Defective recognition and naming of famous people from voice in patients with unilateral temporal lobe tumours

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Defective recognition and naming of famous people from voice in patients with unilateral temporal lobe tumours C. Papagnoa,b,

⁎,1

, G. Mattavellib, A. Casarottic, L. Belloc,d, G. Gainottie,f

a

CeRiN and CIMeC, University of Trento, 38068 Rovereto, Italy Department of Psychology, Centre for Neuroscience, University of Milano-Bicocca, Milano, Italy c Unit of Surgical Neurooncology, Humanitas Research Hospital, Milano, Italy d Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Italy e Institute of Neurology, UCSC University, Roma, Italy f IRCCS Fondazione Santa Lucia, Department of Clinical and Behavioral Neurology, Rome, Italy b

A R T I C L E I N F O

A B S T R A C T

Keywords: Famous voice recognition Unfamiliar voice discrimination Temporal lobe gliomas Lesion laterality Hierarchical models of voice processing

Twenty-nine patients who underwent surgery for a temporal glioma, either in the left (16 patients) or right (13 patients) hemisphere, were administered standardized tests of unknown voice discrimination (UVD) and of famous voice recognition (VO-REC), which included tasks of familiarity evaluation, semantic identification and naming of famous voices. The UVD consisted of twenty stimuli, in which two audio files were consecutively presented; the subject was requested to judge whether the voices belonged to the same or different persons. In the VO-REC, patients were requested to recognize the voices of 40 very well known people; these voices were intermingled with the voices of 20 unknown people for a familiarity check, followed by identification and naming of persons recognized as familiar. We aimed at verifying the effect of laterality and intra-temporal site of lesion on familiarity assessment, false alarms, identification and naming of familiar people. As for the effect of lesion side, our results showed that patients with right temporal gliomas were significantly more impaired in voices discrimination and produced more false alarms than patients with a left glioma, who, in turn, were significantly more impaired in name retrieval than patients with a right temporal glioma. The high number of false alarms in patients with a right temporal glioma suggests that familiarity judgment was impaired. Regarding the neuroanatomical correlates of these different patterns of impairment, MRI data suggested that: (a) UVD disorders are due to lesions involving the whole right anterior temporal lobe and extending to lateral portions of the temporal and frontal lobes; (b) familiarity judgments (testified by an increased number of false alarms) are impaired in lesions restricted to the right anterior temporal lobe; (c) name retrieval deficits are found only in patients with left temporal lesions. UVD disorders were interpreted, at least in part, as due to an impairment of executive functions, resulting from a disconnection of the right temporal lobe from the frontal lobe control. A partly unexpected finding was that some patients with a right temporal tumour had a normal performance in famous voice recognition and identification, in spite of having severe voice discrimination disturbances. These unexpected results, in agreement with previous observation made in the visual (face) modality, are inconsistent with strictly hierarchical models of voice processing.

1. Introduction In humans and in other social species identification of subjects belonging to the same or to a different social group is a fundamental biological function, which has prompted the development in the brain of a complex multimodal recognition system. This system is based on three main sources of information: the face (in the visual modality), the voice (in the auditory modality) and the proper name (in the verbal modality). ⁎

1

Recently, Gainotti (2013a) and Hanley (2014) have reviewed behavioural, neurophysiological and neuroimaging studies, aiming at investigating the neuroanatomical correlates of familiar people recognition through personal name. Behavioural studies, mainly conducted with the divided visual field technique, have consistently shown that recognition of familiar names is lateralized to the left hemisphere. Even if Ohnesorge and Van Lancker (2001) had claimed that the right hemisphere plays an important role in the recognition of famous proper names, Schweinberger et al. (2002a, 2002b) showed that the "link"

Corresponding author at: CeRiN and CIMeC, University of Trento, 38068 Rovereto, Italy. E-mail addresses: [email protected], [email protected] (C. Papagno). CIMeC and CeRiN, University of Trento, via M. Del Ben 5, RoveretoDepartmento of Psychology, University of Milano-Bicocca, Edificio U6, Piazza dell’Ateneo Nuovo 1, Milano.

http://dx.doi.org/10.1016/j.neuropsychologia.2017.07.021 Received 2 March 2017; Received in revised form 13 July 2017; Accepted 17 July 2017 0028-3932/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Papagno, C., Neuropsychologia (2017), http://dx.doi.org/10.1016/j.neuropsychologia.2017.07.021

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have recently failed to confirm this hierarchical organization, because they have shown a high inter-individual variability in the location of the TVAs and highlighted three bilateral clusters of voice-sensitivity, or “voice patches” along posterior (TVAp), mid (TVAm) and anterior (TVAa) superior temporal sulcus and gyrus, respectively. The third source of evidence suggesting a dominance of faces over voices in familiar people identification is the imbalance between the very large number of papers that have investigated face recognition disorders (see Gainotti and Marra, 2011 and Davies-Thompson et al., 2014 for recent reviews), and the handful of articles that have studied voice recognition disorders resulting from brain damage. As for face recognition disorders, Bodamer (1947) proposed the term ‘prosopagnosia’ to denote a form of visual agnosia, selectively affecting face recognition, and many years later De Renzi et al. (1991) distinguished ‘apperceptive’ and ‘associative’ forms of prosopagnosia. The former consists of a deficit not only in the recognition of familiar faces, but also in the discrimination of unfamiliar faces and in processing non personspecific face information (such as age, gender and emotional expression of a target face); this has been ascribed to a high-level visual deficit. The latter, namely associative prosopoagnosia, is a specific impairment in the recognition of familiar faces, with no problems in the discrimination of unfamiliar faces and other subtle visual deficits; this disorder has been attributed to mnesic or associative disturbances. Several years after the identification of prosopagnosia, Van Lancker and Canter (1982) reported instances of voice recognition disorders, that they labelled ‘Phonagnosia’(in analogy with the term ‘prosopagnosia’), to denote voice recognition disorders, that were significantly more prevalent in right-hemisphere patients. Moreover, Van Lancker and Kreiman (1987) and Van Lancker et al. (1988) also applied to phonagnosia the distinction between perceptual (apperceptive) and associative form of voice recognition disorders. As we have previously mentioned, very few anatomo-clinical investigations have studied voice recognition disorders in patients with focal or widespread brain damage. Some studies on groups of unselected right and left brain-damaged subjects and on individual patients with face recognition disorders resulting from right ATL lesions have been reviewed some years ago by Gainotti (2011). Results of that review showed that voice recognition disorders are mainly due to right temporal lesions (analogously to face recognition disorders) and that famous voice recognition disorders can be dissociated from unfamiliar voice discrimination impairments. Furthermore, in two studies by Van Lancker et al. (1988) and by Van Lancker et al. (1989), familiar voice recognition deficits significantly correlated with a right parietal lobe damage, whereas the voice discrimination deficit was associated with a temporal lobe damage either of the right or left hemisphere. The value of these anatomo-clinical correlations is limited by two reasons: (a) they are based on computer tomography which has a poor discriminative power; (b) they are not in line with the results of an event-related fMRI speaker recognition study, in which Bethmann et al. (2012) showed that the temporal lobes (and more precisely the upper and lower banks of the superior temporal sulcus) differentiate between voices of famous and unknown people. On the contrary, the experimental results obtained by Bethmann et al. (2012) are consistent with the anatomo-clinical data reported by Hailstone et al. (2010) in the only case of ‘progressive associative phonagnosia’ that, to our knowledge, has been described in the neuropsychological literature and by Hailstone et al. (2011) in a more general study on voice processing in dementia. As a matter of fact, patient QR, reported by Hailstone et al. (2010) and classified as a behavioural variant of Fronto-Temporal Dementia, showed a fronto-temporal atrophy, which spanned from the temporal pole to the superior temporal sulcus and was more evident on the right side. In a following paper, Hailstone et al. (2011) compared results obtained on tasks of voice recognition (familiarity, identification, naming and cross-modal matching) by patients with Alzheimer's disease and patients with the temporal variant of fronto-temporal degeneration with those obtained by a healthy matched control group, using voxel-based morphometry to assess the

between personal names and the right hemisphere is "illusory" and that a large right visual field advantage exists for famous names, but not for unfamiliar names. Furthermore, Schweinberger et al. (2002a, 2002b) presented, in reply to the comment raised by Van Lancker and Ohnesorge (2002), a new set of divided visual field experiments that supported the role of the left hemisphere in the recognition of famous personal names. Neurophysiological investigations using event-related potentials (ERPs) repetition priming (e.g. Pfutze et al., 2002) have confirmed and specified these findings, highlighting an increased negativity over left temporal areas for familiar but not unfamiliar names. Finally, functional neuroimaging investigations have shown that left temporal areas are activated by proper name processing (e.g. GornoTempini et al., 1998) and that the left anterior temporal lobe (ATL) is strongly involved in proper name retrieval (e.g. Grabowski et al., 2001; Tsukiura et al., 2002). Even if it could be objected that these results simply confirm the left hemisphere competence for linguistic functions, it must be noticed that most of them specifically concerned familiar but not unfamiliar names. Furthermore, the specific representation of familiar names (or personally relevant nouns) is confirmed by data gathered by Van Lanker and Klein (1990) and by Van Lanker and Nicklay (1992) in aphasic patients, because these studies showed a preserved recognition of familiar personal names and a comprehension of personally relevant language in patients with global aphasia. Van Lancker et al. (1991) also showed, in a group of unilateral brain-damaged patients, a right hemisphere ability to recognize personal names. On the other hand, clinical and functional neuroimaging investigations focusing on the perceptual channels of person recognition have shown that highly specific brain structures underlie the identification of familiar people through the visual (face) and the auditory (voice) modality. However, they have also provided a very imbalanced body of knowledge about these perceptual channels of people recognition, suggesting that, from this point of view, faces play a dominant role with respect to voices. Three main sources of evidence support this statement. The first is that data gathered in the field of the experimental social psychology (e.g. Hanley et al., 1998; Damjanovic and Hanley, 2007; Brédart et al., 2009; Hanley and Damjanovic, 2009; Barsics and Brédart, 2011; Barsics and Brédart, 2012) have documented an advantage of faces over voices in terms of access to personal semantic and episodic information. The second source of evidence is that our knowledge of the neural substrates of face recognition is richer and more structured than that concerning brain structures that support voice recognition. All authors acknowledge, in fact, that face recognition is based on the activity of a large network (Haxby et al., 2000) more represented in the right hemisphere (Sergent and Signoret, 1992; Rossion et al., 2012), that includes, in addition to the face fusiform area (FFA)(Kanwisher et al., 1997), the occipital face area (OFA) (Gauthier et al., 2000), the ATL (Barton, 2008; Gainotti, 2013b) and their interconnections (Fox et al., 2008). Furthermore (even if the role of these different regions is controversial), a hierarchy has been proposed between the OFA, which shows sensitivity to physical properties of a face (Pitcher et al., 2011), the FFA that could be involved in perceiving the facial configuration (Parvizi et al., 2012) and the ATL that could allow facial identification (Barton, 2008). As for the neural substrate of voice recognition, functional magnetic resonance imaging studies (fMRI) conducted by several authors (e.g. Belin et al., 2000; Belin et al., 2002; Pernet et al., 2015) have documented higher responses to vocal than to non-vocal sounds in the so-called temporal voice areas (TVAs), that are located in the bilateral superior temporal sulcus and gyrus. Furthermore, as in the case of face recognition, a more important role of the right TVAs in voice (compared to speech) recognition has been shown by von Kriegstein et al. (2003) and by Von Kriegstein and Giraud (2004). A hierarchical organization of the TVAs similar to that observed in the face processing network, with differences between unfamiliar and highly familiar voices increasing towards the anterior temporal cortex, has been reported by some authors (e.g. Bethmann et al., 2012). However, Pernet et al. (2015) 2

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surgery (see Table 2 for neuropsychological results on the main tests). For all the reported tests, including the voice discrimination and recognition tasks, Italian normative data are available: raw scores are adjusted for age, education and, when indicated, for sex, according to the parameters estimated in a normal sample (200–321 neurologically unimpaired subjects) with a multiple regression model (for a detailed explanation of this procedure, see Capitani et al., 1997). During the follow-up phase, patients were submitted to two tests assessing voice recognition (Quaranta et al., 2016).

neuroanatomical regions associated to voice processing performance. The neuroanatomical analysis across both patients’ groups revealed association of familiarity, identification and cross-modal recognition impairments with grey matter loss in the right temporal pole and anterior fusiform gyrus. The neuroanatomical correlates of familiar voice recognition disorders are, therefore, at least in part still controversial with respect to both the prevalent role of the right hemisphere and the intra-hemispheric locus of lesions subsuming a voice discrimination and a voice recognition deficit. Since these inconsistencies are probably in part due to the heterogeneous nature of the patients studied (single-case vs. group studies and vascular vs. degenerative diseases) and of the methods (CT scan vs. MRI) used to collect the neuroanatomical data, we thought it useful to take again into account these problems in a group of patients affected by right or left temporal gliomas, using new tests to assess voice discrimination and voice recognition and MRI to perform the individual lesion mapping. The study was run on patients with temporal gliomas because, as suggested by Campanella et al. (2010), brain tumours can be a relevant source of information in the study of the neuropathological correlates of cognitive disorders. Indeed, some authors (e.g. Bartolomeo, 2011 and Mah et al., 2014) have observed that the typical lesion mapping studies based on groups of vascular patients are prone to substantial spatial distortions, because in these patients, lesions do not follow the functional circuits of the brain, but rather the architecture of its vascular tree. Therefore, studies on cerebrovascular diseases suffer similar limitations than studies on gliomas. The principal aim of the study, therefore, consisted in comparing results obtained on various aspects of voice processing (unknown voice discrimination; familiarity assessment, false alarms and semantic retrieval from voices of famous people; name retrieval from famous voices judged as familiar) by two groups of patients with either a right (RBD) or left temporal (LBD) glioma. A second purpose of our study was to evaluate the anatomo-clinical correlates in subjects with a defect in unknown voice discrimination, familiarity assessment, false alarms, semantic recognition and naming and with a dissociation between preserved voice discrimination, but impaired voice recognition, or, on the contrary, impaired voice discrimination, but preserved voice recognition.

3.1. Unknown voice discrimination (UVD) The test consisted of twenty stimuli, in which two audio files lasting about 15 s were consecutively presented; the subject was requested to judge whether the voices belonged to the same or to different persons. The duration of 15 s was chosen according to Waldron et al. (2014). To reduce the possible interference of the sentence content, the stimuli were subdivided into four groups: same voice/ same phrase; same voice/different phrase; different voice/same phrase; different voice/ different phrase. The total score was obtained by summing the correct answers (range:0–20). The raw score was adjusted for age and education level. Adjusted scores 55% one-sided non-parametric tolerance limit (with 95% CI) are considered pathological: inferential cut-off scores are therefore those at which or below which the probability that an individual belongs to the normal population is < 0.05. Pathological scores are those under the cut-off, and correspond to an equivalent score of 0 (see Table 3 for an explanation of equivalent scores). A performance is considered borderline when the equivalent score is 1. The cut-off score for this test is 13.71. 3.2. Familiarity evaluation, identification and naming of famous people from voices (VO-REC) The VO-REC included 60 items, 40 famous voices (i.e. voices of persons very well known at the national level) and 20 non-famous voices. A pool of fifty-five famous persons was initially selected; audio fragments were extracted from publicly available video or audio recordings. This initial pool of items was administered to a group of 20 subjects of different age and education, who were requested to identify the person to whom the voice belonged. The items were then rankordered on the basis of the frequency of correct answers and the first 40 items were selected for the final version of the test. Each fragment lasted about 15 s and did not contain any element that could allow the direct recognition of the person (neutral discourses). Each subject was asked to carefully listen to the audio fragment and provide a familiarity judgment (‘‘is this voice familiar to you?’’). The familiarity score was obtained by summing the number of voices correctly identified as familiar or as non-familiar (score range: 0–60); a false alarm score was also obtained and corresponded to the number of non-famous voices identified as famous (score range: 0–20). Cut-off scores for familiarity and false alarms are 35.56 and 8.5, respectively (in the case of false alarms normal scores are < 8.5). If the patient judged the voice as familiar and this answer was correct, he/she was asked three further questions. The first two questions had a multiple-choice format and explored the general and specific categories to which famous people belonged. An example of general information (first question) is the following: ‘‘is this person involved in (a) politics; (b) entertainment; (c) sport; (d) civil society?’’; an example of specific information (second question) is the following: ‘‘is this entertainer involved in (a) cinema; (b) theatre; (c) music; (d) TV?’’. The third question was open and the subject was asked to provide univocally identifying information about the person (i.e., movies’ titles, political roles and parties, etc.). One point was assigned to each correct answer (semantic score for each voice: 0–3; total semantic score: 0–120). The cut-off score for semantic information is 34.46.

2. Participants Twenty-nine patients (10 female and 19 male) [mean age 40.93 (SD = 12.45, range = 21–68), mean education 13.97 years (SD = 3.02, range = 8–17)], who underwent surgery for a temporal glioma, either in the left (16 patients) or right (13 patients) hemisphere took part in the study (see Table 1 for patients’ demographic and clinical data). They were tested between October 2013 and October 2016. They were selected according to lesion site, namely either a left or right temporal localization. None of the left brain-damaged people suffered comprehension deficits; only one was impaired in two lexical retrieval tasks, namely picture naming of objects and verbal fluency on semantic cue, while two patients were impaired in one task of verbal fluency (either on semantic or phonologic cue) and two more participants were mildly impaired in picture naming of objects (but not action naming) (see Table 2 for results on neuropsychological tests). Patients with a left temporal and right temporal glioma did not differ in age [t(27) = −0.5, p = 0.62] or years of education [t(27) = −0.42, p = 0.68], or tumour volume [RBD mean volume 31.65, SD = 22.15; LBD mean 28.18, SD = 29.62; t(20) = −0.29, p = 0.78]. Histology was defined according to the World Health Organization (WHO) brain tumour classification. 3. Methods An extensive neuropsychological evaluation, including language, attention, executive and memory tests, and an MRI were performed before and after surgery, and in the follow-up at three months after 3

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Table 1 Demographical and clinical data of 16 left temporal and 13 right temporal patients. N.

Sex

Age

Education

site

Onset

diagnosis-surgery interval

Seizures after diagnosis

WHO

Histology

Volume

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

F M F M M M F F M M M M M M M M M F M F M F F M M F F M M

38 41 58 43 39 21 42 28 27 50 41 64 40 37 33 36 43 57 68 37 58 38 38 32 56 24 24 50 25

13 17 13 13 17 13 13 17 16 8 17 17 13 8 17 8 13 17 8 13 17 13 13 13 13 16 15 17 17

L L L L L L L L L L L L L L L L R R R R R R R R R R R R R

GS GS GS GS anomia GS PS Cacosmia PS GS GS GD GS PS GS GS GS GS MD GS PS headache GS PS GS PS GS anomia GS

2 1 8 1 2 6 2 5 7 5 1 1 5 1 1 2 2 1 2 5 2 11 1 4 5 2 1 2 2

0 0 0 0 0 0 0 0 1 0 0 0 1 after surgery 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

LGG HGG LGG LGG ELGG LGG LGG HGG ELGG LGG LGG HGG LGG ELGG LGG ELGG LGG LGG HGG ELGG ELGG LGG ELGG LGG LGG LGG ELGG ELGG ELGG

OGD II GBL IV Astrocitoma II ODG II AA III DNT ODG II GBL IV GG III Gliosis ODG II GBL IV Dysembrioplastic I AA III GG I AA III ODG II ODG II GBL IV AA III Anaplastic ODG III Astrocitoma II Anaplastic OA III OA II ODG II Cavernous angioma ODG III ODG III Anaplastic OA III

43 5.19 31.5 25.26 1.55 82.706 11.492 3.672 41.82 19.298 3.162 95.07 1.593 29.281

31

65.03 13.981 14.90 1.919 45.967 55.871 24.535

Education is reported in years. Interval onset-surgery is expressed in months. F = female, M = male; L = left; R = right; GS = generalized seizure, PS = partial seizure, GD = gait disorders; MD = motor disorders. LGG = low-grade glioma; ELGG = evolution low-grade glioma; HGG = high-grade glioma. ODG = oligodendroglioma; GBL = glioblastoma; GG: ganglioglioma; OA: oligoastrocytoma; AA: anaplastic astrocytoma; AODG: anaplastic oligodendroglioma.

Table 2 Neuropsychological data of patients submitted to the voice discrimination and voice recognition tasks. CPM = Colored Progressive matrices, TMT = trail making Test. Pathological scores are reported in bold. Stimuli for object naming and word comprehension are 48, while for action naming 50.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Verbal fluency

Token Test

Naming

n.v. ≥ 29

Object n.v. ≥ 41.49

Action n.v. ≥ 36.87

phon n.v. ≥ 17

Sem. n.v. ≥ 25

n.v. ≥ 47.09

forward n.v. ≥ 3.75

46.38 46.38 47.21 46.38 46.38 40.77 46.38 48 43.77 48 34.48 39.41 45.38 44.59 48 38.18 46.59 48 47 48 47.21 48 46.38 45.97 46 48 48 48 48

47.70 43.40 44.10 47 44.40 37.60 44 41.70 45 50 43.40 45.20 47.70 44.70 43.10 39.70 46 42.80 45.20 47.40 50 43.70 46.70 47.40 44.10 42.70 44 42.10 45.60

44 19 28 45 23 21 38 27 32 43 40 26 6 20 28 19 42 37 30 38 25 35 24 48 33 17 30 22 35

51 51 29 67 34 18 44 35 30 69 20 37 32 34 36 25 48 51 48 35 49 36 36 40 40 25 46 34 50

48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

5.50 5.25 3.75 7.50 5.25 4 5.50 5.25 5 5 5.25 5.50 4.50 6.50 6.25 5.50 5.50 5.50 6.25 5.50 3.50 5.50 5.50 3.50 9 5 7.68 5.25 6

32 31.75 32.25 32.50 31.75 32 31.50 31.25 31.75 33 30.75 29.25 31.50 32 31.75 30.50 31.50 31.75 34 31.50 33 32.50 31.50 30.50 32.50 31.25 32.50 31 30.75

Word comprehension

Digit span

4

Corsi span

CPM

TMT B-A

Attentional Matrices

backward n.v. ≥ 3.29

n.v. > 3.50

n.v. ≥ 18

n.v. ≤187

n.v. ≥ 31

3.52 4.37 3.87 5.58 2.37 2.38 4.58 3.29 3.29 4.02 5.37 3.76 4.58 3.52 5.26 2.52 5.64 3.58 4.39 4.52 3.66 4.58 3.58 3.47 5.79 4.21 3.64 4.50 5.21

4.75 5.25 4 4.50 4.25 4.25 4.75 5.50 5.25 6 4.50 4.75 3.50 5.50 4.25 4.50 5.50 4.75 5.25 4.75 4.50 4.75 5.75 3.50 4.75 4.25 3.67 5.50 4.25

33.50 60 26.50 33.50 32 29 26.50 36 31 34 31 30.50 32.50 36 36 25 36 36 32.50 32 36 32.50 32.50 36 32 29 33 29 31

35 89 43 76 70 118 50 79 88 26 86 40 68 66 91 135 26 59 11 70 45 51 92 76 57 106 45 99 98

60 60 51.50 60 40.25 46.75 50.75 46 41.25 60 43.25 47.25 43.25 45.25 44.25 48.25 60 44 54.50 49.75 60 48.75 49.75 45.25 52.50 44 48.25 43.25 43.25

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Table 3 Patients’ scores in the voice discrimination and voice recognition tasks. N

UVD (n.v. > 13.71)

VO REC familiarity (n.v. > 35.56)

VO REC false alarms (n.v. ≥ 8.5)

VO REC semantics (n.v. ≥ 34.46)

Naming (n.v. > 14.71)

Naming % score (n.v. > 36.77)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

17.81[4] 13.09 [0] 17.81[4] 16.81 [3] 17.09 [3] 14.81 [2] 17.81 [4] 16.09 [3] 16.09 [3] 19.71 [4] 12.09 [0] 17.09 [3] 16.81 [2] 17.71 [4] 17.09 [3] 20 [4] 16.81 [3] 9.09 [0] 11.71 [0] 20 [4] 15.09 [2] 11.81 [0] 12.81 [0] 16.81 [3] 9.81 [0] 14.09 [2] 15.81 [3] 11.09 [0] 15.09 [2]

48.6 [3] 52.28 [4] 40.6 [2] 36.6 [1] 50.28 [4] 39.6 [2] 46.6 [3] 40.28 [2] 40.28 [2] 55.44 [4] 49.28 [4] 39.28 [1] 50.60 [4] 45.44 [3] 14.28 [0] 51.44 [4] 45.60 [3] 45.28 [3] 38.44 [1] 51.6 [4] 41.28 [2] 37.6 [1] 45.6 [3] 27.6 [0] 38.6 [1] 28.28 [0] 27.60 [0] 38.28 [1] 43.28 [2]

0 [4] 2.51 [3] 1.28 [4] 1.28 [4] 0 [4] 0 [4] 1.28 [4] 0 [4] 0 [4] 3.69 [2] 1.51 [3] 0 [4] 0 [4] 0 [4] 0 [4] 0 [4] 12.28 [0] 7.51 [1] 20 [0] 0 [4] 1.51 [3] 1.28 [4] 1.28 [4] 0 [4] 11.28 [0] 6.51 [1] 0 [4] 5.51 [1] 11.51 [0]

61.66 [3] 67.82 [3] 35.66 [1] 36.66 [1] 55.82 [3] 38.66 [1] 51.66 [2] 55.82 [3] 44.82 [2] 88.54 [4] 70.82 [4] 42.82 [2] 82.66 [4] 69.54 [4] 35.82 [1] 89.54 [4] 87.66 [4] 61.82 [3] 97.54 [4] 77.56 [4] 48.82 [2] 39.66 [1] 66.66 [3] 17.66 [0] 63.66 [3] 20.82 [0] 15.66 [0] 58.82 [3] 62.82 [3]

13 7 5 9 5 4 9 10 9 13 7 2 13 4 1 1 21 19 27 18 14 10 15 5 12 5 4 19 17

32.5 17.5 12.5 22.5 12.5 10 22.5 25 22.5 32.5 17.5 5 32.5 10 2.5 2.5 52.5 47.5 67.5 45 35 25 37.5 12.5 30 12.5 10 47.5 42.5

UDV = unknown voice discrimination; VO REC = voice recognition, Cut-off and equivalent scores in brackets. Since cut-off scores are not yet available for naming, we have considered 2 SD below the controls’ mean. Adjusted scores are transformed into a five-point interval scale, from 0 to 4 equivalent scores. Zero corresponds to a score below the 5% tolerance limit. Four means better than the mean, and 1, 2, and 3 are intermediated between 0 and on a quasi-interval scale. The main advantage of the equivalent score method is that the sector amplitude for equivalent score 1, 2, 3 compared to 0 depends on the tolerance limit at 95% which in turn depends on the sample size. Equivalent Scores simply combine non-parametric tolerance limits and the demographic adjustment (for a detailed discussion on this point, see Capitani, 1997).

then smoothed in the three planes and inspected by a skilled neurologist and neurosurgeon to ensure that surgery boundaries were correctly defined. Lastly, lesion maps and patients’ MRIs were normalized to an MNI T1 template in SPM8 (Statistical Parametric Mapping; Ashburner and Friston, 1999). The lesion analysis was performed on MRI obtained the same day as testing. After mapping the lesion, we overlapped impaired patients’ maps.

Finally, the patient was asked whether he/she could provide the name of that person. The naming score corresponded to the number of familiar voices correctly named (total naming score: 0–40, cut-off score 15). 3.3. MRI acquisition and lesion mapping MRI was performed on a 3 T MR scanner (Siemens Verio, Erlangen, Germany). Standard MR evaluation for morphological characterization of lesions included axial T2-weighted TSE sequence (TR/TE 3000/ 85 ms; field of view (FOV), 230 mm; 22 slices; section thickness, 5/1mm gap; matrix, 512 × 512; SENSE factor, 1.5), axial 3D-FLAIR sequence (TR/TE 10 000/110 ms; FOV, 230 mm; 120 slices; section thickness, 1.5/0-mm gap; matrix, 224 × 256; SENSE factor, 2) and postcontrast T1-weighted inversion recovery sequence (TR/TE 2000/ 10 ms; FOV, 230 mm; 22 slices; section thickness, 5/1-mm gap; matrix, 400 × 512; SENSE factor, 1.5). Lesion volume was calculated with semi-automatic segmentation with region of interest analysis with iPlan Cranial 3.0 software suite (Brainlab, Feldkirchen, Germany). FLAIR hyperintense and gadolinium-enhanced signal abnormalities were included in the lesion load for low-grade and high-grade gliomas, respectively, and then reported in cm3. The extent of resection (EOR) was measured on pre- and post-operative MR performed after surgery, and classified as previously reported (EOR = [(pre-operative volume - postoperative volume)/pre-operative volume)]*100 (Smith et al., 2008). Individual lesion mapping was performed by two independent judges who manually traced a volume of interest (VOI) overlapping lesion boundaries on each relevant T1 MRI axial slice in MRIcron software (www.mricro.com/mricron). VOI included areas with altered signal, namely the regions removed by surgical procedure. Lesions were

4. Results 4.1. Comparison between patients with right and left temporal tumours At the general neuropsychological examination LBD patients’ performance (M = 44.35, SD = 4.02) significantly differed from RBD patients’ one (M = 47.32; SD = 0.83) only in picture naming of objects [t (16.57) = −2.87, p = 0.011]. The two groups did not differ for other neuropsychological tests included in the battery: Token Test [t (27) = −0.79, p = 0.44], action naming [t(27) = −0.89, p = 0.38], verbal fluency on phonemic [t(27) = −0.89, p = 0.38] and semantic cue [t(27) = −0.68, p = 0.5], span forward [t(27) = −0.73, p = 0.47], span backward [t(27) = −1.37, p = 0.18], Corsi span [t(27) = 0.05, p = 0.96], Colored Progressive Matrices [t(27) = 0.18, p = 0.85], TMT (B-A) [t(27) = 0.75, p = 0.46] and attentional matrices [t (27) = −0.09, p = 0.93]. Concerning unknown voice discrimination, six RBD patients and only two LBD performed under the cut-off. When the two groups were compared, we found that LBD patients performed significantly better (M = 16.53, SD = 1.93) than RBD [13.85, SD = 3.15; t(26) = 2.76, p = 0.011]. 5

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broader involvement of medial subcortical regions, frontal, insular and temporal cortices, including the fusiform gyrus and the Heschl gyrus, whereas in three RBD patients with preserved voice discrimination, but impaired voice recognition (Numbers 24, 26, 27) the lesion was restricted to the ATL and the inferior frontal lobe. To further explore the involvement of the white matter in these two subgroups of patients, lesions were superimposed to a template of subcortical tracts (Catani and Thiebaut de Schotten, 2008). This revealed that the inferior occipito-frontal fasciculus was largely involved in at least three patients (18, 23, 28) with voice discrimination deficit, whereas two patients with selective impairment of voice recognition (24, 27) had only little involvement of the frontal head of the fasciculus; the uncinate fasciculus was damaged in all patients with impaired voice discrimination and for three of them (18, 23, 28), also the dorsal part of the fasciculus was damaged, whereas only two patients with impaired voice recognition (24, 27) had a damage of the uncinate fasciculus and only in its ventral head (Fig. 4).

For the VO-REC, four different scores were analyzed, namely familiarity, false alarms, semantic information, and naming. In voice familiarity, three RBD patients and only one LBD produced a pathological performance. One patient with a right temporal glioma reported as familiar all voices. Independent sample t-test performed to compare the two groups showed that the difference was not significant [t (27) = 1.09, p = 0.29]. However, RBD patients produced a significant higher number of false alarms (M = 6.05, SD = 6.25) than LBD (M = 0.72, SD = 1.12; t (27) = −3.36, p = 0.002): indeed, four patients performed pathologically and three borderline, while none of the LBD produced a pathological or borderline number of false alarms. RBD and LBD patients did not differ also in semantic recognition from voice [t (27) = 0.32, p = 0.75; RBD M = 55.32 (DS = 25.98), LBD M = 57.96 (SD = 18.61)]. However, three RBD patients performed under the cut-off in this task, while none of the LBD patients was impaired in semantic recognition. In addition, one RBD patient and four LBD patients produced a borderline score (equivalent score 1). Crucially, none of the RBD patients with an impaired unknown voice discrimination performance showed a deficit in semantic recognition, while all RBD patients unable to give a correct familiarity judgment were also unable to retrieve the corresponding semantic information. If we consider that (at the individual level) identification was not assessed for items considered as non-familiar by the subject, this result strongly emphasizes the relationships between the systems underlying familiarity and identification processes. Finally, patients’ ability in producing proper names of famous people from voice was analyzed with an ANOVA with lesion side as between subject factor, the absolute naming score as dependent variable and familiarity score as covariate, to control for differences related to the fact that a voice not recognized as famous could not be named. This analysis showed a significant effect of the covariate [F(1,26) = 13.18, p = 0.001] and a significant effect of lesion side [F(1,26) = 24.53, p < 0.001], with RBD patients performing significantly better (M = 14.31, SD = 6.92) than LBD (M = 6.81, SD = 4.31).

5. Discussion In the present discussion, we will first summarize the results obtained comparing patients with right and left temporal gliomas and then we will try to integrate these data with the results obtained studying the neuroanatomical correlates of specific defects in unknown voice discrimination and in famous voice recognition. In our comparative group study, 29 patients who underwent surgery for removal of a temporal lobe glioma were examined with two different voice processing tasks: an unknown voice discrimination test and a test of recognition, identification and naming of famous people from their voice. The main results were: 1) an impaired performance in voice discrimination in patients with a right glioma as compared with patients with a left glioma; 2) an increased amount of false alarms in RBD patients as compared with LBD patients; 3) a lack of significant difference between RBD and LBD patients in people identification from voices; 4) a significantly greater impairment of LBD than RBD patients in retrieving the names of famous people whose voices had been judged as familiar.

4.2. Anatomo-clinical correlates in subjects with a defect in voice discrimination, recognition and naming Figs. 1–3 report the lesion overlapping of patients with different types of impaired performance. Sites of maximum overlapping for each test are reported for regions damaged in at least 75% of patients with a pathological score: number of damaged voxels and its percentage within each region are reported in Tables 4–8 (Appendix). Inspection of Fig. 1 seems to suggest that UVD disorders are mainly observed in patients with lesions involving the whole right ATL and extending to the lateral portions of the temporal and frontal lobe, whereas on the left side only a smaller and more mesial part of the ATL is involved. Data reported in Fig. 2 suggest that only the right ATL is consistently affected in patients with a high number of false alarms. Finally, Fig. 3 shows that the lesion overlap differs when semantic recognition and naming are impaired. In the first case the lesions mainly involve the right temporal (and frontal) lobes, whereas in patients with a naming impairment, the left temporal lobe is selectively affected. Lesion comparison of patients with selective impairment in voice discrimination or voice recognition showed that six right tumour patients with impaired voice discrimination (Numbers 18, 19, 22, 23, 25, 28) had a

The greater impairment in unfamiliar voice discrimination and the increased amount of false alarms for voices in RBD as compared with LBD were not unexpected, because similar differences had been repeatedly reported in the neuropsychological literature on face recognition and in some papers on voice recognition (e.g. Van Lancker and Canter, 1982; Neuner and Schweinberger, 2000). As for the greater impairment of RBD patients on tasks of face discrimination, De Renzi and Spinnler (1966), Warrington and James (1967), Benton and Van Allen (1968), Metha et al. (1987) and Lezak et al. (2004) found that on tasks of unknown face discrimination RBD patients scored significantly worse than LBD patients (see Tranel et al., 2009 for review). In a similar manner, one group study (Rapcsak et al., 1996) and several single case investigations (Rapcsak et al., 1994, 1999; Verstichel, 2005; Gainotti et al., 2008) have shown that an increased sense of familiarity for unknown faces is often observed in patients with right brain damage and in particular in those with right frontal lesions. False alarms have been

Fig. 1. Lesion overlapping for patients with impaired UVD (right is on the right).

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Fig. 2. Lesion overlapping for patients with pathological false alarms.

must be noticed, however, that a trend in this direction was observed in the present study and that the more liberal criterion (with a high number of false alarms) adopted by patients with right temporal lesions, together with the rather low number of patients included in the study may have contributed to the failure to reach a level of statistical significance. Indeed, when considering individual patients, only one of the LBD patients was impaired, while three RBD performed below the cut-off. Concerning semantic recognition, a possible explanation for the low LBD patients’ performance could be the high verbal load that the multiple-choice structure of the test imposed. However, only three out of 16 left brain-damaged patients had a mild impairment of verbal working memory and none showed comprehension deficits. Therefore, this explanation seems unlikely. Also in this case, as for familiarity, it must be underlined that, at the individual level, we found a higher number of RBD than LBD patients with an impaired score. Quite expected and consistent with previous data from the literature is, on the contrary, the difficulty shown by patients with a left temporal glioma to retrieve the names of famous people on the basis of their voices, considering the familiarity score as covariate in the analysis. Several authors (e.g. Grabowski et al., 2001; Seidenberg et al., 2002; Glosser et al., 2003; Drane et al., 2008; Benke et al., 2013) have, indeed, demonstrated that patients with temporal lobe lesions (and in particular those with temporal lobe epilepsy) show a selective impairment in naming famous faces while they do not produce pathological performances in face recognition and semantic identification. This claim is also supported by studies on patients with left gliomas (Papagno et al., 2011, 2016). Furthermore, Waldron et al. (2014) obtained similar results testing the hypothesis that the left temporal pole would be important for naming famous voices. They showed that patients with left temporal pole lesions were able to recognize famous persons from their voices, but were selectively impaired in naming famous persons from their voices. Taken together, all these data are, therefore, consistent with the view assuming that important differences exist between the right and left temporal lobes in the treatment of different aspects of voice processing, with a prevalence of the right temporal lobe in discrimination of unfamiliar voices and in recognition of familiar voices and a prevalence of the left temporal lobe in retrieving the names of famous persons from their voices. Much less informative are our data with respect to the temporal lobe structures subsuming these different components of voice processing, because (as shown in Fig. 4) no significant neuroanatomical differences, but only some suggestive trends, were found between patients with selective unknown voice discrimination disorders and patients with selective deficits of famous voice recognition. In the former group, lesions were usually widespread, involving the whole right ATL

considered by Van Lancker (1991) and by Sidtis and Kreiman (2011) as related to the phenomenon of personal relevance and judgements of familiarity associated with the right hemisphere. Both the significantly higher number of false alarms shown by RBD patients and data about false alarms arising from individual performances are consistent with these views and also support the hypothesis of a link between the right hemisphere and familiarity judgements advanced by Gainotti (2007) in his review on the relationships between familiarity feelings and the right temporal lobe. Other authors have considered them as due, on one hand, to the patients’ tendency to rely more on the analytic functions subsumed by the left hemisphere than to the more efficient holistic visual functions typical of the right hemisphere (e.g. Rapcsak et al., 1994, 1996; Verstichel, 2005) and, on the other hand, to the presence of an executive defect hampering the correction of this inappropriate processing strategy (see Gainotti, 2007 for review). In the present research, a similar dysexecutive mechanism is suggested by the neuroanatomical correlates of the impaired performance in voices discrimination and of the increased amount of false alarms in voice recognition. Patients with unknown voice discrimination disorders showed, indeed, a widespread involvement of the right ATL, with lesions extending both to the right frontal structures and to posterior parts of the right temporal lobe (including the fusiform gyrus, the Heschl gyrus, medial subcortical regions and insular cortices). Furthermore, an analysis of subcortical white matter tracts showed an important disruption of both the inferior frontooccipital fasciculus and the dorsal part of the uncinate fasciculus, connecting the frontal to the anterior temporal lobe. Since unknown voice discrimination tasks certainly require more attentional resources than familiarity assessment (that is partly based on automatic mechanisms) it is likely that executive deficits resulting from the right frontal lesion may impact more upon unknown voice discrimination tasks than upon tasks of familiar voice recognition. More complex is the account that can be given of the prevalence of false alarms in patients with right temporal gliomas, because lesion overlapping shows that only the right ATL is consistently affected in these patients, leading to hypothesize that false alarms are not due to a lesion affecting the right frontal lobe, but to the disconnection of the right temporal structures (subsuming familiarity feelings) from the control functions exerted by the right frontal lobe. The lack of significant difference between patients with left and right temporal gliomas in famous people recognition (feelings of knowing) and identification from voices is at least in part unexpected, because Gainotti (2007b) and Gainotti and Marra (2011) have shown that the most important difference between patients with face recognition disorders resulting from right and left temporal lesions consists of a lack of familiarity feelings for famous faces by patients with right temporal lesions. It

Fig. 3. Lesion overlapping for patients with impaired semantic recognition (RBD) and naming (LBD). The lesion overlapping of 14 LBD patients with impaired naming is reported in red, while the lesion overlapping of RBD patients with impaired semantic recognition is reported in green. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 4. Overlaps of the inferior occipito-frontal fasciculus (green) and uncinate fasciculus (red) with A) lesion overlapping of 6 RBD patients with preserved voice recognition, but impaired voice discrimination and B) lesion overlapping of 3RBD patients with preserved voice discrimination, but impaired voice recognition.

perception, which assumes that re-entrant interactions may also exist between FFA and lower order (OFA) visual areas. The observed dissociation in some right temporal patients between impaired voice discrimination and spared voice recognition/identification may be due to the different intrinsic nature of the tasks. While a voice discrimination task requires same/different comparison of two vocal stimuli, voice recognition/identification tasks require access to information about a person from a single voice stimulus and do not ask to compare the perceptual features of the stimuli. It might well be that the right temporal patients' impairment is, at least partially, caused by some inability to correctly discriminate stimuli rather than to process them individually. However, we aimed at checking the existence of a hierarchical model of voice processing, which assumes that correct voice recognition/identification presupposes intact voice discrimination. The assumption that fine-grained perception, documented through unfamiliar voice discrimination, may be a prerequisite for familiar voice recognition, had already been criticized by Van Lancker et al. (1988) and by Sidtis and Kreiman (2011), and is at variance with results of our investigation. Furthermore, our findings questioning a strictly hierarchical model of voice processing along the TVA are consistent with Pernet et al. (2015) data, which have documented a high inter-individual variability in the location of the TVAs and the existence of a series of extra-temporal areas as part of a large-scale cerebral voice network. Both sets of data are, therefore, more consistent with a complex and differentiated than with a simple and linear model of voice processing.

and spanning to frontal and insular cortices and to posterior temporal lobe regions, including the fusiform gyrus, Heschl gyrus and medial subcortical regions. Furthermore, the study of subcortical tracts showed that in these patients both the inferior frontal occipital fasciculus and the dorsal part of the uncinate fasciculus are usually involved. On the other hand, in patients with preserved voice discrimination, but impaired voice recognition, the cortical lesion was restricted to the right ATL and the inferior frontal lobe and the study of subcortical tracts showed only a small involvement of the frontal head of the inferior frontal occipital fasciculus and of the ventral part of the uncinate fasciculus. These rather inconclusive results are probably due to some limitations of our study, because the relatively small sample size prevented more informative analyses such as voxel-based lesion symptom mapping; in addition, surgery must necessarily include a large area of resection, not allowing a more fine-grained distinction among involved structures. Increasing the number of patients, in particular RBD ones, will allow more informative anatomical analyses. It is, however, interesting to note the fact that some patients showed no deficit in famous voice recognition and identification, in spite of severe voice discrimination disturbances. This dissociation, which argues against a strictly hierarchical model of voice processing, is, however, not new. In the classical literature, Van Lancker and Kreiman (1987) and Van Lancker et al. (1989) already noticed that recognizing a familiar voice and discriminating among unfamiliar voices may be selectively impaired and, more recently, Liu et al. (2016) reported a prosopoagnosic patient (R-AT5) affected by a right temporal tumour, who had right hearing loss and an impaired score for voice discrimination, but performed normally on voice recognition. Furthermore, observations at variance with a strictly hierarchical model of stimulus processing are not confined to voice modality. Rossion et al. (2003) and Rossion (2008), have reported data suggesting a direct pathway from early visual areas to the high level right FFA area, bypassing the OFA and have proposed a reverse hierarchical model of face

Acknowledgments The authors are grateful to Giada Sera and Giulia Ursino for their help in testing patients. This study was in part supported by a FA (FA 2016) grant to CP.

Appendix (See Tables 4–8) Table 4 Damaged regions overlap in at least 5 out of 6 RBD patients with UVD below the cut-off. Area

No of voxels

% of lesioned voxels

No of patients

Temporal_Inf_R Temporal_Pole_Mid_R Temporal_Mid_R Fusiform_R Temporal_Pole_Sup_R ParaHippocampal_R Amygdala_R Temporal_Sup_R Hippocampus_R

5393 4063 2492 1828 1650 1067 110 42 5

0,189441 0,429039 0,070229 0,090374 0,154871 0,118188 0,05598 0,001663 0,000657

6 6 6 6 6 6 6 5 5

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Table 5 Maximum overlap for two LBD patients with UVD below the cut-off. Area

No of voxels

% of lesioned voxels

No of patients

Temporal_Inf_L Insula_L Temporal_Pole_Sup_L Temporal_Mid_L Temporal_Sup_L ParaHippocampal_L Fusiform_L Frontal_Inf_Orb_L Amygdala_L Hippocampus_L Temporal_Pole_Mid_L Olfactory_L Frontal_Sup_Orb_L Putamen_L

4119 3391 3222 2825 2147 1361 1324 1167 1135 1002 637 166 71 28

0,000975 0,160604 0,225691 0,315018 0,071786 0,117278 0,172475 0,072219 0,085872 0,654934 0,134155 0,106451 0,073386 0,009276

2 2 2 2 2 2 2 2 2 2 2 2 2 2

Table 6 Overlap of regions lesioned in at least 3 out of 4 RBD patients with False alarms above cut-off score. Area

No of voxels

% of lesioned voxels

No of patients

Temporal_Inf_R Temporal_Pole_Mid_R Temporal_Pole_Sup_R Temporal_Mid_R Fusiform_R ParaHippocampal_R Temporal_Sup_R Hippocampus_R Amygdala_R Frontal_Inf_Orb_R

5536 4524 3563 3256 2248 1286 864 244 157 8

0,194464 0,477719 0,334428 0,09176 0,111139 0,142446 0,034207 0,03208 0,079898 0,000582

4 4 4 4 4 4 4 3 4 3

Table 7 Overlap of regions lesioned in at least 8 out of 10 LBD patients naming below the cut-off 37,5% of correct naming for familiar stimuli. Area

No of voxels

% of lesioned voxels

No of patients

Fusiform_L Temporal_Mid_L Temporal_Pole_Mid_L Temporal_Inf_L Hippocampus_L ParaHippocampal_L Temporal_Pole_Sup_L Temporal_Sup_L

551 1431 336 3887 12 96 64 13

0,030055 0,036363 0,05615 0,151558 0,001607 0,012166 0,006257 0,00071

10 10 10 10 9 9 9 8

Table 8 Maximum overlap for three RBD patients with VO-REC below cut-off score. Area

No of voxels

% of lesioned voxels

No of patients

Temporal_Inf_R Temporal_Mid_R Temporal_Pole_Mid_R Fusiform_R Temporal_Pole_Sup_R Temporal_Sup_R

3495 3204 945 631 164 10

0,122769 0,090294 0,099789 0,031196 0,015393 0,000396

3 3 3 3 3 3

Bartolomeo, P., 2011. The quest for the 'critical lesion site' in cognitive deficits: problems and perspectives. Cortex 47, 1010–1012. Barton, J.J., 2008. Structure and function in acquired prosopagnosia: lessons from a series of 10 patients with brain damage. J. Neuropsychol. 2, 197–225. Belin, P., Zatorre, R.J., Ahad, P., 2002. Human temporal-lobe response to vocal sounds. Cogn. Brain Res. 13, 17–26. Belin, P., Zatorre, R.J., Lafaille, P., Ahad, P., Pike, B., 2000. Voice-selective areas in human auditory cortex. Nature 403, 309–312. Benke, T., Kuen, E., Schwarz, M., Walser, G., 2013. Proper name retrieval in temporal

References Ashburner, J., Friston, K.J., 1999. Nonlinear spatial normalization using basis functions. Human. Brain Mapp. 7, 254–266. Barsics, C., Brédart, S., 2011. Recalling episodic information about personally known faces and voices. Conscious Cogn. 20, 303–308. Barsics, C., Brédart, S., 2012. Recalling semantic information about newly learned faces and voices. Memory 205, 527–534.

9

Neuropsychologia xxx (xxxx) xxx–xxx

C. Papagno et al.

remapped. Brain 137, 2522–2531. Mehta, Z., Newcombe, F., Damasio, H., 1987. A left hemisphere contribution to visuospatial processing. Cortex 23, 447–461. Neuner, F., Schweinberger, S.R., 2000. Neuropsychological impairments in the recognition of faces, voices, and personal names. Brain Cogn. 44, 342–366. Ohnesorge, C., Van Lancker, D., 2001. Cerebral laterality for famous proper nouns: visual recognition by normal subjects. Brain Lang. 77, 135–165. Papagno, C., Casarotti, A., Comi, A., Pisoni, A., Lucchelli, F., Bizzi, A., et al., 2016. Longterm proper name anomia after removal of the uncinate fasciculus. Brain Funct. Struct. 221, 687–694. Papagno, C., Miracapillo, C., Casarotti, A., Romero Lauro, L., Castellano, A., Falini, A., et al., 2011. What is the role of the uncinate fasciculus? Surgical removal and proper name retrieval. Brain 134, 405–414. Parvizi, J., Jacques, C., Foster, B.L., Witthoft, N., Rangarajan, V., Weiner, K.S., GrillSpector, K., 2012. Electrical stimulation of human fusiform face-selective regions distorts face perception. J. Neurosci. 32, 14915–14920. Pernet, C.R., McAleer, P., Latinus, M., Gorgolewski, K.J., Charest, I., Bestelmeyer, P.E., et al., 2015. The human voice areas: spatial organization and inter-individual variability in temporal and extra-temporal cortices. NeuroImage 119, 164–174. Pfutze, E.-M., Sommer, W., Schweinberger, S.R., 2002. Age-related slowing in face and name recognition: evidence from event-related brain event potentials. Psychol. Aging 17, 140–160. Pitcher, D., Duchaine, B., Walsh, V., Yovel, G., Kanwisher, N., 2011. The role of lateral occipital face and object areas in the face inversion effect. Neuropsychologia 49, 3448–3453. Quaranta, D., Piccininni, C., Carlesimo, G.A., Luzzi, S., Marra, C., Papagno, C., et al., 2016. Recognition disorders for famous faces and voices: a review of the literature and normative data of a new test battery. Neurol. Sci. 37, 345–352. Rapcsak, S.Z., Polster, M.R., Comer, J.F., Rubens, A.B., 1994. False recognition and misidentification of faces following right hemisphere damage. Cortex 30, 565–583. Rapcsak, S.Z., Polster, M.R., Glisky, M.L., Comer, J.F., 1996. False recognition of unfamiliar faces following right hemisphere damage: neuropsychological and anatomical observations. Cortex 32, 593–611. Rapcsak, S.Z., Reminger, S.L., Glisky, E.L., Kasnziak, A.W., Comer, J.F., 1999. Neuropsychological mechanisms of false facial recognition following frontal lobe damage. Cogn. Neuropsychol. 16, 267–292. Rossion, B., 2008. Constraining the cortical face network by neuroimaging studies of acquired prosopagnosia. NeuroImage 40, 423–426. Rossion, B., Caldara, R., Seghier, M., Schuller, A.M., Lazeyras, F., Mayer, E., 2003. A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing. Brain 126, 2381–2395. Rossion, B., Hanseeuw, B., Dricot, L., 2012. Defining face perception areas in the human brain: a large scale factorial fMRI face localizer analysis. Brain Cogn. 79, 138–157. Schweinberger, S.R., Kaufmann, J.M., McColl, A., 2002a. Famous personal names and the right hemisphere: the link keeps missing. Brain Lang. 82, 95–110. Schweinberger, S.R., Landgrebe, A., Mohr, B., Kaufmann, J.M., 2002b. Personal names and the human right hemisphere: an illusory link? Brain Lang. 80, 111–120. Seidenberg, M., Griffith, R., Sabsevitz, D., Moran, M., Haltiner, A., Bell, B., et al., 2002. Recognition and identification of famous faces in patients with unilateral temporal lobe epilepsy. Neuropsychologia 40, 446–456. Sergent, J., Signoret, J.L., 1992. Varieties of functional deficits in prosopagnosia. Cereb. Cortex 2, 375–388. Sidtis, D., Kreiman, J., 2011. In the beginning was the familiar voice: personally familiar voices in the evolutionary and contemporary biology of communication. Integr. Psychol. Behav. Sci. 46, 146–159. Smith, J.S., Chang, E.F., Lamborn, K.R., Chang, S.M., Prados, M.D., Cha, S., et al., 2008. Role of extent of resection in the long-term outcome of low-grade hemispheric gliomas. J. Clin. Oncol. 26, 1338–1345. Tranel, D., Vianna, E., Manzel, K., Damasio, H., Grabowski, T., 2009. Neuroanatomical correlates of the Benton Facial Recognition Test and Judgment of Line Orientation Test. J. Clin. Exp. Neuropsychol. 31, 219–233. Tsukiura, T., Fujii, T., Fukatsu, R., Otsuki, T., Okuda, J., Umetsu, A., et al., 2002. Neural basis of the retrieval of people's names: evidence from brain-damaged patients and fMRI. J. Cogn. Neurosci. 14, 922–937. Van Lancker, D., 1991. Personal relevance and the human right hemisphere. Brain Cogn. 17, 64–92. Van Lancker, D.R., Canter, G.J., 1982. Impairment of voice and face recognition in patients with hemispheric damage. Brain Cogn.1 185–195. Van Lancker, D.R., Cummings, J.L., Kreiman, J., Dobkin, B.H., 1988. Phonagnosia: a dissociation between familiar and unfamiliar voices. Cortex 24, 195–209. Van Lancker, D., Lanto, A., Klein, K., Riege, W., Hanson, W., Metter, E. J. (1991). Preferential representation of personal names in the right hemisphere. ClinAphasiol 20, pp. 181–89. Van Lancker, D., Klein, K.K., 1990. Preserved recognition of familiar personal nouns in global aphasia. Brain Lang. 39, 511–529. Van Lancker, D., Kreiman, J., 1987. Voice discrimination and recognition are separate abilities. Neuropsychologia 25, 829–834. Van Lancker, D., Kreiman, J., Cummings, J., 1989. Voice perception deficits: neuroanatomical correlates of phonagnosia. J. Clin. Exp. Neuropsychol. 11, 665–674. Van Lancker, D., Nicklay, C., 1992. Comprehension of personally relevant (PERL) versus novel language in two globally aphasic patients. Aphasiology 6, 37–61. Van Lancker, D., Ohnesorge, C., 2002. Personally familiar proper names are relatively successfully processed in the human right hemisphere; or, the missing link. Brain

lobe epilepsy: naming of famous faces and landmarks. Epilepsy Behav. 27, 371–377. Benton, A.L., Van Allen, M.W., 1968. Impairment in facial recognition in patients with cerebral disease. Cortex 4, 344–358. Bethmann, A., Scheich, H., Brechmann, A., 2012. The temporal lobes differentiate between the voices of famous and unknown people: an event-related fMRI study on speaker recognition. PLoS One 7 (10), e47626. http://dx.doi.org/10.1371/journal. pone.0047626. Bodamer, J. (1947). Die Prosopoagnosic. Archiv für Psychiatrie und Nervenkrankheiten 179, pp. 6–53. Brédart, S., Barsics, C., Hanley, R., 2009. Recalling semantic information about personally known faces and voices. Eur. J. Cognit. Psychol. 21 (7), 1013–1021. Campanella, F., D’Agostini, S., Skrap, M., Shallice, T., 2010. Naming manipulable objects: anatomy of a category specific effect in left temporal tumours. Neuropsychologia 48, 1583–1597. Capitani, E., 1997. Normative data and neuropsychological assessment. common problems in clinical practice and research. Neuropsychol. Rehabil. 7, 293–310. Catani, M., Thiebaut de Schotten, M., 2008. A diffusion tensor imaging tractography atlas for virtual in vivo dissections. Cortex 44, 1105–1132. Damjanovic, L., Hanley, J.R., 2007. Recalling episodic and semantic information about famous faces and voices. Mem. Cogn. 35, 1205–1210. Davies-Thompson, J., Pancaroglu, R., Barton, J., 2014. Acquired prosopoagnosia: structural basis and processing impairments. Front. Biosci. 6, 159–174. De Renzi, E., Faglioni, P., Grossi, D., Nichelli, P., 1991. Apperceptive and associative forms of prosopagnosia. Cortex 27, 213–221. De Renzi, E., Spinnler, H., 1966. Facial recognition in brain-damaged patients. Neurology 16, 145–152. Drane, D.L., Ojemann, G.A., Aylward, E., Ojemann, J.G., Johnson, L.C., Silbergeld, D.L., et al., 2008. Category-specific naming and recognition deficits in temporal lobe epilepsy surgical patients. Neuropsychologia 46, 1242–1255. Fox, C.J., Iaria, G., Barton, J.J., 2008. Disconnection in prosopagnosia and face processing. Cortex 44, 996–1009. Gainotti, G., 2007. Face familiarity feelings, the right temporal lobe and the possibile underlying neural mechanisms. Brain Res. Rev. 56, 214–235. Gainotti, G., 2011. What the study of voice recognition in normal subjects and braindamaged patients tells us about models of familiar people recognition. Neuropsychologia 49, 2273–2282. Gainotti, G., 2013a. Laterality effects in normal subjects' recognition of familiar faces, voices and names. Percept. Represent. Compon. Neuropsychol. 51, 1151–1160. Gainotti, G., 2013b. Is the Right Anterior Temporal Variant of Prosopagnosia a Form of 'Associative Prosopagnosia' or a Form of 'Multimodal Person Recognition Disorder'? Neuropsychol. Rev. 23, 99–110. Gainotti, G., Ferraccioli, M., Quaranta, D., Marra, C., 2008. Cross-modal recognition disorders for persons and other unique entities in a patient with right fronto-temporal degeneration. Cortex 44, 238–248. Gainotti, G., Marra, C., 2011. Differential contribution of right and left temporo-occipital and anterior temporal lesions to face recognition disorders. Front. Hum. Neurosci. 5 (55), 1–11. http://dx.doi.org/10.3389/fnhum.2011.00055. Gauthier, I., Tarr, M.J., Moylan, J., Skudlarski, P., Gore, J.C., Anderson, A.W., 2000. The fusiform “face area” is part of a network that processes faces at the individual level. J. Cogn. Neurosci. 12, 495–504. Glosser, G., Salvucci, A.E., Chiaravalloti, N.D., 2003. Naming and recognizing famous faces in temporal lobe epilepsy. Neurology 61, 81–86. Gorno-Tempini, M.L., Price, C.J., Josephs, O., Vandenberghe, R., Cappa, S.F., Kapur, N., Frackowiak, R.S.J., 1998. The neural systems sustaining face and propername processing. Brain 121, 2103–2118. Grabowski, T.J., Damasio, H., Tranel, D., Ponto, L.L.B., Hichwa, R.D., Damasio, A.R., 2001. A role for left temporal pole in the retrieval of words for unique entities. Hum. Brain Mapp. 13, 199–212. Hailstone, J.C., Crutch, S.J., Vestergaard, M.D., Patterson, R.D., Warren, J.D., 2010. Progressive associative phonagnosia: a neuropsychological analysis. Neuropsychologia 48, 1104–1114. Hailstone, J.C., Ridgway, G.R., Bartlett, J.W., Goll, J.C., Buckley, A.H., Crutch, S.J., Warren, J.D., 2011. Voice processing in dementia: a neuropsychological and neuroanatomical analysis. Brain 134, 2535–2547. http://dx.doi.org/10.1093/brain/ awr205. Hanley, J.R., 2014. Accessing stored knowledge of familiar people from faces, names and voices: a review. Front. Biosci. 6, 198–207. Hanley, J.R., Damjanovic, L., 2009. It is more difficult to retrieve a familiar person's name and occupation from their voice than from their blurred face. Memory 17, 830–839. Hanley, J.R., Smith, T., Hadfield, J., 1998. I recognise you but I can’t place you: an investigation of familiar-only experiences during tests of voice and face recognition. Q. J. Exp. Psychol. 51A, 179–195. Haxby, J.V., Hoffman, E.A., Gobbini, M.I., 2000. The distributed human neural system for face perception. Tr. Cogn. Sci. 4, 223–233. Kanwisher, N., McDermott, J., Chun, M.M., 1997. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311. Lezak, M.D., Howieson, D.B., Loring, D.W., 2004. Neuropsychological Assessment, 4th ed. Oxford University Press, New York. Liu, R.R., Pancaroglu, R., Hills, C.S., Duchaine, B., Barton, J.J., 2016. Voice recognition in face-blind patients. Cereb. Cortex 26, 1473–1487. http://dx.doi.org/10.1093/cercor/ bhu240. Mah, Y.H., Husain, M., Rees, G., Nachev, P., 2014. Human brain lesion-deficit inference

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Neuropsychologia xxx (xxxx) xxx–xxx

C. Papagno et al.

Von Kriegstein, K., Giraud, A.L., 2004. Distinct functional substrates along the right superior temporal sulcus for the processing of voices. NeuroImage 22 (2), 948–955. Waldron, E.J., Manzel, K., Tranel, D., 2014. The left temporal pole is a heteromodal hub for retrieving proper names. Front. Biosci. 6, 50–57. Warrington, E., James, M., 1967. An experimental investigation of facial recognition in patients with unilateral cerebral lesions. Cortex 3, 317–326.

Lang. 80, 121–129. Verstichel, P., 2005. Hyperfamiliarité stéréotypée pour les visages au cours d’une démence fronto-temporale avec prosopagnosie. Rev. Neurol. 161, 804–816. von Kriegstein, K., Eger, E., Kleinschmidt, A., Giraud, A.L., 2003. Modulation of neural responses to speech by directing attention to voices or verbal content. Cognit. Brain Res. 17, 48–55.

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