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Hartwigsen, G.

Publications and source records attributed to Hartwigsen, G..

At least 19 recordsLinked to original sources

Executive and language systems competitively shape predictive processing during reading

When we read, our brains constantly generate predictions about upcoming words, which is thought to make comprehension faster and more efficient. Yet it remains unclear whether this predictive mechanism relies on the same domain-general executive resources the brain uses for other demanding cognitive tasks, or operates largely independently within the language system. Here we tested this question using transcranial magnetic stimulation (TMS) in twenty-five healthy adults, who performed self-paced naturalistic reading, an n-back task, and a dual task of concurrent reading and n-back, allowing us to place competing demands on cognitive resources. In three sessions, we stimulated the left angular gyrus alone, the angular gyrus together with dorsolateral prefrontal cortex, a hub of executive control, or delivered sham stimulation, and used computational modeling of decision-making to isolate how each brain state altered the underlying cognitive processes. Combined stimulation of the angular gyrus and prefrontal cortex selectively weakened the reading-time costs of unexpected words, but only when reading competed with the working-memory task, revealing that linguistic prediction draws on executive resources specifically under cognitive load. Computational models showed that the relationship was bidirectional: Unpredictable words also disrupted concurrent working-memory decisions, slowing the accumulation of evidence and increasing response caution. Together, these findings show that predictive language processing is not a fixed, encapsulated function but is dynamically coupled to executive control when cognitive demands compete. Our results provide evidence that prediction during language comprehension is embedded within a broader, demand-sensitive cognitive architecture that flexibly coordinates linguistic and executive resources.

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Changes in Neural Dynamics of Brain Activity and Connectivity Independently Predict Post-Stroke Aphasia Recovery

Post-stroke language recovery involves reorganization of left-hemisphere language and bilateral domain-general multiple-demand networks. Neuroimaging predictors of recovery are widely used, yet, they are often grouped into broad predictor families, limiting clinical translation and the identification of specific therapeutic targets. Here, we assess brain region-specific neural predictors of recovery using task-related activity and connectivity within a multivariate, cross-validated predictive framework. Forty-seven patients with aphasia were examined longitudinally in the acute, subacute, and chronic phases after ischemic stroke using a sentence comprehension paradigm during functional neuroimaging, with regions of interest spanning language and multiple-demand networks. Confound-controlled multivariate regularized regression with feature ablation tested whether predictor families explained language recovery beyond lesion, age, and aphasia severity, and identified the most relevant region-specific predictors. Early recovery was independently predicted by acute and subacute activity and connectivity, whereas later improvement was predicted by activity alone. Subacute connectivity from multiple-demand to language regions predicted early recovery, while acute multiple-demand network activity predicted long-term outcomes. Later subacute-to-chronic recovery was instead predicted by subacute and chronic activity in bilateral inferior frontal regions. These findings identify phase-specific functional biomarkers of aphasia recovery beyond traditional clinical measures, highlighting multiple-demand and inferior frontal regions as candidate targets for phase-adapted neurostimulation approaches.

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Cortical Stimulation Strength and sgACC Connectivity Shape Neuro-Cardiac Responses to Prefrontal TMS

Autonomic dysregulation is a core feature of major depressive disorder and a promising physiological readout for early signs of clinical effectiveness of therapeutic TMS targeting prefrontal regions. Yet the stimulation dose and network properties required to optimally engage autonomic circuits remain elusive. Here, we applied a cortex- and circuit-centered dosing framework combining resting-state fMRI, simulations of the TMS-induced electric field, and electrocardiography acquired during repetitive TMS of six left dorsolateral prefrontal cortex (DLPFC) targets in healthy adults. Heart-brain coupling (HBC), defined as spectral power in the cardiac response locked to the TMS onset frequency, was modeled as a function of either conventional motor-threshold-based dose or cortical electric-field strength, with and without DLPFC connectivity to the subgenual anterior cingulate cortex (sgACC). Across linear and nonlinear models, cortical electric-field dose explained substantially more variance in HBC, indicating that prefrontal TMS dosing is best assessed at the cortical level. Incorporating sgACC connectivity further improved model fit and revealed site-specific electric-field-by-connectivity interactions, with the strongest and most reliable HBC modulation at DLPFC regions anticorrelated with sgACC. Voxel-wise TMS mapping identified individualized cortical hotspots spatially overlapping with sgACC-anticorrelated tissue. Notably, whereas negative connectivity showed the most robust and monotonic effects, nonlinear dose-response analyses suggested a confined stimulation range over which positively connected sites also exhibited HBC modulation. Together, these findings position HBC as a network-sensitive physiological readout of DLPFC-sgACC-vagal engagement and offer a principled answer to where and how much to stimulate, supporting an electric-field- and connectivity-informed dosing framework for refining prefrontal TMS in depression-related autonomic dysregulation.

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Beyond dual hubs: Task and aging shape taxonomic and thematic semantic relationships in the human brain

Semantic knowledge about concepts and their relationships is central to human cognition. Taxonomic relationships link concepts belonging to the same category (e.g. dog and bear), while thematic relationships connect concepts co-occurring in the same events (e.g. dog and leash). The dual-hub theory proposes that taxonomic relations preferentially engage the anterior temporal lobe (ATL), whereas thematic relations preferentially involve the temporo-parietal cortex (TPC). However, it remains unclear whether taxonomic and thematic representations depend on the concurrent task and how they change with aging. The present fMRI study addressed these gaps by jointly investigating the effects of semantic relationship, task, and age on semantic processing. 41 young and 34 older adults performed taxonomic and thematic judgments on picture pairs that were taxonomically related, thematically related, or unrelated. Our results do not support the dual-hub theory: Both TPC and ATL preferentially responded to thematic over taxonomic relationships. Moreover, their activity was task-dependent. Semantic control regions flexibly responded to task-relevant semantic relations, while inhibiting task-irrelevant relations. Finally, aging was associated with a decline in domain-general and domain-specific semantic control, more bilateral ATL engagement, as well as behavioral and neural shifts from taxonomic towards thematic processing. Increased thematic activity was associated with higher accuracy but slower responses. These findings support accounts of age-related neural dedifferentiation and semanticization: Older adults require increased cognitive resources to maintain accuracy at a high level, but this comes at the cost of efficiency.

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Temporo-Occipital and Medial Temporal Networks Underlying Object-Location Learning

Object-location memory (OLM), a fundamental component of spatial memory, is essential for everyday functioning yet declines with aging and neurodegenerative disorders. Functional neuroimaging studies have consistently implicated medial temporal lobe (MTL) structures, including the hippocampus and parahippocampal gyrus, as well as medial and lateral temporo-occipital regions, in object-location associative learning. However, the neural mechanisms and functional network interactions supporting OLM acquisition remain largely unknown. To address this gap, we examined twenty healthy adults (18-45 years) performing an object-location learning task during functional MRI. As a first main finding, task-related functional connectivity analyses revealed enhanced coupling between MTL structures, ventral visual regions, and temporo-occipital cortices during OLM learning. Secondly, stronger connectivity within this network was associated with higher learning accuracy, highlighting the behavioral relevance of coordinated cortical-MTL interactions. Thirdly, these connectivity patterns were not static but evolved across learning stages: interregional coupling was strongest during early learning and progressively attenuated as performance stabilized, suggesting sharpening and increased efficiency of network interactions with learning. Together, our results provide mechanistic insight into OLM acquisition at the functional network level and offer an evidence-based framework for identifying target networks to enhance spatial memory through non-invasive brain stimulation.

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Harmonizing the stimulation dose of focal tDCS across target sites

Non-invasive brain stimulation is an established tool for modulating neural activity that holds promise for advancing both cognitive neuroscience and clinical interventions. Focal transcranial direct current stimulation (tDCS), using center-surround electrode montages, enables more region-specific targeting. Although computational models can simulate individual electric fields, no existing approach enables the prospective individualization of electrode placement while standardizing the dose across targeted brain regions. In the current preparatory methodological study, we present a modeling-based framework that harmonizes the electric field strength between different target regions at the group level, but preserves inter-individual variability. This enables systematic examination of dose-response relationships and their regional differences. Positioning of the center-surround electrode montages is individualized to ensure focusing of the electric field on the target regions. We started by defining brain targets for eight cognitive and motor functions using MRI data from 43 participants. Using field simulations, we then estimated a group-average field strength in the target regions that had led to behavioral and physiological effects in prior tDCS studies (resulting in 0.2 V/m). The radii of the center-surround montages were optimized for each target region to achieve the intended field strength while maximizing focality. Validation in an independent sample (n=53) confirmed that the intended target field strength is achieved on average for new participants. The described computational tools are made available as open-source software, allowing other researchers to apply our individualization framework with parameters (target regions and target field strengths) tailored to their specific research questions; and are currently being implemented in a multi-center study involving approximately 1,000 datasets.

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Linguistic information compensates for age-related decline in attentional filtering

As we age, understanding speech in social situations imposes an increasingly difficult challenge to the auditory system. However, the attentional mechanisms underlying age-related speech comprehension difficulties in multitalker situations remain unclear. We collected EEG signals while 63 normal hearing participants from 19 to 71 years performed a speech comprehension task involving a multitalker paradigm at individually adjusted target-to-distractor ratios. Combining trial-resolved multivariate temporal response function modeling with detailed behavioral comprehension responses, we provide a window into lower-level impairments and higher-level compensatory mechanisms across the adult life span. Neuro-behavioral correlations on a trial-by-trial level provide direct evidence for increased distractor representation underlying reduced behavioral performance in late adulthood. This points towards increased distractibility as a potential mechanism underlying age-related speech comprehension deficits. Additionally, at the behavioral and neural levels, we show that older adults relied more on higher-level linguistic information. Finally, we show that an increased reliance on word-level linguistic information may compensate for increased distractor tracking and adaptively support comprehension performance across the adult life span. Specifically, we directly show that increased reliance on higher-level processing can offset age-related impairments in attentional filtering.

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A novel approach to map the causal impact of brain stimulation on semantic processing with language models

Non-invasive brain stimulation (NIBS) studies on semantic cognition hold the promise of revealing the functional relevance of brain areas through causal intervention. A primary challenge, however, is that findings are often interpreted through binary distinctions between sets of stimuli (e.g. related/unrelated words, same/different semantic category). This approach ignores the analysis of individual words, which mirrors every-day language use and is crucial for understanding semantic cognition. In this work, we used semantic similarity, as measured by a language model, to investigate how Transcranial Magnetic Stimulation (TMS) effects on semantic cognition unfold at the level of individual words. We re-analyzed 5 publicly available TMS datasets, covering multiple stimulation sites and lexical semantics tasks. We propose a simple methodology that can straightforwardly be applied to any TMS experiment on semantic cognition, and showcase its potential to generate new insights. We modelled trial-level response times using the language model and computed the correlation between the two. We also repeated the analyses for two lower-level variables (word frequency and length). Importantly, for each dataset, we compared correlations for effective and control (sham or vertex) stimulation conditions. We found that, for the language model, correlation was almost always significantly different depending on the type of stimulation (effective or control). Our results provide evidence that the stimulation effect interacts with the meaning of individual words. However, a similar pattern emerged in some cases for word frequency and length, suggesting that the effects of TMS on cognition can be widespread, well beyond their intended functional target. Collectively, our results demonstrate that language models provide new insight into the impact of neurostimulation on semantic processing, complementing standard measures.

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Causal Contributions of Left Inferior and Medial Frontal Cortex to Semantic and Executive Control

Semantic control guides the targeted and context-based retrieval from semantic memory. The overlap with and dissociation from domain-general executive control in the frontal lobe remains contentious. Here, we used transcranial magnetic stimulation (TMS) to probe the functional relevance of the left inferior frontal gyrus (IFG) and pre-supplementary motor area (pre-SMA) for semantic and executive control. Across four sessions, 24 participants received 1 Hz repetitive TMS to each region individually, dual-site TMS targeting both regions sequentially (IFG followed by pre-SMA), and sham TMS. Participants then completed semantic fluency, figural fluency, and picture-naming tasks. Stimulation of either region broadly disrupted both semantic and figural fluency, suggesting shared functionality. However, electric field modeling of the induced stimulation strength revealed distinct specializations: The left IFG was primarily associated with semantic control, as evidenced by verbal fluency deficits, while the pre-SMA played a domain-general role in executive functions, affecting non-verbal fluency and cognitive flexibility (e.g., clustering and switching during semantic fluency). Notably, only dual-site TMS impaired accuracy in figural fluency, providing unique evidence for successful compensation of executive functions through either the left IFG or pre-SMA following single-site perturbation. These findings underscore the multidimensionality of cognitive control and suggest a flexible task-dependent contribution of the IFG to control processes, either as semantic-specific or general executive resource. Furthermore, they highlight the tightly interconnected network of executive control subserved by the left IFG and pre-SMA, advancing our understanding of the neural basis of semantic and executive functions.

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Attentional engagement with target and distractor streams predicts speech comprehension in multitalker environments

Understanding speech while ignoring competing speech streams in the surrounding environment is challenging. Previous studies have demonstrated that attention shapes the neural representation of speech features. Attended streams are typically represented more strongly than unattended ones, suggesting either enhancement of the attended or suppression of the unattended stream. However, it is unclear how these complementary processes support attentional filtering and speech comprehension on different hierarchical levels. In this study, we used multivariate temporal response functions to analyze the EEG signals of 43 young adults (24 women), examining the relationship between the neural tracking of acoustic and higher-level linguistic features and a fine-grained speech comprehension measure. We show that the neural tracking of word and phoneme onsets and word-level linguistic features in the attended stream predicted comprehension at the individual single-trial level. Moreover, acoustic tracking of the ignored speech stream was positively correlated with comprehension performance, whereas word level linguistic neural tracking of the ignored stream was negatively correlated with comprehension. Collectively, our results suggest that attentional filtering during speech comprehension requires target enhancement as well as distractor suppression at different hierarchical levels. Significance StatementIn social settings, speech comprehension is often challenged by the presence of multiple speakers talking simultaneously. The ability to focus on a relevant stream while ignoring irrelevant speech information in the background is crucial for successful and efficient interpersonal interactions. However, the precise neural mechanisms underlying this selective filtering process remain unclear. We establish the interplay of acoustic and higher-level information as objective markers of attentional selection and comprehension success.

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Target-Specificity and Repeatability in Neuro-Cardiac-Guided TMS for Heart-Brain Coupling

The dorsolateral prefrontal cortex (DLPFC) is a principal target for transcranial magnetic stimulation (TMS) in treating major depressive disorder, with therapeutic effects thought to be mediated by its connectivity with the subgenual anterior cingulate cortex. As both regions are involved in autonomic regulation, short-term heart rate changes following DLPFC stimulation may serve as physiological markers to identify stimulation targets. We employed neuro-cardiac guided TMS in a cohort of healthy participants to examine the effects of stimulation intensity and DLPFC target specificity on heart-brain coupling (HBC). We used generalized additive models to assess nonlinear effects of stimulation intensity and target location on HBC, while accounting for pain ratings and other side effects. Intra-subject repeatability across three sessions was evaluated using intraclass correlation coefficients. We observed a non-linear modulation of HBC depending on stimulation intensity and target location, with greater effects at the F3 lateral and F3 posterior targets compared to sham. By evaluating these effects across sessions within participants, we demonstrate the robustness of our results beyond the influence of pain and other side effects on HBC modulation. Exploratory analyses of the directionality show a consistent decrease in HR only at the F3 lateral target with suprathreshold stimulation. These results demonstrate that HBC is modulated in a target- and intensity-specific manner, with particularly consistent effects at F3 lateral sites within the DLPFC. The findings enhance the understanding of TMS-modulated heart-brain interactions, offering a potential framework for optimizing individualized rTMS treatment protocols for depression.

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Hindering memory suppression by perturbing the right dorsolateral prefrontal cortex

A reminder of the past can trigger the involuntary retrieval of an unwanted memory. Yet, we can intentionally stop this process and thus prevent the memory from entering awareness. Such suppression not only transiently hinders the retrieval of the memory, it can also induce forgetting. Neuroimaging has implicated the right dorsolateral prefrontal cortex (dlPFC) in initiating this process. Specifically, this region seems to downregulate activity in brain systems that would otherwise support memory reinstatement. Here, we probed the causal contribution of the right dlPFC to suppression by combining the Think/No-Think task with repetitive transcranial magnetic stimulation (rTMS). Participants first learned pairs of cue and target words, and then repeatedly recalled some of the targets (think condition) and suppressed others (no-think condition). We applied 10 Hz rTMS bursts to the right dlPFC during the suppression of half the no-think items and to the contra-lateral primary motor area (M1) as an active control site during the other half. As hypothesized, participants experienced less success at keeping the memories out of awareness with concurrent dlPFC than M1 stimulation. Similarly, a memory test yielded evidence for suppressioninduced forgetting (SIF) following M1 but not dlPFC stimulation. However, the difference in forgetting between the stimulation conditions was not significant. The study thus provides causal evidence for the role of the dlPFC in preventing retrieval. Future work will need to conclusively establish the relationship between this transient effect and suppression-induced forgetting.

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Effects of Electric Field Direction on TMS-based Motor Cortex Mapping

BackgroundTranscranial magnetic stimulation (TMS) modulates brain activity by inducing electric fields (E-fields) that can elicit action potentials in cortical neurons. Neuronal responses to TMS depend not only on the magnitude of the induced E-field but also on various physiological factors. In this study, we incorporated a novel average response model that efficiently estimates the firing threshold of neurons based on their orientation relative to the applied E-field, thereby advancing TMS mapping for motor function. MethodsWe conducted a regression-based TMS mapping experiment with fourteen subjects to localize cortical origins of motor evoked potential (MEP) on the first dorsal interosseous (FDI) muscle. Firing thresholds were estimated for excitatory neurons in cortical layers 2/3 and 5 via an average response model. Regression was performed between MEPs and three E-field quantities: the magnitude (magnitude model), the normal component (cosine model), and the effective E-field, which scales the E-field magnitude based on the firing thresholds specific to the neuronal orientation (neuron model). To validate, we applied TMS to ten subjects with optimized coil placements based on these three models to determine which model could yield the highest MEPs. ResultsThe magnitude and neuron models performed similarly, while the cosine model showed lower explained variance in regression results, required more TMS trials for stable mapping, and yielded the lowest MEP in the validation. ConclusionThis study is the first to advance TMS modeling by incorporating neuron-specific factors at the individual level. Results show that on the motor cortex, the magnitude model is-as expected-a good approximation of cortical TMS effects as it shows similar results as the neuron model. In contrast, the classic cosine model exhibited lower performance and required more TMS trials for stable results, and is not recommended for future studies.

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Semantic integration demands modulate large-scale network interactions in the brain

The ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear. In this study, 32 healthy participants (30-75 years) performed an auditory cloze probability task during functional magnetic resonance imaging (fMRI), requiring lexical decisions on the sentences final words. Semantic integration demands were implicitly modulated by presenting sentences with expected, unexpected, anomalous, or pseudoword endings. To elucidate network interactions supporting semantic integration, we combined univariate task-based fMRI analyses with seed-based connectivity and between-network connectivity analyses. Behavioral data revealed typical semantic integration effects, with increased integration demands being associated with longer response latencies and reduced accuracy. Univariate results demonstrated increased left frontal and temporal brain activity for sentences with higher integration demands. Between-network interactions highlighted the role of task-positive and default mode networks for sentence processing with increased semantic integration demands. Furthermore, increasing integration demands led to a higher number of behaviorally relevant network interactions, suggesting that the increased between-network coupling becomes more relevant for successful task performance as integration demands increase. Our findings elucidate the complex network interactions underlying semantic integration across the aging continuum. Stronger interactions between various task-positive and default mode networks correlated with more efficient processing of sentences with increased semantic integration demands. These results may inform future studies with healthy old and clinical populations.

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Limited cognitive resources reduce the language predictability benefit across the adult lifespan

Humans routinely anticipate upcoming language, but whether such predictions come at a cognitive cost remains debated. In this study, we demonstrate the resource-dependent nature of predictive mechanisms in language comprehension across the lifespan: Experimentally limiting executive resources through a concurrent task reduces the effect of language predictability on reading time. Participants (N=175, replication N=96) read short articles presented word-by-word while completing a secondary font colour n-back task, thus varying cognitive demand. Language predictability was indexed by word surprisal as derived from a pre-trained large language model (GPT-2). Across two independent samples, our findings reveal that language predictions are not cost-free: They draw on executive control resources, and this dependency becomes more pronounced with age (18-85 years). These results help resolve the debate over cognitive demands in language comprehension and highlight prediction as a dynamic, resource-dependent process across the lifespan.

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Assessing adverse effects and unspecific effects of transcutaneous spinal direct current stimulation (tsDCS)

BackgroundTranscutaneous spinal direct current stimulation (tsDCS) is a relatively recent method for non-invasively modulating neuronal activity in the human spinal cord. Despite its growing prominence, comprehensive studies addressing its potential adverse effects (AEs) and unspecific effects (UEs) are lacking. ObjectiveIn this study, we conducted a systematic investigation into the potential AEs and UEs of tsDCS in healthy volunteers. MethodsWe used a randomized double-blind within-participant design, employing anodal, cathodal and sham tsDCS of the thoracolumbar spinal cord. Our approach involved a newly-developed structured questionnaire (to assess subjectively-reported AEs) in combination with tsDCS-concurrent recording of skin conductance, cardiac and respiratory activity (to assess UEs in bodily state). ResultsThe most frequently participant-reported AEs were sensations of burning, tingling, and itching, although they were largely described as mild; skin redness (experimenter-reported) occurred even more frequently. Importantly, when comparing AEs between active and sham tsDCS via frequentist and Bayesian analysis approaches, the results were largely in favour of no difference between conditions (with the exception of skin redness). A similar picture emerged for most UE metrics, suggesting that tsDCS does not induce changes in bodily state, at least as measured by our autonomic nervous system metrics. ConclusionWe believe that the strategy employed here could serve as a starting point for a systematic AE and UE assessment in clinical populations, longitudinal designs and when stimulating different spinal sites. Taken together, our results contribute to assessing the tolerability, safety and specificity of tsDCS, in order to further the investigation of spinal cord function in health and disease.

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Bayesian modeling disentangles language versus executive control disruption in stroke

Stroke is the leading cause of long-term disability worldwide. Incurred brain damage disrupts cognition, often with persisting deficits in language and executive capacities. Despite their clinical relevance, the commonalities, and differences of language versus executive control impairments remain under-specified. We tailored a Bayesian hierarchical modeling solution in a largest-of-its-kind cohort (1080 stroke patients) to deconvolve language and executive control in the brain substrates of stroke insults. Four cognitive factors distinguished left- and right-hemispheric contributions to ischemic tissue lesion. One factor delineated language and general cognitive performance and was mainly associated with damage to left-hemispheric brain regions in the frontal and temporal cortex. A factor for executive control summarized control and visual-constructional abilities. This factor was strongly related to right-hemispheric brain damage of posterior regions in the occipital cortex. The interplay of language and executive control was reflected in two factors: executive speech functions and verbal memory. Impairments on both were mainly linked to left-hemispheric lesions. These findings shed light onto the causal implications of hemispheric specialization for cognition; and make steps towards subgroup-specific treatment protocols after stroke.

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Electrical field based dosing improves non-invasive brain stimulation

AbstractTranscranial magnetic stimulation (TMS) is an invaluable non-invasive brain stimulation (NIBS) technique to modulate cortical activity and behavior, but high within- and between-participant variability limits its efficacy and reliability. Here, we explore the potential of electric field (e-field) based TMS dosing to reduce its variability and discuss current challenges as well as future pathways. In contrast to previous dosing approaches, e-field dosing better matches the stimulation strength across cortical areas, both within and across individuals. Challenges include methodological uncertainties of the e-field simulation, target definitions, and comparability of different stimulation thresholds across cortical areas and NIBS protocols. Despite these challenges, e-field dosing promises to substantially improve NIBS applications in neuroscientific research and personalized medicine. Outstanding Questions Box O_TEXTBOXOutstanding Questions O_LIDoes the cortical threshold for effective stimulation differ between primary regions and higher-level association areas? How large is the impact of cytoarchitectonic differences between regions on a stimulation threshold? C_LIO_LIDo cortical stimulation thresholds differ across individuals? Are thresholds stable within an individual across the lifespan? What are the physiological factors influencing these thresholds? C_LIO_LICan a cortical stimulation threshold measured with single-pulse TMS be transferred to repetitive TMS protocols for the study of cognition? C_LIO_LIHow does the cortical stimulation threshold interact with the current brain state? C_LI C_TEXTBOX Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/551253v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@16d6e44org.highwire.dtl.DTLVardef@1626d90org.highwire.dtl.DTLVardef@10713e7org.highwire.dtl.DTLVardef@1abdcaa_HPS_FORMAT_FIGEXP M_FIG C_FIG

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