The Routledge Handbook of Second Language Acquisition and Neurolinguistics

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DOI: 10.4324/9781003190912-12

THE NEUROLINGUISTICS

OF THE SECOND LANGUAGE

MORPHOLOGICAL SYSTEM

The Role of Grammar- Related and

Speaker- Related Factors

Nicoletta Biondo, Nicola Molinaro, and Simona Mancini

Introduction and Critical Definitions

Morphemes are the smallest units that convey meaning in language. Inflectional morphemes like - i

and - ed in (1) and (2) below are combined with a stem via affixation to generate different forms of the

same lexical item, for example, a verb with different number, person, or tense features.

(1) Re- �

stem- affix1.sg.past/ ‘I laughed’

(2) Laugh- ed

stem- affix.past

A native or proficient non- native speaker of Spanish will be able to extract a composite set of

information from the morpheme - � in (1), namely that a single individual laughed at some point in the

past and that this is the speaker of the utterance. Conversely, a reader with little knowledge of Spanish

may be unable to extract the full set of information provided by the verb.

How is morphological knowledge attained in a second language (L2)? Can it become native- like,

and how? We review and critically evaluate recent neuroimaging studies that have addressed these

questions, with the goal of highlighting the role that grammar- and speaker- related factors play in

shaping the L2 morphological system and its neurocognitive underpinnings. Native- like morpho-

logical knowledge refers here to the ability of L2 speakers to process the L2 as efficiently and auto-

matically as their native language. Yet, we clarify that native- likeness does not assume the existence

of a monolingual speaker norm and recognizes that L2 speakers can only become bilingual, by defin-

ition, given that they already possess the knowledge of one language (their mother tongue).

L2 learning occurs either simultaneously (e.g., in early bilinguals) or sequentially (e.g., in late

learners) with respect to the first language (L1). Understanding the (possible) cross- linguistic transfer

of rules, and the conditions under which it occurs is thus pivotal to understanding how the L2 language

system develops (e.g., MacWhinney, 2005). We refer to this factor as the L1– L2 similarity factor (see

Sabourin & Manning, this volume). L1– L2 similarity refers to structurally mappable features, that is,

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features that are present both in the L1 and in the L2 (MacWhinney, 2005). Morphological features

can also be similarly or dissimilarly realized/ distributed across constituents in the two languages.

The L1 and the L2 are considered similar here if the morphological feature at issue (e.g., number) is

present and realized on the same constituents (e.g., noun– verb, adjective– noun) in both languages.

However, both aspects of similarity are also considered separately, when possible.

Experience- related factors that pertain to the speakers’ L2 history, such as age of acquisition

(AoA), proficiency, and immersion in an L2 environment are also considered crucial during learning

(e.g., Ullman, 2014, 2020; see Luque & Covey, this volume). AoA refers to the starting point of L2

learning, i.e., when the speaker was first exposed to the language. Proficiency refers to the ability to

use a language, as measured by performance on standardized tests or task- related accuracy scores.

Immersion duration refers to the length of residence in an L2- speaking country. We review evi-

dence about all these factors, mainly from electroencephalography (EEG/ ERPs) and functional

magnetic resonance imaging (fMRI), but also briefly from non- invasive brain stimulation (NIBS),

and comment on their potential to investigate L2 morphological processing and the brain areas that

support it. Because of the few ERP studies available on L2 morphological production, our focus will

be primarily on L2 sentence comprehension studies.

Critical Issues and Theoretical Perspectives

Within neurolinguistics, historical, theoretical, and methodological issues exist in defining how L2

morphological knowledge is attained and whether it can reach native- likeness. Historically, early

experimental research on L2 processing was mainly conducted in English, a language with an

impoverished morphological system. Such findings are therefore difficult to generalize to morpho-

logically richer languages (such as Spanish, Hindi, or Finnish), in which inflection and morpho-

syntactic relations can include a wider set of features (e.g., gender, person, number, and tense) and

constituents (e.g., determiners, adjectives, as well as demonstratives, nouns, and verbs).

Theoretically, models of L2 processing differ in the relevance they attribute to linguistic and experi-

ential factors in L2 processing. Whereas proposals like the competition Model (MacWhinney, 2005,

2018) formalize and discuss how L1– L2 cross- language interaction can affect ultimate L2 attainment,

accounts like the declarative/ procedural model (Ullman, 2014, 2020; see also Ullman & Morgan-

Short, this volume) highlight the importance of experience- related factors such as L2 AoA and

immersion.

In this vein, previous reviews and meta- analyses have failed to reach a consensus on the relative

weight that grammar- and speaker- related factors have on the native- likeness of L2 morphological

processing (e.g., Caffarra et al., 2015, De Diego- Balaguer & Rodriguez- Fornells, 2010; Roncaglia-

Denissen & Kotz, 2016; Tanner et al., 2014). L1– L2 similarity has been indicated as a key factor in

some analyses (e.g., Kotz, 2009) but less crucial in others (e.g., Caffarra et al., 2015; Polczynska &

Bookheimer, 2021). The so- called critical period hypothesis (Birdsong, 2018; Hartshorne et al., 2018;

Johnson & Newport, 1989; Newport et al., 2001), and the assumption that the later the L2 is acquired

the lower its native- likeness is, gave a prominent role to AoA, although more recent work suggests

that this factor may be less crucial than previously considered (e.g., Kotz, 2009; Steinhauer, 2014;

see also Caffarra et al., 2015).

In addition to L1– L2 similarity and AoA, proficiency has been indicated as a key factor in deter-

mining the temporal dynamics of L2 morphological processing and the degree of neural convergence

between L1 and L2 (e.g., Steinhauer et al., 2009; see also Kotz, 2009; Van Hell & Tokowicz, 2010).

Yet, this factor has also been considered problematic, due to differences in its measurement across

studies and its correlation with other variables such as exposure, AoA, and immersion (Ullman, 2014;

for more on AoA and proficiency, see Fromont, this volume). Finally, the learning environment also

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plays a significant role in L2 final attainment. Immersive contexts have a positive impact on L2

acquisition (for a recent overview, see Jackson & Schwiter, 2019) because they provide more natur-

alistic and variegated exposure to the L2 compared to formal education settings in the L1- speaking

country. Longer immersion duration can lead to higher grammatical sensitivity (Caffarra et al., 2015).

However, the evidence available is still limited, as few studies have focused on this variable (for more

on learning context, see Bowden & Faretta- Stutenberg, this volume).

From a methodological perspective, the available neuroimaging evidence on L2 morphological

processing mainly comes from EEG/ ERP studies, arguably because this technique is more accessible

across laboratories than (more expensive) techniques such as fMRI, or does not have potential side

effects, as with NIBS. Combining the experimental evidence from these three different techniques

enables the characterization of both the time course and the neural implementation of the mechanisms

that subserve L2 morphological processing, as well as the identification of the brain substrates that

could be causally involved. This is the approach that we undertake in this review.

Thus, the goals of the current review are to provide an updated picture of the role of grammar- and

speaker- related factors based on recent neuroimaging evidence and to identify overlooked aspects

that may deepen our insight into the complexity of L2 morphological processing.

Critical Research Outcomes and Current Empirical Knowledge

Event- Related Potential (ERP) Studies

ERPs have been widely adopted in L2 research (for more on this method, see Dickson & Pelzl, this

volume). ERPs are computed by averaging the portion of the electroencephalogram (EEG) signal

that is time- locked to the presentation of a relevant stimulus (e.g., an isolated word, or a word in a

sentence). The main advantages of ERP data are the ability to record neural activity continuously,

without time delay, and with a high temporal resolution (in the millisecond range).

Sentence comprehension ERP studies offer a comprehensive picture of the role of grammar- and

speaker- related factors during L2 morphosyntactic processing. Sentences are generally presented

visually word- by- word at the center of the screen at a fixed pace, and the participant is required to

provide a grammaticality judgment at the end of each sentence. The electrophysiological activity

generated by a word containing a grammatical error (e.g., *My cat are cute) is then compared with the

activity generated by the same word in a grammatical sentence (e.g., My cats are cute).

Inflection errors tend to elicit early negativities (250– 500 ms after stimulus presentation), followed

by a late positivity peaking about 600 ms post- stimulus onset. An early negativity with anterior and

left- lateralized topography is referred to as left- anterior negativity (LAN), as opposed to the more

broadly distributed negativity that characterizes the N400 effect. These negativities are thought to

reflect automatic morphosyntactic processing (see Molinaro et al., 2011 for a review) and semantic/

lexical integration difficulties (see Lau et al., 2008 for a review). Whereas these early negativities

are not consistently reported across studies and languages, late positive- going deflections represent a

rather stable correlate of morpho- syntactic anomalies. They are typically evident in central- posterior

areas of the scalp and are often referred to as a “P600.” Functionally, P600 effects are generally

interpreted as an index of structure integration or reanalysis (see Molinaro et al., 2011 for a review).

The emergence of early negative and late positive effects has been used to delineate different

stages in the development of L2 morphosyntactic knowledge (e.g., Osterhout et al., 2004; Osterhout

et al., 2006; Steinauer et al., 2009). When the speaker has very little knowledge of the L2 grammar, no

ERP effects arise when comparing grammatically correct and incorrect sentences because the speaker

cannot detect the grammatical error. Subsequently, the speaker may start memorizing salient word/

morphological combinations (e.g., My cats are…) as unanalyzed chunks. At this stage, any violation

of the memorized pattern (e.g., *My cat are…) would result as unfamiliar, thus triggering an N400,

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which is highly sensitive to word sequence probabilities. Finally, when L2 proficiency is attained, the

speaker is able to abstract morphosyntactic rules successfully, and consequently shows native- like

ERP patterns in response to violations, i.e., left- anterior or bilateral early negativities followed by

a P600. In these accounts, different stages of morphosyntactic acquisition are mainly driven by L2

proficiency.

However, in their meta- analysis, Caffarra et al. (2015) found that other factors may play a

role. Immersion duration had an impact on early ERP responses and their underlying cognitive

mechanisms: The probability of reporting a LAN effect was higher when the immersion in an L2-

speaking country was long (> 5 years). Conversely, proficiency had an impact on late mechanisms of

(morpho)syntactic processing: More P600 effects were found when L2 proficiency was high (above

75%). Interestingly, AoA only marginally affected N400 effects, and L1– L2 similarity did not play a

crucial role in any ERP effect.

Table 9.1A summarizes ERP violation studies investigating sentence- level comprehension of L2

inflection published after Caffarra et al.’s meta- analysis. Considering these recent studies, it seems

that the native- likeness of the ERP patterns changes as a function of several factors, as suggested in

previous work and reviewed below.

Grammar- Related Factors

By considering different dimensions of L1– L2 similarity (type of feature, type of relation/ configur-

ation), our review of more recent studies suggests that a finer- grained classification of L1– L2 simi-

larity can capture effects (see Alem�n Ba��n et al., 2017; D�az et al., 2016; Gabriele et al., 2021;

Martinez de la Hidalga et al., 2021) that previous work could not identify, although the evidence

still appears somewhat heterogeneous. Gabriele et al. (2021) found similar ERP responses (P600) in

response to subject– verb and adjective– noun number violations in L1 English L2 Spanish speakers,

thus suggesting that the presence/ absence of a feature in the L1 inventory plays a bigger role

compared to the morphological realization of this feature across languages. In contrast, D�az et al.

(2016) reported data from Basque suggesting that the way a feature is realized is important. They

tested two groups of L1 Spanish L2 Basque speakers with early and later L2 AoA. The violation of a

shared feature (number) that is expressed on different constituents in the L2 (object- verb) triggered

an N400 in the group of late learners and a marginal P600 in early bilinguals. Native speakers showed

P600 effects in response to these violations (D�az et al., 2011).

Speaker- Related Factors

In contexts where the L2 speakers cannot exploit consolidated L1 grammatical knowledge to process

L2 morphology, speaker- related factors seem to become relevant. In a study with L1 Polish/ Russian–

L2 German speakers, Meulman et al. (2015) showed that morphological similarity may determine

the appearance of AoA effects. They found different P600 effects as a function of AoA when pro-

cessing an L1– L2 dissimilar phenomenon (i.e., determiner– noun gender agreement; see also Nichols

& Joanisse, 2019), but not when processing a similar phenomenon (tense/ finiteness marking). These

findings suggest that when the L1 and the L2 share similar morphological properties, both early and

late learners can reach native- like processing. Conversely, when the L1 and the L2 differ morpho-

logically, native- like processing may be attained only if the L2 is acquired earlier in life.

Similarly, L2 proficiency has been shown to interact with L1– L2 similarity. For example, Alem�n

Ba��n et al. (2018) and Gabriele et al. (2021) investigated similarity effects with L1 English speakers

of L2 Spanish. When the morphological patterns differed (e.g., gender, which is not morphologically

realized in adjective– noun relations in English), only highly proficient speakers of Spanish showed

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P600 effects. When a feature present in both languages was manipulated (number), both low and

high- proficiency speakers showed P600 effects.

Higher proficiency is generally reported to trigger larger P600 effects (Alem�n Ba��n et al., 2018,

2021; Bice & Kroll, 2021; Gabriele et al., 2021; Nichols & Joanisse, 2019; but see Armstrong et al.,

2018). Interestingly, Alem�n Ba��n et al. (2018) compared the impact of two different measures of

proficiency, namely d- prime scores derived from a grammaticality judgment task performed during

EEG recording and overall L2 proficiency derived from standardized grammar tests. Whereas task-

related proficiency correlated with P600 amplitudes in all conditions, overall proficiency scores

did not.

Few ERP studies have investigated immersion duration effects, and just one reported a signifi-

cant effect on the amplitude of late components (Alem�n Ba��n et al., 2021). In line with Caffarra

et al. (2015), other studies that tested immersion (Table 9.1A) showed early negativities (either LAN

or N400, but see Meykadeh, Golfam, Nasrabadi et al., 2021), but only with intermediate or long

immersion duration.

Summary of ERP Findings

The ERP studies presented here show that the emergence of early negativities mirroring automatic

(native- like) processing is not solely driven by L2 morphosyntactic knowledge/ proficiency. LAN

effects have been reported in two studies testing determiner– noun violations (Caffarra et al., 2017;

Nichols & Joanisse, 2019). However, many studies have failed to find LAN effects not only in L2 but

also in native speakers, demonstrating that such findings cannot be related to a low level of morpho-

logical knowledge. N400 effects were found to mirror intermediate stages of L2 knowledge only in

some studies (D�az et al., 2016; Martinez de la Hidalga et al., 2021), whereas in other studies N400

effects (followed by P600s) mirrored native- like processing (Zawiszewski & Laka, 2020; Bice &

Kroll, 2021). The only ERP component that was reliably affected by proficiency was the P600, in line

with Caffarra et al.’s finding. However, the P600 amplitude was also reduced by L1– L2 dissimilar-

ities, later AoA, and shorter immersion duration. In other words, evidence coming from recent ERP

research shows that additional (grammar- and speaker- related) factors should be taken into account

when predicting the time course of L2 morphological processing.

Functional Magnetic Resonance Imaging (fMRI)

The slow temporal resolution that characterizes fMRI makes it unsuitable for capturing the time

course of neurocognitive processes, but its exquisite spatial resolution can give invaluable insights

into the brain areas that are actively involved during a linguistic task (for more on this method, see

Kousaie & Klein, this volume). fMRI is therefore an extraordinary resource to assess the extent of

overlap or segregation in the cortical representations of L1 and L2 and modulation of brain activation

patterns by experience- and grammar- related factors. Yet, fMRI investigations on L2 morphological

processing are still scant, and the evidence for the effect of grammar- and speaker- related variables

appears to be quite fragmented. Moreover, unlike ERPs, there is no meta- analysis or review of fMRI

studies specifically on L2 morphological processing to date. Therefore, the review below is based on

the available fMRI literature that could be identified at the time of writing this chapter.

fMRI studies investigating L2 morphological processing have mostly examined English regular

and irregular tense inflection at the single- word level. Few studies have investigated the processing

of morphosyntactic relations in sentences (e.g., subject– verb agreement, see Table 9.1B for an over-

view). Overall, the available evidence points to substantial neuroanatomical overlap between L1

and L2 morphological systems. Across studies (see Table 9.1B and references therein), consistent

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Nicoletta Biondo, Nicola Molinaro, and Simona Mancini

Table 9.1 Experimental Studies Investigating Morphosyntactic Violations

Table 9.A

Study

Feature

Constituents

L1– L2 AOA

PRF

IMM N400

LAN

P600

Meulman

et al.

(2015)

Polish/

Russian

German

Tense/ Finiteness

Gender

Det- N

X (AOA)

D�az et al.

(2016)

Spanish

Basque

Case

Number

Obj- V

Subj- V

X (delayed)

X (marginal)

X (early)

Alem�n

Ba��n

et al.

(2017)

English

Spanish

Number

Gender

NP- Adj

X (larger)

X (smaller)

Caffarra et al.

(2017)

Basque

Spanish

Gender

Det- N

Alem�n

Ba��n

et al.

(2018)

English

Spanish

Number

Gender

NP - Adj

NP- Adj

Armstrong

et al.

(2018)

Chinese

English

Number

Subj- V

Nichols &

Joanisse

(2019)

English

French

Gender

Det- N

I/ L

X (AOA) X* (AOA,

PRF)

Zawiszewski

& Laka

(2020)

Spanish

Basque

Spanish

Case– ergative

Case– dative

Case– allative

Case– accusative

Case– dative

Case– allative

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Neurolinguistics of the Second Language Morphological System

Alem�n

Ba��n

et al.

(2021)

English

Spanish

Person– 1st

Person– 3rd

Subj- V

X (PRF)

X (IMM)

Bice and

Kroll

(2021)

Spanish

English

Number

Subj- V

X (PRF)

Cheng et al.

(2021)

Chinese

English

Number

Subj- V

Gabriele

et al.

(2021)

English

Spanish

Number

Gender

Subj- V

NP- Adj

X (PRF)

(PRF)

Liang et al

(2021)

English/

Dutch/

Italian/

Polish/

Swedish

Chinese

Aspect

Mart�nez de

la Hidalga

et al.

(2021)

Spanish

Basque

Number

Person

Number

Person

Subj(erg)- V

Subj(abs)- V

X* (smaller)

X (larger)

Meykadeh

et al.

(2021)

Turkish

Farsi

Number

Subj- V

Morgan-

Short et al.

(2022)

English

Spanish

Number

Subj- V

(Continued)

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Nicoletta Biondo, Nicola Molinaro, and Simona Mancini

Table 9.1B

Study

Feature

Constituents

L1– L2 AOA

PRF

IMM Main findings

Wartenburger

et al.

(2003)

Italian

German

Person/ Number/ Case Subject- verb

E/ L

H/ L

L/ I/ S L1– L2 overlap in left IFG at early

AoA. Increased IFG activation in

the late- AoA group.

Sakai et al.

(2004)

Japanese English

Tense

Single word (verb) D

(During

experiment

training)

L1– L2 overlap in left IFG

Tatsuno

and Sakai

(2005)

Japanese English

Tense

Single word (verb) D

(During

experiment

training)

L/ H (two

groups)

Less left IFG activation

corresponding to higher proficiency

Hernandez

et al.

(2007)

Spanish

English

Gender

Single word (noun) D

E/ L

Greater activation for L2 late learners.

Lehtonen

et al.

(2009)

Finnish/

Swedish

Finnish/

Swedish

Inflected vs. non-

inflected nouns

Single word (noun) D

Greater left IFG activation for Finnish

vs. Swedish inflected words

Pliatsikas

et al.

(2014)

Greek

English

Tense

Single word (verb) S

Overlapping activation patterns for

natives and non- natives.

L2 immersion modulates activation

difference between regular and

irregular in left IFG. L2 proficiency

modulates activation difference

between regular and irregular in left

caudate modulated.

Yan et al.

(2016)

Chinese

English

Tense

Single word (verb) D

Increased activation in left IFG,

anterior/ posterior STG, MTG, IPL,

and BG for regular compared to

irregular tense.

Table 9.1 (Continued)

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Meykhadeh

et al.

(2021)

Turkish

Persian

Person, Number

Subject- verb

L1– L2 overlap

L1: Left pars opercularis more

sensitive to ungrammatical (relative

to grammatical conditions).

L2: Greater activation in left STG

for ungrammatical compared to

grammatical conditions.

Notes: We report the speakers’ L1, L2, morphosyntactic Feature tested, Constituents involved. L1– L2 (S: similar; D: different): “similar” when the feature at issue

was present in both languages and the violation involved the same constituents in both languages, “different” in all the other cases. AOA (E: early; L: late): “early” for

a mean AoA value below 10 years; “late” for a mean AoA above 10. PRF (L: low; H: high) was “low” for mean proficiency values below 75%; “high” for mean values

above 75%; IMM (S: short; I: intermediate; L: long) was “short” for mean length of residence in the L2- speaking country less than 2 years, “intermediate” for mean

values between 2 and 5 years, “long” for mean values above 5 years. Table 9.1 A summarizes the ERP literature. The grey boxes identify the factors that were formally

analyzed, either in traditional group- analyses or in correlation/ regression analyses in relation with ERP effect amplitudes (in this last case, we report their effect in

parentheses). In the N400/ LAN/ P600 columns X stands for the presence of an ERP effect (violation– control condition). The asterisk (*) stands for smaller amplitude

compared to native speakers. Table 9.1 B summarizes the fMRI literature. Legend: IFG: Inferior Frontal Gyrus; STG: Superior Temporal Gyrus; IPL: Inferior Parietal

Lobule; BG: Basal Ganglia; NA= not available.

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activation patterns have been identified both cortically, especially in left frontal regions, and

subcortically, in the left caudate nucleus, the basal ganglia, and the cerebellum.

Research on native and non- native processing offers two different functional interpretations of

the involvement of the left inferior frontal gyrus (IFG) during morphological processing. Some

proposals emphasize the domain- specific nature of the morphosyntactic computations supported by

this region (e.g., Friederici, 2017), especially with regard to the pars opercularis. In contrast, other

accounts associate this region with domain- general cognitive control mechanisms (e.g., Bornkessel-

Schlesewsky & Schlesewsky, 2013) that support linguistic processing, in light of the white- matter

tracts that connect this area with subcortical regions such as the caudate nuclei. Interestingly, studies

with bilingual speakers have functionally associated these subcortical regions with the monitoring

and control functions that are triggered when the linguistic system is required to switch between two

languages (Branzi et al., 2021; Crinion et al., 2006; Lehtonen et al., 2005; see Abutalebi, 2008 for

a review).

Grammar– and speaker- related variables can influence the amount of language control necessary to

monitor L1 interference, and thus the degree of automaticity with which L2 processing mechanisms

are performed (see Abutalebi, 2008; Polczynska & Bookheimer, 2021; Roncaglia- Denissen & Kotz,

2016 for reviews). Neurophysiologically, such factors can modulate the degree of efficiency of a

given area in supporting a specific cognitive function. In fact, the neuronal organization of a brain

region could be optimized for native language processing and its automatized mechanisms, but not

for the L2 and its more controlled computations (Abulalebi, 2008; Indefrey, 2006). The involvement

of larger neuronal populations, and so the emergence of stronger activation patterns, could there-

fore compensate for the lower neuronal and computational efficiency of the L2. As L2 processing

becomes more automatic, the neuronal organization of the involved region(s) could become more

efficient, leading to a change in the linkage between performance and strength of activation (Indefrey,

2006), i.e., a decrease in activation.

Grammar- Related Factors

Contrary to electrophysiological studies, inherently linguistic factors such as L1– L2 similarity have

received scarce attention in the fMRI literature on morphological processing. Previous reviews have

suggested that, across linguistic domains, typologically similar languages are more likely to show a

convergent neuroanatomical representation (Polczynska & Bookheimer, 2021; Roncaglia- Denissen

& Kotz, 2016). However, the studies reviewed in Table 9.1B suggest that neuroanatomical overlap

can also occur across typologically dissimilar languages. Converging patterns of activation in left

IFG regions have been found in comparisons between languages that differ in their degree of mor-

phological richness (e.g., agglutinating Finnish vs. fusional Swedish morphology in simultaneous

bilingual speakers, Lehtonen et al., 2005), or in the way a morphological feature is expressed on a

verb (e.g., tense in English L2 vs. Japanese and Chinese as L1, Sakai et al., 2004; Tatsuno & Sakai,

2005; Yan et al., 2016). These results are similar to contrasts between languages that share morpho-

syntactic features (tense in Greek and English, Pliatsikas et al., 2014; person/ number in German and

Italian, as in Wartenburger et al., 2003, and in Persian and Turkish, Meykadeh, Golfam, Batouli, &

Sommer, 2021).

To complicate matters further, in both morphologically similar and dissimilar L1– L2 pairs, the

neural overlap can be accompanied by either quantitative or qualitative differences. For example,

Lehtonen et al. (2009) showed that the processing of the complex agglutinative morphology of

Finnish yielded stronger activation of the left IFG compared to the simpler fusional morphology

of Swedish. Meykadeh et al. (2021) tested Turkish and Persian, which similarly encode person and

number agreement on the verb (and showed that within their common left fronto- temporal network,

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the left IFG was more engaged by grammatical sentences in the L1 (Turkish), whereas the left pos-

terior superior temporal gyrus was more sensitive to ungrammaticality in the L2 (Persian).

Part of the difficulty in identifying the contribution of cross- linguistic similarity to the neural

representation of L2 morphology is likely to be methodological in nature. Although L1– L2 similarity

is usually acknowledged in the rationale of the functional neuroimaging studies we reviewed, it is

neither entered in the experimental design so as to test the effect of shared vs. non- shared morpho-

logical features, nor is a precise definition of cross- linguistic (dis- )similarity provided, contrary to the

ERP studies previously described. It is therefore difficult to disentangle the effect of L1– L2 similarity

from that elicited by speaker- related variables. For example, Wartenburger et al. (2003) reported

overlapping patterns of activation between Italian L1 and German L2 (both languages similarly mark

number and gender information in determiners, nouns, adjectives, and verbs), but only at high levels

of proficiency and early AoA (i.e., when more automatic and efficient processing is expected). With a

later AoA and lower proficiency, quantitative differences between L1 and L2 emerged. Similarly, the

partial L2 specialization in left temporal areas reported by Meykadeh et al. (2021) could be modulated

by the different AoA of Persian and the different immersion that characterized the languages (natural-

istic for L1 and a mixture of naturalistic and formal for L2). These factors could affect the efficiency

and native- likeness of the response, even at very high levels of L2 proficiency. In this respect, fMRI

findings align with ERP evidence on the interaction between L1– L2 similarity and speaker- related

factors.

Speaker- Related Factors

Clearer but not fully consistent scenarios emerge for the role of proficiency and AoA. A negative

correlation is usually identified between proficiency and neural activation: As proficiency progresses

towards a native- like level, L2 activation in a given area decreases (Tatsuno & Sakai, 2005) and

becomes indistinguishable from the L1. Pliatsikas et al. (2014) reported a positive correlation between

the size of the regularity effect (regular > irregular forms) in the left caudate nucleus and the L2 pro-

ficiency of a group of late Greek- English bilinguals. As English proficiency increased, so did the

efficiency with which English morphologically complex words were processed, such that left- caudate

activation became statistically indistinguishable from that of native speakers.

When proficiency is kept constant across groups, AoA has been found to influence morphological

processing in the L2 and lead to quantitative modulations in activation patterns, as evidenced by the

greater left IFG involvement associated with categorizing gender- irregular nouns for late learners

compared to native speakers of Spanish (Hernandez et al., 2007). Likewise, highly proficient Italian–

German speakers who had acquired their L2 late (> 6 years) showed stronger left IFG activation for

the L2 compared to the L1 in response to morphosyntactic violations (Wartenburger et al., 2003). In

both studies, following Indefrey (2006), the stronger involvement of left IFG in the L2 could be due

to this region’s lower efficiency in processing a later- learned language. However, in contrast to these

studies, Pliatsikas et al. (2014) observed no quantitative differences between native speakers and

late- learners of English in the patterns of activation elicited by regular and irregular past- tense pro-

cessing in a lexical decision task. This suggests that efficient, native- like neuronal organization can

be achieved even when the L2 is acquired late.

Task- related differences may explain the seemingly inconsistent conclusions reached by the three

studies. Compared to lexical decision tasks (as in Pliatsikas et al., 2014), gender categorization or

grammaticality judgments (as in Hernandez et al., 2007, and Wartenburger et al., 2003, respectively)

involve additional rule- based mechanisms aimed at verifying inflectional consistency across lexical

items (e.g., noun– verb, determiner– noun). Such mechanisms are activated even when not explicitly

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required, as in gender- decision tasks (see Cubelli et al., 2005). Several single- word production studies

have shown that patterns of cortical activations during lexical access are modulated by the speakers’

L2 proficiency (low > high proficiency), but not by AoA, which appears to have a more sizeable

impact on rule- based morphosyntactic processing (Abutalebi, 2008; Indefrey, 2006; Wartenburger

et al., 2003). Thus, the distinct effects of AoA across the three studies could be due to the different

sensitivity that behavioral tasks have to this speaker- related factor.

To our knowledge, no hemodynamic study has so far systematically tested whether L2 immersion

duration has any effect on the neuroanatomical correlates of L2 morphological processing. Of the

eight functional neuroimaging studies included in this review, only three report their participants

to have been naturalistically immersed in the L2 environment, ranging from short to long periods

(Meykhadeh, Golfam, Nasrabadi et al., 2021; Pliatsikas et al., 2014; Wartenburger et al., 2003).

Both Pliatsikas et al. (2014) and Wartenburger et al. (2003) found L1– L2 overlap with increasing

immersion, thus suggesting that naturalistic exposure can guide the L2 towards reaching a native-

like neural representation. This is in line with ERP studies showing that learning in immersion- like

contexts leads to electrophysiological signatures more fully typical of native speakers (Morgan- Short

et al., 2012). However, more research is necessary to determine whether immersion duration is a

strong and independent predictor of the cortical representation of L2 morphology (for the effect of

immersion on volumetric brain changes, see Korenar & Pliatsikas, this volume).

Summary of fMRI Findings

The findings reviewed above suggest that L1– L2 similarity alone is not a robust and independent

predictor of the neural representation of L2 morphology. However, research that systematically

manipulates this factor or uses techniques with the finest spatial resolution, such as invasive brain

stimulation in neurosurgical studies, would confirm this conclusion. Speaker- related factors have the

most tangible effects on the neural representation of L2 morphology. However, as will be discussed

below, when examining the role of such variables and their predictive power, it is important to con-

sider the degree of collinearity that exists between AoA, proficiency, and immersion duration (i.e.,

early exposure to the L2 is usually associated with naturalistic immersion, thus higher proficiency).

Current Trends and Future Directions

Native- likeness refers to the ability of speakers to process stimuli in an L2 (almost) as efficiently and

automatically as in their native language. The degree of overlap between L1 and L2 electrophysio-

logical and neuroanatomical correlates is taken to be a marker of the level of native- likeness achieved

by a group of speakers. The greater their similarity, the more native- like, and so the more efficient

and automatic, L2 processing is assumed to be. Our review shows that quantitative and qualitative

modulations relative to native patterns of reference can depend on grammar- and speaker- related

factors.

Inherent to the definition of native- likeness provided above is a controversial assumption that

characterizes the profile of native speakers, namely their homogeneity in terms of processing routines,

as well as the homogeneity of the electrophysiological and hemodynamic responses to stimuli in

their native language. A legitimate question is whether it makes sense to consider native speakers as

a homogeneous group, given the increasing bi/ multilingual status and globalization of the world’s

population. Many studies have suggested reconsidering the “gold standard” for nativelikeness in

ERPs and investigating L1 and L2 processing along a continuum (e.g., Tanner et al., 2013, 2014;

see also Freunberger et al., 2022). Future challenges in the field could therefore be to identify the

variables that can account for inter- individual variability both in native and non- native processing, as

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well as the appropriate methodology to investigate and account for such variability (see for example,

Fromont, and Luque & Covey, this volume).

Factors Affecting Morphological Processing

Our review suggests that to date, none of the different grammar- and speaker- related factors considered

here are independent predictors of L2 native- likeness. This is partly due to differences in the depth

with which the different techniques have been used to examine the effects of specific predictors, as in

the case of L1– L2 similarity and proficiency, as well as the number of studies adopting these different

methodologies to investigate L2 morphosyntactic processing.

ERP research has proceeded as far as to investigate (dis- )similarities in single features and the

position in which they are expressed within morphosyntactic relations across languages. In contrast,

fMRI studies have predominantly focused on the regular vs. irregular past tense opposition and how it

is handled across broadly defined typologically similar or dissimilar languages. Future hemodynamic

studies should therefore go beyond single- word processing and assess L1– L2 (dis- )similarities at

the sentence level. In this respect, a fruitful testing ground is the contrast between morphological

features and their presence/ absence in L1 and L2 languages, thus extending and complementing

existing single- word (e.g., Hernandez et al., 2007) and sentence- level L1 studies (Carreiras et al.,

2015; Mancini et al., 2017; Qui�ones et al., 2014, 2018).

Like L1– L2 similarity, proficiency encompasses distinct components— such as global and task-

related proficiency— that can differentially affect the response of interest. Empirical evidence

concerning the impact that distinct proficiency assessments have on morphological processing comes

from ERP research, while to the best of our knowledge, fMRI studies have not addressed this issue.

Task- related proficiency reflects a specific and less naturalistic measure of proficiency, which, unlike

global proficiency, cannot provide a complete measure of the real linguistic abilities of L2 speakers

in everyday life. Consequently, the role that this type of proficiency has in the modulation of late ERP

components should be interpreted with more caution. One possibility, albeit more radical, would be

to abandon the general concept of proficiency and rely on more specific indices of L2 experience such

as the type and amount of L2 exposure and immersion (e.g., Ullman, 2014) and/ or the frequency of

L2 use (e.g., Martinez de la Hidalga et al., 2021; Osterhout et al., 2006).

A Note on Non- Invasive Brain Stimulation

Research on non- invasive brain stimulation (NIBS) investigates the effects that magnetic and electric

stimulation, namely TMS (transcranial magnetic stimulation) and tDCS (transcranial direct current

stimulation), have on participants’ performance (see Pandža, this volume). In language research,

participants are generally asked to produce a word/ sentence or to perform a metalinguistic task (e.g.,

grammaticality judgments) while specific brain regions are stimulated. The stimulation can either

have disruptive effects, mirrored by longer reaction times and/ or lower task accuracy, or it can posi-

tively enhance the participants’ performance, leading to shorter reaction times and/ or higher accuracy.

NIBS research on L2 acquisition is still in its early stages (see Pandža, this volume). For instance,

studies of picture naming (Tussis et al., 2017) and language switching (Holtzheimer et al., 2005) have

been reported. Although these studies did not manipulate morphology or morphosyntax specifically,

their results suggest that research on L2 processing could benefit from non- invasive brain stimulation

techniques.

Available NIBS evidence on native language processing with healthy and brain- damaged speakers

points to a causal role of the left IFG in morphosyntactic processing (for a review see Maran et al.,

2022) and of the temporal lobe in the retrieval of irregular past tense verbs in English (Holland &

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Lambon- Ralph, 2010). These findings lend support to the correlational evidence provided by the

hemodynamic studies discussed above, suggesting that NIBS could provide useful insights into the

neural representation of the L1 and L2.

Final Remarks

In the introduction to this chapter, we highlighted theoretical, historical, and methodological issues

behind the lack of a comprehensive neurolinguistic account of L2 morphological processing. Our

review of recent ERP, fMRI, and NIBS literature shows that while historical limitations have been

overcome, there are still some methodological aspects that should be considered in future research.

A case in point is represented by the use of rigid categories to assess the effects of experience- related

variables (i.e., division into distinct low- and high- proficiency groups). L2 data are subject to a

high degree of variability, as it is notoriously difficult to find bilingual speakers with homogeneous

linguistic profiles, and this variability is not accounted for in the statistical analyses. New methodo-

logical approaches are thus needed (see Fromont, this volume).

Finally, ERP studies have provided a fine- grained picture of the temporal dynamics related to the

processing of different morphosyntactic features and relations, while a more fragmented scenario

emerges from fMRI and NIBS. Brain areas and networks involved during L2 morphological pro-

cessing have been identified but, to date, it is still hard to define whether these networks change as a

function of different morphosyntactic features/ relations.

Further Readings

This article attempts to provide a set of global principles that determine the neuroanatomical overlap of languages

in the brain.

Połczyńska, M.M., & Bookheimer, S.Y. (2021). General principles governing the amount of neuroanatomical

overlap between languages in bilinguals. Neuroscience & Biobehavioral Reviews, 130, 1– 14. https:// doi.org/

10.1016/ j.neubio rev.2021.08.005

This article discusses issues related to a rigid concept of native- likeness in ERP research.

Freunberger, D., Bylund, E., & Abrahamsson, N. (2022). Is it time to reconsider the “gold standard” for

nativelikeness in ERP studies on grammatical processing in a second language? A critical assessment based

on qualitative individual differences. Applied Linguistics, 43(3), 433– 452. https:// doi.org/ 10.1093/ app lin/

amab 058

Acknowledgments

The authors acknowledge funding from the Basque Government (BERC 2022– 2025 program), the Spanish

State Research Agency (BCBL Severo Ochoa excellence accreditation CEX2020- 001010- S, grants PSI2015-

65694- P, RTI2018- 096311- B- I00, and PCI2022- 135031- 2 to NM, grants RYC- 2017- 22015 and PID2020-

113945RB- I00 to SM), Marie Sklodowska- Curie grant agreement No 101028370 to NB.

References

Abutalebi, J. (2008). Neural aspects of second language representation and language control. Acta Psychologica,

128(3), 466– 478. https:// doi.org/ 10.1016/ j.act psy.2008.03.014

Alem�n Ba��n, J., Fiorentino, R., & Gabriele, A. (2018). Using event- related potentials to track morphosyntactic

development in second language learners: The processing of number and gender agreement in Spanish. PloS

ONE, 13(7), Article e0200791. https:// doi.org/ 10.1371/ jour nal.pone.0200 791

Alem�n Ba��n, J., Miller, D., & Rothman, J. (2017). Morphological variability in second language learners: An

examination of electrophysiological and production data. Journal of Experimental Psychology: Learning,

Memory, and Cognition, 43(10), 1509– 1536. http:// dx.doi.org/ 10.1037/ xlm 0000 394

Page 15

Neurolinguistics of the Second Language Morphological System

129

Alem�n Ba��n, J., Miller, D., & Rothman, J. (2021). Examining the contribution of markedness to the L2

processing of Spanish person agreement: An event-related potentials study. Studies in Second Language

Acquisition, 43(4), 699– 728. https:// doi.org/ 10.1017/ S02722 6312 0000 479

Armstrong, A., Bulkes, N., & Tanner, D. (2018). Quantificational cues modulate the processing of English

subject- verb agreement by native Chinese speakers: An ERP study. Studies in Second Language Acquisition,

40(4), 731– 754. https:// doi.org/ 10.1017/ S02722 6311 8000 013

Bice, K., & Kroll, J.F. (2021). Grammatical processing in two languages: How individual differences in language

experience and cognitive abilities shape comprehension in heritage bilinguals. Journal of Neurolinguistics,

58, Article 100963. https:// doi.org/ 10.1016/ j.jne urol ing.2020.100 963

Birdsong, D. (2018). Plasticity, variability and age in second language acquisition and bilingualism. Frontiers in

Psychology, 9, Article 81. https:// doi.org/ 10.3389/ fpsyg.2018.00081

Bornkessel- Schlesewsky, I., & Schlesewsky, M. (2013). Reconciling time, space and function: A new dorsal–

ventral stream model of sentence comprehension. Brain and Language, 125(1), 60– 76. https:// doi.org/

10.1016/ j.bandl.2013.01.010

Bowden, H., & Faretta- Stutenberg, M. (this volume). Context of learning in second language neurocognition.

In K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition and

neurolinguistics. Routledge.

Branzi, F.M., Martin, C.D., & Paz- Alonso, P.M. (2021). Task- relevant representations and cognitive control

demands modulate functional connectivity from ventral occipito- temporal cortex during object recognition

tasks. Cerebral Cortex, 32(14), 3068– 3080. https:// doi.org/ 10.1093/ cer cor/ bhab 401

Caffarra, S., Barber, H., Molinaro, N., & Carreiras, M. (2017). When the end matters: Influence of gender cues

during agreement computation in bilinguals. Language, Cognition and Neuroscience, 32(9), 1069– 1085.

https:// doi.org/ 10.1080/ 23273 798.2017.1283 426

Caffarra, S., Molinaro, N., Davidson, D., & Carreiras, M. (2015). Second language syntactic processing revealed

through event- related potentials: An empirical review. Neuroscience & Biobehavioral Reviews, 51, 31– 47.

https:// doi.org/ 10.1016/ j.neubio rev.2015.01.010

Carreiras, M., Qui�ones, I., Mancini, S., Hern�ndez- Cabrera, J.A., & Barber, H. (2015). Verbal and nominal

agreement: An fMRI study. NeuroImage, 120, 88– 103. https:// doi.org/ 10.1016/ j.neu roim age.2015.06.075

Cheng, Y., Cunnings, I., Miller, D., & Rothman, J. (2021). Double- number marking matters for both L1 and L2

processing of nonlocal agreement similarly: An ERP investigation. Studies in Second Language Acquisition,

44(5), 1309– 1329. https:// doi.org/ 10.1017/ S02722 6312 1000 772

Crinion, J., Turner, R., Grogan, A., Hanakawa, T., Noppeney, U., Devlin, J.T., Aso, T., Urayama, S., Fukuyama,

H., Stockton, K., Usui, K., Green, D.W., & Price, C.J. (2006). Language control in the bilingual brain.

Science, 312(5779), 1537– 1540. www.jstor.org/ sta ble/ 3846 323

Cubelli, R., Lotto, L., Paolieri, D., Girelli, M., & Job, R. (2005). Grammatical gender is selected in bare noun

production: Evidence from the picture– word interference paradigm. Journal of Memory and Language,

53(1), 42– 59. https:// doi.org/ 10.1016/ j.jml.2005.02.007

De Diego- Balaguer, R., & Rodriguez- Fornells, A. (2010). Contributions to the functional neuroanatomy

of morphosyntactic processing in L2. Language Learning, 60(1), 231– 259. https:// doi.org/ 10.1111/

j.1467- 9922.2009.00557.x

D�az, B., Erdocia, K., De Menezes, R.F., Mueller, J.L., Sebasti�n- Gall�s, N., & Laka, I. (2016). Electrophysiological

correlates of second- language syntactic processes are related to native and second language distance regard-

less of age of acquisition. Frontiers in Psychology, 7, Article 133. https:// doi.org/ 10.3389/ fpsyg.2016.00133

D�az, B., Sebasti�n- Gall�s, N., Erdocia, K., Mueller, J.L., & Laka, I. (2011). On the cross- linguistic validity of

electrophysiological correlates of morphosyntactic processing: A study of case and agreement violations in

Basque. Journal of Neurolinguistics, 24(3), 357– 373. https:// doi.org/ 10.1016/ j.jne urol ing.2010.12.003

Dickson, D., & Pelzl, E. (this volume). Using time- based electroencephalography to investigate second lan-

guage. In K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition

and neurolinguistics. Routledge.

Freunberger, D., Bylund, E., & Abrahamsson, N. (2022). Is it time to reconsider the “gold standard” for

nativelikeness in ERP studies on grammatical processing in a second language? A critical assessment based

on qualitative individual differences. Applied Linguistics, 43(3), 433– 452. https:// doi.org/ 10.1093/ app lin/

amab 058

Friederici, A.D. (2017). Language in our brain: The origins of a uniquely human capacity. MIT Press. https://

doi.org/ 10.7551/ mitpr ess/ 11173.001.0001

Fromont, L. (this volume). Age and proficiency in second language neurocognition. In K. Morgan- Short & J.G.

van Hell (Eds.), The Routledge handbook of second language acquisition and neurolinguistics. Routledge.

Page 16

Nicoletta Biondo, Nicola Molinaro, and Simona Mancini

130

Gabriele, A., Alem�n Ba��n, J., Hoffman, L., Covey, L., Rossomondo, A., & Fiorentino, R. (2021). Examining

variability in the processing of agreement in novice learners: Evidence from event- related potentials. Journal

of Experimental Psychology: Learning, Memory, and Cognition, 47(7), 1106– 1140. https:// doi.org/ 10.1037/

xlm 0000 983

Hartshorne, J.K., Tenenbaum, J.B., & Pinker, S. (2018). A critical period for second language acquisition: Evidence

from 2/ 3 million English speakers. Cognition, 177, 263– 277. https:// doi.org/ 10.1016/ j.cognit ion.2018.04.007

Hernandez, A.E., Hofmann, J., & Kotz, S.A. (2007). Age of acquisition modulates neural activity for both

regular and irregular syntactic functions. NeuroImage, 36(3), 912– 923. https:// doi.org/ 10.1016/ j.neu roim

age.2007.02.055

Holland, R., & Lambon Ralph, M.A. (2010). The anterior temporal lobe semantic hub is a part of the language

neural network: Selective disruption of irregular past tense verbs by rTMS. Cerebral Cortex, 20(12), 2771–

2775. https:// doi.org/ 10.1093/ cer cor/ bhq 020

Holtzheimer, P., Fawaz, W., Wilson, C., & Avery, D. (2005). Repetitive transcranial magnetic stimulation may

induce language switching in bilingual patients. Brain and Language, 94(3), 274– 277. https:// doi.org/

10.1016/ j.bandl.2005.01.003

Indefrey, P. (2006). A meta- analysis of hemodynamic studies on first and second language processing: Which

suggested differences can we trust and what do they mean? Language Learning, 56, 279– 304. https:// doi.org/

10.1111/ j.1467- 9922.2006.00365.x

Jackson, J., & Schwieter, J. (2019). Study abroad and immersion. In J. Schwieter, & A. Benati (Eds.), The

Cambridge handbook of language learning (pp. 727– 750). Cambridge University Press. https:// doi.org/

10.1017/ 978110 8333 603

Johnson, J.S., & Newport, E.L. (1989). Critical period effects in second language learning: The influence of

maturational state on the acquisition of English as a second language. Cognitive Psychology, 21(1), 60– 99.

https:// doi.org/ 10.1016/ 0010- 0285(89)90003- 0

Korenar, M., & Pliatsikas, C. (this volume). Second language acquisition and neuroplasticity: Insights from

the Dynamic Restructuring Model. In K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of

second language acquisition and neurolinguistics. Routledge.

Kotz, S.A. (2009). A critical review of ERP and fMRI evidence on L2 syntactic processing. Brain and Language,

109(2– 3), 68– 74. https:// doi.org/ 10.1016/ j.bandl.2008.06.002

Kousaie, S., & Klein, D. (this volume). Using functional neuroimaging to investigate second language organiza-

tion. In K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition

and neurolinguistics. Routledge.

Lau, E.F., Phillips, C., & Poeppel, D. (2008). A cortical network for semantics: (De) constructing the N400.

Nature Reviews Neuroscience, 9(12), 920– 933. https:// doi.org/ 10.1038/ nrn2 532

Lehtonen, M., Vorobyev, V., Soveri, A., Hugdahl, K., Tuokkola, T., & Laine, M. (2009). Language- specific

activations in the brain: Evidence from inflectional processing in bilinguals. Journal of Neurolinguistics,

22(5), 495– 513. https:// doi.org/ 10.1016/ j.jne urol ing.2009.05.001

Lehtonen, M.H., Laine, M., Niemi, J., Thomsen, T., Vorobyev, V.A., & Hugdahl, K. (2005). Brain correlates of

sentence translation in Finnish– Norwegian bilinguals. NeuroReport, 16(6), 607– 610. https:// doi.org/ 10.1097/

00001 756- 200504 250- 00018

Liang, L., Chondrogianni, V., & Chen, B. (2021). Online processing of the grammatical aspect marker by L2

Chinese learners. Second Language Research, 38(4), 765– 786. https:// doi.org/ 10.1177/ 02676 5832 1996 423

Luque, A. & Covey, L. (this volume). Factors accounting for individual differences in second language

neurocognition. In K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of second language

acquisition and neurolinguistics. Routledge.

MacWhinney, B. (2005). New directions in the competition model. In M. Tomasello, & D.I. Slobin (Eds.),

Beyond nature- nurture: Essays in honor of Elizabeth Bates (pp. 81– 110). Routledge. https:// doi.org/ 10.4324/

978141 0611 192

MacWhinney, B. (2018). A unified model of first and second language learning. In M. Hickmann, E. Veneziano,

& H. Jisa (Eds.), Sources of variation in first language acquisition: Languages, contexts and learners (pp.

287– 312). John Benjamins Publishing Company. https:// doi.org/ 10.1075/ tilar.22

Mancini, S., Qui�ones, I., Molinaro, N., Hernandez- Cabrera, J.A., & Carreiras, M. (2017). Disentangling

meaning in the brain: Left temporal involvement in agreement processing. Cortex, 86, 140– 155. https:// doi.

org/ 10.1016/ j.cor tex.2016.11.008

Maran, M., Friederici, A.D., & Zaccarella, E. (2022). Syntax through the looking glass: A review on two- word

linguistic processing across behavioral, neuroimaging and neurostimulation studies. Neuroscience and

Biobehavioral Reviews, 142, Article 104881. https:// doi.org/ 10.1016/ j.neubio rev.2022.104 881

Page 17

Neurolinguistics of the Second Language Morphological System

131

Mart�nez de la Hidalga, G., Zawiszewski, A., & Laka, I. (2021) Going native? Yes, if allowed by cross- linguistic

similarity. Frontiers in Psychology, 12, Article 742127. https:// doi.org/ 10.3389/ fpsyg.2021.742 127

Meulman, N., Wieling, M., Sprenger, S.A., Stowe, L.A., & Schmid, M.S. (2015). Age effects in L2 grammar

processing as revealed by ERPs and how (not) to study them. PloS ONE, 10(12), Article e0143328. https://

doi.org/ 10.1371/ jour nal.pone.0143 328

Meykadeh, A., Golfam, A., Batouli, S.A.H., & Sommer, W. (2021). Overlapping but language- specific

mechanisms in morphosyntactic processing in highly competent L2 acquired at school entry: fMRI evidence

from an alternating language switching task. Frontiers in Human Neuroscience, 15, Article 728549. https://

doi.org/ 10.3389/ fnhum.2021.728 549

Meykadeh, A., Golfam, A., Nasrabadi, A.M., Ameri, H., & Sommer, W. (2021). First event- related potentials

evidence of auditory morphosyntactic processing in a subject- object- verb nominative- accusative language

(Farsi). Frontiers in Psychology, 12, Article 698165. https:// doi.org/ 10.3389/ fpsyg.2021.698 165

Molinaro, N., Barber, H.A., & Carreiras, M. (2011). Grammatical agreement processing in reading: ERP findings

and future directions. Cortex, 47(8), 908– 930. https:// doi.org/ 10.1016/ j.cor tex.2011.02.019

Morgan- Short, K., Finestrat, I., Luque, A., & Abugaber, D. (2022). Exploring new insights into explicit and

implicit second language processing: Event- related potentials analyzed by source attribution. Language

Learning, 72(2), 365– 411. https:// doi.org/ 10.1111/ lang.12492

Morgan- Short, K., Steinhauer, K., Sanz, C., & Ullman, M.T. (2012). Explicit and implicit second language

training differentially affect the achievement of native- like brain activation patterns. Journal of Cognitive

Neuroscience, 24(4), 933– 947. https:// doi.org/ 10.1162/ jocn_ a_ 00 119

Newport, E.L., Bavelier, D., & Neville, H.J. (2001). Critical thinking about critical periods: Perspectives on a crit-

ical period for language acquisition. In E. Dupoux (Ed.), Language, brain, and cognitive development: Essays

in honor of Jacques Mehler (pp. 481– 502). MIT Press. https:// doi.org/ 10.7551/ mitpr ess/ 4108.001.0001

Nichols, E.S., & Joanisse, M.F. (2019). Individual differences predict ERP signatures of second language

learning of novel grammatical rules. Bilingualism: Language and Cognition, 22(1), 78– 92. https:// doi.org/

10.1017/ S13667 2891 7000 566

Osterhout, L., McLaughlin, J., Kim, A., Greenwald, R., & Inoue, K. (2004). Sentences in the brain: Event-

related potentials as real- time reflections of sentence comprehension and language learning. In M. Carreiras,

& C. Clifton, Jr. (Eds.), The on- line study of sentence comprehension: Eyetracking, ERP, and beyond (pp.

271– 308). Routledge. https:// doi.org/ 10.4324/ 978020 3509 050

Osterhout, L., McLaughlin, J., Pitk�nen, I., Frenck- Mestre, C., & Molinaro, N. (2006). Novice learners, longi-

tudinal designs, and event- related potentials: A means for exploring the neurocognition of second language

processing. Language Learning, 56, 199– 230. https:// doi.org/ 10.1111/ j.1467- 9922.2006.00361.x

Pandža, N. (this volume). Using non- invasive brain stimulation to investigate second language. In K. Morgan-

Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition and neurolinguistics.

Routledge

Pliatsikas, C., Johnstone, T., & Marinis, T. (2014). fMRI evidence for the involvement of the procedural memory

system in morphological processing of a second language. PloS ONE, 9(5), Article e97298. https:// doi.org/

10.1371/ jour nal.pone.0097 298

Połczyńska, M.M., & Bookheimer, S.Y. (2021). General principles governing the amount of neuroanatomical

overlap between languages in bilinguals. Neuroscience & Biobehavioral Reviews, 130, 1– 14. https:// doi.org/

10.1016/ j.neubio rev.2021.08.005

Qui�ones, I., Molinaro, N., Mancini, S., Hern�ndez- Cabrera, J.A., & Carreiras, M. (2014). Where agreement

merges with disagreement: fMRI evidence of subject– verb integration. NeuroImage, 88, 188– 201. https:// doi.

org/ 10.1016/ j.neu roim age.2013.11.038

Qui�ones, I., Molinaro, N., Mancini, S., Hern�ndez- Cabrera, J.A., Barber, H., & Carreiras, M. (2018). Tracing

the interplay between syntactic and lexical features: fMRI evidence from agreement comprehension.

NeuroImage, 175, 259– 271. https:// doi.org/ 10.1016/ j.neu roim age.2018.03.069

Roncaglia- Denissen, M.P., & Kotz, S.A. (2016). What does neuroimaging tell us about morphosyntactic pro-

cessing in the brain of second language learners? Bilingualism: Language and Cognition, 19(4), 665– 673.

https:// doi.org/ 10.1017/ S13667 2891 5000 413

Sabourin, L., & Manning, G. (this volume). Cross- linguistic transfer in second language neurocognition. In

K. Morgan- Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition and

neurolinguistics. Routledge.

Sakai, K.L., Miura, K., Narafu, N. and Muraishi, Y. (2004). Correlated functional changes of the prefrontal cortex

in twins induced by classroom education of second language. Cerebral Cortex, 14(11), 1233– 1239. https://

doi.org/ 10.1093/ cer cor/ bhh 084

Page 18

Nicoletta Biondo, Nicola Molinaro, and Simona Mancini

132

Steinhauer, K. (2014). Event- related potentials (ERPs) in second language research: A brief introduction to the

technique, a selected review, and an invitation to reconsider critical periods in L2. Applied Linguistics, 35(4),

393– 417. https:// doi.org/ 10.1093/ app lin/ amu 028

Steinhauer, K., White, E.J., & Drury, J.E. (2009). Temporal dynamics of late second language acquisi-

tion: Evidence from event- related brain potentials. Second Language Research, 25(1), 13– 41. https:// doi.org/

10.1177/ 02676 5830 8098 995

Tanner, D., McLaughlin, J., Herschensohn, J., & Osterhout, L. (2013). Individual differences reveal stages of L2

grammatical acquisition: ERP evidence. Bilingualism: Language and Cognition, 16(2), 367– 382. https:// doi.

org/ 10.1017/ S13667 2891 2000 302

Tanner, D., Inoue, K., & Osterhout, L. (2014). Brain- based individual differences in online L2 grammatical com-

prehension. Bilingualism: Language and Cognition, 17(2), 277– 293. https:// doi.org/ 10.1017/ S13667 2891

3000 370

Tatsuno, Y., & Sakai, K.L. (2005). Language- related activations in the left prefrontal regions are differentially

modulated by age, proficiency, and task demands. Journal of Neuroscience, 25(7), 1637– 1644. https:// doi.

org/ 10.1523/ JNEURO SCI.3978- 04.2005

Tussis, L., Sollmann, N., Boeckh- Behrens, T., Meyer, B., & Krieg, S.M. (2017). Identifying cortical first and

second language sites via navigated transcranial magnetic stimulation of the left hemisphere in bilinguals.

Brain and Language, 168, 106– 116. https:// doi.org/ 10.1016/ j.bandl.2017.01.011

Ullman, M.T. (2014). The declarative/ procedural model: A neurobiologically motivated theory of first and second

language. In B. VanPatten, & J. Williams (Eds.), Theories in second language acquisition: An introduction

(2nd ed., pp. 147– 172). Routledge. https:// doi.org/ 10.4324/ 978020 3628 942

Ullman, M.T. (2020). The declarative/ procedural model: A neurobiologically motivated theory of first and second

language. In B. VanPatten, G.D. Keating, & S. Wulff (Eds.), Theories in second language acquisition: An

introduction (3rd ed., pp. 128– 161). Routledge. https:// doi.org/ 10.4324/ 978042 9503 986

Ullman, M.T., & Morgan-Short, K. (this volume). How the declarative and procedural memory brain circuits

support second language: Electrophysiological, neuroimaging, and neurological evidence. In K. Morgan-

Short & J.G. van Hell (Eds.), The Routledge handbook of second language acquisition and neurolinguistics.

Routledge.

Van Hell, J.G., & Tokowicz, N. (2010). Event- related brain potentials and second language learning: Syntactic

processing in late L2 learners at different L2 proficiency levels. Second Language Research, 26(1), 43– 74.

https:// doi.org/ 10.1177/ 02676 5830 9337 637

Wartenburger, I., Heekeren, H.R., Abutalebi, J., Cappa, S. F., Villringer, A., & Perani, D. (2003). Early

setting of grammatical processing in the bilingual brain. Neuron, 37(1), 159– 170. https:// doi.org/ 10.1016/

S0896- 6273(02)01150- 9

Yan, H., Zhang, Y.M., Xu, M., Chen, H.Y. and Wang, Y.H. (2016). What to do if we have nothing to rely on: Late

bilinguals process L2 grammatical features like L1 natives. Journal of Neurolinguistics, 40, 1– 4. https:// doi.

org/ 10.1016/ j.jne urol ing.2016.04.002

Zawiszewski, A., & Laka, I. (2020). Bilinguals processing noun morphology: Evidence for the language distance

hypothesis from event- related potentials. Journal of Neurolinguistics, 55, Article 100908. https:// doi.org/

10.1016/ j.jne urol ing.2020.100 908