Biology subjects

Brown, E. C.

Publications and source records attributed to Brown, E. C..

4 recordsLinked to original sources

bioRxiv2024

Neural synchrony is "good enough" for speech comprehension

Neural populations exhibit low-frequency phase synchrony to inferred phrase and constituent boundaries during speech comprehension, widely interpreted as reflecting the endogenous construction of syntactic structure. Good-enough processing (GEP) accounts suggest this structure-building is not obligatory for every utterance but graded: listeners may scale back syntactic computation when meaning can be recovered from local lexical-semantic context. Whether this graded reliance on syntax is reflected uniformly in delta-band neural activity remains unresolved, partly because syntactic processing comprises several dissociable demands that prior work has not modeled concurrently. We reanalyzed an open-source EEG dataset recorded during audiobook listening and used delta-band temporal response functions to model four syntactic constructs concurrently: syntactic surprisal, closing-node count, and integration and storage cost from Dependency Locality Theory. For each construct, we tested whether its contribution to the delta-band response was modulated by local semantic dissimilarity, computed from contextualized word embeddings. Semantic dissimilarity significantly modulated the response to syntactic surprisal and closing-node count, showed a smaller but reliable modulation of storage cost, and showed no modulation of integration cost; a repeated-measures comparison confirmed this graded hierarchy differed reliably across constructs. These results indicate that semantic predictability does not discount syntactic processing across the board but selectively affects the anticipation and construction of structure and its ongoing maintenance, while leaving retrieval of an already-resolved dependency largely unaffected. We interpret this pattern as sharpening, rather than merely reiterating, the claim that listeners prioritize efficiency during real-time comprehension.

neuroscience↗

bioRxiv2024

Modular Phoneme Processing in Human Superior Temporal Gyrus

Modular organization is fundamental to cortical processing, but its presence is human association cortex is unknown. We characterized phoneme processing with 128-1024 channel micro-arrays at 50-200m pitch on superior temporal gyrus of 7 patients. High gamma responses were highly correlated within [~]1.7mm diameter modules, sharply delineated from adjacent modules with distinct time-courses and phoneme-selectivity. We suggest that receptive language cortex may be organized in discrete processing modules.

neuroscience↗

bioRxiv2021

Speech-related auditory salience detection in the posterior superior temporal region

Processing auditory human speech requires both detection (early and transient) and analysis (sustained). We analyzed high gamma (70-110Hz) activity of intracranial electroencephalography waveforms acquired during an auditory task that paired forward speech, reverse speech, and signal correlated noise. We identified widespread superior temporal sites with sustained activity responding only to forward and reverse speech regardless of paired order. More localized superior temporal auditory onset sites responded to all stimulus types when presented first in a pair and responded in recurrent fashion to the second paired stimulus in select conditions even in the absence of interstimulus silence; a novel finding. Auditory onset activity to a second paired sound recurred according to relative salience, with evidence of partial suppression during linguistic processing. We propose that temporal lobe auditory onset sites facilitate a salience detector function with hysteresis of 200ms and are influenced by cortico-cortical feedback loops involving linguistic processing and articulation.

neuroscience↗

bioRxiv2018

Impaired expected value computations in schizophrenia are associated with a reduced ability to integrate reward probability and magnitude of recent outcomes.

ABSTRACTO_ST_ABSBackgroundC_ST_ABSMotivational deficits in people with schizophrenia (PSZ) are associated with an inability to integrate the magnitude and probability of previous outcomes. The mechanisms that underlie probability-magnitude integration deficits, however, are poorly understood. We hypothesized that increased reliance on \"value-less\" stimulus-response associations, in lieu of expected value (EV)-based learning, could drive probability-magnitude integration deficits in PSZ with motivational deficits.\n\nMethodsHealthy volunteers (n= 38) and PSZ (n=49) completed a reinforcement learning paradigm consisting of four stimulus pairs. Reward magnitude (3/2/1/0 points) and probability (90%/80%/20%/10%) together determined each stimulus EV. Following a learning phase, new and familiar stimulus pairings were presented. Participants were asked to select stimuli with the highest reward value.\n\nResultsPSZ with high motivational deficits made increasingly less optimal choices as the difference in reward value (probability*magnitude) between two competing stimuli increased. Using a previously-validated computational hybrid model, PSZ relied less on EV (\"Q-learning\") and more on stimulus-response learning (\"actor-critic\"), which correlated with SANS motivational deficit severity. PSZ specifically failed to represent reward magnitude, consistent with model demonstrations showing that response tendencies in the actor-critic were preferentially driven by reward probability.\n\nConclusionsProbability-magnitude deficits in PSZ with motivational deficits arise from underutilization of EV in favor of reliance on value-less stimulus-response associations. Consistent with previous work and confirmed by our computational hybrid framework, probability-magnitude integration deficits were driven specifically by a failure to represent reward magnitude. This work reconfirms the importance of decreased Q-learning/increased actor-critic-type learning as an explanatory framework for a range of EV deficits in PSZ.

neuroscience↗