Sahin, Pinker, Cash, Schomer, & Halgren (2009)

Sequential processing of lexical, grammatical, and phonological information within Broca’s area

Broca’s Area

• Implicated in several kinds of processes

– Language• Phonology• Morphology• Syntax

– More generally• Sequential ordering?• (Near motor face and hand regions)

Brodmann Areas

Defined histologically

Broca’s Area = 44 & 45

Depth Electrodes

- Used in surgical patients only - Seizures not sufficiently controlled by meds

- Surgery to excise tissue causing seizures- Main purpose to help localize seizure focus

- Contacts every 5mm at different depths along a single needle - Electrode diameter = 1 mm

- Record from adjacent pairs (= bipolar) - Less noisy - Polarity reversals when cross sources - Allows better localization of seizure source

- Record Local Field Potentials (LFP)

Participants (Patients)

Patient Sex Age

Seizure

Onset Age

fMRI done?

Completed runs (of 9)

A F 41 14 Yes 6

B F 51 18 No 9

C F 38 5 Yes 7

Inclusion criteria:- No clinical language or cognitive impairments- Right handed- Seizures thought to have a focal source not in language areas - Electrode placements through language areas

From supporting online materialwww.sciencemag.org/cgi/content/full/326/5951/445/DCI

Electrode Placement

Electrodes A & B

During Surgery

Depths 1-6along one probe

Electrode Locations Determined with Structural MRI

Experimental Design

Evidence of Relatively Normal Processing in Broca’s Area in These

Patients

Same paradigm & stimuliused with normal participants& these same patientsin an fMRI study

Relationship of fMRI Loci of Activity & Depth Probe Locations

Grand Means Across All Conditions

Triphasic response - Notice polarity reversals across channels - Means local generators

Regional Specificity of Triphasic LFPs

Response to Cue vs Target in Broca’s Area

Response to cue not reliably modulated by experimental condition

Evidence 1st Peak Reflects Lexical Processing

- Amplitude reliably bigger for rarer words

- But not reliably affected by word length

- Peak time consistent w/ other estimates of word ID time

Evidence 2nd Peak Reflects Inflectional Processing

Amplitude equally large forNull- & Overt-Inflection

What else do 2 “inflection” conditions have in common?

No Differences for InflectingNouns vs Verbs

Evidence 3rd Peak Reflects Phonological Processing

Amplitude larger in Overt-Inflection

Additional Evidence 3rd Peak Reflects Phonological Processing

Amplitude larger for longer words

Consistency of 1st peak of triphasic response across participants

From supporting online materialwww.sciencemag.org/cgi/content/full/326/5951/445/DCI

Consistency of 2nd peak of triphasic response across paticipants

- Notice differences in - Amplitude scales - Electrode channels - Polarity

From supporting online materialwww.sciencemag.org/cgi/content/full/326/5951/445/DCI

Consistency of 3rd peak of triphasic response across participants

- Notice different channels than previous figure

From supporting online materialwww.sciencemag.org/cgi/content/full/326/5951/445/DCI

Localizing Generators (Equivalent Current Dipole [ECD] Modeling)

Conclusions

• Processing a word for production– (in these hybrid comp/prod tasks)– Consists of sequentially ordered processes– Originating in spatially close but distinct regions

in Broca’s area

• Argue that this provides better support for– Language production models that have discrete

non-interactive stages for different components of production

• e.g. Levelt, Roelofs, & Meyer

– Over models that incorporate interaction & feedback

• e.g., Dell; Goldrick

Conclusions

• Stronger conclusion than warranted by data– Online response from Goldrick, Dell, Kroll, &

Rapp “…full discreteness claim is not required by the Sahin et al. data and

conflicts with an extensive body of research that has already demonstrated its inadequacy. … To account for the inadequacy of both fully discrete and fully interactive theories, language production models must allow for interaction while incorporating critical constraints on the degree of coupling between processing components. Such architectures respect the sequentiality of processing different types of information (in line with Sahin et al.’s results) without sacrificing the ability to account for interactive effects. Rather than viewing results such as those of Sahin et al.’s through a Boolean lens – supporting either fully interactive or fully discrete models – a more profitable approach would acknowledge the continuum of possibilities between these extremes.”