Document text
Principal Investigator: GINA R KUPERBERG
Organization: MASSACHUSETTS GENERAL HOSPITAL
Fiscal Year: 2024
Award: $587,007
Funding agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development
For language comprehension to succeed in noisy and ambiguous environments, the human brain must use
contextual information to actively predict upcoming linguistic inputs. Impairments in top-down prediction are
thought to contribute to language and communicative dysfunction in a variety of neurodevelopmental disorders,
from the reading disabilities associated with dyslexia, to the profound social and communicative dysfunctions
that characterize schizophrenia and autism spectrum disorder. In neurotypical adults, linguistic prediction is
known to modulate neural activity within a left-lateralized fronto-temporal network. However, little is known about
the computational mechanisms that determine the timing of feedforward and feedback activity across this
network. This grant asks whether these neural dynamics can be explained by predictive coding — a unifying
theory of perceptual and cognitive function. According to predictive coding, the brain infers the meaning of
sensory inputs by minimizing prediction error across multiple levels of the cortical hierarchy. To test this theory,
this grant proposes a series of experiments using three complementary neuroimaging techniques ––
magneto-encephalography (MEG), electroencephalography (EEG) and functional MRI –– to probe the
timecourse and location of neural activity to incoming words during language comprehension. Computational
simulations using an implemented predictive coding model of language processing will serve as a powerful
complementary research tool, allowing for the testing of explicit, computationally motivated hypotheses. Aim
1 (EEG/MEG) will test the hypothesis that the timecourse and localization of evoked (phase-locked) neural
activity within the left temporal cortex can be explained by prediction error at multiple levels of linguistic
representation. Aim 2 (MEG/EEG) will use Representational Similarity Analysis to directly capture neural pre-
activation of specific words at different levels of linguistic representation in predictive sentence contexts. These
methods will also be used to track the timecourse of converging on sharpened neural representations after word
onset in both predictive and non-predictive contexts. In both these Aims, computational simulations using the
same items will proceed in parallel with these neuroimaging studies, guiding interpretation. Aim
3 (MEG/EEG/fMRI) asks whether the principles of dynamic predictive coding framework can explain how the
brain is able to flexibly shift away from prior predictions in order to rapidly infer a new underlying message.
Specifically, this Aim asks whether these principles can explain neural activity at the highest level of the fronto-
temporal language hierarchy — the left inferior frontal cortex — as well as top-down feedback to lower cortical
regions at a later stage of processing. By directly linking the neurobiology of language comprehension to a central
theory of human cortical function, this project will identify core neural and computational mechanisms that may
be disrupted in multiple language disorders. It therefore lays the foundation for the development of targeted,
theoretically motivated neurocognitive strategies for the treatment and prevention of communicative disability.
Terms: <21+ years old><ASD><Adult><Adult Human><Anterior><Appearance><Autism><Autistic Disorder><Belief><Brain><Brain Nervous System><Code><Coding System><Communication><Communication Disability><Communicative Disability><Communicative Dysfunctions><Computer Models><Computer Simulation><Computer based Simulation><Computerized Models><Cues><Development><Disease><Disorder><Dyslexia><EEG><Early Infantile Autism><Electroencephalogram><Electroencephalography><Encephalon><Environment><Event><Event-Related Potentials><Failure><Feedback><Foundations><Frequencies><Functional MRI><Functional Magnetic Resonance Imaging><Grant><Human><Image><Impairment><Infantile Autism><Inferior><Kanner's Syndrome><Language><Language Disorders><Left><Linguistic><Linguistics><Link><Location><MEG imaging><Magnetoencephalography><Methods><Modeling><Modern Man><Neighborhoods><Neurobiology><Neurocognitive><Neurodevelopmental Disorder><Neurological Development Disorder><Orthography><Phase><Prefrontal Cortex><Prevention><Reading Disabilities><Reading disability><Research><Schizophrenia><Schizophrenic Disorders><Semantics><Sensory><Series><Social Functioning><Stimulus><Techniques><Temporal Lobe><Testing><Word Blindness><adulthood><autism spectral disorder><autism spectrum disorder><autistic spectrum disorder><cognitive function><comprehending language><computational modeling><computational models><computational simulation><computer based models><computerized modeling><computerized simulation><dementia praecox><developmental><event related potential><experiment><experimental research><experimental study><experiments><fMRI><flexibility><flexible><frontal cortex><frontal lobe><function socially><functioning social><imaging><insight><language comprehension><language deficit><language processing><lexical><magnetoencephalogram><magnetoencephalographic imaging><multi-modal neuro-imaging><multi-modal neuroimaging><multimodal neuro-imaging><multimodal neuroimaging><neural><neural imaging><neural patterning><neuro-imaging><neurobiological><neurodevelopmental disease><neuroimaging><neurological imaging><neuropsychiatric disease><neuropsychiatric disorder><remediation><response><schizophrenic><semantic processing><sensory input><social defects><social deficits><social disorders><social dysfunction><spatiotemporal><support network><temporal cortex><theories><tool><treatment strategy>