Search

Prior studies have shown that the left posterior superior temporal sulcus (pSTS) and left temporo-parietal junction (TPJ) both contribute to phonological short-term memory, speech perception and speech production. Here, by conducting a within-subjects multi-factorial fMRI study, we dissociate the response profiles of these regions and a third region - the anterior ascending terminal branch of the left superior temporal sulcus (atSTS), which lies dorsal to pSTS and ventral to TPJ. First, we show that each region was more activated by (i) 1-back matching on visually presented verbal stimuli (words or pseudowords) compared to 1-back matching on visually presented non-verbal stimuli (pictures of objects or non-objects), and (ii) overt speech production than 1-back matching, across 8 types of stimuli (visually presented words, pseudowords, objects and non-objects and aurally presented words, pseudowords, object sounds and meaningless hums). The response properties of the three regions dissociated within the auditory modality. In left TPJ, activation was higher for auditory stimuli that were non-verbal (sounds of objects or meaningless hums) compared to verbal (words and pseudowords), irrespective of task (speech production or 1-back matching). In left pSTS, activation was higher for non-semantic stimuli (pseudowords and hums) than semantic stimuli (words and object sounds) on the dorsal pSTS surface (dpSTS), irrespective of task. In left atSTS, activation was not sensitive to either semantic or verbal content. The contrasting response properties of left TPJ, dpSTS and atSTS was cross-validated in an independent sample of 59 participants, using region-by-condition interactions. We also show that each region participates in non-overlapping networks of frontal, parietal and cerebellar regions. Our results challenge previous claims about functional specialisation in the left posterior superior temporal lobe and motivate future studies to determine the timing and directionality of information flow in the brain networks involved in speech perception and production., (Copyright © 2021. Published by Elsevier Inc.)

Controversy surrounds the interpretation of higher activation for pseudoword compared to word reading in the left precentral gyrus and pars opercularis. Specifically, does activation in these regions reflect: (1) the demands on sublexical assembly of articulatory codes, or (2) retrieval effort because the combinations of articulatory codes are unfamiliar? Using fMRI, in 84 neurologically intact participants, we addressed this issue by comparing reading and repetition of words (W) and pseudowords (P) to naming objects (O) from pictures or sounds. As objects do not provide sublexical articulatory cues, we hypothesis that retrieval effort will be greater for object naming than word repetition/reading (which benefits from both lexical and sublexical cues); while the demands on sublexical assembly will be higher for pseudoword production than object naming. We found that activation was: (i) highest for pseudoword reading [P>O&W in the visual modality] in the anterior part of the ventral precentral gyrus bordering the precentral sulcus (vPCg/vPCs), consistent with the sublexical assembly of articulatory codes; but (ii) as high for object naming as pseudoword production [P&O>W] in dorsal precentral gyrus (dPCg) and the left inferior frontal junction (IFJ), consistent with retrieval demands and cognitive control. In addition, we dissociate the response properties of vPCg/vPCs, dPCg and IFJ from other left frontal lobe regions that are activated during single word speech production. Specifically, in both auditory and visual modalities: a central part of vPCg (head and face area) was more activated for verbal than nonverbal stimuli [P&W>O]; and the pars orbitalis and inferior frontal sulcus were most activated during object naming [O>W&P]. Our findings help to resolve a previous discrepancy in the literature, dissociate three functionally distinct parts of the precentral gyrus, and refine our knowledge of the functional anatomy of speech production in the left frontal lobe., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Deaf late signers provide a unique perspective on the impact of impoverished early language exposure on the neurobiology of language: insights that cannot be gained from research with hearing people alone. Here we contrast the effect of age of sign language acquisition in hearing and congenitally deaf adults to examine the potential impact of impoverished early language exposure on the neural systems supporting a language learnt later in life. We collected fMRI data from deaf and hearing proficient users (N ​= ​52) of British Sign Language (BSL), who learnt BSL either early (native) or late (after the age of 15 years) whilst they watched BSL sentences or strings of meaningless nonsense signs. There was a main effect of age of sign language acquisition (late ​> ​early) across deaf and hearing signers in the occipital segment of the left intraparietal sulcus. This finding suggests that late learners of sign language may rely on visual processing more than early learners, when processing both linguistic and nonsense sign input - regardless of hearing status. Region-of-interest analyses in the posterior superior temporal cortices (STC) showed an effect of age of sign language acquisition that was specific to deaf signers. In the left posterior STC, activation in response to signed sentences was greater in deaf early signers than deaf late signers. Importantly, responses in the left posterior STC in hearing early and late signers did not differ, and were similar to those observed in deaf early signers. These data lend further support to the argument that robust early language experience, whether signed or spoken, is necessary for left posterior STC to show a 'native-like' response to a later learnt language., Competing Interests: Declaration of competing interest None., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

This fMRI study of 24 healthy human participants investigated whether any part of the auditory cortex was more responsive to self-generated speech sounds compared to hearing another person speak. The results demonstrate a double dissociation in two different parts of the auditory cortex. In the right posterior superior temporal sulcus (RpSTS), activation was higher during speech production than listening to auditory stimuli, whereas in bilateral superior temporal gyri (STG), activation was higher for listening to auditory stimuli than during speech production. In the second part of the study, we investigated the function of the identified regions, by examining how activation changed across a range of listening and speech production tasks that systematically varied the demands on acoustic, semantic, phonological and orthographic processing. In RpSTS, activation during auditory conditions was higher in the absence of semantic cues, plausibly indicating increased attention to the spectral-temporal features of auditory inputs. In addition, RpSTS responded in the absence of any auditory inputs when participants were making one-back matching decisions on visually presented pseudowords. After analysing the influence of visual, phonological, semantic and orthographic processing, we propose that RpSTS (i) contributes to short term memory of speech sounds as well as (ii) spectral-temporal processing of auditory input and (iii) may play a role in integrating auditory expectations with auditory input. In contrast, activation in bilateral STG was sensitive to acoustic input and did not respond in the absence of auditory input. The special role of RpSTS during speech production therefore merits further investigation if we are to fully understand the neural mechanisms supporting speech production during speech acquisition, adult life, hearing loss and after brain injury., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

This paper provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). It steps through an analysis in detail and provides a tutorial style explanation of the underlying theory and assumptions (i.e, priors). The analysis procedure involves specifying a hierarchical model with two or more levels. At the first level, state space models (DCMs) are used to infer the effective connectivity that best explains a subject's neuroimaging timeseries (e.g. fMRI, MEG, EEG). Subject-specific connectivity parameters are then taken to the group level, where they are modelled using a General Linear Model (GLM) that partitions between-subject variability into designed effects and additive random effects. The ensuing (Bayesian) hierarchical model conveys both the estimated connection strengths and their uncertainty (i.e., posterior covariance) from the subject to the group level; enabling hypotheses to be tested about the commonalities and differences across subjects. This approach can also finesse parameter estimation at the subject level, by using the group-level parameters as empirical priors. The preliminary first level (subject specific) DCM for fMRI analysis is covered in a companion paper. Here, we detail group-level analysis procedures that are suitable for use with data from any neuroimaging modality. This paper is accompanied by an example dataset, together with step-by-step instructions demonstrating how to reproduce the analyses., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs of researchers in cognitive and clinical neuroscience. In this guide, we step through an exemplar fMRI analysis in detail, reviewing the current implementation of DCM and demonstrating recent developments in group-level connectivity analysis. In the appendices, we detail the theory underlying DCM and the assumptions (i.e., priors) in the models. In the first part of the guide (current paper), we focus on issues specific to DCM for fMRI. This is accompanied by all the necessary data and instructions to reproduce the analyses using the SPM software. In the second part (in a companion paper), we move from subject-level to group-level modelling using the Parametric Empirical Bayes framework, and illustrate how to test for commonalities and differences in effective connectivity across subjects, based on imaging data from any modality., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

During word and object recognition, extensive activation has consistently been observed in the left ventral occipito-temporal cortex (vOT), focused around the occipito-temporal sulcus (OTs). Previous studies have shown that there is a hierarchy of responses from posterior to anterior vOT regions (along the y-axis) that corresponds with increasing levels of recognition - from perceptual to semantic processing, respectively. In contrast, the functional differences between superior and inferior vOT responses (i.e. along the z-axis) have not yet been elucidated. To investigate, we conducted an extensive review of the literature and found that peak activation for reading varies by more than 1 cm in the z-axis. In addition, we investigated functional differences between superior and inferior parts of left vOT by analysing functional MRI data from 58 neurologically normal skilled readers performing 8 different visual processing tasks. We found that group activation in superior vOT was significantly more sensitive than inferior vOT to the type of task, with more superior vOT activation when participants were matching visual stimuli for their semantic or perceptual content than producing speech to the same stimuli. This functional difference along the z-axis was compared to existing boundaries between cytoarchitectonic areas around the OTs. In addition, using dynamic causal modelling, we show that connectivity from superior vOT to anterior vOT increased with semantic content during matching tasks but not during speaking tasks whereas connectivity from inferior vOT to anterior vOT was sensitive to semantic content for matching and speaking tasks. The finding of a functional dissociation between superior and inferior parts of vOT has implications for predicting deficits and response to rehabilitation for patients with partial damage to vOT following stroke or neurosurgery., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce. Regardless of the inconsistencies across levels, and contrary to past studies which implicated differential neural substrates for hand and finger imitation, we find no consistent voxels or regions, where damage affects one imitation skill and not the other, at any of the three analysis levels. Our novel Bayesian approach indicates that any apparent differences appear to be driven by an increased sensitivity of hand imitation skills to lesions that also impair finger imitation. In our analyses, the results of the highest level of analysis (region-pairs) emphasise a role of the primary somatosensory and motor cortices, and the occipital lobe in imitation. We argue that this emphasis supports an account of both imitation tasks based on direct sensor-motor connections, which throws doubt on past accounts which imply the need for an intermediate (e.g. body-part-coding) system of representation., (Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.)

In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Brain imaging studies of functional outcomes after white matter damage have quantified the severity of white matter damage in different ways. Here we compared how the outcome of such studies depends on two different types of measurements: the proportion of the target tract that has been destroyed ('lesion load') and tract disconnection. We demonstrate that conclusions from analyses based on two examples of these measures diverge and that conclusions based solely on lesion load may be misleading. First, we reproduce a recent lesion-load-only analysis which suggests that damage to the arcuate fasciculus, and not to the uncinate fasciculus, is significantly associated with deficits in fluency and naming skills. Next, we repeat the analysis after replacing the measures of lesion load with measures of tract disconnection for both tracts, and observe significant associations between both tracts and both language skills: i.e. the change increases the apparent relevance of the uncinate fasciculus to fluency and naming skills. Finally we show that, in this dataset, disconnection data explains significant variance in both language skills that is not accounted for by lesion load or volume, but lesion load data explains no unique variance in those skills, once disconnection and lesion volume are taken into account., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

The PLORAS Database is a relational repository of anatomical and functional imaging data that has primarily been acquired from stroke survivors, along with standardized scores on a wide range of sensory, motor and cognitive abilities, demographic details and medical history. As of January 2015, we have data from 750 patients with an expected accrual rate of 200 patients per year. Expansion will accelerate as we extend our collaborations. The main aim of the database is to Predict Language Outcome and Recovery After Stroke (PLORAS) on the basis of a single structural (anatomical) brain scan that indexes the stereotactic location and extent of brain damage. Predictions are made for individual patients by indicating how other patients with the most similar brain damage, cognitive abilities and demographic details recovered their language skills over time. Predictions are validated by longitudinal follow-ups of patients who initially presented with speech and language difficulties. The PLORAS Database can also be used to predict recovery of other cognitive abilities on the basis of anatomical brain scans. The functional imaging data can be used to understand the neural mechanisms that support recovery from brain damage; and all the data can be used to understand the main sources of inter-subject variability in structure-function mappings in the human brain. Data will be made available for sharing, subject to: funding, ethical approval and patient consent., (Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.)

The anatomy of language has been investigated with PET or fMRI for more than 20 years. Here I attempt to provide an overview of the brain areas associated with heard speech, speech production and reading. The conclusions of many hundreds of studies were considered, grouped according to the type of processing, and reported in the order that they were published. Many findings have been replicated time and time again leading to some consistent and undisputable conclusions. These are summarised in an anatomical model that indicates the location of the language areas and the most consistent functions that have been assigned to them. The implications for cognitive models of language processing are also considered. In particular, a distinction can be made between processes that are localized to specific structures (e.g. sensory and motor processing) and processes where specialisation arises in the distributed pattern of activation over many different areas that each participate in multiple functions. For example, phonological processing of heard speech is supported by the functional integration of auditory processing and articulation; and orthographic processing is supported by the functional integration of visual processing, articulation and semantics. Future studies will undoubtedly be able to improve the spatial precision with which functional regions can be dissociated but the greatest challenge will be to understand how different brain regions interact with one another in their attempts to comprehend and produce language., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Although interactivity is considered a fundamental principle of cognitive (and computational) models of reading, it has received far less attention in neural models of reading that instead focus on serial stages of feed-forward processing from visual input to orthographic processing to accessing the corresponding phonological and semantic information. In particular, the left ventral occipito-temporal (vOT) cortex is proposed to be the first stage where visual word recognition occurs prior to accessing nonvisual information such as semantics and phonology. We used functional magnetic resonance imaging (fMRI) to investigate whether there is evidence that activation in vOT is influenced top-down by the interaction of visual and nonvisual properties of the stimuli during visual word recognition tasks. Participants performed two different types of lexical decision tasks that focused on either visual or nonvisual properties of the word or word-like stimuli. The design allowed us to investigate how vOT activation during visual word recognition was influenced by a task change to the same stimuli and by a stimulus change during the same task. We found both stimulus- and task-driven modulation of vOT activation that can only be explained by top-down processing of nonvisual aspects of the task and stimuli. Our results are consistent with the hypothesis that vOT acts as an interface linking visual form with nonvisual processing in both bottom up and top down directions. Such interactive processing at the neural level is in agreement with cognitive and computational models of reading but challenges some of the assumptions made by current neuro-anatomical models of reading., (Copyright © 2011 Elsevier Inc. All rights reserved.)

A number of modern digital anatomy techniques, based on structural MR brain images, have recently become applicable to the non-human primate brain. Such voxel-based quantitative techniques require a species-specific standardized brain template. Here we present a brain template for the Japanese macaque (Macaca fuscata). The template was designed to be used as a tool for spatially normalising Japanese macaque brains into a standard space. Although this species of macaque monkey is widely used in neuroscience research, including studies of higher cognitive brain functions, no standard MRI template of its brain is presently available. The template presented here is based on T1/T2* weighted, high-resolution 4T MR images obtained from 16 male adult Japanese macaque monkeys. T1/T2* images were used to correct the signal inequalities resulting from the use of a surface coil. Based on these images, population-averaged probability maps were created for grey matter, white matter and cerebrospinal fluid. The new template presented here should facilitate future brain research using the Japanese macaque monkey. Whole brain templates are available at http://brainatlas.brain.riken.jp/jm/modules/xoonips/listitem.php?index_id=9., (Copyright 2010 Elsevier Inc. All rights reserved.)

In this study we illustrate how the functional networks involved in a single task (e.g. the sensory, cognitive and motor components) can be segregated without cognitive subtractions at the second-level. The method used is based on meaningful variability in the patterns of activation between subjects with the assumption that regions belonging to the same network will have comparable variations from subject to subject. fMRI data were collected from thirty nine healthy volunteers who were asked to indicate with a button press if visually presented words were semantically related or not. Voxels were classified according to the similarity in their patterns of between-subject variance using a second-level unsupervised fuzzy clustering algorithm. The results were compared to those identified by cognitive subtractions of multiple conditions tested in the same set of subjects. This illustrated that the second-level clustering approach (on activation for a single task) was able to identify the functional networks observed using cognitive subtractions (e.g. those associated with vision, semantic associations or motor processing). In addition the fuzzy clustering approach revealed other networks that were not dissociated by the cognitive subtraction approach (e.g. those associated with high- and low-level visual processing and oculomotor movements). We discuss the potential applications of our method which include the identification of "hidden" or unpredicted networks as well as the identification of systems level signatures for different subgroupings of clinical and healthy populations.

Cognitive models of reading predict that high frequency regular words can be read in more than one way. We investigated this hypothesis using functional MRI and covariance analysis in 43 healthy skilled readers. Our results dissociated two sets of regions that were differentially engaged across subjects who were reading the same familiar words. Some subjects showed more activation in left inferior frontal and anterior occipito-temporal regions while other subjects showed more activation in right inferior parietal and left posterior occipito-temporal regions. To explore the behavioural correlates of these systems, we measured the difference between reading speed for irregularly spelled words relative to pseudowords outside the scanner in fifteen of our subjects and correlated this measure with fMRI activation for reading familiar words. The faster the lexical reading the greater the activation in left posterior occipito-temporal and right inferior parietal regions. Conversely, the slower the lexical reading the greater the activation in left anterior occipito-temporal and left ventral inferior frontal regions. Thus, the double dissociation in irregular and pseudoword reading behaviour predicted the double dissociation in neuronal activation for reading familiar words. We discuss the implications of these results which may be important for understanding how reading is learnt in childhood or re-learnt following brain damage in adulthood.

In this paper, we propose a new automated procedure for lesion identification from single images based on the detection of outlier voxels. We demonstrate the utility of this procedure using artificial and real lesions. The scheme rests on two innovations: First, we augment the generative model used for combined segmentation and normalization of images, with an empirical prior for an atypical tissue class, which can be optimised iteratively. Second, we adopt a fuzzy clustering procedure to identify outlier voxels in normalised gray and white matter segments. These two advances suppress misclassification of voxels and restrict lesion identification to gray/white matter lesions respectively. Our analyses show a high sensitivity for detecting and delineating brain lesions with different sizes, locations, and textures. Our approach has important implications for the generation of lesion overlap maps of a given population and the assessment of lesion-deficit mappings. From a clinical perspective, our method should help to compute the total volume of lesion or to trace precisely lesion boundaries that might be pertinent for surgical or diagnostic purposes.

Inter-subject variability in evoked brain responses is attracting attention because it may reflect important variability in structure-function relationships over subjects. This variability could be a signature of degenerate (many-to-one) structure-function mappings in normal subjects or reflect changes that are disclosed by brain damage. In this paper, we describe a non-iterative fuzzy clustering algorithm (FCP: fuzzy clustering with fixed prototypes) for characterizing inter-subject variability in between-subject or second-level analyses of fMRI data. The approach identifies the contribution of each subject to response profiles in voxels surviving a classical F-statistic criterion. The output identifies subjects who drive activation in specific cortical regions (local effects) or in voxels distributed across neural systems (global effects). The sensitivity of the approach was assessed in 38 normal subjects performing an overt naming task. FCP revealed that several subjects had either abnormally high or abnormally low responses. FCP may be particularly useful for characterizing outlier responses in rare patients or heterogeneous populations. In these cases, atypical activations may not be detected by standard tests, under parametric assumptions. The advantage of using FCP is that it searches all voxels systematically and can identify atypical activation patterns in a quantitative and unsupervised manner.

In this functional magnetic resonance imaging study, we investigated human brain mechanisms that are involved in the analysis of voices as sound sources and in the pre-semantic analysis of voice information. The source of the voice was altered by changing the speaker, and the salience of the voice was altered by changing the amount of spectrotemporal detail. We identified a mechanism for detecting a change in the source of the voice in the posterior superior temporal lobe and anatomically distinct mechanisms for the detailed analysis of voice information in a bilateral network extending from the posterior to the anterior superior temporal lobe surrounding the superior temporal sulcus. The findings are consistent with a processing hierarchy in which general source attributes are analyzed in the posterior superior temporal lobe, abstraction of voice identity features occurs in posterior superior temporal sulcus, and further analysis of voice information occurs in anterior superior temporal sulcus and higher order cortices in the middle and anterior temporal lobe.

We used functional Magnetic Resonance Imaging to explore the neural correlates of semantic relevance in 12 healthy participants performing a picture-naming task. In addition, we tested the hypothesis that category effects typically found in functional imaging can be partly explained in terms of different semantic relevance for animals and artefacts. We report that semantic relevance modulates neuronal responses in the medial fusiform gyrus bilaterally. As predicted, category effects in this region are strongly modulated by the semantic relevance of the items. Specifically, the effect of artefacts > animals is greatly reduced when the two categories are matched for semantic relevance. Thus, the present study demonstrates that neuronal responses during concept retrieval are modulated by the semantic relevance of the features. It also suggests that increased activation in the medial fusiform gyrus typically found for artefacts > animals can be explained by different semantic relevance for animal and artefact items.

Group studies implicitly assume that all subjects activate one common system to sustain a particular cognitive task. Intersubject variability is generally treated as well-behaved and uninteresting noise. However, intersubject variability might result from subjects engaging different degenerate neuronal systems that are each sufficient for task performance. This would produce a multimodal distribution of intersubject variability. We have explored this idea with the help of Gaussian Mixture Modeling and Bayesian model comparison procedures. We illustrate our approach using a crossmodal priming paradigm, in which subjects perform a semantic decision on environmental sounds or their spoken names that were preceded by a semantically congruent or incongruent picture or written name. All subjects consistently activated the superior temporal gyri bilaterally, the left fusiform gyrus and the inferior frontal sulcus. Comparing a One and Two Gaussian Mixture Model of the unexplained residuals provided very strong evidence for two groups with distinct activation patterns: 6 subjects exhibited additional activations in the superior temporal sulci bilaterally, the right superior frontal and central sulcus. 11 subjects showed increased activation in the striate and the right inferior parietal cortex. These results suggest that semantic decisions on auditory-visual compound stimuli might be accomplished by two overlapping degenerate neuronal systems.

This paper uses whole brain functional neuroimaging in neurologically normal participants to explore how reading aloud differs from object naming in terms of neuronal implementation. In the first experiment, we directly compared brain activation during reading aloud and object naming. This revealed greater activation for reading in bilateral premotor, left posterior superior temporal and precuneus regions. In a second experiment, we segregated the object-naming system into object recognition and speech production areas by factorially manipulating the presence or absence of objects (pictures of objects or their meaningless scrambled counterparts) with the presence or absence of speech production (vocal vs. finger press responses). This demonstrated that the areas associated with speech production (object naming and repetitively saying "OK" to meaningless scrambled pictures) corresponded exactly to the areas where responses were higher for reading aloud than object naming in Experiment 1. Collectively the results suggest that, relative to object naming, reading increases the demands on shared speech production processes. At a cognitive level, enhanced activation for reading in speech production areas may reflect the multiple and competing phonological codes that are generated from the sublexical parts of written words. At a neuronal level, it may reflect differences in the speed with which different areas are activated and integrate with one another.

Behavioural and neuropsychological evidence suggests that abstract and concrete concepts might be represented, retrieved and processed differently in the human brain. Using fMRI, we demonstrate that retrieval of abstract relative to sensory-based semantics during synonym judgements increased activation in a left frontotemporal system that has been associated with semantic processing particularly at the sentence level. Since activation increases were observed irrespective of the degree of difficulty, we suggest that these differential activations might reflect a particular retrieval mechanism or strategy for abstract concepts. In contrast to sensory-based semantics, the meaning of abstract concepts is largely specified by their usage in language rather than by their relations to the physical world. Subjects might therefore generate an appropriate semantic sentential context to fully explore and specify the meaning of abstract concepts. Our results also explain why abstract semantics is vulnerable to left frontotemporal lesions.

In this paper we discuss cognitive and anatomical models of reading that have emerged from behavioral and lesion studies of dyslexia and functional neuroimaging studies of normal subjects. We then suggest that discrepancies in their findings can partly be overcome by functional neuroimaging studies of patients with acquired dyslexia. We present two such studies. One patient had a large left temporoparietal lesion which limited his reading to words with high semantic associations. When he read these words aloud, activation was observed in all areas of the normal reading system with the exception of the damaged left superior temporal lobe. The second patient had anterior temporal lobe atrophy with semantic dementia and a deficit in reading words that rely on lexical or semantic mediation. When asked to read aloud words on which she was likely to succeed, she activated all the normal areas, with increased activation in a left sensorimotor area associated with phonological processing and decreased activation in several areas associated with semantic processing. By relating these findings to those from lesion studies and imaging studies of normals, we propose that the translation of orthography to phonology is mediated semantically by the anterior part of the left midfusiform gyrus. In contrast, when semantic processing is compromised, the translation of orthography to phonology will be more reliant on the posterior part of the left midfusiform and the left frontal areas associated with phonology. Future studies are required to examine the connectivity between these areas during normal and abnormal reading.

Recent functional imaging studies have referred to a posterior region of the left midfusiform gyrus as the "visual word form area" (VWFA). We review the evidence for this claim and argue that neither the neuropsychological nor neuroimaging data are consistent with a cortical region specialized for visual word form representations. Specifically, there are no reported cases of pure alexia who have deficits limited to visual word form processing and damage limited to the left midfusiform. In addition, we present functional imaging data to demonstrate that the so-called VWFA is activated by normal subjects during tasks that do not engage visual word form processing such as naming colors, naming pictures, reading Braille, repeating auditory words, and making manual action responses to pictures of meaningless objects. If the midfusiform region has a single function that underlies all these tasks, then it does not correspond to visual word form processing. On the other hand, if the region participates in several functions as defined by its interactions with other cortical areas, then identifying the neural system sustaining visual word form representations requires identification of the set of regions involved. We conclude that there is no evidence that visual word form representations are subtended by a single patch of neuronal cortex and it is misleading to label the left midfusiform region as the visual word form area.

In this study we demonstrate that, even in blocked design fMRI, an event-related analysis may provide a more accurate model of the hemodynamic responses than an epoch-related analysis. This is because the temporal shape of the predicted response differs between the event-related and the epoch model, with the former reaching its peak sooner and returning to baseline later than the latter. We present data from a blocked design fMRI study of single word reading alternated with rest. Conventionally, such a design would be analyzed using an epoch analysis with boxcar regressors. However, here we used a combined model in which trials were modeled as both single events and epochs. This allowed us to estimate the variance in the BOLD signal that was explained by either the event-related or the epoch regressors having discounted the effect of the other. We found that, in a number of language regions, the event-related model explained changes in activity that were not accounted for by the epoch model. In addition, we show that the advantage of the event-related over epoch model was engendered by its early onset rather than its late offset, relative to the epoch model.

This technical note deals with a priori estimation of efficiency of functional magnetic resonance imaging (fMRI) designs. The efficiency of an estimator is a measure of how reliable it is and depends on error variance (the variance not modeled by explanatory variables in the design matrix) and the design variance (a function of the explanatory variables and the contrast tested). Changes in the experimental design can induce changes in the variance of estimated responses. This translates into changes in the standard error of the response estimate or equivalently into changes in efficiency. One consequence is that statistics, testing for the same activation in different contexts (i.e., experimental designs), can change substantially even if the activation and error variance are exactly the same. We demonstrate this effect using an event-related fMRI study of single word reading during blocked and randomized trial presentations. Furthermore, we show that the error variance can change with the experimental design. This highlights a problem with a priori comparison of efficiency for two or more experimental designs, which usually assumes identical error variance.

In this study we demonstrate the importance of distributed sampling of peristimulus time in blocked design fMRI studies. Distributed sampling ensures all the components of an event-related hemodynamic response are sampled and avoids the bias incurred when stimulus presentation is time-locked to data acquisition. We found that differences in the temporal offset between stimulus presentation and data acquisition had a significant effect on some language-related activations. These effects, induced by simply shifting stimulus presentation by a fraction of the interscan interval, suggest that fixed sampling does indeed bias estimated responses, even in blocked designs.

This article is about intersubject variability in the functional integration of activity in different brain regions. Previous studies of functional and effective connectivity have dealt with intersubject variability by analyzing data from different subjects separately or pretending the data came from the same subject. These approaches do not allow one to test for differences among subjects. The aim of this work was to illustrate how differences in connectivity among subjects can be addressed explicitly using structural equation modeling. This is enabled by constructing a multisubject network that comprises m regions of interest for each of the n subjects studied, resulting in a total of m x n nodes. Constructing a network of regions from different subjects may seem counterintuitive but embodies two key advantages. First, it allows one to test directly for differences among subjects by comparing models that do and do not allow a particular connectivity parameter to vary over subjects. Second, a multisubject network provides additional degrees of freedom to estimate the model's free parameters. Any neurobiological hypothesis normally addressed by single-subject or group analyses can still be tested, but with greater sensitivity. The common influence of experimental variables is modeled by connecting a virtual node, whose time course reflects stimulus onsets, to the sensory or "input" region in all subjects. Further experimental changes in task or cognitive set enter through modulation of the connections. This approach allows one to model both endogenous (or intrinsic) variance and exogenous effects induced by experimental design. We present a functional magnetic resonance imaging study that uses a multisubject network to investigate intersubject variability in functional integration in the context of single word and pseudoword reading. We tested whether the effect of word type on the reading-related coupling differed significantly among subjects. Our results showed that a number of forward and backward connections were stronger for reading pseudowords than words, and, in one case, connectivity showed significant intersubject variability. The discussion focuses on the implications of our findings and on further applications of the multisubject network analysis.

Conceptual knowledge is thought to be represented in a large distributed network, indexing a range of different semantic features (e.g., visual, auditory, functional). We investigated the anatomical organization of these features, using PET, by contrasting brain activity elicited by heard words with (i) visual (e.g., blue), (ii) auditory (e.g., noise), or (iii) abstract (e.g., truth) meaning. The activation task was either repetition or semantic decision (e.g., does the meaning of the word relate to religion?). In the baseline conditions, the sound track of the words was reversed and subjects had to say "OK" (control for repetition) or make an acoustic decision (control for semantic decision). Irrespective of task, words relative to their corresponding controls activated the left posterior inferior temporal and inferior frontal cortices. In addition, semantic decisions on words with sensory (visual and auditory) meanings enhanced activation in a ventral region of the left anterior temporal pole. These results are consistent with neuropsychological studies showing that anterior temporal lobe damage can cause deficits for items that are mainly defined by their sensory features (i.e., concrete, particularly living items). Since modality-specific activation was observed only during the semantic decision task, we discuss whether it reflects retrieval of sensory semantics per se or the degree to which semantic associations are triggered during effortful retrieval., ((C)2002 Elsevier Science (USA).)

To investigate the neural correlates of semantic processing, previous functional imaging studies have used semantic decision and generation tasks. However, in addition to activating semantic associations these tasks also involve executive functions that are not specific to semantics. The study reported in this paper aims to dissociate brain activity due to stimulus-driven semantic associations and task-induced semantic and executive processing by using repetition and semantic decision on auditorily presented words in a cognitive conjunction design. The left posterior inferior temporal, inferior frontal (BA 44/45), and medial orbital gyri were activated by both tasks, suggesting a general role in stimulus-driven semantic and phonological processing. In addition, semantic decision increased activation in (i) left ventral inferior frontal cortex (BA 47), right cerebellum, and paracingulate, which have all previously been implicated in executive functions, and (ii) a ventral region in the left anterior temporal pole which is commonly affected in patients with semantic impairments. We attribute activation in this area to the effortful linkage of semantic features. Thus, our study replicated the functional dissociation between dorsal and ventral regions of the left inferior frontal cortex. Moreover, it also dissociated the semantic functions of the left posterior inferior temporal gyrus and anterior temporal pole: The posterior region subserves stimulus-driven activation of semantic associations and the left anterior region is involved in task-induced association of semantic information., ((C)2002 Elsevier Science (USA).)

Many cognitive theories of semantic organization stem from reports of patients with selective, category-specific deficits for particular classes of objects (e.g., fruit). The anatomical assumptions underlying the competing claims can be evaluated with functional neuroimaging but the findings to date have been inconsistent and insignificant when standard statistical criteria are adopted. We hypothesized that category differences in functional brain responses might be small and task dependent. To test this hypothesis, we entered data from seven PET studies into a single multifactorial design which crossed category (living vs man-made) with a range of tasks. Reliable category-specific effects were observed but only for word retrieval and semantic decision tasks. Living things activated medial aspects of the anterior temporal poles bilaterally while tools activated a left posterior middle temporal region. These category-by-task interactions provide robust evidence for an anatomical double dissociation according to category and place strong constraints on cognitive theories of the semantic system. Furthermore they reconcile some of the apparent inconsistencies between lesion studies and functional neuroimaging data., (©2002 Elsevier Science (USA).)

Enumeration of small groups of four or fewer objects is very fast and accurate (often called "subitizing"), but gets slower and more error prone for more than four items ("counting"). Many theories have been proposed to account for this dichotomy, most suggesting that "subitizing" and "counting" are two qualitatively different and separable processes. Others, in contrast, have proposed that the two operations reflect two different levels along a continuum of complexity. In this paper we present a PET study that attempts to characterize subitizing and counting at a neural level in order to investigate whether they are implemented as separate or functionally overlapping processes. Subjects performed an enumeration task on visual arrays of dots that varied in numerosity (1-4 and 6-9 dots) and spatial arrangement (canonical and random). The results demonstrated a common network for subitizing and counting that comprises extrastriate middle occipital and intraparietal areas. The intensity and spatial extent of this network were modulated by the number of dots and their spatial arrangement: activation increased as the number of items in the visual array increased, reaching maximum peak and extent for counting 6-9 randomly arranged items. Direct comparison between subitizing and counting showed that counting, relative to subitizing, was correlated with increased activity in this occipitoparietal network, while subitizing did not show areas of increased activation with respect to counting. Results speak against the idea of the two processes being implemented in separable neural systems.

We introduce a new method for detecting differences in the latency of blood oxygenation level-dependent (BOLD) responses to brief events within the context of the General Linear Model. Using a first-order Taylor approximation in terms of the temporal derivative of a canonical hemodynamic response function, statistical parametric maps of differential latencies were estimated via the ratio of derivative to canonical parameter estimates. This method was applied to two example datasets: comparison of words versus nonwords in a lexical decision task and initial versus repeated presentations of faces in a fame-judgment task. Tests across subjects revealed both magnitude and latency differences within several brain regions. This approach offers a computationally efficient means of detecting BOLD latency differences over the whole brain. Precise characterization of the hemodynamic latency and its interpretation in terms of underlying neural differences remain problematic, however.

The aim of this work was to investigate the dependence of BOLD responses on different patterns of stimulus input/neuronal changes. In an earlier report, we described an input-state-output model that combined (i) the Balloon/Windkessel model of nonlinear coupling between rCBF and BOLD signals, and (ii) a linear model of how regional flow changes with synaptic activity. In the present investigation, the input-state-output model was used to explore the dependence of simulated PET (rCBF) and fMRI (BOLD) signals on various parameters pertaining to experimental design. Biophysical simulations were used to estimate rCBF and BOLD responses as functions of (a) a prior stimulus, (b) epoch length (for a fixed SOA), (c) SOA (for a fixed number of events), and (d) stimulus amplitude. We also addressed the notion that a single neuronal response may differ, in terms of the relative contributions of early and late neural components, and investigated the effect of (e) the relative size of the late or "endogenous" neural component. We were interested in the estimated average rCBF and BOLD responses per stimulus or event, not in the statistical efficiency with which these responses are detected. The BOLD response was underestimated relative to rCBF with a preceding stimulus, increasing epoch length, and increasing SOA. Furthermore, the BOLD response showed some highly nonlinear behaviour when varying stimulus amplitude, suggesting some form of hemodynamic "rectification." Finally, the BOLD response was underestimated in the context of large late neuronal components. The difference between rCBF and BOLD is attributed to the nonlinear transduction of rCBF to BOLD signal. Our simulations support the idea that varying parameters that specify the experimental design may have differential effects in PET and fMRI. Moreover, they show that fMRI can be asymmetric in its ability to detect deactivations relative to activations when an absolute baseline is stipulated. Finally, our simulations suggest that relative insensitivity to BOLD signal in specific regions, such as the temporal lobe, may be partly explained by higher cognitive functions eliciting a relatively large late endogenous neuronal component., (Copyright 2001 Academic Press.)

Voxel-based morphometry (VBM) is a powerful tool for analyzing changes in gray or white matter density of the brain. By using an automated segmentation procedure and standardized parametric statistics it avoids biases inherent in operator-dependent morphological operations (J. Ashburner and K. J. Friston, 2000, NeuroImage 11, 805-821). Since its introduction in 1995, VBM has been used to examine anatomical changes in a variety of diseases associated with neurologic and psychiatric dysfunction. Given the power of this technique for discerning subtle anatomical changes, we wanted to assess its performance on brains with gross structural abnormalities. Such results could have implications regarding the difficulties to be faced when examining other types of distorted brains (e.g., brains with changes due to degenerative disease). This report describes the use of VBM for examining individual and group changes in gray matter concentration in five patients who had recovered from herpes simplex encephalitis (HSE) compared with age- and sex-matched controls. Because HSE tends to affect a specific set of brain regions we thought that this would (1) provide an opportunity to assess the anatomical face validity of VBM, (2) allow us to assess the problems of this technique when used on distorted brains, and (3) provide an in vivo demonstration of the gray matter changes due to HSE. We found that, despite problems in normalizing and segmenting these severely distorted brains, VBM was able to identify correctly a number of the regional gray matter abnormalities in HSE. The results, while consistent with the well-known histopathology of the disease, also demonstrate potential difficulties with this method., (Copyright 2001 Academic Press.)

In this paper, we present a post hoc method for identifying regions where functional MRI data are subject to signal reduction that may compromise sensitivity to activations. The motivation for developing this technique derives from recent language studies that showed responses in the inferior temporal lobe that could be detected by PET but not by fMRI. Reduced signal is due mostly to susceptibility artifacts and can be identified by comparing the T2* images (which are subject to susceptibility artifacts) with T2 images (which are not). However, T2 images are not usually acquired in fMRI studies. Therefore, we propose that areas with reduced signal can be identified by comparing T2* images that are corrected for nonuniformity with the original uncorrected images. The technique provides a voxel-wise characterization of signal reduction that pertains to the particular data that enter into a statistical model. It requires only the functional data and can thus be applied post hoc and without any additional scans., (Copyright 2001 Academic Press.)

There is a growing appreciation of the importance of nonlinearities in evoked responses in fMRI, particularly with the advent of event-related fMRI. These nonlinearities are commonly expressed as interactions among stimuli that can lead to the suppression and increased latency of responses to a stimulus that are incurred by a preceding stimulus. We have presented previously a model-free characterization of these effects using generic techniques from nonlinear system identification, namely a Volterra series formulation. At the same time Buxton et al. (1998) described a plausible and compelling dynamical model of hemodynamic signal transduction in fMRI. Subsequent work by Mandeville et al. (1999) provided important theoretical and empirical constraints on the form of the dynamic relationship between blood flow and volume that underpins the evolution of the fMRI signal. In this paper we combine these system identification and model-based approaches and ask whether the Balloon model is sufficient to account for the nonlinear behaviors observed in real time series. We conclude that it can, and furthermore the model parameters that ensue are biologically plausible. This conclusion is based on the observation that the Balloon model can produce Volterra kernels that emulate empirical kernels. To enable this evaluation we had to embed the Balloon model in a hemodynamic input-state-output model that included the dynamics of perfusion changes that are contingent on underlying synaptic activation. This paper presents (i) the full hemodynamic model (ii), how its associated Volterra kernels can be derived, and (iii) addresses the model's validity in relation to empirical nonlinear characterizations of evoked responses in fMRI and other neurophysiological constraints., (Copyright 2000 Academic Press.)

In this paper we report three neuroimaging studies of language that investigate potential sources of inconsistency in measured hemodynamic responses: (1) between sessions for fMRI, including differences in hormonal status, (2) between sessions for PET, and (3) between scanning modalities (PET and fMRI). Differences in evoked responses between sessions of the same modality were small. In particular we did not find any effect of hormone levels when testing during the first and third weeks of the menstrual cycle (although we cannot exclude the possibility that activation in the temporoparietal regions is sensitive to hormonal status). Comparing the two modalities showed that prefrontal regions were more activated in fMRI than in PET. This may relate to task switching between blocks in fMRI that is not induced by PET paradigms or increased error variance in these regions for PET. In contrast, temporal activations were found in PET more than in fMRI. We attribute the lack of temporal activations, in fMRI, to a combination of factors, including susceptibility artifacts, anticipatory activity during the control condition, discontinuous sampling of peristimulus time, and differences in the source, acquisition, and analysis of the measured signals. It is concluded that although there is sufficient reproducibility of results for these paradigms within each modality, the regionally specific differences in sensitivity found between modalities warrant further investigation. These regionally specific differences are important for a properly qualified interpretation of activation profiles in fMRI., (Copyright 2000 Academic Press.)

Functional magnetic resonance imaging (fMRI) has become a popular tool for investigations into the neural correlates of cognitive activity. One limitation of fMRI, however, is that it has difficulty imaging regions near tissue interfaces due to distortions from macroscopic susceptibility effects which become more severe at higher magnetic field strengths. This difficulty can be particularly problematic for language tasks that engage regions of the temporal lobes near the air-filled sinuses. This paper investigates susceptibility-induced signal loss in the temporal lobes and proposes that by defining a priori regions of interest and using the small-volume statistical correction of K. J. Worsley, S. Marrett, P. Neelin, A. C. Vandal, K. J. Friston, and A. C. Evans (1996, Hum. Brain Mapp. 4: 58-83), activations in these areas can sometimes be detected by increasing the statistical power of the analysis. We conducted two experiments, one with PET and the other with fMRI, using almost identical semantic categorization paradigms and comparable methods of analysis. There were areas of overlap as well as differences between the PET and fMRI results. One anticipated difference was a lack of activation in two regions in the temporal lobe on initial analyses in the fMRI data set. With a specific region of interest, however, activation in one of the regions was detected. These experiments demonstrate three points: first, even for almost identical cognitive tasks such as those in this study, PET and fMRI may not produce identical results; second, differences between the two methods due to macroscopic susceptibility artifacts in fMRI can be overcome with appropriate statistical corrections, but only partially; and third, new data acquisition paradigms are necessary to fully deal with susceptibility-induced signal loss if the sensitivity of the fMRI experiment to temporal lobe activations is to be enhanced., (Copyright 2000 Academic Press.)

In this paper we present an approach to making inferences about generic activations in groups of subjects using fMRI. In particular we suggest that activations common to all subjects reflect aspects of functional anatomy that may be "typical" of the population from which that group was sampled. These commonalities can be identified by a conjunction analysis of the activation effects in which the contrasts, testing for an activation, are specified separately for each subject. A conjunction is the joint refutation of multiple null hypotheses, in this instance, of no activation in any subject. The motivation behind this use of conjunctions is that fixed-effect analyses are generally more "sensitive" than equivalent random-effect analyses. This is because fixed-effect analyses can harness the large degrees of freedom and small scan-to-scan variability (relative to the variability in responses from subject to subject) when assessing the significance of an estimated response. The price one pays for the apparent sensitivity of fixed-effect analyses is that the ensuing inferences pertain to, and only to, the subjects studied. However, a conjunction analysis, using a fixed-effect model, allows one to infer: (i) that every subject studied activated and (ii) that at least a certain proportion of the population would have shown this effect. The second inference depends upon a meta-analytic formulation in terms of a confidence region for this proportion. This approach retains the sensitivity of fixed-effect analyses when the inference that only a substantial proportion of the population activates is sufficient., (Copyright 1999 Academic Press.)

This study investigates word and object processing during naming and viewing tasks and identifies three distinct regions in the left ventral occipitotemporal cortex. Irrespective of task, words and objects (relative to meaningless visual controls) activated the medial surface of the left anterior fusiform gyrus, a region that has previously been associated with semantic knowledge. A more lateral region was differentially active for naming words and objects relative to viewing the same stimuli and a more posterior region was differentially active for objects relative to words irrespective of task. In addition, we found that word processing resulted in greater activation than object processing on the dorsal surface of the left superior temporal gyrus and the left supramarginal gyrus. These regions appear to be important for converting orthography into phonology; their response to words irrespective of task is consistent with established psychological evidence that implicit phonological processing is stronger for words than objects., (Copyright 1999 Academic Press.)

This paper concerns the experimental design and statistical models employed by fMRI activation studies which block presentation of linguistic stimuli. In particular, we note that the relationship between the timing of stimulus presentation and data acquisition can have a substantial impact on the ability to detect activations in critical language areas, even when the stimuli are presented in blocks. Using a blocked word rhyming paradigm and repeated investigations on a single subject, activation was observed in Broca's area (left inferior frontal cortex) and Wernicke's area (left posterior temporoparietal cortex) when (i) the timing of data acquisition was distributed throughout the peristimulus time and (ii) an event-related analysis was used to model the phasic nature of the hemodynamic response within each block of repeated word stimuli. In contrast, when the timing of data acquisition relative to stimulus presentation was fixed, activation was detected in Broca's area but not consistently in Wernicke's area. Our results indicate that phasic responses to stimuli occur even in a blocked design and that the sampling and proper modeling of these responses can have profound effects on their detection. Specifically, distributed sampling over peristimulus time is essential in order to detect small activations particularly when they are transient. These findings are likely to generalize to the detection of transient signals in any cognitive paradigm., (Copyright 1999 Academic Press.)

In this positron emission tomography study, we investigated the neural correlates of semantic priming, where response to a word is facilitated when preceded by a semantically related word. Nine normal subjects were scanned while performing a lexical decision task. Within this condition, the proportion of related prime-target word pairs was varied across scans from 0 to 100%. The control task involved letter decision on consonant letter strings, controlling orthographic processing and response selection. First, lexical decision (relative to letter decision) activated regions previously observed in lexicosemantic tasks, i.e., the left anterior and inferior temporal lobe and left inferior frontal gyrus. Behavioral analysis confirmed significant facilitation of lexical decision to related targets (mean priming effect 68 ms). It also suggested the contribution of both automatic and strategic processes, consistent with theoretical accounts of priming. Automatic priming was indicated by consistent RTs to related targets irrespective of the proportion of related word pairs per scan. Strategic processing was indicated by decreases in RTs to nonwords as the proportion of related targets increased. Nonlinear correlational analysis of cerebral activity during lexical decision revealed a neurophysiological correlate of these behavioral effects in (i) the left anterior temporal lobe (BA 38), a region involved in lexicosemantic processing; (ii) the anterior cingulate cortex, right premotor region (BA 6), and right superior parietal lobe (BA 7), regions associated with attentional processes. We conclude that in this experimental context, semantic priming involves both automatic and strategic processing., (Copyright 1999 Academic Press.)

This paper introduces the concepts and procedures of "cognitive conjunction," a new approach to designing and analyzing cognitive activation experiments. Cognitive conjunction compliments categorical approaches such as cognitive subtraction and requires a specific form of statistical inference that involves the conjunction of several hypotheses. While cognitive subtraction studies are designed such that a pair of tasks differ only by the processing component(s) of interest, cognitive conjunction studies are designed such that two or more distinct task pairs each share a common processing difference. The neural correlates of the process of interest are then associated with the common areas of activation for each task pair. There are two main advantages of cognitive conjunction relative to cognitive subtraction. The first is that it provides a greater latitude for selecting baseline tasks because it is not necessary to control for all but the component of interest. The only constraint on selecting the baseline is that the component of interest is the only process that differs in each task pair. The second advantage is that cognitive conjunction does not depend on "pure insertion"--the assumption that the addition of an extra processing component in the activation task has no effect on the implementation of processes that are also engaged by the baseline task. The differences between the design and the statistical analysis of experiments based on cognitive subtraction, cognitive conjunction, and factorial designs are illustrated with a study of phonological retrieval. Cognitive conjunction analysis indicates that irrespective of whether subjects name words, objects, letters, or colors, there is activation of the left posterior basal temporal lobe, the left frontal operculum, the left thalamus, and the midline cerebellum.