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Mugler, E. M.

Publications and source records attributed to Mugler, E. M..

4 recordsLinked to original sources

Identifying Naturalistic Movies from Human Brain Activity with High-Density Diffuse Optical Tomography

Modern neuroimaging modalities, particularly functional MRI (fMRI), can decode detailed human experiences. Thousands of viewed images can be identified or classified, and sentences can be reconstructed. Decoding paradigms often leverage encoding models that reduce the stimulus space into a smaller yet generalizable feature set. However, the neuroimaging devices used for detailed decoding are non-portable, like fMRI, or invasive, like electrocorticography, excluding application in naturalistic use. Wearable, non-invasive, but lower-resolution devices such as electroencephalography and functional near-infrared spectroscopy (fNIRS) have been limited to decoding between stimuli used during training. Herein we develop and evaluate model-based decoding with high-density diffuse optical tomography (HD-DOT), a higher-resolution expansion of fNIRS with demonstrated promise as a surrogate for fMRI. Using a motion energy model of visual content, we decoded the identities of novel movie clips outside the training set with accuracy far above chance for single-trial decoding. Decoding was robust to modulations of testing time window, different training and test imaging sessions, hemodynamic contrast, and optode array density. Our results suggest that HD-DOT can translate detailed decoding into naturalistic use.

bioengineering↗

Ultra-high density imaging arrays for diffuse optical tomography of human brain improve resolution, signal-to-noise, and information decoding

Functional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing ([~]13 mm) than sparse fNIRS ([~]30 mm) and therefore provide higher image quality, with spatial resolution [~]1/2 that of fMRI. Herein, simulations indicated reducing inter-optode spacing to 6.5 mm would further improve image quality and noise-resolution tradeoff, with diminishing returns below 6.5 mm. We then constructed an ultra-high-density DOT system (6.5-mm spacing) with 140 dB dynamic range that imaged stimulus-evoked activations with 30-50% higher spatial resolution and repeatable multi-focal activity with excellent agreement with participant-matched fMRI. Further, this system decoded visual stimulus position with 19-35% lower error than previous HD-DOT, throughout occipital cortex.

bioengineering↗

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

neuroscience↗

Differential representation of articulatory gestures and phonemes in motor, premotor, and inferior frontal cortices

Speech is a critical form of human communication and is central to our daily lives. Yet, despite decades of study, an understanding of the fundamental neural control of speech production remains incomplete. Current theories model speech production as a hierarchy from sentences and phrases down to words, syllables, speech sounds (phonemes) and the movements of speech articulator muscles used to produce these sounds (articulatory gestures). Here, we investigate the cortical representation of articulatory gestures and phonemes in speech motor, premotor, and inferior frontal cortices. Our results indicate that primary motor and premotor areas represent gestures to a greater extent than phonemes, while inferior frontal cortex represents both gestures and phonemes. These findings suggest that the cortical control of speech production shares a common representation with that of other types of movement, such as arm and hand movements.

neuroscience↗