC) is structured by a projective geometry and under the control of a process of active inference. The FoC in the PCM combines multisensory evidence with prior beliefs in memory and frames them by selecting points of view and perspectives according to preferences. The choice of projective frames governs how expectations are transformed by consciousness. Violations of expectation are encoded as free energy. Free energy minimization drives perspective taking, and controls the switch between perception, imagination and action. In the PCM, consciousness functions as an algorithm for the maximization of resilience, using projective perspective taking and imagination in order to escape local minima of free energy. The PCM can account for a variety of psychological phenomena: the characteristic spatial phenomenology of subjective experience, the distinctions and integral relationships between perception, imagination and action, the role of affective processes in intentionality, but also perceptual phenomena such as the dynamics of bistable figures and body swap illusions in virtual reality. It relates phenomenology to function, showing the computational advantages of consciousness. It suggests that changes of brain states from unconscious to conscious reflect the action of projective transformations and suggests specific neurophenomenological hypotheses about the brain, guidelines for designing artificial systems, and formal principles for psychology.

Functional Connectivity's Degenerate View of Brain Computation.

Brain computation relies on effective interactions between ensembles of neurons. In neuroimaging, measures of functional connectivity (FC) aim at statistically quantifying such interactions, often to study normal or pathological cognition. Their capacity to reflect a meaningful variety of patterns as expected from neural computation in relation to cognitive processes remains debated. The relative weights of time-varying local neurophysiological dynamics versus static structural connectivity (SC) in the generation of FC as measured remains unsettled. Empirical evidence features mixed results: from little to significant FC variability and correlation with cognitive functions, within and between participants. We used a unified approach combining multivariate analysis, bootstrap and computational modeling to characterize the potential variety of patterns of FC and SC both qualitatively and quantitatively. Empirical data and simulations from generative models with different dynamical behaviors demonstrated, largely irrespective of FC metrics, that a linear subspace with dimension one or two could explain much of the variability across patterns of FC. On the contrary, the variability across BOLD time-courses could not be reduced to such a small subspace. FC appeared to strongly reflect SC and to be partly governed by a Gaussian process. The main differences between simulated and empirical data related to limitations of DWI-based SC estimation (and SC itself could then be estimated from FC). Above and beyond the limited dynamical range of the BOLD signal itself, measures of FC may offer a degenerate representation of brain interactions, with limited access to the underlying complexity. They feature an invariant common core, reflecting the channel capacity of the network as conditioned by SC, with a limited, though perhaps meaningful residual variability.

Predicting functional connectivity from structural connectivity via computational models using MRI: an extensive comparison study.

The relationship between structural connectivity (SC) and functional connectivity (FC) in the human brain can be studied using magnetic resonance imaging (MRI). However many of the underlying physiological mechanisms and parameters cannot be directly observed with MRI. This limitation has motivated the recent use of various computational models meant to bridge the gap. However their absolute and relative explanatory power and the properties that actually drive that power remain insufficiently characterized. We performed an extensive comparison of seven mainstream computational models predicting FC from SC. We investigated the extent to which simulated FC could predict empirical FC. We also applied graph theory to the entire set of simulated and empirical FCs in order to further characterize the relationships between the models and the MRI data. The comparison was performed at three different spatial scales. We found that (i) there were significant effects of scale and model on predictive power; (ii) among all models, the simplest model, the simultaneous autoregressive (SAR) model, was found to consistently perform better than the other models; (iii) the SAR also appeared more 'central' from a graph theory perspective; and (iv) empirical FC only appeared weakly correlated with simulated FCs, and was featured as 'peripheral' in the graph analysis. We conclude that the substantial differences existing between these computational models have little impact on their predictive power for FC and that their capacity to predict FC from SC appears to be both moderate and essentially underlined by a simple core linear process embodied by the SAR model.

Relating structure and function in the human brain: relative contributions of anatomy, stationary dynamics, and non-stationarities.

Investigating the relationship between brain structure and function is a central endeavor for neuroscience research. Yet, the mechanisms shaping this relationship largely remain to be elucidated and are highly debated. In particular, the existence and relative contributions of anatomical constraints and dynamical physiological mechanisms of different types remain to be established. We addressed this issue by systematically comparing functional connectivity (FC) from resting-state functional magnetic resonance imaging data with simulations from increasingly complex computational models, and by manipulating anatomical connectivity obtained from fiber tractography based on diffusion-weighted imaging. We hypothesized that FC reflects the interplay of at least three types of components: (i) a backbone of anatomical connectivity, (ii) a stationary dynamical regime directly driven by the underlying anatomy, and (iii) other stationary and non-stationary dynamics not directly related to the anatomy. We showed that anatomical connectivity alone accounts for up to 15% of FC variance; that there is a stationary regime accounting for up to an additional 20% of variance and that this regime can be associated to a stationary FC; that a simple stationary model of FC better explains FC than more complex models; and that there is a large remaining variance (around 65%), which must contain the non-stationarities of FC evidenced in the literature. We also show that homotopic connections across cerebral hemispheres, which are typically improperly estimated, play a strong role in shaping all aspects of FC, notably indirect connections and the topographic organization of brain networks.

Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex.

A considerable body of previous research on the prefrontal cortex (PFC) has helped characterize the regional specificity of various cognitive functions, such as cognitive control and decision making. Here we provide definitive findings on this topic, using a neuropsychological approach that takes advantage of a unique dataset accrued over several decades. We applied voxel-based lesion-symptom mapping in 344 individuals with focal lesions (165 involving the PFC) who had been tested on a comprehensive battery of neuropsychological tasks. Two distinct functional-anatomical networks were revealed within the PFC: one associated with cognitive control (response inhibition, conflict monitoring, and switching), which included the dorsolateral prefrontal cortex and anterior cingulate cortex and a second associated with value-based decision-making, which included the orbitofrontal, ventromedial, and frontopolar cortex. Furthermore, cognitive control tasks shared a common performance factor related to set shifting that was linked to the rostral anterior cingulate cortex. By contrast, regions in the ventral PFC were required for decision-making. These findings provide detailed causal evidence for a remarkable functional-anatomical specificity in the human PFC.

Virtual reality vs. tablet for procedural comfort using an identical game in children undergoing venipuncture: a randomized clinical trial.

Introduction: Recent research has explored the effectiveness of interactive virtual experiences in managing pain and anxiety in children during routine medical procedures, compared to conventional care methods. However, the influence of the specific technology used as an interface, 3-dimensions (D) immersive virtual reality (VR) vs. 2D touch screens, during pediatric venipuncture, remains unexamined. This study aimed to determine if immersive VR is more effective than a tablet in reducing pain and anxiety during short procedures. Methods: An interactive game was designed by clinicians and psychologists, expert in pain theory, hypnosis, and procedural pain and anxiety relief, and was tailored for both VR and tablet use. Fifty patients were randomly assigned to either the Tablet or VR group. The primary outcome measures were pain and anxiety levels during the procedure. Secondary outcome measures included the need for physical restraint, duration of the procedure, enjoyment levels, and satisfaction ratings from both parents and nurses. Results: Participants, in both groups, had low levels of pain and anxiety. Physical restraint was infrequently used, procedures were brief, and high satisfaction levels were reported by patients, parents, and nurses. Discussion: This study suggests that the type of technology used as a support for the game has a minimal effect on the child's experience, with both groups reporting low pain and anxiety levels, minimal physical restraint, and high enjoyment. Despite immersive VR's technological advancements, this study underscores the value of traditional tablets with well-designed interactive games in enhancing children's wellbeing during medical procedures. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT05065307].

Anterior prefrontal cortex contributes to action selection through tracking of recent reward trends.

The functions of prefrontal cortex remain enigmatic, especially for its anterior sectors, putatively ranging from planning to self-initiated behavior, social cognition, task switching, and memory. A predominant current theory regarding the most anterior sector, the frontopolar cortex (FPC), is that it is involved in exploring alternative courses of action, but the detailed causal mechanisms remain unknown. Here we investigated this issue using the lesion method, together with a novel model-based analysis. Eight patients with anterior prefrontal brain lesions including the FPC performed a four-armed bandit task known from neuroimaging studies to activate the FPC. Model-based analyses of learning demonstrated a selective deficit in the ability to extrapolate the most recent trend, despite an intact general ability to learn from past rewards. Whereas both brain-damaged and healthy controls used comparisons between the two most recent choice outcomes to infer trends that influenced their decision about the next choice, the group with anterior prefrontal lesions showed a complete absence of this component and instead based their choice entirely on the cumulative reward history. Given that the FPC is thought to be the most evolutionarily recent expansion of primate prefrontal cortex, we suggest that its function may reflect uniquely human adaptations to select and update models of reward contingency in dynamic environments.

The Projective Consciousness Model: Projective Geometry at the Core of Consciousness and the Integration of Perception, Imagination, Motivation, Emotion, Social Cognition and Action.

Consciousness has been described as acting as a global workspace that integrates perception, imagination, emotion and action programming for adaptive decision making. The mechanisms of this workspace and their relationships to the phenomenology of consciousness need to be further specified. Much research in this area has focused on the neural correlates of consciousness, but, arguably, computational modeling can better be used toward this aim. According to the Projective Consciousness Model (PCM), consciousness is structured as a viewpoint-organized, internal space, relying on 3D projective geometry and governed by the action of the Projective Group as part of a process of active inference. The geometry induces a group-structured subjective perspective on an encoded world model, enabling adaptive perspective taking in agents. Here, we review and discuss the PCM. We emphasize the role of projective mechanisms in perception and the appraisal of affective and epistemic values as tied to the motivation of action, under an optimization process of Free Energy minimization, or more generally stochastic optimal control. We discuss how these mechanisms enable us to model and simulate group-structured drives in the context of social cognition and to understand the mechanisms underpinning empathy, emotion expression and regulation, and approach-avoidance behaviors. We review previous results, drawing on applications in robotics and virtual humans. We briefly discuss future axes of research relating to applications of the model to simulation- and model-based behavioral science, geometrically structured artificial neural networks, the relevance of the approach for explainable AI and human-machine interactions, and the study of the neural correlates of consciousness.

Medial PFC damage abolishes the self-reference effect.

Functional neuroimaging studies suggest that the medial PFC (mPFC) is a key component of a large-scale neural system supporting a variety of self-related processes. However, it remains unknown whether the mPFC is critical for such processes. In this study, we used a human lesion approach to examine this question. We administered a standard trait judgment paradigm [Kelley, W. M., Macrae, C. N., Wyland, C. L., Caglar, S., Inati, S., & Heatherton, T. F. Finding the self? An event-related fMRI study. Journal of Cognitive Neuroscience, 14, 785-794, 2002] to patients with focal brain damage to the mPFC. The self-reference effect (SRE), a memory advantage conferred by self-related processing, served as a measure of intact self-processing ability. We found that damage to the mPFC abolished the SRE. The results demonstrate that the mPFC is necessary for the SRE and suggest that this structure is important for self-referential processing and the neural representation of self.

Alterations in brain structure and functional connectivity in prescription opioid-dependent patients.

A dramatic increase in the use and dependence of prescription opioids has occurred within the last 10 years. The consequences of long-term prescription opioid use and dependence on the brain are largely unknown, and any speculation is inferred from heroin and methadone studies. Thus, no data have directly demonstrated the effects of prescription opioid use on brain structure and function in humans. To pursue this issue, we used structural magnetic resonance imaging, diffusion tensor imaging and resting-state functional magnetic resonance imaging in a highly enriched group of prescription opioid-dependent patients [(n=10); from a larger study on prescription opioid dependent patients (n=133)] and matched healthy individuals (n=10) to characterize possible brain alterations that may be caused by long-term prescription opioid use. Criteria for patient selection included: (i) no dependence on alcohol or other drugs; (ii) no comorbid psychiatric or neurological disease; and (iii) no medical conditions, including pain. In comparison to control subjects, individuals with opioid dependence displayed bilateral volumetric loss in the amygdala. Prescription opioid-dependent subjects had significantly decreased anisotropy in axonal pathways specific to the amygdala (i.e. stria terminalis, ventral amygdalofugal pathway and uncinate fasciculus) as well as the internal and external capsules. In the patient group, significant decreases in functional connectivity were observed for seed regions that included the anterior insula, nucleus accumbens and amygdala subdivisions. Correlation analyses revealed that longer duration of prescription opioid exposure was associated with greater changes in functional connectivity. Finally, changes in amygdala functional connectivity were observed to have a significant dependence on amygdala volume and white matter anisotropy of efferent and afferent pathways of the amygdala. These findings suggest that prescription opioid dependence is associated with structural and functional changes in brain regions implicated in the regulation of affect and impulse control, as well as in reward and motivational functions. These results may have important clinical implications for uncovering the effects of long-term prescription opioid use on brain structure and function.

Damage to association fiber tracts impairs recognition of the facial expression of emotion.

An array of cortical and subcortical structures have been implicated in the recognition of emotion from facial expressions. It remains unknown how these regions communicate as parts of a system to achieve recognition, but white matter tracts are likely critical to this process. We hypothesized that (1) damage to white matter tracts would be associated with recognition impairment and (2) the degree of disconnection of association fiber tracts [inferior longitudinal fasciculus (ILF) and/or inferior fronto-occipital fasciculus (IFOF)] connecting the visual cortex with emotion-related regions would negatively correlate with recognition performance. One hundred three patients with focal, stable brain lesions mapped onto a reference brain were tested on their recognition of six basic emotional facial expressions. Association fiber tracts from a probabilistic atlas were coregistered to the reference brain. Parameters estimating disconnection were entered in a general linear model to predict emotion recognition impairments, accounting for lesion size and cortical damage. Damage associated with the right IFOF significantly predicted an overall facial emotion recognition impairment and specific impairments for sadness, anger, and fear. One subject had a pure white matter lesion in the location of the right IFOF and ILF. He presented specific, unequivocal emotion recognition impairments. Additional analysis suggested that impairment in fear recognition can result from damage to the IFOF and not the amygdala. Our findings demonstrate the key role of white matter association tracts in the recognition of the facial expression of emotion and identify specific tracts that may be most critical.

The practice of meditation is not associated with improved interoceptive awareness of the heartbeat.

Meditation is commonly assumed to be associated with enhanced interoceptive accuracy. We previously found that experienced meditators did not exhibit a greater ability than nonmeditators to detect heartbeat sensations at rest, despite the meditators' reported subjective ratings of higher accuracy and lower difficulty. Here, attempting to overcome previous methodological limitations, we assessed interoceptive awareness of heartbeat and breathing sensations across physiological arousal levels using infusions of isoproterenol, a beta-adrenergic agonist similar to adrenaline. We hypothesized that meditators would display greater interoceptive awareness than nonmeditators, as evidenced by higher interoceptive detection rates, increased interoceptive accuracy, and differences in localization of heartbeat sensations. We studied 15 meditators and 15 nonmeditators, individually matched on age, gender, and body mass index, using randomized, double-blinded, and placebo-controlled bolus infusions of isoproterenol. Participants reported their experience of heartbeat and breathing sensations using a dial during infusions and the location of heartbeat sensations on a two-dimensional manikin afterward. There was no evidence of higher detection rates or increased accuracy across any dose, although meditators showed a tendency to report cardiorespiratory sensation changes sooner at higher doses. Relative to nonmeditators, meditators exhibited prominent geographical differences in heartbeat localization, disproportionally reporting sensations throughout central regions of the chest, abdomen, neck, back, and head. To further assess indications of potential differences in cardiac interoceptive accuracy between meditators and nonmeditators, we conducted a meta-analysis including 724 participants and found little evidence for such differences. We conclude that the practice of meditation is not associated with improved cardiac interoceptive awareness.

Rapid interactions between the ventral visual stream and emotion-related structures rely on a two-pathway architecture.

Visual attention can be driven by the affective significance of visual stimuli before full-fledged processing of the stimuli. Two kinds of models have been proposed to explain this phenomenon: models involving sequential processing along the ventral visual stream, with secondary feedback from emotion-related structures ("two-stage models"); and models including additional short-cut pathways directly reaching the emotion-related structures ("two-pathway models"). We tested which type of model would best predict real magnetoencephalographic responses in subjects presented with arousing visual stimuli, using realistic models of large-scale cerebral architecture and neural biophysics. The results strongly support a "two-pathway" hypothesis. Both standard models including the retinotectal pathway and nonstandard models including cortical-cortical long-range fasciculi appear plausible.

Does the Clock Drawing Test have focal neuroanatomical correlates?

The Clock Drawing Test (CDT) is widely used in clinical neuropsychological practice. The CDT has been used traditionally as a "parietal lobe" test (e.g., Kaplan, 1988), but most empirical work has focused on its sensitivity and specificity for detecting and differentiating subtypes of dementia. There are surprisingly few studies of its neuroanatomical correlates. The authors investigated the neuroanatomical correlates of the CDT, using 133 patients whose lesions provided effective coverage of most of both hemispheric convexities and underlying white matter. On the CDT, 30 subjects were impaired and 87 were unimpaired (16 were "borderline"). Impairments on the CDT were associated with damage to right parietal cortices (supramarginal gyrus) and left inferior frontal-parietal opercular cortices. Visuospatial errors were predominant in patients with right hemisphere damage, whereas time setting errors were predominant in patients with left hemisphere lesions. These findings provide new empirical evidence regarding the neuroanatomical correlates of the CDT, and together with previous work, support the use of this quick and easily administered test not only as a screening measure but also as a good index of focal brain dysfunction.