This study contrasted two approaches to word meaning: the statistically determined role of high-contribution features like striped in the meaning of complex nouns like “tiger” typically used in studies of semantic memory, and the contribution of diagnostic features like parent's brother that play a critical role in the meaning of nominal kinds like “uncle.” fMRI monitored regional brain activity while participants read complex noun descriptions consisting of statistically high-contribution and low-contribution features; and nominal kind descriptions consisting of diagnostic and characteristic features. We found different patterns of activation depending on the type of noun and the type of feature contributing to the noun. Complex nouns recruited significantly greater bilateral superior temporal and left prefrontal activation compared to nominal kind nouns, while nominal kind nouns activated bilateral medial parietal and right inferior parietal regions more than complex nouns. Moreover, features making a statistically high contribution to complex noun meaning activated right inferior frontal cortex relative to low-contribution features, while diagnostic features of nominal kinds activated left dorsolateral prefrontal and right parietal regions more than characteristic features. These findings are consistent with the hypothesis that at least two different neural mechanisms appear to support word meaning: one driven by a statistically determined approach to feature knowledge, and the other sensitive to the qualitatively critical role that a specific diagnostic feature plays in word meaning.

We used functional magnetic resonance imaging (fMRI) to test competing claims about the role of executive resources during the disambiguation of a sentence featuring a temporary structural ambiguity. Written sentences with a direct object (DO) structure or a sentential complement (SC) structure were shown to 19 healthy, right-handed, young adults in a phrase-by-phrase manner. These sentences contained a main verb that is statistically more likely to be associated with a DO structure or an SC structure. Half of each type of sentence also contained an extra phrase strategically located to stress working memory prior to disambiguating the sentence. We found that sentences featuring a less consistent verb-structure mapping recruit greater dorsolateral prefrontal cortex (dlPFC) activation than sentences with a more consistent verb-structure mapping, implicating strategic on-line planning during resolution of a temporary structural ambiguity. By comparison, we observed left inferior parietal cortex (IPC) activation in sentences with an increased working memory demand compared to sentences with a low working memory load. These findings are consistent with a large-scale neural network for sentence processing that recruits distinct planning and working memory processing resources as needed to support the comprehension of sentences.

University of Pennsylvania School of Medicine, Department of Neurology, Philadelphia, Pennsylvania, USAAccepted 6 July 2006IntroductionAnomiacanresultfromarangeofperceptualdeficits(e.g.,agnosia);cen-tral semantic degradation (e.g., dementia); impaired linguistic access (e.g.,aphasia);oracombinationofthesefactors(HodgesPMar-tin & Saffran, 1990). One unexplored possibility, however, is that anomiamayalsostemfromimpairedmappingofarbitraryphonologicalformsontoconcepts. Here, we investigated integrity of the phonology-semantics map-pingprocessinapatientwithposteriorcorticalatrophyassociatedwithAlz-heimer’s disease. We predicted that visual deficits should interfere with theability to link phonetic attributes to a novel object. We introduce anapproach, known as phonetic symbolism, to test this hypothesis.Some phonemic combinations have been found to be associated withideas such as magnitude of physical size, brightness, affection, and propernounsacrossmanyunrelatedlanguages(Nuckolls,1999;Ohala,1994;Sapir,1949). This effect, phonetic symbolism, is tested with a novel object and achoiceofpossiblenonwordnames.The‘‘best’’nameisselectedbymappingacoustic-phoneticpropertiesofaworddirectlyontophysicalfeaturesoftheobject (Ohala, 1994). For example, if one is forced to choose between twonames (pleek or ploke) for a tiny, bright yellow animal, they choose Pleekwithagreementfargreaterthanchance.Thischoiceismadethroughnon-ar-bitrary mapping of phonology directly onto an object’s visual attributes.Phonetic symbolism taps many crucial elements of word learning thatarenotdirectlyaccessiblethroughassessmentofknownobjectsandwords.Inordertocorrectlychoosethename,Pleek,apersonmustperceivesalientvisual attributes (e.g., brightness), process acoustic-phonetic features (e.g.,vowel height), and then complete a mapping of these characteristics. Theuse of novel stimuli (both words and objects), therefore, provides a uniqueway of examining potential deficits in word to object mapping.MethodCase descriptionAtrophy in the occipital and temporal visual areas and posterior por-tions of the parietal lobes causes patients with the visual-variant of Alzhei-mer’s disease (vAD) to have object recognition deficits and visuospatialproblems including optic apraxia and simultanagnosia. As vAD evolves,memory and language difficulties also become prevalent (Levine, Lee, F Ross, Graham, Stuart-Green, & Prins, 1996). CP is a 61-year-old, right-handed female diagnosed with vAD through examinationby a behavioral neurologist and consensus review using NINCDS-ADRDA criteria (McKhann et al., 1984).CP initially presented to the University of Pennsylvania (12/03) withsignificant visual-perceptual difficulties (profound difficulty copying thesimplest visual geometric designs) and also demonstrates mild semanticimpairment (Pyramids & Palm Trees Words 46/52). CP shows impairedconfrontation naming of pictures (Boston Naming Test: 3/15) and speechproduction significant for frequent circumlocutions, word-finding pausesand anomia. She was able to read and could appreciate the color butnot the form of visual stimuli. Structural MRI obtained in 2003 revealedleft ventral-occipital and parietal-occipital atrophy as well as mild rightparietal and inferior frontal atrophy Fig. 1.Experiment 1—Phonetic symbolismCP viewed 25 randomized images of novel objects (i.e., blobs, n = 10)and pseudoanimals (n = 15) presented via E-prime software on a laptopcomputer. Stimuli were manipulated by salience of visual features, includ-ing: brightness, physical size, angularity, roundness, motion, and loudness.Two monosyllabic (CVC or CVCC) nonwords appeared below eachimage. Nonwords varied by medial vowel, which maximally differed byplace and height (e.g., pleek–ploke). CP was instructed to ‘‘choose the bestname’’ for each image by signaling with a key-press. 13 healthy controlsdemonstrated high agreement on the target nonword selected as a namefor each item. Small, bright pseudoanimals were associated with high fre-quency/narrow vocal tract vowels; large, dark pseudoanimals with low fre-quency/wide vocal tract vowels; dull, dark blobs with back vowelsproduced with lip rounding; and sharp, bright blobs with high frequen-cy/narrow vocal tract vowels.ResultsCP did show a strong effect of phonetic symbolism for the manipula-tion of ‘‘roundness’’ collapsed across conditions. That is, CP reliably asso-ciated back, rounded vowels (e.g., ‘‘mome’’) with rounded objects andpseudoanimals (8/8) p < .004. Otherwise she did not associate phoneticfeatures with visual-perceptual attributes of novel objects andpseudoanimals.doi:10.1016/j.bandl.2006.06.075* Corresponding author. Fax: +1 215 349 8464.www.elsevier.com/locate/b&lBrain and Language 99 (2006) 8–219

University of Pennsylvania School of Medicine, Department of Neurology, Philadelphia, Pennsylvania, PA, USAAccepted 6 July 2006IntroductionSemantic dementia (SD) results in a progressive loss of conceptualknowledge in the context of preserved syntactic, auditory, and visual spa-tial abilities (Grossman & Ash, 2004; Hodges, 2003; Paterson, Knott, H moderate: 66). The mean MMSEwas 18.75 (mild: 24; moderate: 13.5). Semantic memory impairment asmeasured by the Pyramids and Palm Trees test (Howard & Patterson,1992) averaged, for pictures and words, 43.75/52 (mild: 47.25; moderate:40.25). Average confrontation naming on the Boston Naming Test (Kap-lan, Goodglass, & Weintraub, 1976) averaged 5.75 of 15 (mild: 9; moder-ate: 2.5). All patients passed a pure tone hearing screening at 1, 2, and4 kHz. Patients were instructed through training sessions before each task.All auditory stimuli were digitized and administered by headphones with afrequency response range of 8–25 kHz.Structural MRI scans of milder SD revealed atrophy in the left ventral,anterolateral cortex (see Fig. 1a for VBM analysis of significant corticalatrophy in a mild SD patient). Patients with moderate SD showed atrophyspread to the posterior temporal cortex (see Fig. 1b for a VBM analysis ofsignificant cortical atrophy in a moderate SD patient).Experiment 1: Pure tone acoustic discriminationPure tones varying in frequency from 300 to 5000 Hz were presented inpairs, with a 1000 ms interstimulus interval (ISI). Half the tone pairs wereidentical; the remainder differed by increments of 25–4000 Hz. ParticipantsindicatedwhethereachtonepairwastheSAMEorDIFFERENTwithakeypress.ResultsOverall accuracy of pure tone discrimination was 82.5% (p < .001,binomial test differing from chance). The within-group contrast of mildSD versus moderate SD demonstrated greater discrimination difficultyin moderate SD (mild accuracy: 90%; moderate accuracy: 75%;v

We assessed cerebrospinal fluid (CSF) levels of tau and other biomarkers of neurodegenerative disease. CSF tau levels vary widely in reports of frontotemporal dementia (FTD). CSF samples were assayed for tau, amyloid β 1‐42 (A 1‐42 ), and the isoprostane 8,12‐ iso ‐iPF 2a ‐VI (iP) prospectively in 64 patients with FTD, retrospectively in 26 autopsied cases with FTD or Alzheimer's disease (AD), and in 13 healthy seniors. To validate our observations in vivo, we correlated CSF tau levels with cortical atrophy in 17 FTD patients using voxel‐based morphometry analyses of high‐resolution magnetic resonance imaging. CSF levels of tau, Aβ 1‐42 , and iP differed significantly in FTD compared with AD. Individual patient analyses showed that 34% of FD patients had significantly low levels of CSF tau, although this was never seen in AD. A discriminant analysis based on CSF levels of tau, Aβ 1‐42 , and iP was able to classify 88.5% of these patients in a manner that corresponds to their clinical or autopsy diagnosis. Magnetic resonance imaging studies showed that CSF tau levels correlate significantly with right frontal and left temporal cortical atrophy, brain regions known to be atrophic in patients with autopsy‐proved FTD. We conclude that CSF tau levels are significantly reduced in many patients with FTD. Ann Neurol 2005;57:721–729